pi3k regulatory subunit p85alpha plays a tumor suppressive role in the transformation of mammary
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Citation Thorpe, Lauren Marie. 2015. PI3K regulatory subunit p85alphaplays a tumor suppressive role in the transformation of mammaryepithelial cells. Doctoral dissertation, Harvard University, GraduateSchool of Arts & Sciences.
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PI3K regulatory subunit p85alpha plays a tumor suppressive role
in the transformation of mammary epithelial cells
A dissertation presented
by
Lauren Marie Thorpe
to
The Division of Medical Sciences
in partial fulfillment of the requirements
for the degree of
Doctor of Philosophy
in the subject of
Virology
Harvard University
Cambridge, Massachusetts
December 2014
© 2014 Lauren Marie Thorpe
All rights reserved.
iii
Dissertation Advisor: Dr. Jean J. Zhao Lauren Marie Thorpe
PI3K regulatory subunit p85alpha plays a tumor suppressive role
in the transformation of mammary epithelial cells
Abstract
Hyperactivation of the phosphatidylinositol 3-kinase (PI3K) pathway is one of the most
common events in human cancers. Class IA PI3Ks are heterodimers of a p110 catalytic
and a p85 regulatory subunit that coordinate the cellular response to extracellular stimuli.
Activating mutations in class IA PIγK catalytic isoform p110g are well established as
causative in a number of cancer types. More recently, mutation or loss of the class IA
regulatory isoform p85g (encoded by PIK3R1) has emerged as contributing to
oncogenesis. In this dissertation, we use both in vitro and in vivo approaches to examine
the role of p85g as a tumor suppressor in the transformation of mammary epithelial cells.
Using publically available online databases, we find heterozygous deletion of PIK3R1
occurs in 19-26% of breast tumors. Moreover, PIK3R1 expression is significantly
decreased in breast tumors compared to normal breast tissue. In human mammary
epithelial cells expressing dominant negative p53 (DDp53-HMECs), RNAi-mediated
knockdown of PIK3R1 increases PI3K/AKT activation in response to growth factor
stimulation and leads to transformation as assessed by anchorage-independent growth.
PIK3R1 knockdown also augments transformation of DDp53-HMECs by oncogenes,
including activated HER2/neu. In a mouse model of HER2/neu-driven breast cancer,
genetic ablation of Pik3r1 accelerates mammary tumor development. Transformation
driven by p85g loss is largely mediated by signaling through catalytic isoform p110g, as
iv
selective pharmacological inhibition of p110g but not p110く effectively blocks colony
formation of PIK3R1 knockdown DDp53-HMECs and growth of Pik3r1 knockout tumors.
Mechanistically, we find that partial reduction of p85g increases the amount of p85-
p110g bound to activated receptors, augmenting PI3K signaling and oncogenic
transformation.
Together the work presented in this dissertation suggests that p85g depletion selectively
targets a free negative regulator pool of this regulatory subunit that modulates PI3K
activation under normal conditions, and transforms cells when lost. Furthermore, our
work indicates that p85g plays a tumor suppressive role in the pathogenesis of breast
tumors. Isoform-selective PI3K inhibitors are currently emerging in the clinic, and may
offer improved specificity and reduced toxicity over first-generation pan-PI3K inhibitors.
Our findings suggest p110g-selective therapies may be an effective treatment for breast
cancers with reduced p85g expression.
v
Table of Contents Abstract iii Acknowledgements vi Index of Figures vii Index of Tables x List of Abbreviations xi Glossary of Terms xvi Chapter 1: Introduction 1 Chapter 2: PI3K regulatory subunit p85alpha plays a tumor suppressive role in human mammary epithelial cells 46 Chapter 3: PI3K regulatory subunit p85alpha plays a tumor suppressive role in a genetically engineered mouse model of mammary tumorigenesis 94 Chapter 4: Summary, discussion, and future directions 132 Materials and Methods 150 References 165 Appendix A: Supplemental table of class I PI3K alterations in cancer, with complete references 192 Appendix B: Supplemental table of genetically engineered mouse models of PI3K isoforms in cancer, with complete references 200
vi
Acknowledgements
I am deeply grateful to the many people who have supported me both professionally and
personally throughout my years of study. Thank you to my undergraduate mentor, Dr.
Brooke McCartney, who gave me my first true research experience at Carnegie Mellon
University, and encouraged me to pursue graduate school. Thank you to my graduate
mentor, Dr. Jean Zhao, an insightful scientist and caring mentor, who has afforded me
many great opportunities during my time at Harvard University. Thank you to the past
and current members of the Zhao lab for their guidance, in particular Dr. Hailing Cheng,
Thanh Von, Stephanie Santiago, Dr. Linda Clayton, Carolynn Ohlson, and Dr. Haluk
Yuzugullu. Thank you to my Dissertation Advisory Committee, Drs. Karl Münger, Lewis
Cantley, and Myles Brown, for their time and scientific expertise over the years; I am
especially grateful to Karl for his mentoring and advice. Thank you to the Virology
program, in particular Dr. David Knipe, and to my cohort of twelve, the Vironauts. Thank
you to all of my friends and teammates, who have helped remind me that there is life
outside the lab, and that it is good. Thank you to Hyun Kim, who has supported me
every day and in every possible way. Thank you to my family: my parents Tom and Deb,
my sister Jessica, and my brother David. You’ve been there for me through it all. This
dissertation is dedicated to you.
vii
Index of Figures Chapter 1
Figure 1.1 The PI3K family comprises multiple classes and isoforms 7 Figure 1.2 Signaling by class I PI3K isoforms 8 Figure 1.3 Signaling by class II PI3K isoforms 10 Figure 1.4 Signaling by class III PI3K isoforms 11 Figure 1.5 Divergent roles of class I PI3K catalytic isoforms in the context
of RTK, GPCR, and small GTPase inputs 19 Figure 1.6 Competition model for p110g and p110く regulation of RTK-
mediated PI3K signaling 20 Figure 1.7 Molecular contexts dictating applications for isoform-selective
PI3K inhibitors 21 Figure 1.8 Rational combination of PI3K inhibitors and other targeted
therapeutics 32 Chapter 2
Figure 2.1 PIK3R1 expression is significantly reduced in breast cancers 54 Figure 2.2 Generation of DDp53-HMECs with stable RNAi-mediated
PIK3R1 knockdown 57 Figure 2.3 PIK3R1 knockdown transforms DDp53-HMECs and increases
growth factor-stimulated PI3K/AKT activation 59 Figure 2.4 Augmented PI3K/AKT activation in PIK3R1 knockdown
DDp53-HMECs is rescued by ectopic expression of PIK3R1 61 Figure 2.5 Generation of DDp53-HMECs with activated HER2/neu
and RNAi-mediated PIK3R1 knockdown 63 Figure 2.6 PIK3R1 knockdown increases transformation and PI3K/AKT
signaling driven by activated HER2/neu in DDp53-HMECs 64 Figure 2.7 PIK3R1 knockdown increases transformation and PI3K/AKT
signaling driven by p110g-H1047R in DDp53-HMECs 66 Figure 2.8 Transformation of PIK3R1 knockdown DDp53-HMECs is
blocked by p110g-selective pharmacological inhibition 68
viii
Figure 2.9 Transformation of PIK3R1 knockdown DDp53-HMECs with activated HER2/neu is blocked by p110g-selective inhibition 69
Figure 2.10 PI3K/AKT signaling in PIK3R1 knockdown DDp53-HMECs
with activated HER2/neu is blocked by p110g-selective inhibition 71 Figure 2.11 Endogenous p85g and PTEN do not appear to interact in
DDp53-HMECs 72 Figure 2.12 PTEN and p85g do not appear to interact in a variety of cell
types 74 Figure 2.13 PIK3R1 knockdown does not affect PTEN mRNA levels or lipid
phosphatase activity in DDp53-HMECs 77 Figure 2.14 PIK3R1 knockdown does not increase growth factor-stimulated
RTK phosphorylation in DDp53-HMECs 80 Figure 2.15 PIK3R1 knockdown does not affect growth factor-stimulated
RTK trafficking in DDp53-HMECs 82 Figure 2.16 PIK3R1 knockdown increases transformation of DDp53-HMECs
expressing activated ErbB3 84 Figure 2.17 PIK3R1 knockdown increases the amount of p85-p110g bound
to activated RTKs in DDp53-HMECs 86 Figure 2.18 Model: partial p85g loss leads to increased PI3K/AKT signaling
and transformation 87 Chapter 3
Figure 3.1 Schematic of mammary gland development in the mouse 97 Figure 3.2 Schematic of Pik3r1 conditional knockout allele and breeding
scheme for mammary-specific Pik3r1 ablation 101 Figure 3.3 Transgenic MMTV-Cre ablates Pik3r1 expression in mouse
mammary epithelial cells 103 Figure 3.4 Pik3r1 expression is not required for mouse mammary gland
development 104 Figure 3.5 PI3K/AKT pathway activation in spontaneous mammary tumors
from Pik3r1 knockout mice 109 Figure 3.6 Pathology of primary spontaneous mammary tumors and lung
metastases from Pik3r1 knockout mice 110 Figure 3.7 Adjacent mammary glands from Pik3r1 knockout mice with
spontaneous mammary tumors have a hypermorphic phenotype 111
ix
Figure 3.8 Schematic of the transgenic NIC allele and breeding scheme for mammary-specific HER2/neu expression and Pik3r1 ablation 113
Figure 3.9 Pik3r1 ablation reduces the latency of HER2/neu-driven
mammary tumor development 114 Figure 3.10 Effect of Pik3r1 ablation on PI3K/AKT pathway activation in
HER2/neu-driven mammary tumors 116 Figure 3.11 Quantification of the effect of Pik3r1 ablation on PI3K/AKT
pathway activation in HER2/neu-driven mammary tumors 117
Figure 3.12 Effect of Pik3r1 ablation on tumor pathology and proliferation of HER2/neu-driven mammary tumors 119
Figure 3.13 Pan-PIγK or p110g-selective inhibitors block the growth of transplanted HER2/neu tumors with Pik3r1 ablation 121 Figure 3.14 Pan-PIγK or p110g-selective inhibitors suppress PI3K/AKT
activation in transplanted HER2/neu tumors with Pik3r1 ablation 123 Figure 3.15 Pan-PIγK or p110g-selective inhibitors suppress proliferation
and induce apoptosis in transplanted HER2/neu tumors with Pik3r1 ablation 124
Figure 3.16 Model: heterozygous or homozygous Pik3r1 ablation has a
similar effect on HER2/neu-driven tumorigenesis 130 Chapter 4
Figure 4.1 Model: modulation of p85g levels might produce a range of RTK-mediated PI3K activity 140
x
Index of Tables
Chapter 1
Table 1.1 Class I PI3K isoform alterations in cancer 4 Table 1.2 Pan-PI3K inhibitors and their clinical applications 29 Table 1.3 Dual pan-PI3K/mTOR inhibitors and their clinical applications 30 Table 1.4 Isoform-selective PI3K inhibitors and their clinical applications 31 Table 1.5 Combination of PI3K inhibitors with other targeted therapies
in the clinic 33 Chapter 2
Table 2.1 PIK3R1 expression is significantly reduced in breast cancers across multiple microarray datasets 55
Chapter 3
Table 3.1 Nulliparous female mice with mammary-specific Pik3r1 ablation develop spontaneous mammary tumors 106
Table 3.2 Comparison of mammary tumor development in Pik3r1 knockout
mice to other established GEMMs of breast cancer 107
xi
List of Abbreviations
4G10 antibody clone specific to phosphotyrosines
ALL acute lymphoblastic leukemia
AML acute myeloid leukemia
ANOVA analysis of variance
BCL2 B cell lymphoma 2
BCL-XL B cell lymphoma-extra large
BCR B cell receptor
BET bromodomain and extraterminal domain
BH breakpoint cluster homology domain
BSA bovine serum albumin
C/EBPく CCAAT/enhancer binding protein beta
Ca2+ calcium ion
CDK4 cyclin-dependent kinase 4
CDK6 cyclin-dependent kinase 6
CEF chicken embryo fibroblast
CLL chronic lymphocytic leukemia
CML chronic myelogenous leukemia
CRPC castration-resistant prostate cancer
CSF1 colony stimulating factor 1
DDp53 dominant negative p53 mutant
DM1 mertansine, a cytotoxic agent
DMEM Dulbecco’s modified eagle medium
DMEM/F12 Dulbecco’s modified eagle medium, nutrient mixture F1β
DTT dithiothreitol
EDTA ethylenediaminetetraacetic acid
xii
EGF epidermal growth factor
EGFR epidermal growth factor receptor
ERK extracellular signal-regulated kinase
ESCC esophageal squamous cell carcinoma
FBS fetal bovine serum
FOXO forkhead box O transcription factors
GAP GTPase activating protein
GBM glioblastoma multiforme
GEF guanine nucleotide exchange factor
GEMM genetically engineered mouse model
GIST gastrointestinal stromal tumor
GPCR G-protein coupled receptor
H&E hematoxylin and eosin
HCC hepatocellular carcinoma
HMEC human mammary epithelial cell
hTERT human telomerase reverse transcriptase
ID2 inhibitor of DNA binding 2
IGF1 insulin-like growth factor 1
IHC immunohistochemistry
INHL indolent non-Hodgkin lymphoma
INPP4B type II inositol 3,4-bisphosphate 4-phosphatase
IP immunoprecipitation
IR insulin receptor
IRES internal ribosomal entry site
IRS1 insulin receptor substrate 1
iSH2 inter-SH2 domain
xiii
JAK2 Janus kinase 2
KI gene knock-in
KO gene knockout
LPA lysophosphatidic acid
LTR long terminal repeat
MAPK mitogen-activated protein kinase
MCL mantle cell lymphoma
MCL1 myeloid cell leukemia sequence 1
MEF mouse embryo fibroblast
MEK MAPK/ERK kinase
miRNA micro RNA
MM multiple myeloma
MMEC mouse mammary epithelial cell
MMTV mouse mammary tumor virus
mRNA messenger RNA
MTM myotubularin family phosphatases
mTOR mammalian target of rapamycin
mTORC1 mTOR complex 1
NcrNu Ncr nude athymic mouse strain
NRG1 neuregulin 1
NSCLC non-small cell lung carcinoma
P proline-rich domain
p16INK4A cyclin-dependent kinase 4 inhibitor A
p85 BD p85-binding domain
p90RSK p90 ribosomal S6 kinase
PAGE polyacrylamide gel electrophoresis
xiv
PARP poly-(ADP-ribose) polymerase
PBS phosphate buffered saline
PCR polymerase chain reaction
PHTS PTEN hamartoma tumor syndrome
PI phosphatidylinositide; see also PtdIns
PI3K phosphatidylinositol 3-kinase
PIN prostatic intraepithelial neoplasia
PIP phosphatidylinositol 3-phosphate; see also PtdIns(3)P
PIP2 PtdIns 4,5-bisphosphate; see also PtdIns(4,5)P2
PIP3 PtdIns 3,4,5-trisphosphate; see also PtdIns(3,4,5)P3
PPARけ peroxisome proliferator-activated receptor gamma
PPRE peroxisome proliferator response element
PR prolactin receptor
PtdIns phosphatidylinositide; see also PI
PtdIns(3)P phosphatidylinositol 3-phosphate; see also PIP
PtdIns(3,4)P2 PtdIns 3,4-bisphosphate
PtdIns(3,4,5)P3 PtdIns 3,4,5-trisphosphate; see also PIP3
PtdIns(4,5)P2 phosphatidylinositol 4,5-bisphosphate; see also PIP2
PTEN phosphatase and tensin homolog phosphatase
PyMT polyoma middle T
qPCR quantitative polymerase chain reaction
RANKL receptor activator of nuclear factor kappa-B ligand
RBD RAS-binding domain
RNAi RNA interference
RTK receptor tyrosine kinase
S6K p70 ribosomal protein S6 kinase
xv
SABCS San Antonio Breast Cancer Symposium
SCCHN squamous cell carcinoma of the head and neck
SD standard deviation
SDS sodium dodecyl sulfate
SEM standard error of the mean
SHH sonic hedgehog
shRNA short hairpin RNA
SLL small lymphocytic leukemia
SMO smoothened
sqNSCLC squamous non-small cell lung cancer
STAT3 signal transducer and activator of transcription 3
STAT5 signal transducer and activator of transcription 5
T-ALL T cell acute lymphoblastic leukemia
TBS tris-buffered saline
TBST tris-buffered saline with tween
TCC transitional cell carcinoma
TCGA The Cancer Genome Atlas
TCR T cell receptor
T-DM1 conjugate of DM1 to the monoclonal antibody Trastuzumab
TEB terminal end bud
TNBC triple-negative breast cancer
TUNEL terminal deoxynucleotidyl transferase dUTP nick end labeling
UTR untranslated region
WCL whole cell lysate
xvi
Glossary of Terms
Angiogenesis: the formation of new blood vessels from pre-existing vessels. Physiological angiogenesis is critical for normal growth and development, while pathophysiological angiogenesis is important for tumor growth. Myristoylated: irreversible co-translational modification of proteins in which a myristoyl group is covalently attached to an N-terminal amino acid of a nascent polypeptide, promoting membrane localization of the modified protein. Congenital mosaic overgrowth syndromes: a clinically heterogeneous group of genetic disorders characterized by abnormal progressive localized growth. They are caused by diverse somatic mutations and associated with increased cancer risk. Inter-SH2 (iSH2) domain: the domain of p85 regulatory PI3K isoforms that is located between the C- and N-terminal SH2 domains and directly interacts with class IA p110 catalytic isoforms. Megalencephaly syndromes: a collection of sporadic overgrowth disorders characterized by enlarged brain size and other distinct features. SH2 domain: SRC homology 2 domain; a structurally conserved protein–protein interaction domain that facilitates interaction with phosphorylated tyrosine residues on other proteins. RAS superfamily proteins: small monomeric membrane-associated GTPases, which are divided into the RAS, RHO, RAB, ARF, and RAN subfamilies based on structure and function. RAS GTPases: subfamily of RAS superfamily GTPases that plays critical roles in signal transduction. In mammals, the three major RAS subfamily members are HRAS, KRAS, and NRAS. RHO GTPases: subfamily of RAS superfamily proteins that shares similar roles in signal transduction to RAS GTPases and is best characterized for the regulation of cell shape, movement, and polarity. Xenograft: transplantation of living cells, tissues, or organs from one species to another. Human cell lines are often xenografted into mice to study factors affecting tumor growth.
Chapter 1: Introduction
2
Acknowledgements
A manuscript based on the work in this chapter was accepted for publication in Nature
Reviews Cancer and is currently in press with the following authors: Lauren Thorpe,
Haluk Yuzugullu, and Jean Zhao. This content has been used in accordance with Nature
Publishing Group policy, which states that authors retain the right to reproduce their
contribution in whole or in part in any printed volume of which they are an author. It has
been reformatted to adhere to dissertation formatting guidelines.
Haluk Yuzugullu and Jean Zhao wrote the section on therapeutic targeting of PI3K
isoforms in cancer, and Lauren Thorpe wrote all other sections. Lauren Thorpe, Haluk
Yuzugullu, and Jean Zhao edited the manuscript, and Lauren Thorpe and Haluk
Yuzugullu prepared the tables and figures.
We would additionally like to thank Tom Roberts for critical reading of the manuscript,
and Tom Roberts and Lewis Cantley for helpful discussions.
3
Preface
Phosphatidylinositol 3-Kinases (PI3Ks) are critical coordinators of intracellular signaling
in response to extracellular stimuli. Hyperactivation of PI3K signaling cascades is one of
the most common events in human cancers. In this chapter, we discuss recent advances
in our knowledge of the roles of distinct PI3K isoforms in normal and oncogenic
signaling, the different ways in which PI3K can be upregulated, and the current state and
future potential of targeting this pathway in the clinic.
Introduction
Phosphatidylinositol 3-Kinases (PI3Ks) are a family of lipid kinases that integrate signals
from growth factors, cytokines, and other environmental cues, translating them into
intracellular signals that regulate multiple signaling pathways. These pathways control
many physiological functions and cellular processes, including cell proliferation, growth,
survival, motility, and metabolism (Engelman et al., 2006; Liu et al., 2009;
Vanhaesebroeck et al., 2010). Activating alterations in PI3K are frequent in a variety of
cancers (Table 1.1; for a fully referenced version see Appendix A), making this class of
enzymes a prime drug target (Engelman, 2009; Liu et al., 2009). Tremendous efforts
have been devoted to the development of effective PI3K inhibitors for cancer therapy.
Initial PI3K-directed drugs in clinical trials, consisting largely of non-isoform-selective
pan-PI3K inhibitors, have not yielded exciting results. However, recent preclinical studies
have demonstrated that different PI3K isoforms play divergent roles in cellular signaling
and cancer, suggesting that inhibitors targeting individual isoforms may be able to
achieve greater therapeutic efficacy. Isoform-selective inhibitors are now emerging in the
clinic, and have had promising success. In this chapter, we provide an update on what
has been learned in recent years about PI3K isoform-specific functions, differences in
the modes of PI3K isoform activation, and the progress of isoform-selective inhibitors in
4
Table 1.1: Class I PI3K isoform alterations in cancer
Alteration Type Cancer Type Frequency of Alteration
Sample Size Range
Class IA
PIK3CA (p110g) Mutation Endometrial 10.3-53.0% 29-232 Breast 7.1-35.5% 65-507 Ovarian 33.0% 97 Colorectal 16.9
†-30.6%
72-195
Bladder 5.0-20.0% 20-130 Lung 0.6-20.0% 5-183 Cervical 13.6% 22 Glioblastoma 4.3-11.0% 91-291 Head and neck 8.1-9.4%
32-74
Esophageal 5.5%
145 Melanoma 5.0%
121
Prostate 1.3-3.6%
55-156 Sarcoma 2.9%
207
Renal 1.0-2.9%
98-417 Liver 1.6% 125 Megalencephaly
‡ 48.0% 50
Copy number Head and neck 9.1-100% 11-117 gain/amplification Cervical 9.1-76.4% 22-55 Lung 9.5-69.6% 3-92 Lymphoma 16.7-68.2% 22-60 Ovarian 13.3-39.8% 60-93 Gastric 36.4% 55 Thyroid 30.0% 110 Prostate 28.1% 32 Breast 8.7-13.4% 92-209 Glioblastoma 1.9-12.2% 139-206 Endometrial 10.3% 29 Thyroid 9.4% 128 Esophageal 5.7% 87 Leukemia 5.6% 161
Increased expression Prostate 40.0% 25
PIK3CB (p110く) Mutation Breast 0.5% 183
Copy number Lung 56.5% 46 gain/amplification Thyroid 42.3% 97 Ovarian 5-26.9% NA-93
Lymphoma 20.0% 60
Glioblastoma 5.8% 103 Breast 4.9-5% NA-81
Increased expression Prostate 46.7% 30 Glioblastoma 3.9% 103
PIK3CD (p110h) Copy number gain Glioblastoma 40.0% 10
Increased expression Neuroblastoma 52.6% 19 Glioblastoma 5.8% 103
5
Table 1.1: Class I PI3K isoform alterations in cancer (continued)
Alteration Type Cancer Type Frequency of Alteration
Sample Size Range
Class IA
PIK3R1 (p85g, p55g, p50g) Mutation Endometrial 19.8-32.8% 108-243 Pancreatic 16.7% 6 Glioblastoma 7.6-11.3% 91-291 Colorectal 4.6
†-8.3% 108-195
Melanoma 4.4% 68 Ovarian 3.8% 80 Esophageal 3.4%
145
Breast 1.1-2.8% 62-507 Colon 1.7% 60
Decreased expression Breast 61.8% 458 Prostate 17-75%* NA Lung 19-46%* NA Ovarian 22%* NA Breast 18%* NA Bladder 18%* NA
Copy number loss Ovarian 21.5% 93
PIK3R2 (p85く) Mutation Endometrial 4.9% 243 Colorectal 0.9% 108 Megalencephaly
‡ 22.0% 50
Amplification Lymphoma 23.3% 60
Increased expression Colon 55.0% 20 Breast 45.7% 35
PIK3R3 (p55け) Copy number gain Ovarian 15.0% 93
Class IB
PIK3CG (p110け) Copy number gain Ovarian 19.3% 93
Increased expression Breast 77.5% 40
Prostate 72.4% 29
Medulloblastoma 52.9% 17
PIK3R5 (p101)
Mutation Melanoma 38.2% 68 Gastric 2.7% 37
For further detail and references, see the expanded version of this table in Appendix A. ‡ Megalencephaly syndromes are a collection of sporadic overgrowth disorders characterized by enlarged brain size and other distinct features. † Combined number of hypermutated and non-hypermutated colon and colorectal patient samples with mutations in the indicated gene. * Represents the percent reduction in gene expression. NA Sample size not available for this study.
6
preclinical and early clinical studies.
Multiple PI3K classes and isoforms
PIγKs phosphorylate the γ’-hydroxyl group of phosphatidylinositides (PtdIns). They are
divided into three classes based on their structures and substrate specificities (Figure
1.1). In mammals, class I PI3Ks are further divided into subclasses IA and IB based on
their modes of regulation. Class IA PI3Ks are heterodimers of a p110 catalytic subunit
and a p85 regulatory subunit. The genes PIK3CA, PIK3CB, and PIK3CD respectively
encode three highly homologous class IA catalytic isoforms, p110g, p110く, and p110h.
These isoforms associate with any of five regulatory isoforms, p85g (and its splicing
variants p55g and p50g, encoded by PIK3R1), p85く (PIK3R2), and p55け (PIK3R3),
collectively called p85 type regulatory subunits (reviewed in (Engelman et al., 2006;
Mellor et al., 2012)). Class IB PIγKs are heterodimers of a p110け catalytic subunit
(encoded by PIK3CG) coupled with regulatory isoforms p101 (PIK3R5) or p87 (p84 or
p87PIKAP, encoded by PIK3R6). While p110g and p110く are ubiquitously expressed,
p110h and p110け expression is largely restricted to leukocytes (Okkenhaug and
Vanhaesebroeck, 2003).
In the absence of activating signals, p85 interacts with p110, inhibiting p110 kinase
activity. Upon receptor tyrosine kinase (RTK) or G-protein coupled receptor (GPCR)
activation, class I PI3Ks are recruited to the plasma membrane, where p85 inhibition of
p110 is relieved and p110 phosphorylates PtdIns 4,5-bisphosphate (PtdIns(4,5)P2) to
generate PtdIns(3,4,5)P3 (Figure 1.2). This lipid product acts as a second messenger,
activating AKT-dependent and –independent downstream signaling pathways (reviewed
in (Engelman et al., 2006; Liu et al., 2009; Vanhaesebroeck et al., 2010)). The
phosphatase and tensin homolog (PTEN) lipid phosphatase removes the γ’ phosphate
7
Figure 1.1: The PI3K family comprises multiple classes and isoforms. PI3Ks are classified based on their substrate specificities and structures. In vivo, class IA and IB PI3Ks phosphorylate PtdIns(4,5)P2, while class III PI3Ks phosphorylate PtdIns. Some evidence suggests that class II PI3Ks may also preferentially phosphorylate PtdIns in vivo (Falasca et al., 2007; Maffucci et al., 2005; Yoshioka et al., 2012). Class IA PI3Ks are heterodimers of a p110 catalytic subunit and a p85 regulatory subunit. Class IA catalytic isoforms (p110g, p110く, and p110h) possess a p85-binding domain (p85 BD), RAS-binding domain (RBD), helical domain, and catalytic domain. Class IA p85 regulatory isoforms (p85g, p85く, p55g, p55け, and p50g) possess an inter-SH2 (iSH2) domain that binds class IA catalytic subunits, flanked by SH2 domains that bind phosphorylated YXXM motifs. The longer isoforms, p85g and p85く, additionally possess N-terminal SH3 and breakpoint cluster homology (BH) domains. Class IB PI3Ks are heterodimers of a p110け catalytic subunit and a p101 or p87 regulatory subunit. p110け possesses an RBD, helical domain, and catalytic domain. The domain structures of p101 and p87 are not fully known, but a C-terminal region of p101 has been identified as binding Gくけ subunits (Vadas et al., 2013). The monomeric class II isoforms (PI3K-Cβg, PI3K-Cβく, and PIγK-Cβけ) possess an RBD, helical domain, and catalytic domain. VPS34, the only class III PI3K, possesses helical and catalytic domains. VPS34 forms a constitutive heterodimer with the myristoylated, membrane-associated VPS15 protein. Other indicated domains include proline-rich (P) domains and membrane-interacting C2 domains. Modified with permission from (Liu et al., 2009).
8
Figure 1.2: Signaling by class I PI3K isoforms. Upon receptor tyrosine kinase (RTK) or G-protein coupled receptor (GPCR) activation, class I PI3Ks are recruited to the plasma membrane by interaction with phosphorylated YXXM motifs on RTKs or their adaptors, or with GPCR-associated Gくけ subunits. There they phosphorylate PtdIns(4,5)P2 (PIP2) to generate PtdIns(3,4,5)P3 (PIP3), a second messenger which activates a number of AKT-dependent and –independent downstream signaling pathways regulating diverse cellular functions including growth, metabolism, motility, survival, and transformation. The phosphatase and tensin homolog (PTEN) lipid phosphatase removes the γ’ phosphate from PtdIns(γ,4,5)P3 to inactivate class I PI3K signaling. Modified with permission from (Liu et al., 2009).
9
from PtdIns(3,4,5)P3 to inactivate PI3K signaling.
Relatively little is known about class II PI3Ks. There are three class II isoforms, PI3K-
Cβg, PIγK-Cβく, and PIγK-Cβけ, respectively encoded by PIK3C2A, PIK3C2B, and
PIK3C2G. These monomeric lipid kinases do not possess a regulatory subunit. PI3K-
Cβg and PIγK-Cβく are broadly expressed, while PIγK-Cβけ expression is limited to the
liver, prostate, and breast (Falasca and Maffucci, 2012). Although early experiments
indicated that PI3K-Cβg and PIγK-Cβく could phosphorylate both PtdIns and PtdIns(4)P,
in vivo PtdIns may be the preferred substrate, generating PtdIns(3)P (Falasca et al.,
2007; Maffucci et al., 2005; Yoshioka et al., 2012). The physiological roles of class II
PI3Ks are not fully understood, but recent studies suggest that PI3K-Cβg is important in
angiogenesis (Yoshioka et al., 2012) and primary cilium function (Franco et al., 2014). In
addition, PI3K-Cβg and PIγK-Cβく have been reported to regulate cellular functions
including growth and survival (reviewed in (Falasca and Maffucci, 2012;
Vanhaesebroeck et al., 2010)) (Figure 1.3).
The single class III PI3K, VPS34, is encoded by PIK3C3. VPS34 forms a constitutive
heterodimer with the myristoylated, membrane-associated VPS15 (encoded by PIK3R4),
and phosphorylates PtdIns to produce PtdIns(3)P (Schu et al., 1993; Volinia et al.,
1995). In mammals, VPS34 is ubiquitously expressed (Volinia et al., 1995). The VPS34-
VPS15 dimer is found in distinct multiprotein complexes, which have critical roles in
intracellular trafficking and autophagy (reviewed in (Backer, 2008; Vanhaesebroeck et
al., 2010)) (Figure 1.4). The myotubularin (MTM) family phosphatases MTM1 and
MTMRβ remove the γ’ phosphate from PtdIns(γ)P, regulating the lipid products of class
II and III PI3Ks (Blondeau et al., 2000; Cao et al., 2008; Lu et al., 2012; Velichkova et al.,
2010).
10
Figure 1.3: Signaling by class II PI3K isoforms. Class II PI3Ks are not well understood, but may be activated by a number of different stimuli, including hormones, growth factors, chemokines, cytokines, phospholipids, and calcium (Ca2+). Although in vitro class II PI3Ks can phosphorylate both PtdIns and PtdIns(4)P, in vivo this class may preferentially phosphorylate PtdIns (PI) to generate PtdIns(3)P (PIP) (Falasca et al., 2007; Maffucci et al., 2005; Yoshioka et al., 2012). Class II PI3Ks regulate cellular functions including glucose transport, endocytosis, cell migration, and survival. Myotubularin (MTM) family phosphatases remove the γ’ phosphate from PtdIns(γ)P to inactivate class II PI3K signaling.
11
Figure 1.4: Signaling by class III PI3K isoforms. The class III VPS34-VPS15 heterodimer is found in distinct multiprotein complexes, which perform specific cellular functions. VPS34 may be activated by stimuli including amino acids, glucose, and other nutrients, and phosphorylates PtdIns (PI) to generate PtdIns(3)P (PIP). It plays critical roles in autophagy, endosomal trafficking, and phagocytosis. MTM family phosphatases remove the γ’ phosphate from PtdIns(γ)P to inactivate class III PIγK signaling.
12
Alterations of PI3K isoforms in cancer
Overactivation of the PI3K pathway is one of the most frequent events in human
cancers. The most common mechanism leading to aberrant PI3K signaling is somatic
loss of PTEN via genetic or epigenetic alterations (reviewed in (Parsons, 2004; Song et
al., 2012)). The PI3K pathway can also be upregulated by activation of RTKs, or
alterations in isoforms of PI3K itself (Table 1.1).
Class I PI3K catalytic isoform alterations
The transforming potential of class I PI3K catalytic isoforms was first demonstrated by
studies in the late 1990s and early β000s, which showed that fusion of p110g to viral
sequences (Chang et al., 1997) or the SRC myristoylation sequence (Klippel et al.,
1996; Zhao et al., 2003; Zhao et al., 2005) was activating and highly oncogenic. The
2004 discovery of frequent PIK3CA mutations in human cancers (Samuels et al., 2004)
brought PI3K to the forefront as a major cancer driver and potential drug target. PIK3CA
mutation has since been firmly established as causative in many cancer types (Table
1.1). Missense mutations occur in all domains of p110g, but the majority cluster in two
hotspots, the most common being E542K and E545K in the helical domain and H1047R
in the kinase domain. Cell-based analyses confirmed that these hotspot mutations
confer transformation via constitutive activation of p110g (Isakoff et al., 2005; Kang et
al., 2005; Zhao et al., 2005). Subsequently, several studies using genetically engineered
mouse models (GEMMs) demonstrated roles for mutant PIK3CA in tumor initiation,
progression, and maintenance (Engelman et al., 2008; Kinross et al., 2012; Liu et al.,
2011; Wu et al., 2013; Yuan et al., 2013) (Appendix B). Helical domain mutations
reduce inhibition of p110g by p85 (Burke et al., 2012; Huang et al., 2007; Miled et al.,
2007; Zhao and Vogt, 2010) or facilitate direct interaction of p110g with insulin receptor
substrate 1 (IRS1) (Hao et al., 2013), while kinase domain mutations increase interaction
13
of p110g with lipid membranes (Burke et al., 2012; Huang et al., 2007; Mandelker et al.,
2009). Other PIK3CA mutations mimic distinct structural conformation changes that
occur during activation of PI3K (Burke et al., 2012). Interestingly, some of these
mutations in PIK3CA have also been reported in congenital mosaic overgrowth
syndromes (Kurek et al., 2012; Orloff et al., 2013; Rios et al., 2013; Riviere et al., 2012).
In contrast, mutations in other class I catalytic isoforms are rare. While activating
PIK3CD mutations have been described in immune deficiencies (Angulo et al., 2013;
Lucas et al., 2014), they have not been linked to cancer. One PIK3CB mutation was
detected in a single case of breast cancer (Kan et al., 2010); this helical domain
substitution enhances basal PIγK activation, potentially by increasing p110く association
with membranes (Dbouk et al., 2013). Recent structural studies have indicated that
p110く may be less inhibited by p85 (Dbouk et al., 2010; Vogt, 2011; Zhang et al., 2011)
and thus has higher basal transforming potential. Interestingly, p110h expression has
been detected in some human solid cancer cell lines (Sawyer et al., 2003), and
overexpression of wildtype p110く, p110h, or p110け, but not p110g, transforms cells in
vitro (Kang et al., 2006). This is consistent with the fact that PIK3CB, PIK3CD, and
PIK3CG are generally amplified or overexpressed, but not mutated, in cancers (Table
1.1).
Class I PI3K regulatory isoform alterations
Recent studies have converged to implicate the p85 regulatory isoforms in
tumorigenesis. Since the initial discovery of PIK3R1 mutations in human cancer cell lines
and primary tumors (Philp et al., 2001), somatic mutations in PIK3R1 have been
identified in a number of different cancers (Cancer Genome Atlas Research, 2008;
Cheung et al., 2011; Cizkova et al., 2013; Jaiswal et al., 2009; Urick et al., 2011) (Table
14
1.1). The majority are substitutions or in-frame insertions or deletions in the inter-SH2
(iSHβ) domain of p85g (Cancer Genome Atlas Research, 2008; Cheung et al., 2011;
Jaiswal et al., 2009; Urick et al., 2011), the region of the protein that makes contact with
p110 (Huang et al., 2007), indicating this domain as a mutation hotspot (Cheung et al.,
2011). A number of these iSH2 domain mutants retain the ability to bind and stabilize
p110 isoforms, but promote enhanced PI3K activity and transformation due to reduced
ability to inhibit p110 (Cheung et al., 2011; Jaiswal et al., 2009; Sun et al., 2010; Urick et
al., 2011; Wu et al., 2009).
In addition, reduced expression of PIK3R1 has been reported in some cancers (Cizkova
et al., 2013; Taniguchi et al., 2010) (Table 1.1). PIK3R1 mRNA levels inversely
correlated with malignancy grade and incidence of metastasis in both breast and liver
cancers (Cizkova et al., 2013; Taniguchi et al., 2010). In mice, Pik3r1 ablation increased
epithelial neoplasia driven by Pten loss (Luo et al., 2005c) and led to spontaneous
development of aggressive liver tumors (Taniguchi et al., 2010). This work indicates that
p85g can negatively regulate PIγK signaling in cancer, and suggests that p85g has
tumor suppressive functions in certain tissues (Luo and Cantley, 2005).
Alterations in genes encoding other regulatory isoforms have also been detected, albeit
at a lower frequency. Increased PIK3R2 expression has been reported in breast and
colon cancers (Cortes et al., 2012) (Table 1.1). Consistent with this, overexpression of
wildtype p85く increased PIγK pathway activation in cells and tumor formation in mice
(Cortes et al., 2012). Somatic PIK3R2 mutations have been found in endometrial and
colorectal cancers (Cheung et al., 2011; Jaiswal et al., 2009), and causative germline
PIK3R2 mutations have been reported in megalencephaly syndromes (Riviere et al.,
2012). All PIK3R2 mutations described to date are substitutions with no apparent
15
hotspot region, and similar to some p85g mutants, mutations in p85く increase PIγK
activation without affecting p110 binding (Cheung et al., 2011). Together these studies
indicate that PI3K regulatory isoforms may contribute to tumorigenesis by multiple
mechanisms.
Class II PI3K isoform alterations
Although class II PI3Ks are not well understood, PIK3C2A or PIK3C2B expression has
been implicated in physiological functions important to tumorigenesis (Biswas et al.,
2013; Diouf et al., 2011; Elis et al., 2008; Katso et al., 2006; Maffucci et al., 2005).
PIK3C2B amplification has been reported in glioblastoma (Knobbe and Reifenberger,
2003; Nobusawa et al., 2010; Rao et al., 2010), and somatic PIK3C2B mutations were
detected in non-small cell lung cancer (Liu et al., 2012), but the functional consequence
of these mutations is unknown. Perhaps the most convincing evidence towards a role for
class II PI3Ks in tumorigenesis comes from a recent study demonstrating that mice with
Pik3c2a ablation had compromised angiogenesis and vascular barrier integrity, and
significant reduction in the size and microvessel density of implanted tumors (Yoshioka
et al., 2012). Since mice with embryonic Pik3c2a or Pik3c2b knockout (KO) are viable
(Harada et al., 2005; Harris et al., 2011), a class II-selective PI3K inhibitor might target
tumor angiogenesis with tolerable side effects, although toxicity due to the critical role of
PI3K-Cβg in maintaining normal renal homeostasis (Harris et al., 2011) would need to be
considered.
Type II inositol 3,4-bisphosphate 4-phosphatase (INPP4B), the phosphatase responsible
for dephosphorylation of PtdIns(3,4)P2 to PtdIns(3)P (Gewinner et al., 2009; Norris et al.,
1997), has also been implicated in cancer. In human mammary cell lines, INPP4B
knockdown increased AKT activation and transformation (Fedele et al., 2010; Gewinner
16
et al., 2009). INPP4B loss-of-heterozygosity has been detected in cancers (Gewinner et
al., 2009; Stjernstrom et al., 2014), and reduced INPP4B expression has been correlated
with high tumor grade, earlier recurrence, and decreased survival (Fedele et al., 2010;
Gewinner et al., 2009; Hodgson et al., 2011). Identification of INPP4B as a tumor
suppressor suggests that deregulation of the class II PI3K lipid products may contribute
to tumorigenesis.
Class III PI3K isoform alterations
There is currently little evidence indicating an oncogenic role for VPS34. One recent
study suggested that VPS34 is tyrosine-phosphorylated and activated downstream of
SRC, and its lipid kinase activity is required for SRC-mediated transformation (Hirsch et
al., 2010). However, overexpression of wildtype or myristoylated VPS34 was not
sufficient to induce cellular transformation (Denley et al., 2009). Another study indicated
that VPS34 activity might be decreased in the context of activated epidermal growth
factor receptor (EGFR) (Wei et al., 2013). Further investigation is needed to determine
whether VPS34 plays a role in transformation.
Divergent roles of class I PI3K catalytic isoforms
Class I PI3K catalytic isoforms share a conserved domain structure. They utilize the
same lipid substrates and generate the same lipid products. Despite their similarities,
accumulating evidence indicates these isoforms have distinct roles in mediating PI3K
signaling in physiological and oncogenic contexts.
GEMMs have been used to elucidate the roles of individual class I PI3K isoforms. Mice
with germline KO of Pik3ca or knock-in (KI) of a kinase-dead Pik3ca allele die at day
E10.5 (Bi et al., 2002; Bi et al., 1999). Interestingly, Pik3cb KO mice die much earlier at
17
day E3.5 (Bi et al., 2002), while kinase-dead Pik3cb KI mice develop to maturity with
minor defects in size and glucose metabolism, and major defects in male fertility (Ciraolo
et al., 2008; Ciraolo et al., 2010). These differences suggest an important kinase-
independent scaffolding role for p110く (Ciraolo et al., 2008). Germline inactivation of
Pik3cd or Pik3cg by KO or KI of kinase-dead alleles yields viable mice that grow to
adulthood; however, loss of p110h results in functional defects in lymphocytes,
neutrophils, and mast cells (Ali et al., 2004; Clayton et al., 2002; Jou et al., 2002;
Okkenhaug et al., 2002), while loss of p110け impairs thymocyte development, T cell
activation, and neutrophil migration (Martin et al., 2008; Sasaki et al., 2000; Yum et al.,
2001). These studies indicate non-redundant roles in mouse embryonic development for
p110g and p110く, the two ubiquitously expressed class I PIγK isoforms, and distinct
roles in the immune system and inflammatory response for p110h and p110け, the two
leukocyte-restricted isoforms.
Technological developments have facilitated further insight into the individual roles of
PI3K enzymes. The generation of conditional KO animals using the Cre/loxP
recombination system has allowed the functions of each isoform to be studied in
different tissues, stages of development, and pathological settings (Appendix B).
Additional progress has come from studies using RNA interference (RNAi) and a new
generation of isoform-selective PI3K inhibitors. These have advanced our understanding
of the roles of class I catalytic isoforms in mediating signaling downstream of RTKs,
GPCRs, and small GTPases (Figure 1.5 and Figure 1.6), and in the context of PTEN
deficiency (Figure 1.7).
In mediating RTK signaling
Binding of growth factor ligands induces RTK dimerization, activation, and auto-
18
phosphorylation of tyrosine-containing YXXM motifs on the receptors or their associated
adaptor proteins. Class IA p110-p85 heterodimers are then recruited to activated RTKs
through direct interaction of p85 SH2 domains with these phosphorylated YXXM motifs
(Rameh et al., 1995; Yu et al., 1998a; Yu et al., 1998b) (Figure 1.2). Accordingly p110g,
p110く, and p110h can complex with activated RTKs (Figure 1.5), and might be
expected to mediate growth factor signaling.
Studies using isoform-selective pharmacological inhibitors and genetic inactivation or
ablation indicated that loss of p110g activity was sufficient to largely block PI3K signaling
in response to a number of growth factors (Foukas et al., 2006; Graupera et al., 2008;
Knight et al., 2006; Sopasakis et al., 2010; Utermark et al., 2012; Zhao et al., 2006).
Notably, genetic ablation or inactivation of p110く had only a modest effect on PIγK
signaling following acute RTK activation (Ciraolo et al., 2008; Guillermet-Guibert et al.,
2008; Jia et al., 2008). It was suggested that the relative abundance of catalytic isoforms
in a particular tissue might dictate which isoforms are dominant in mediating RTK
signaling (Chaussade et al., 2007). This may explain the role of p110h, which is mainly
expressed in leukocytes and is the primary isoform regulating PI3K signaling
downstream of certain RTKs in mast cells and macrophages (Ali et al., 2004;
Papakonstanti et al., 2008; Vanhaesebroeck et al., 1999). However, differential
expression does not completely explain isoform dependence, as in many tissues p110く
levels are comparable to or even higher than levels of p110g (Geering et al., 2007).
The involvement of p110く in RTK signaling remained puzzling, until a recent study from
our group suggested a new model. In mice, while p110g ablation blocked normal
mammary development and mammary tumorigenesis driven by polyoma middle T
(PyMT) or HERβ (also known as ERBBβ), p110く ablation increased mammary gland
19
Figure 1.5: Divergent roles of class I PI3K catalytic isoforms in the context of RTK, GPCR, and small GTPase inputs. Class I PI3Ks mediate signaling downstream of RTKs, GPCRs, and small GTPases. Left: p85 regulatory subunits bind phosphorylated YXXM motifs on activated RTKs. Because p110g, p110く, and p110h bind p85, these isoforms mediate signaling downstream of RTKs. Recent evidence also suggests that p87-p110け may be activated by certain RTKs (Schmid et al., 2011). Middle: Small GTPases synergize with RTK and GPCR signals to directly activate PI3Ks by interacting with their RAS-binding domains (RBDs). Isoforms p110g, p110h, and p110け bind RAS family GTPases, while p110く binds the RHO family GTPases RAC1 and CDC42 (Fritsch et al., 2013). Right: Gg and Gくけ proteins dissociate from activated GPCRs. Catalytic isoforms p110く and p110け, and regulatory isoform p101, directly bind and are activated by Gくけ. p110h may be activated downstream of GPCRs, but the mechanism is unknown (Durand et al., 2009; Reif et al., 2004; Saudemont et al., 2009). Gg proteins have been reported to directly bind and inhibit p110g (Ballou et al., 2006; Ballou et al., 2003; Yeung and Wong, 2010). Modified with permission from (Vanhaesebroeck et al., 2010).
20
Figure 1.6: Competition model for p110g and p110く regulation of RTK-mediated PI3K signaling. Based on work presented in (Utermark et al., 2012). Both p85-p110g and p85-p110く compete for phosphorylated YXXM sites on activated RTKs. However, the maximal specific activity and enzymatic rate of p110g are higher than that of p110く (Beeton et al., 2000; Meier et al., 2004), and RTK-associated p110g may have higher lipid kinase activity than p110く (Utermark et al., 2012). By this model, loss or inactivation of p110g or p110く differentially modulates RTK signaling. Knockout of p110g allows all sites to be occupied by the less active p110く, decreasing RTK output. Conversely, knockout of p110く allows all sites to be bound by the more active p110g, increasing RTK output. Genetically or pharmacologically inactivated p110g or p110く can still bind RTKs but cannot signal, reducing RTK output.
21
Figure 1.7: Molecular contexts dictating applications for isoform-selective PI3K inhibitors. Red box: Upregulation or mutation of receptor tyrosine kinases (RTKs), oncogenic RAS mutations, or activating p110g mutations all increase PtdIns(γ,4,5)P3
production through p110g, which can be amplified by mutation or loss of PTEN. In these contexts use of p110g-selective inhibitors is effective. Blue box: In the absence of other oncogenic alterations, PTEN loss or mutation increases PtdIns(3,4,5)P3 production through p110く, perhaps due to RAC1- or CDC42-mediated p110く activation, or the basal activity of this isoform. In this context use of p110く-selective inhibitors is effective. Green box: Upregulation or mutation of B cell receptors (BCRs), cytokine receptors, or other immune cell surface markers increases PtdIns(3,4,5)P3 production through p110h. In this context use of p110h-selective inhibitors is effective.
22
outgrowth and accelerated tumor formation driven by these oncogenic RTKs (Utermark
et al., 2012). To explain this negative role of p110く, a competition model was proposed:
if p110g has higher RTK-associated lipid kinase activity than p110く, the less-active
p110く could compete with p110g for phosphorylated YXXM sites on receptors to
modulate PI3K signal strength downstream of RTKs (Utermark et al., 2012) (Figure 1.6).
Although direct comparison of RTK-associated p110g and p110く lipid kinase activity has
not been shown, the maximal specific activity and enzymatic rate of p110g are higher
than that of p110く (Beeton et al., 2000; Meier et al., 2004). Biochemical data were
consistent with this proposed model, demonstrating that in p110く KO cells, activated
RTKs had more bound p110g and higher associated lipid kinase activity (Utermark et al.,
2012). Furthermore, pharmacologically inactivated p110く could still compete with p110g
for binding sites on activated receptors, modestly reducing signaling and tumor growth
driven by PyMT or HER2 (Utermark et al., 2012). This model also explains moderately
decreased AKT activation, mild hyperglycemia, and delayed HER2-driven tumor
formation observed in mice with KI of kinase-dead p110く (Ciraolo et al., 2008), a
scenario mimicking p110く-selective kinase inhibition. These studies not only reveal a
novel p110く-based regulatory mechanism in RTK-mediated PI3K signaling, but also
identify p110g as an important target in cancers driven by oncogenic RTKs.
Initial studies suggested that class IA isoforms mediated signaling downstream of RTKs,
while the class IB isoform signaled downstream of GPCRs. Although p110け activation by
GPCRs is well established, a recent report suggested that this class IB isoform might
also function downstream of RTKs through regulatory isoform p87 in mouse myeloid
cells (Schmid et al., 2011) (Figure 1.5). Given that p87 and p101 may have distinct
tissue distribution (Bohnacker et al., 2009; Shymanets et al., 2013; Voigt et al., 2006)
and non-redundant functions (Bohnacker et al., 2009; Kurig et al., 2009; Schmid et al.,
23
2011; Shymanets et al., 2013), this suggests that the two class IB regulatory isoforms
may mediate p110け activation in response to specific upstream signals.
In mediating GPCR signaling
GPCRs are a family of seven-transmembrane domain receptors that associate with
heterotrimeric G proteins composed of the Gg and Gくけ subunits. Ligand binding to
GPCRs results in allosteric activation and disassociation of bound G proteins into their
separate subunits, which can then act on intracellular targets.
The single class IB PIγK isoform, p110け, is activated by G proteins (Brock et al., 2003;
Maier et al., 1999; Stoyanov et al., 1995) (Figure 1.2). Although association of p110け
with either its p101 or p87 regulatory isoforms increased its activation in response to Gくけ
(Brock et al., 2003; Stephens et al., 1997; Suire et al., 2005), recent evidence indicated
that p101 is the main regulatory isoform involved in GPCR-mediated p110け signaling
(Kurig et al., 2009; Schmid et al., 2011) (Figure 1.5). Both p110け and p101 interact
directly with Gくけ heterodimers, and these contacts are critical for signaling and
transformation mediated by p110け (Brock et al., 2003; Vadas et al., 2013). Recent
studies have shown that in myeloid cells, p110け can be activated by GPCR and RTK
signals in a RAS- or RAP1A-dependent manner to mediate integrin g4く1 activity,
leading to tumor inflammation and progression (Schmid et al., 2011; Schmid et al.,
2013). Thus p110け-mediated signaling may contribute to tumorigenesis by controlling
both tumor cell characteristics and the tumor microenvironment.
Interestingly, in vitro experiments (Kubo et al., 2005; Kurosu et al., 1997; Maier et al.,
1999; Murga et al., 2000) and subsequent GEMM studies (Ciraolo et al., 2008;
Guillermet-Guibert et al., 2008; Jia et al., 2008) demonstrated a role for p110く in G
24
protein-mediated PI3K signaling (Figure 1.2). Recently a region in the C2-helical domain
linker of p110く was shown to bind Gくけ subunits (Figure 1.5); this region is not present in
other class IA isoforms (Dbouk et al., 2012), and is similar to the region of p110け that
binds Gくけ (Vadas et al., 2013). Abrogation of p110く-Gくけ interaction blocked p110く-
mediated signaling and transformation downstream of GPCRs, and inhibited the
proliferation and invasiveness of cancer cells (Dbouk et al., 2012). Although p110h does
not directly interact with G proteins, a non-redundant role for this isoform in GPCR-
mediated leukocyte migration has been demonstrated in certain contexts (Durand et al.,
2009; Reif et al., 2004; Saudemont et al., 2009); however, the mechanism of p110h
activation downstream of GPCRs is unknown. It has also been reported that some Gg
proteins directly bind and inhibit p110g (Ballou et al., 2006; Ballou et al., 2003; Yeung
and Wong, 2010). Clearly, class I PI3K isoforms cooperate with GPCRs in a number of
different ways to regulate signaling and transformation.
Downstream of RAS and other small GTPases
RAS superfamily proteins are direct activators of the PI3K pathway. All class I PI3K
catalytic isoforms possess an N-terminal RAS-binding domain (RBD) (Figure 1.1)
allowing them to interact with RAS GTPases or other RAS superfamily members (Figure
1.5).
Activated or oncogenic mutant RAS proteins directly bind and increase the enzymatic
activity of both p110g (Rodriguez-Viciana et al., 1994; Rodriguez-Viciana et al., 1996)
and p110け (Pacold et al., 2000; Rubio et al., 1997; Suire et al., 2002). Cellular and
structural studies suggest that p110け association with RAS might both increase its
membrane translocation (Kurig et al., 2009; Pacold et al., 2000) and allosterically
increase p110け kinase activity (Pacold et al., 2000). Interestingly, RAS is required for
25
activation of p110け bound to regulatory isoform p87, but not p101 (Kurig et al., 2009). In
vitro, the transforming capability of both helical domain p110g mutants (Zhao and Vogt,
2008, 2010) and of overexpressed wildtype p110け (Denley et al., 2008; Kang et al.,
2006) are dependent on their association with RAS. GEMM studies using KI of Pik3ca
with an RBD mutation or KO of endogenous Pik3ca revealed that the p110g-RAS
interaction is critical for both the initiation and maintenance of lung tumors (Castellano et
al., 2013; Gupta et al., 2007) and the development of myeloid leukemia (Gritsman et al.,
2014) driven by oncogenic KRAS. In mice, p110け-RAS binding is required for
inflammation-induced PtdIns(3,4,5)P3 accumulation (Suire et al., 2006) and
inflammation-associated tumor progression (Schmid et al., 2011; Schmid et al., 2013).
These studies highlight the importance of p110g or p110け interaction with RAS in both
normal PI3K signaling and transformation.
Although p110h was shown to bind RAS in vitro (Fritsch et al., 2013; Vanhaesebroeck et
al., 1997), some studies indicated that p110h kinase activity was not stimulated by
HRAS, NRAS, or KRAS, but instead by RRAS and TC21 (also known as RRAS2)
(Murphy et al., 2002; Rodriguez-Viciana et al., 2004). Furthermore, B and T cells derived
from Tc21 KO mice displayed diminished PIγK activity and recruitment of p110h to T cell
receptors (TCRs) and B cell receptors (BCRs), suggesting that TC21 might function
upstream of p110h (Delgado et al., 2009). Thus PI3K signaling through p110h may be
regulated by additional RAS subfamily members.
It was initially anticipated that all p110 isoforms bearing a RBD might interact with RAS
GTPases. Surprisingly, in vitro studies determined that p110く kinase activity was not
stimulated by any RAS subfamily members (Rodriguez-Viciana et al., 2004). A recent
extensive biochemical study demonstrated that p110く is instead regulated by RAC1 and
26
CDC42 of the RHO GTPase subfamily (Fritsch et al., 2013) (Figure 1.5). Direct
interaction between the p110く RBD and RAC1 is important for GPCR-mediated
activation of p110く (Fritsch et al., 2013), indicating cooperative Gくけ and RHO GTPase
signaling through p110く. Previous studies reported that an intact RBD was required for
signaling and oncogenic transformation by wildtype p110く in cultured cells (Denley et
al., 2008; Kang et al., 2006), suggesting a potential role for RHO GTPase interaction
with p110く in transformation. Notably, RAC1 and CDC4β can also be activated
downstream of PI3K by PtdIns(3,4,5)P3-dependent guanine nucleotide exchange factors
(GEFs) and GTPase activating proteins (GAPs) (Klarlund et al., 1997; Krugmann et al.,
2002; Welch et al., 2002). The finding of distinct p110く regulation by RAC1 and CDC4β
expands PI3K signaling input by GTPases beyond the RAS subfamily, and also supports
the notion that PI3K can act both upstream and downstream of GTPases, potentially
allowing for positive feedback loops in cancer settings.
In PTEN deficiency
The PTEN lipid phosphatase counteracts class I PI3K activity, making it an important
tumor suppressor. Somatic loss of PTEN in human cancers is common. Germline PTEN
mutations are also found in several genetic disorders characterized by multiple
hamartomas with overgrowth phenotypes, collectively termed PTEN hamartoma tumor
syndromes (PHTS) (Liaw et al., 1997).
Pten KO mouse models provided a tool to explore the molecular mechanisms underlying
diseases caused by PTEN loss. While embryonic Pten KO is lethal (Di Cristofano et al.,
1998; Stambolic et al., 1998), heterozygous or conditional Pten KO animals
recapitulated human disease phenotypes, including development of prostate cancer
(Alimonti et al., 2010; Kwabi-Addo et al., 2001; Wang et al., 2003). Surprisingly, ablation
27
of p110く, but not p110g, blocked prostatic intraepithelial neoplasia (PIN) induced by
PTEN loss (Jia et al., 2008). Subsequent studies demonstrated a correlation between
PTEN deficiency and sensitivity to p110く knockdown or inhibition in human cancer cell
lines both in vitro and in mouse xenografts (Ni et al., 2012; Torbett et al., 2008; Wee et
al., 2008). However, the mechanism governing the specific importance of p110く in the
context of PTEN loss remains elusive. Perhaps the unique role for p110く as a
convergence point for GPCR and RAC1 or CDC42 signals (Figure 1.7) contributes to
transformation induced by PTEN deficiency. Structural studies have also suggested that
compared to p110g, p110く is less inhibited by p85, and may supply a basal level of
PtdIns(3,4,5)P3 (Dbouk et al., 2010; Vogt, 2011; Zhang et al., 2011). This may explain
why wildtype p110く can be oncogenic when it is overexpressed (Denley et al., 2008;
Kang et al., 2006) or when PTEN is lost.
Although p110く is the primary PIγK isoform involved in many cases of tumorigenesis
driven by PTEN loss, studies have shown that depending on the tissue type and
pathology both p110g and p110く may be involved (Berenjeno et al., 2012; Jia et al.,
2013; Schmit et al., 2014). Mice with Pten ablation in the basal epidermal compartment
require both p110g and p110く for the development of hyperproliferative epidermal
lesions closely resembling PHTS (Wang et al., 2013a; Wang et al., 2013b). In this
model, spatially distinct roles for these isoforms in epidermal compartments were
identified: p110g is responsible for RTK signaling in and survival of suprabasal cells,
whereas p110く is important for GPCR signaling in and proliferation of basal cells (Wang
et al., 2013a). In mice with thymocyte-specific Pten KO, not surprisingly both p110h and
p110け were required for the development of T cell acute lymphoblastic leukemia (T-ALL)
(Subramaniam et al., 2012). This suggests that in certain contexts, transformation driven
by PTEN loss may be governed by the PI3K isoforms that are dominant in that tissue or
28
compartment.
Since PTEN loss removes one mechanism of PI3K pathway negative regulation, the
specific roles of p110 isoforms in this pathogenic context can be influenced by other
activating inputs. These can be cues from the tissue microenvironment, or other co-
existing genetic events. A recent GEMM study demonstrated that concomitant activation
of oncogenic KRAS in ovarian endometrioid adenocarcinoma driven by Pten ablation
shifted the PIγK isoform reliance from p110く to p110g (Schmit et al., 2014) (Figure 1.7).
Consistent with this, a subset of PTEN-mutant human endometrioid endometrial cancer
cell lines harboring other PI3K-activating mutations were found to be resistant to p110く
inhibition (Weigelt et al., 2013). It is also possible that other genetic events downstream
of PI3K or in PI3K-independent pathways may render PTEN-null tumors less reliant on
PI3K. Thus determination of isoform dependency in PTEN-deficient tumors remains a
challenge.
Therapeutic targeting of PI3K isoforms in cancer
The central role of PI3K in cancer makes it an attractive therapeutic target. Enormous
efforts have focused on the development of drugs targeting PI3K, many of which are
undergoing clinical evaluation (Table 1.2, Table 1.3, and Table 1.4). Unlike drugs
targeting other oncogenic kinases, such as EGFR, BRAF, and ALK, PI3K inhibitors have
shown limited efficacy as mono-therapies in early trials on patients with tumors harboring
PI3K pathway activation (Rodon et al., 2013). The effectiveness of these early PI3K
inhibitors may have been limited by their lack of specificity, and by compensatory
signaling feedback loops and co-existing genetic and epigenetic alterations. The
development of novel isoform-selective PI3K inhibitors (Figure 1.7) and their rational
combination with other therapeutics (Figure 1.8 and Table 1.5) may substantially
29
Table 1.2: Pan-PI3K inhibitors and their clinical applications
Agent Company Target Trial stage* Tumor types*
BKM120 Novartis Class I PI3Ks I, II, and III NSCLC Endometrial Thyroid CRPC Breast Colorectal Head and neck GBM Renal cell B cell lymphoma GIST Melanoma Ovarian Prostate Pancreatic Leukemia Esophageal Cervical Non-Hodgkin lymphoma Squamous NSCLC Adv. solid tumors
GDC0941 Genentech Class I PI3Ks I and II Breast NSCLC Non-Hodgkin lymphoma Adv. solid tumors
BAY80-6946 Bayer Class I PI3Ks I and II Non-Hodgkin lymphoma Adv. solid tumors
ZSTK474 Zenyaku Kogyo Co. Class I PI3Ks I and II Adv. solid tumors
PX866 Oncothyreon Class I PI3Ks I and II Colorectal SCCHN Melanoma NSCLC Prostate GBM Adv. solid tumors
XL147 Exelixis/Sanofi-Aventis
Class I PI3Ks I and II Breast Endometrial Ovarian Lymphoma GBM NSCLC Adv. solid tumors
CH5132799 Chugai Pharma Europe
Class I PI3Ks I Adv. solid tumors
NSCLC, non-small cell lung carcinoma; CRPC, castration-resistant prostate cancer; GIST, gastrointestinal stromal tumor; SCCHN, squamous cell carcinoma of the head and neck; GBM, glioblastoma multiforme. * Data taken from an April 2014 search of http://www.clinicaltrials.gov.
30
Table 1.3: Dual pan-PI3K/mTOR inhibitors and their clinical applications
Agent Company Target Trial stage* Tumor types*
GDC0980 Genentech PI3K/mTOR I and II Prostate Breast Endometrial Renal cell Non-Hodgkin
lymphoma Adv. solid tumors
PF04691502 Pfizer PI3K/mTOR I Adv. solid tumors
BGT226 Novartis PI3K/mTOR I and II Adv. solid tumors
BEZ235 Novartis PI3K/mTOR I and II Breast Renal cell Prostate TCC ALL AML CML Pancreatic
neuroendocrine Adv. solid tumors
XL765 Sanofi PI3K/mTOR I GBM Adv. solid tumors
GSK2126458 GlaxoSmithKline PI3K/mTOR I Solid tumors Lymphoma
DS7423 Daiichi Sankyo PI3K/mTOR I Solid tumors
PWT33597 Pathway Therapeutics PI3K/mTOR I Adv. solid tumors
SF1126 Semafore Pharmaceuticals
PI3K/mTOR I Adv. solid tumors
PF05212384 Pfizer PI3K/mTOR I and II Adv. solid tumors
TCC, transitional cell carcinoma; ALL, acute lymphoblastic leukemia; AML, acute myeloid leukemia; CML, chronic myelogenous leukemia; GBM, glioblastoma multiforme. * Data taken from an April 2014 search of http://www.clinicaltrials.gov.
31
Table 1.4: Isoform-selective PI3K inhibitors and their clinical applications
Agent Company Target Trial stage* Tumor types*
BYL719 Novartis p110g I and II SCCHN ESCC Colorectal Breast GIST Kidney Pancreas Gastric Adv. solid tumors
GDC0032 Genentech p110g I Breast Adv. solid tumors
INK1117 Intellikine/Millenium p110g I Adv. solid tumors
AZD8186 Astra-Zeneca p110く I CRPC sqNSCLC TNBC Adv. solid tumors with
PTEN deficiency
GSK2636771 GlaxoSmithKline p110く I and II Adv. solid tumors with PTEN deficiency
SAR260301 Sanofi p110く I Adv. solid tumors Lymphoma
IPI145 Infinity p110h and p110け
I, II, and III CLL SLL ALL INHL Hematologic malignancies
AMG319 Amgen p110h I Lymphoid malignancies
CAL101 (GS101)
Gilead Sciences p110h I, II, and III INHL CLL MCL SLL Hodgkin lymphoma Non-Hodgkin lymphoma Other lymphomas AML MM Hematologic malignancies
GS9820 Gilead Sciences p110く and p110h
I Lymphoid malignancies
SCCHN, squamous cell carcinoma of the head and neck; ESCC, esophageal squamous cell carcinoma; GIST, gastrointestinal stromal tumor; CRPC, castration-resistant prostate cancer; sqNSCLC, squamous non-small cell lung cancer; TNBC, triple-negative breast cancer; CLL, chronic lymphocytic leukemia; SLL, small lymphocytic leukemia; ALL, acute lymphoblastic leukemia; INHL, indolent non-Hodgkin lymphoma; MCL, mantle cell lymphoma; AML, acute myeloid leukemia; MM, multiple myeloma. * Data taken from an April 2014 search of http://www.clinicaltrials.gov.
32
Figure 1.8: Rational combination of PI3K inhibitors and other targeted therapeutics. Pan-PI3K and dual pan-PI3K/mTOR inhibitors are currently being tested in clinical trials (grey box). These agents are being combined with mTOR-selective inhibitors (also in grey box), RAS-RAF-MEK-ERK pathway inhibitors (yellow box), RTK or other membrane-associated protein inhibitors (blue box), hormone signaling inhibitors (purple box), and other agents inhibiting the cell cycle, apoptosis machinery, or other signaling pathways (red box). Colored number symbols indicate targeted therapeutics currently in clinical trials for combination with the designated PI3K inhibitor. Asterisks denote targeted therapeutics expected to cooperate with PI3K therapies based on preclinical studies. For further detail, see Table 1.5.
33
Ta
ble
1.5
: C
om
bin
ati
on
of
PI3
K in
hib
ito
rs w
ith
oth
er
targ
ete
d t
hera
pie
s in
th
e c
lin
ic
Ag
en
t C
om
pa
ny
Ta
rget
Co
mb
inati
on
th
era
py t
ria
ls
Ag
en
t T
arg
et
Tu
mo
r ty
pe
s*
Cli
nic
al tr
ial*
Cla
ss
I p
an
-PI3
K in
hib
ito
rs
BK
M1
20
No
va
rtis
C
lass I
PI3
Ks
L
ap
atin
ib
F
ulv
estr
an
t
Tra
stu
zu
ma
b
L
etr
ozo
le
E
GF
R/H
ER
2
E
R
H
ER
2
A
rom
ata
se
B
reast
NC
T0
158
9861
N
CT
01
33
9442
N
CT
01
13
2664
N
CT
01
24
8494
G
efitin
ib
E
rlo
tin
ib
E
GF
R
E
GF
R
N
SC
LC
N
CT
01
57
0296
N
CT
01
48
7265
P
an
itu
mu
mab
EG
FR
Co
lore
cta
l N
CT
01
59
1421
C
etu
xim
ab
E
GF
R
H
ead
an
d n
eck
NC
T0
181
6984
B
eva
ciz
um
ab
V
EG
FR
†
GB
M
R
ena
l ce
ll N
CT
01
34
9660
N
CT
01
28
3048
IN
C2
80
c-M
ET
GB
M
NC
T0
187
0726
R
itu
xim
ab
C
D2
0
B
ce
ll ly
mp
hom
a
NC
T0
204
9541
Im
atin
ib
B
CR
-AB
L
G
IST
N
CT
01
46
8688
V
em
ura
fen
ib
E
ncora
fen
ib
B
RA
F
B
RA
F
M
ela
nom
a
NC
T0
151
2251
N
CT
01
82
0364
O
lap
arib
P
AR
P
T
NB
C
O
va
ria
n
NC
T0
162
3349
A
bira
tero
ne
a
ce
tate
CY
P1
7
P
rosta
te
NC
T0
163
4061
E
rism
od
eg
ib
T
ram
etin
ib
M
EK
16
2
E
ve
rolim
us
S
mo
oth
ene
d
M
EK
1/2
ME
K1
/2
m
TO
R
A
dv. so
lid tu
mo
rs
NC
T0
157
6666
N
CT
01
15
5453
N
CT
01
36
3232
N
CT
01
47
0209
GD
C0
94
1
Ge
ne
nte
ch
Cla
ss I
PI3
Ks
F
ulv
estr
an
t
Tra
stu
zu
ma
b
E
R
H
ER
2
B
reast
NC
T0
143
7566
N
CT
00
92
8330
B
eva
ciz
um
ab
V
EG
FR
†
Bre
ast
N
SC
LC
N
CT
00
96
0960
N
CT
00
97
4584
E
rlo
tin
ib
C
ob
ime
tin
ib
E
GF
R
M
EK
1
A
dv. so
lid tu
mo
rs
NC
T0
097
5182
N
CT
00
99
6892
34
Ta
ble
1.5
: C
om
bin
ati
on
of
PI3
K in
hib
ito
rs w
ith
oth
er
targ
ete
d t
hera
pie
s i
n t
he
clin
ic (
co
nti
nu
ed
)
Ag
en
t C
om
pa
ny
Ta
rget
Co
mb
inati
on
th
era
py t
ria
ls
Ag
en
t T
arg
et
Tu
mo
r ty
pe
s*
Cli
nic
al tr
ial*
Cla
ss
I p
an
-PI3
K in
hib
ito
rs
PX
86
6
On
co
thyre
on
Cla
ss I
PI3
Ks
C
etu
xim
ab
E
GF
R
C
olo
recta
l
SC
CH
N
NC
T0
125
2628
N
CT
01
25
2628
V
em
ura
fen
ib
B
RA
F
M
ela
nom
a
NC
T0
161
6199
XL
14
7
Exe
lixis
/ S
an
ofi-A
ve
ntis
Cla
ss I
PI3
Ks
T
rastu
zu
ma
b
L
etr
ozo
le
H
ER
2
A
rom
ata
se
B
reast
NC
T0
104
2925
N
CT
01
08
2068
E
rlo
tin
ib
M
M1
21
X
L6
47
E
GF
R
H
ER
3
R
TK
s
A
dv. so
lid tu
mo
rs
NC
T0
069
2640
N
CT
00
70
4392
N
CT
01
43
6565
Iso
form
-se
lec
tive
PI3
K i
nh
ibit
ors
BY
L7
19
No
va
rtis
p
11
0g
C
etu
xim
ab
E
GF
R
S
CC
HN
N
CT
01
60
2315
L
JM
71
6
H
ER
3
E
SC
C
NC
T0
182
2613
E
ncora
fen
ib
C
etu
xim
ab
B
RA
F
E
GF
R
C
olo
recta
l N
CT
01
71
9380
F
ulv
estr
an
t
ER
Bre
ast
A
dv. so
lid tu
mo
rs
NC
T0
208
8684
N
CT
01
21
9699
Im
atin
ib
B
CR
-AB
L
G
IST
N
CT
01
73
5968
L
etr
ozo
le
E
xe
me
sta
ne
T
DM
-1
L
EE
01
1
A
rom
ata
se
A
rom
ata
se
H
ER
2‡
C
DK
4/6
B
reast
NC
T0
187
0505
N
CT
01
87
0505
N
CT
02
03
8010
N
CT
02
08
8684
E
ve
rolim
us
E
xe
me
sta
ne
m
TO
R
A
rom
ata
se
B
reast
K
idn
ey
P
an
cre
as
NC
T0
207
7933
A
UY
92
2
H
SP
90
G
astr
ic
NC
T0
161
3950
G
an
itu
mab
B
GJ3
98
M
EK
16
2
IG
F1
R
F
GF
R
M
EK
1/2
A
dv. so
lid tu
mo
rs
NC
T0
170
8161
N
CT
01
92
8459
N
CT
01
44
9058
GD
C0
03
2
Ge
ne
nte
ch
p1
10g
L
etr
ozo
le
F
ulv
estr
an
t
Aro
ma
tase
E
R
B
reast
NC
T0
129
6555
35
Ta
ble
1.5
: C
om
bin
ati
on
of
PI3
K in
hib
ito
rs w
ith
oth
er
targ
ete
d t
hera
pie
s i
n t
he
clin
ic (
co
nti
nu
ed
)
Ag
en
t C
om
pa
ny
Ta
rget
Co
mb
inati
on
th
era
py t
ria
ls
Ag
en
t T
arg
et
Tu
mo
r ty
pe
s*
Cli
nic
al tr
ial*
Iso
form
-se
lec
tive
PI3
K i
nh
ibit
ors
INK
11
17
Inte
llikin
e/
Mill
en
ium
p
11
0g
M
LN
01
28
m
TO
RC
1/2
Ad
v. n
on
-h
em
ato
log
ical
ma
lign
an
cie
s
NC
T0
189
9053
SA
R2
60
30
1
Sa
no
fi
p1
10
く
Ve
mu
rafe
nib
BR
AF
Me
lan
om
a
NC
T0
167
3737
IPI1
45
In
fin
ity
p1
10
h an
d
p1
10け
O
fatu
mu
mab
C
D2
0
C
LL
S
LL
NC
T0
204
9515
R
itu
xim
ab
C
D2
0
H
em
ato
log
ic
ma
lign
an
cie
s
NC
T0
187
1675
AM
G3
19
Am
ge
n
p1
10
h
NC
T0
130
0026
CA
L1
01
(G
S1
01
) G
ilea
d S
cie
nce
s
p1
10
h
Ritu
xim
ab
Ofa
tum
um
ab
E
ve
rolim
us
B
ort
ezo
mib
C
D2
0
C
D2
0
m
TO
R
N
FせB
IN
HL
C
LL
M
CL
NC
T0
108
8048
G
S9
97
3
S
YK
He
ma
tolo
gic
m
alig
nan
cie
s
NC
T0
179
6470
E
ve
rolim
us
m
TO
R
M
CL
NC
T0
108
8048
Du
al p
an
-PI3
K/m
TO
R in
hib
ito
rs
GD
C0
98
0
Ge
ne
nte
ch
PI3
K/m
TO
R
F
ulv
estr
an
t
ER
Bre
ast
NC
T0
143
7566
A
bira
tero
ne
a
ce
tate
CY
P1
7
P
rosta
te
NC
T0
148
5861
B
eva
ciz
um
ab
V
EG
FR
†
Bre
ast
A
dv. so
lid tu
mo
rs
NC
T0
125
4526
N
CT
01
33
2604
PF
04
691
502
Pfize
r P
I3K
/mT
OR
PD
03
25
901
M
EK
Ad
v. so
lid tu
mo
rs
NC
T0
134
7866
36
Ta
ble
1.5
: C
om
bin
ati
on
of
PI3
K in
hib
ito
rs w
ith
oth
er
targ
ete
d t
hera
pie
s i
n t
he
clin
ic (
co
nti
nu
ed
)
Ag
en
t C
om
pa
ny
Ta
rget
Co
mb
inati
on
th
era
py t
ria
ls
Ag
en
t T
arg
et
Tu
mo
r ty
pe
s*
Cli
nic
al tr
ial*
Du
al p
an
-PI3
K/m
TO
R in
hib
ito
rs
BE
Z2
35
No
va
rtis
P
I3K
/mT
OR
Tra
stu
zu
ma
b
H
ER
2
B
reast
A
dv. so
lid tu
mo
rs
NC
T0
147
1847
N
CT
01
28
5466
E
ve
rolim
us
m
TO
R
B
reast
R
ena
l ce
ll
Ad
v. so
lid tu
mo
rs
NC
T0
148
2156
N
CT
01
50
8104
A
bira
tero
ne
a
ce
tate
CY
P1
7
P
rosta
te
NC
T0
171
7898
L
etr
ozo
le
A
rom
ata
se
B
reast
NC
T0
124
8494
E
ve
rolim
us
M
EK
16
2
m
TO
R
M
EK
Ad
v. so
lid tu
mo
rs
NC
T0
148
2156
N
CT
01
33
7765
XL
76
5
Sa
no
fi
PI3
K/m
TO
R
L
etr
ozo
le
A
rom
ata
se
B
reast
NC
T0
108
2068
E
rlo
tin
ib
E
GF
R
A
dv. so
lid tu
mo
rs
NC
T0
077
7699
PF
05
212
384
Pfize
r P
I3K
/mT
OR
PD
03
25
901
M
EK
Ad
v. so
lid tu
mo
rs
NC
T0
134
7866
C
etu
xim
ab
E
GF
R
C
olo
recta
l ca
ncer
NC
T0
192
5274
B
eva
ciz
um
ab
V
EF
GR
Co
lore
cta
l ca
ncer
NC
T0
193
7715
T
NB
C, tr
iple
-neg
ative b
rea
st
cancer;
GIS
T, ga
str
oin
testin
al str
om
al tu
mor;
NS
CLC
, n
on
-sm
all
cell
lung c
arc
inom
a; E
SC
C,
esoph
age
al sq
uam
ou
s c
ell
ca
rcin
om
a; S
CC
HN
, sq
uam
ou
s c
ell
ca
rcin
om
a o
f th
e h
ead a
nd
ne
ck; sq
NS
CLC
, squa
mous n
on
-sm
all
cell
lung c
ancer;
TC
C,
tran
sitio
nal cell
carc
inom
a; IN
HL,
indole
nt non
-Hodg
kin
lym
pho
ma
; M
CL,
mantle c
ell
lym
ph
om
a; C
LL
, chro
nic
ly
mpho
cytic le
ukem
ia;
SLL
, sm
all
lym
phocytic le
ukem
ia;
ALL
, acute
lym
phob
lastic le
uke
mia
; A
ML,
acute
myelo
id leukem
ia; C
ML,
ch
ron
ic m
yelo
ge
nou
s leuke
mia
; M
M,
multip
le m
yelo
ma; C
RP
C, castr
ation
-resis
tan
t pro
sta
te c
ancer;
GB
M, glio
bla
sto
ma m
ultiform
e.
* D
ata
taken f
rom
an
Apri
l 20
14 s
earc
h o
f http
://w
ww
.clin
icaltrials
.gov.
† Bevaciz
um
ab is a
mono
clo
na
l a
ntibod
y targ
etin
g V
EG
F th
at p
revents
sig
nalin
g thro
ug
h V
EF
GR
. ‡ T
-DM
1 is a
conju
ga
te o
f th
e c
yto
toxic
ag
ent
mert
an
sin
e (
DM
1)
to t
he m
onoclo
nal an
tib
ody T
rastu
zum
ab t
arg
eting H
ER
2.
37
improve therapeutic outcomes.
Emerging isoform-selective PI3K inhibitors
Most PI3K inhibitors in early clinical trials are ATP-competitive agents that target all
class I isoforms with similar potencies. These include pan-PI3K inhibitors (Table 1.2)
such as GDC0941 (Raynaud et al., 2009) and dual pan-PI3K/mTOR inhibitors (Table
1.3) such as BEZ235 (Maira et al., 2008). Though these drugs display potent preclinical
anti-tumor activity, their success in clinical trials as single agents has been modest
(Rodon et al., 2013). The therapeutic window and efficacy of pan-PI3K inhibitors are
limited in some cases by adverse effects arising from a broader spectrum of off-target
effects (Fruman and Rommel, 2014). Furthermore, while both pan-PI3K and isoform-
selective inhibitors have on-target effects from suppression of essential PI3K functions,
for example glucose homeostasis, pan-PI3K inhibitors likely have additional on-target
effects from inhibiting isoforms that are not contributing to tumorigenesis. Isoform-
selective inhibitors may achieve greater efficacy with fewer toxic effects, and are
emerging in the clinic (Table 1.4).
The most effective single agent PI3K-based therapy to date is idelalisib (CAL101 or
GS1101), a p110h-selective inhibitor. Idelalisib has achieved notable success in early
trials for patients with chronic lymphocytic leukemia or indolent lymphoma, and is
currently in phase III clinical trials (Furman et al., 2014; Gopal et al., 2014). Interestingly,
this dramatic response is not due to genetic activation of the PI3K pathway, as neither
PI3K mutation nor PTEN loss is common in these malignancies. Given the important role
of p110h in signaling downstream of BCRs (Clayton et al., 2002; Jou et al., 2002;
Okkenhaug et al., 2002) and the fact that leukemic B cells have been shown to be
dependent on BCR signaling, it is likely that idelalisib functions by blocking essential
38
BCR signals. Two recent articles provide great insight into the success of idelalisib trials
(see (Fruman and Cantley, 2014) and (Vanhaesebroeck and Khwaja, 2014)).
In addition to the role of p110h in B cell malignancies, a recent preclinical study showed
that this isoform also contributes to PTEN-null T-ALL (Subramaniam et al., 2012).
However, p110h-selective inhibition in this study was insufficient to suppress
tumorigenesis; combined inhibition of both p110h and p110け was required for effective
anti-PI3K therapy (Subramaniam et al., 2012). The involvement of p110h and p110け in
leukocyte signaling and hematological malignancies has drawn great attention, and new
inhibitors that target both isoforms simultaneously are in clinical trials for B and T cell
lymphomas (Table 1.4). These isoforms may also mediate immune responses that
support the growth of solid tumors. In a mouse model, p110け inhibition blocked myeloid
cell recruitment to tumors, thus suppressing malignancy by targeting the tumor
microenvironment (Schmid et al., 2011). Another study indicated that p110h inhibition
impaired tumor growth by disrupting regulatory T cell-mediated immune tolerance (Ali et
al., 2014). These findings indicate potential new applications for p110h- or p110け-
selective therapies in cancer.
The frequency of PIK3CA mutations in solid tumors has generated great interest in the
potential for p110g-selective inhibitors in targeting these cancers. Data presented at the
2013 San Antonio Breast Cancer Symposium (SABCS) indicated promising early clinical
activity of p110g-selective inhibitors BYL719 or GDC0032 as single agents in patients
with PIK3CA-mutant advanced breast tumors (Juric et al., 2013b). Recent preclinical
findings that HER2- or KRAS-driven tumors rely on p110g (Castellano et al., 2013;
Gritsman et al., 2014; Gupta et al., 2007; Schmit et al., 2014; Utermark et al., 2012)
underscore the need for clinical evaluation of p110g-selective drugs in these disease
39
settings. In these studies, growth of HER2- or KRAS-driven solid tumors is inhibited
similarly by pan- and p110g-selective inhibitors (Castellano et al., 2013; Utermark et al.,
2012), but only modestly by p110く-selective inhibition (Schmit et al., 2014; Utermark et
al., 2012). However, further study is needed to determine the contexts in which
simultaneous inhibition of p110g and p110く can improve outcomes of KRAS- or HER2-
driven disease.
One drawback of p110g-selective inhibitors is their inevitable on-target adverse effects
on insulin signaling and glucose metabolism, since p110g is the major isoform mediating
these functions (Knight et al., 2006; Sopasakis et al., 2010). In the clinic, the effect of
p110g-selective inhibitors on glucose homeostasis must be carefully managed (Busaidy
et al., 2012), and is in some cases limiting (Rodon et al., 2013). To circumvent this,
inhibitors are being developed that specifically target p110g harboring hotspot mutations.
Such agents might be used at high doses with low toxicity, similar to mutant-selective
BRAF inhibitors that have had great clinical success (Bollag et al., 2010; Chapman et al.,
2011). A major obstacle to this approach is the heterogeneity of oncogenic PIK3CA
mutations. Some progress has been made with the discovery of GDC0032, which was
reported at the 2013 SABCS to have enhanced potency in PIK3CA mutant breast cancer
models (Sampath et al., 2013); one preclinical study also reported success using stapled
peptides to specifically disrupt the interaction of p110g-E545K with IRS1 (Hao et al.,
2013). However, devising strategies to selectively interrupt mutant-specific function
remains challenging. If developed, this class of inhibitor will likely be most effective in
early stage tumors with PIK3CA mutations, as advanced PIK3CA-mutant tumors may
have escaped their dependency on oncogenic p110g (Liu et al., 2011). Such drugs
would also be ideal for treating congenital overgrowth syndromes caused by PIK3CA
mutations occurring during early embryonic development (Kurek et al., 2012; Orloff et
40
al., 2013; Rios et al., 2013; Riviere et al., 2012). In these contexts, p110g mutant-
selective inhibitors may yield improved therapeutic index.
Several preclinical studies have documented that certain PTEN-deficient tumors depend
on p110く (Jia et al., 2008; Ni et al., 2012; Wee et al., 2008), prompting a new clinical
trial with the p110く-selective inhibitor GSK2636771 in patients with PTEN-deficient
advanced solid tumors (NCT01458067). However, since PTEN is a negative regulator of
PI3K, isoform-dependency of PTEN-deficient tumors can be complicated as it can be
affected by tissue type, co-existing genetic events, and microenvironmental cues that
fuel cancer cells. In model systems where PTEN-deficient tumors are found to be
dependent on p110く, addition of oncogenic RTKs, RAS, or mutant PIK3CA can shift
dependency partially or totally to p110g (Figure 1.7). Recent studies also show that
prolonged treatment of PTEN-deficient tumor cells with p110く-selective inhibitors can
shift isoform dependency from p110く to p110g (N. Rosen, unpublished observations).
Therefore in most PTEN-deficient solid tumors, both p110g and p110く should be
targeted.
Although development of dual p110g/p110く-selective inhibitors has proven difficult
(Knight et al., 2006), combination of individual p110g- and p110く-selective inhibitors
might offer flexibility in the dosing of each isoform-selective inhibitor to further reduce
toxicity and increase the therapeutic window. One approach could involve continuous
inhibition of p110く to suppress elevated basal PIγK activity due to PTEN loss, combined
with pulsatile inhibition of p110g to avoid toxicity due to glucose elevation. Such a
strategy might also avoid the reported shift in isoform dependency of tumors from p110g
to p110く after prolonged treatment with the p110g-selective inhibitor BYL719 (J.A.
Engelman, unpublished observations). Ultimately, the success of targeting PI3K in
41
cancer will likely require better understanding of which PI3K isoforms to target in a given
disease setting, improved inhibitors, and more careful dosing strategies.
Resistance mechanisms and combination therapeutic strategies
PI3K-based therapeutic approaches have encountered a number of roadblocks in the
form of intrinsic and acquired resistance mechanisms. A large body of work has
identified multiple signaling feedback loops, compensatory parallel signaling pathways,
and modes of downstream pathway activation that may result in clinical resistance to
PI3K inhibitors. Consequently, combination therapies are being developed and
evaluated in both preclinical and clinical settings (Figure 1.8 and Table 1.5), and will be
necessary to maximize clinical efficacy of PI3K inhibitors.
The first indication of feedback loops in the PI3K pathway came from experiments with
mTOR inhibitors. In early studies mTOR inhibition led to p70 ribosomal protein S6 kinase
(S6K) suppression, IRS1 upregulation, and PI3K-AKT activation (O'Reilly et al., 2006).
This prompted the development of dual pan-PI3K/mTOR inhibitors that are currently in
clinical trials (Table 1.3). Interestingly, feedback loops can also arise from dual pan-
PI3K/mTOR inhibition. A recent preclinical report suggested that PI3K and mTOR
blockade activated the Janus kinase 2 (JAK2)-signal transducer and activator of
transcription 5 (STAT5) signaling axis via IRS1, generating resistance to dual
PI3K/mTOR inhibition, which could be overcome by targeting JAK2 (Britschgi et al.,
2012). Similarly, in another preclinical study treatment with BEZ235 increased
phosphorylation of multiple signaling molecules, including STAT3, STAT5, JUN, and p90
ribosomal S6 kinase (p90RSK) (Muranen et al., 2012). Isoform-selective PI3K inhibitors
can also generate feedback loops: in a recent study of PIK3CA mutant breast tumors,
mTOR complex 1 (mTORC1) reactivation by insulin-like growth factor 1 (IGF1) and
42
neuregulin 1 (NRG1) was associated with tumor resistance to the p110g-selective agent
BYL719, necessitating concurrent mTORC1 inhibition using RAD001 (Elkabets et al.,
2013). Inhibiting both PI3K and mTOR, possibly in conjunction with additional signaling
pathways, may be required to achieve effective anti-tumor activity.
Another important resistance mechanism to PI3K pathway inhibition is increased
expression of RTKs, such as HER3, IGF1R, insulin receptor (IR), and EGFR, via
forkhead box O (FOXO)-mediated transcriptional upregulation (Chandarlapaty et al.,
2011). Robust HER3 induction in response to PI3K inhibition has been reported in
several tumor types (Garrett et al., 2011; Muranen et al., 2012; Sergina et al., 2007).
While HER3 itself does not possess strong tyrosine kinase activity, it dimerizes with
EGFR, HER2, or HER4, hyperactivating the PI3K pathway and dampening the efficacy
of PI3K drugs. A preclinical study demonstrated that combination of the HER3-
neutralizing antibody LJM716 and the p110g-selective inhibitor BYL719 potently blocked
PI3K signaling and growth of HER2-positive breast tumor xenografts, even without a
direct HER2 antagonist (Garrett et al., 2013). Similarly, combination of the dual
EGFR/HER3 inhibitor MEHD7945A with a PI3K inhibitor (GDC0941) or AKT inhibitor
(GDC0068) effectively blocked the growth of triple-negative breast cancer cells in vitro
and in xenografts in a preclinical study (Tao et al., 2014). Blockade of PI3K along with
upstream RTKs may therefore circumvent certain PI3K therapy resistance mechanisms
(Figure 1.8).
Activation of convergent signaling pathways, for example the RAS-RAF-MEK-ERK
pathway, can also lead to PI3K pathway inhibition resistance. Mutant RAS can activate
both the RAF-ERK and PI3K-AKT-mTOR pathways in cancer cells; blocking the PI3K
pathway in such cells leads to upregulation of the ERK pathway (Serra et al., 2011).
43
Inhibition of both PI3K and ERK pathways successfully suppressed the growth of cancer
cells in mouse models (Castellano et al., 2013; Engelman et al., 2008; Will et al., 2014),
and combinations of MEK inhibitors and pan- or isoform-selective PI3K agents are being
evaluated in clinical trials. However, there is preclinical evidence that some of these
combinations may be limited due to synergistic toxicity (Castellano et al., 2013).
Preclinical studies indicate that pulsatile inhibition of both PI3K and ERK pathways may
provide more effective anti-tumor activity while limiting toxic effects (Will et al., 2014),
suggesting that optimization of such combinations in the clinic will require careful dosing
strategies.
Another mode of resistance to PI3K-directed therapies arises from the activation of
transcription downstream or outside of the PI3K pathway. Several reports have indicated
MYC amplification or overexpression (Ilic et al., 2011; Liu et al., 2011) or activation of the
Notch and WNT/く-catenin pathways (Muellner et al., 2011; Tenbaum et al., 2012) as
mechanisms of resistance to PI3K inhibition. Recently, the bromodomain and
extraterminal (BET) inhibitor JQ1 has been shown to downregulate transcription of MYC,
among other targets (Delmore et al., 2011). XAV939 has also been identified as an
inhibitor of WNT/く-catenin-mediated transcription (Huang et al., 2009). Combination of
PI3K inhibition with these agents is being actively pursued in preclinical settings.
Other combination therapies have been suggested by assessing pathways that may
synergize with PI3K (Figure 1.8). As presented at the 2012 and 2013 SABCS, anti-
estrogen therapies are being tested in combination with PI3K inhibitors in clinical trials
for breast cancer patients (Juric et al., 2012; Juric et al., 2013a; Juric et al., 2013b). In a
brain tumor study, coordinate activation of sonic hedgehog (SHH) and PI3K signaling
was found in PTEN-deficient glioblastoma; combination of BKM120, a pan-PI3K
44
inhibitor, and LED225, a smoothened (SMO) inhibitor that blocks SHH signaling,
resulted in synergistic anti-tumor effects (Gruber Filbin et al., 2013). Poly-(ADP-ribose)
polymerase (PARP) and PI3K inhibitors have been found to cooperate in prostate and
triple-negative breast cancers (Gonzalez-Billalabeitia et al., 2014; Ibrahim et al., 2012;
Juvekar et al., 2012). It appears that PI3K inhibition downregulates BRCA1 and BRCA2,
impairing homologous recombination and sensitizing BRCA-wildtype cancer cells to
PARP inhibition. Another attractive approach is combination of PI3K-targeted agents
with drugs that suppress anti-apoptotic factors. B cell lymphoma 2 (BCL2), myeloid cell
leukemia sequence 1 (MCL1), and other pro-survival proteins are frequently upregulated
in cancer, and may explain why PI3K inhibition is often cytostatic in tumor cells. BCL2 or
MCL1 suppression may induce cytotoxicity in response to PI3K inhibition (Rahmani et
al., 2013). Finally, an emerging approach is to combine PI3K inhibitors with agents that
disrupt cell cycle machinery (Vora et al., 2014). The p16-Cyclin D-cyclin-dependent
kinase 4 (CDK4)-CDK6 pathway is frequently dysregulated in cancer. A number of
CDK4/CDK6 inhibitors, including LEE011 and palbociclib (PD0332991), are entering
clinical trials for combination with pan- or p110g-selective inhibitors. Such rational
combination therapies will be required to increase the success of PI3K inhibitors.
Conclusions and perspective
Targeting the PI3K pathway remains both an opportunity and a challenge for cancer
therapy. Recent advances have provided the framework and rationale for inhibiting
select class I PI3K catalytic isoforms. We have learned a great deal about the divergent
roles of these isoforms in different signaling contexts, and are beginning to understand
the importance of each isoform in various tissues, compartments, and cancer types.
These findings have informed preclinical and clinical studies with isoform-selective PI3K
agents, which offer improved specificity and reduced toxicity over first-generation pan-
45
PI3K drugs. Isoform-selective PI3K inhibitors have seen promising success in early- and
late-stage clinical trials for solid and hematological malignancies, highlighting the
potential for isoform-selective PI3K therapeutics.
Although we have made substantial progress, further efforts are needed. We have only
recently begun to appreciate the importance of class I regulatory isoforms in
tumorigenesis. The different ways in which p85 subunits contribute to cancer, and the
effective means to pharmacologically inhibit these mechanisms, are still not fully
understood. Similarly, while a recent study indicates that class II isoform PI3K-Cβg is
important for pathophysiological angiogenesis, the roles of class II and III PI3Ks in
cancer remain unclear.
For the class I catalytic isoforms, we must continue to precisely define the disease
settings in which different PI3K isoforms will need to be targeted. To better inform
isoform-selective therapeutic strategies, a set of biomarkers to predict the active p110
isoforms in a given tumor would be ideal, but development of this will require systematic
studies. Continued work to understand the underlying cellular programs that protect
tumors with aberrant PI3K activation from PI3K-targeted therapy will also be important.
This will allow for better rational design of combination therapies, which will be
necessary to overcome compensatory pathway activation and acquired resistance
mechanisms and maximize the anti-tumor activity of PI3K inhibitors. Dosing strategies
will also need to be carefully considered, as recent studies suggest that in some cases
pulsatile inhibition may reduce toxicity without sacrificing efficacy. Progress in these
areas should increase the effectiveness of PI3K-directed therapies in the clinic.
Chapter 2: PI3K regulatory subunit p85alpha plays a tumor
suppressive role in human mammary epithelial cells
47
Acknowledgements
Hailing Cheng and Jean Zhao conceived the initial project idea. Lauren Thorpe
performed all experiments and data analysis.
I would additionally like to thank Hailing Cheng for providing HMECs and plasmids, for
teaching initial techniques, and for assistance in troubleshooting experiments. Thank you
to Haluk Yuzugullu for assistance in subcloning the neuT construct. Thank you to
Jennifer Spangle for providing detailed protocols for receptor internalization and
degradation assays. I would also like to thank Lewis Cantley for helpful discussions
conceptualizing the mechanism portion of this work, and Lewis Cantley, Karl Münger,
and Myles Brown for helpful discussions on experimental confirmation of this
mechanism.
48
Preface
In this chapter, we use human mammary epithelial cells (HMECs), a normal, non-
transformed cell culture system, to examine the in vitro effects of partial p85g loss on
PI3K signaling and cell transformation. We find that RNAi-mediated PIK3R1 knockdown
increases growth factor-dependent PIγK signaling through catalytic isoform p110g,
facilitating cellular transformation. We furthermore demonstrate that knockdown of
PIK3R1 augments PI3K signaling and transformation mediated by oncogenes, including
activated HERβ/neu. Finally, we show that partial reduction of p85g leads to an
increased amount of p110g bound to activated receptor tyrosine kinases (RTKs).
Together these findings suggest that p85g depletion selectively targets a free negative
regulator pool of the PI3K regulatory subunit that fine tunes RTK-mediated PI3K
activation under normal conditions, and transforms cells when lost.
Introduction
Class IA phosphatidylinositol 3-kinases (PI3Ks) are critical coordinators of the cellular
response to extracellular signals. They are heterodimers comprised of a p110 catalytic
subunit (p110g, p110く, or p110h) and a p85 regulatory subunit (p85g, p55g, p50g,
p85く, or p55け, collectively referred to as p85) (Figure 1.1). In quiescent cells, the iSH2
domain of the p85 regulatory subunit binds and stabilizes the p110 catalytic subunit
while maintaining p110 in a low-activity state (Yu et al., 1998b). Upon growth factor
stimulation, the SH2 domains of p85 bind tyrosine-phosphorylated YXXM motifs on
activated RTKs or their adaptors, recruiting p110 to the plasma membrane and
simultaneously relieving its inhibition (Yu et al., 1998a) (Figure 1.2). The activated p110
catalytic subunit phosphorylates the γ’-hydroxyl group of phosphatidylinositol 4,5-
bisphosphate (PtdIns(4,5)P2) to produce phosphatidylinositol 3,4,5-trisphosphate
(PtdIns(3,4,5)P3), a cellular second messenger which goes on to activate multiple AKT-
49
dependent and –independent downstream signaling pathways. PI3K signaling controls
diverse cellular activities, including cell growth, proliferation, survival, and transformation
(Liu et al., 2009; Wong et al., 2010). The phosphatase and tensin homologue (PTEN)
lipid phosphatase removes the γ’ phosphate from PtdIns(γ,4,5)P3 to inactivate PI3K
signals.
Several reports have linked p85g to activity or stability of the PTEN lipid phosphatase. In
liver lysates from mice with liver-specific Pik3r1 knockout, PtdIns(3,4,5)P3 production
was more sustained and AKT activation was increased, while the lipid phosphatase
activity of PTEN was found to be reduced, suggesting that p85g may enhance PTEN
activity (Taniguchi et al., 2006). This finding was corroborated by in vitro assays, where
addition of increasing amounts of purified p85g augmented dephosphorylation of
PtdIns(3,4,5)P3 by PTEN (Chagpar et al., 2010). Furthermore, co-immunoprecipitation
experiments have suggested an interaction between p85g and PTEN (Chagpar et al.,
2010; Cheung et al., 2011; Rabinovsky et al., 2009); this interaction was shown to be
direct and to require the N-terminal SHγ and BH domains of p85g (Chagpar et al., 2010).
In addition to effects on PTEN lipid phosphatase activity, p85g has been linked to PTEN
expression and protein stability. Although liver-specific ablation of Pik3r1 had no effect
on the levels of PTEN protein in mouse liver lysates (Taniguchi et al., 2006; Taniguchi et
al., 2010), these mice developed liver tumors within 14-20 months, and lysates from
these tumors had significantly reduced PTEN protein and mRNA levels (Taniguchi et al.,
2010). In a separate study, ectopic expression of wildtype p85g increased PTEN protein
levels, while expression of the endometrial cancer-associated p85g-E160* mutant
enhanced ubiquitination and proteasomal degradation of PTEN; in these contexts, PTEN
mRNA levels were unchanged (Cheung et al., 2011). Together these findings suggest
that p85g may affect PTEN expression, stability, or activity, potentially contributing to
50
negative regulation of the PI3K pathway.
In addition to its reported effects on PTEN, p85g has also been shown to have a
GTPase activating protein (GAP) function towards select Rab proteins. Rabs are a large
family of small GTPases critical for the regulation of intracellular trafficking (Jean and
Kiger, 2012; Stenmark, 2009). One mechanism controlling receptor-mediated signaling
is the endocytosis of receptors following their activation; receptors are targeted to the
early endosome, then either transported to the lysosome for degradation, terminating
signaling, or recycled back to the plasma membrane, allowing for potentially sustained
signaling (Miaczynska, 2013). Of the many Rab proteins, in particular Rab4 and Rab5
are important for transport from the plasma membrane to early endosomes, and Rab11
is important for recycling of endosomes back to the plasma membrane (Jean and Kiger,
2012; Stenmark, 2009). The N-terminal breakpoint cluster homology (BH) domain of
p85g has been reported to directly bind and have GAP activity towards Rab5; in
addition, p85g showed GAP activity toward Rab4, but not Rab11 (Chamberlain et al.,
2004). Ectopic expression of a p85g mutant with disrupted Rab-GAP activity led to
increased growth factor-stimulated PI3K/AKT activation and cellular transformation
(Chamberlain et al., 2004; Chamberlain et al., 2008), apparently due to more rapid and
sustained internalization and reduced degradation of RTKs (Chamberlain et al., 2008;
Chamberlain et al., 2010). Similarly, a recent report demonstrated that RNAi-mediated
p85g downregulation lead to an increase in active GTP-bound Rab5 and PI3K/AKT
pathway activation (Dou et al., 2013). Together this suggests that p85g might also
contribute to regulation of PI3K signaling by effects on activation of Rab proteins
controlling receptor trafficking.
Hyperactivation of the PI3K pathway is one of the most common events in human
51
cancers (Table 1.1 and Appendix A). This can be a result of lesions along the pathway,
such as loss of the PTEN phosphatase opposing PI3K (Cully et al., 2006), or of
mutations in PI3K itself. Oncogenic mutations frequently occur in the PIK3CA gene
encoding catalytic isoform p110g (Cancer Genome Atlas Research, 2008; Parsons et
al., 2008; Samuels et al., 2004; Thomas et al., 2007), and confer constitutive p110g
activation leading to transformation (Gymnopoulos et al., 2007; Hon et al., 2012; Isakoff
et al., 2005; Kang et al., 2005; Mandelker et al., 2009; Samuels et al., 2005; Zhao et al.,
2005). More recently, somatic mutations in PIK3R1 (encoding p85g and its splicing
variants p55g and p50g) and PIK3R2 (encoding p85く) have been reported in
glioblastoma (Cancer Genome Atlas Research, 2008; Parsons et al., 2008) and in
endometrial cancer (Cheung et al., 2011; Urick et al., 2011). A majority of PIK3R1
mutations occur in iSH2 domain hotspots (Cancer Genome Atlas Research, 2008;
Cheung et al., 2011; Jaiswal et al., 2009; Urick et al., 2011); subsequent studies
demonstrated that many of these iSH2 mutants retain the ability to bind and stabilize
p110, but are less able to inhibit p110 catalytic activity, resulting in increased PI3K
activation and transformation (Cheung et al., 2011; Jaiswal et al., 2009; Urick et al.,
2011; Wu et al., 2009). A smaller fraction of PIK3R1 mutations found in cancers occur in
other domains of the protein; interestingly, some of these mutants lack the iSH2 domain
and are unable to bind p110 (Cheung et al., 2011; Jaiswal et al., 2009; Urick et al.,
2011). Ectopic expression of the truncation mutant p85g-E160* has been reported to
contribute to destabilization of PTEN protein (Cheung et al., 2011), but the effects of
other truncation mutations has not yet been determined. The discovery and
characterization of mutations in PIK3R1 has established a previously unreported role for
the p85 regulatory subunit in cancer, potentially by multiple distinct mechanisms.
In addition to oncogenic mutations in PIK3R1, accumulating evidence suggests that
52
changes in the levels of p85g can have an important effect on PI3K activation. In mice,
although complete Pik3r1 ablation is perinatally lethal (Fruman et al., 2000), partial loss
of different p85 isoforms improves insulin sensitivity and insulin-stimulated AKT
activation (Chen et al., 2004; Mauvais-Jarvis et al., 2002; Terauchi et al., 1999; Ueki et
al., 2002a; Ueki et al., 2002b). It has been suggested that in some tissues, the p85
regulatory subunit is present in excess of p110, and that monomeric free p85 is capable
of acting as a negative regulator of PI3K signaling (Luo and Cantley, 2005; Mauvais-
Jarvis et al., 2002; Ueki et al., 2002a; Ueki et al., 2003). In support of this model, p85g
overexpression in L6 myotubes significantly reduced insulin-stimulated PI3K/AKT
activation (Ueki et al., 2000), and mice with p85g overexpression had decreased skeletal
muscle insulin signaling (Barbour et al., 2005). Furthermore, monomeric p85g has been
shown to downregulate insulin-stimulated PI3K activity by forming a sequestration
complex with non-signaling IRS1 adaptors (Luo et al., 2005a). Loss of p85g has also
recently been proposed to play a role in cancer. Significant PIK3R1 underexpression
was recently detected in breast cancers, and correlated with poorer metastasis-free
survival (Cizkova et al., 2013). In mice, liver-specific Pik3r1 deletion eventually led to
development of aggressive high-grade hepatocellular carcinoma (HCC)-like tumors with
upregulated AKT activation (Taniguchi et al., 2010). Together these studies indicate that
partial reduction of p85 can upregulate PI3K in response to insulin, and that furthermore
loss of p85 may contribute to tumorigenesis in the breast and liver.
In this chapter, we examine the importance of p85g levels in regulating PIγK/AKT
activation in mammary epithelial cells. We use RNAi techniques to downregulate
PIK3R1 expression in human mammary epithelial cells, and explore the effects on
PI3K/AKT signaling and cellular transformation. We then use isoform-selective
pharmacological inhibitors to identify the PI3K catalytic isoforms that contribute to
53
signaling in the context of reduced p85g. Finally, we use immunoprecipitation
experiments to identify a potential mechanism linking the levels of p85g to the magnitude
of RTK-mediated PI3K/AKT signaling activation. Our findings support previous reports
that p85g levels modulate PIγK output, and importantly demonstrate that a reduction in
p85g is sufficient to transform mammary epithelial cells in vitro.
Results
PIK3R1 expression is significantly reduced in breast cancer
To determine whether p85g may play a tumor suppressive role in breast cancer, we
analyzed expression levels of the PIK3R1 gene encoding p85g in different publically
available datasets from breast cancer patients. We used the cBioPortal for Cancer
Genomics (http://www.cbioportal.org, (Cerami et al., 2012; Gao et al., 2013)) to query
data from a 2012 comprehensive study of human breast tumors by The Cancer Genome
Atlas Network (TCGA) (Cancer Genome Atlas, 2012) and an additional provisional
TCGA data set for copy number loss (as determined by GISTIC) or mutation of PIK3R1.
Such alterations in PIK3R1 occurred in 23% and 28% of breast cancer cases in these
studies respectively, with the vast majority of these being heterozygous loss of the gene
(Figure 2.1 A). We also used Oncomine, an online database compiling expression data
from thousands of microarray experiments (https://www.oncomine.org, (Rhodes et al.,
2007; Rhodes et al., 2004)), to analyze PIK3R1 expression in other breast cancer
datasets. Across multiple studies, PIK3R1 mRNA expression was significantly reduced
by 50-77% in breast cancer samples when compared to normal breast tissue (Figure
2.1 B and Table 2.1). Together these results indicate that in breast cancers, PIK3R1 is
consistently decreased at both the genomic and mRNA expression levels, suggesting
that reduced levels of p85g may play a functional role in tumorigenesis of this tissue.
54
Figure 2.1: PIK3R1 expression is significantly reduced in breast cancers. Publically available datasets were queried for changes in PIK3R1 associated with breast cancer. (A) The cBio Portal for Cancer Genomics (http://www.cbioportal.org) was used to determine the incidence of PIK3R1 copy number loss or mutation in both a comprehensive 2012 study and an additional provisional study of breast cancer from The Cancer Genome Atlas Network (TCGA). In the 2012 study, such alterations occurred in 23% (111/482) of cases; in the provisional study, these alterations occurred in 28% (271/962) of cases. (B) The Oncomine database (https://www.oncomine.org/) was used to determine changes in PIK3R1 expression in breast cancer as compared to normal breast tissue. Microarray data from representative studies was converted to raw expression levels by taking the inverse log2, and then normalized to the mean raw expression level of normal breast tissue in that specific study. Means ± SEM are shown. Statistical significance was determined using unpaired t-test. For more detail on individual studies, see Table 2.1. *, P < 0.05; **, P < 0.01; ****, P < 0.0001.
55
Ta
ble
2.1
: P
IK3R
1 e
xp
ress
ion
is s
ign
ific
an
tly r
ed
uc
ed
in
bre
as
t ca
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cro
ss m
ult
iple
mic
roarr
ay d
ata
sets
Stu
dy n
am
e
Pu
blic
ati
on
C
on
tro
l ti
ssu
e
Co
ntr
ol N
C
an
ce
r ti
ssu
e
Ca
nce
r N
%
re
du
cti
on
in
PIK
3R
1
p v
alu
e
So
rlie
Bre
ast
(So
rlie
et a
l., 2
00
1)
No
rma
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reast
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Du
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l b
rea
st
ca
rcin
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a
65
50
.80
%
0.0
16
0
So
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(S
orlie
et a
l., 2
00
3)
No
rma
l b
reast
4
Du
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rea
st
ca
rcin
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a
81
50
.06
%
0.0
07
9
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56
RNAi-mediated PIK3R1 knockdown transforms human mammary epithelial cells
To study whether partial loss of p85g could contribute to transformation, we chose to use
human mammary epithelial cells (HMECs), a well-established system for the study of
PI3K-mediated transformation in vitro. In this system, HMECs are immortalized by
expression of the human telomerase reverse transcriptase (hTERT) catalytic subunit;
these cells have also been characterized to lack functional cyclin-dependent kinase 4
inhibitor A (p16INK4A) and have increased MYC expression (Romanov et al., 2001;
Utermark et al., 2007; Wang et al., 2000). HMECs expressing a dominant negative p53
mutant (DDp53) are unable to form colonies in agar (Zhao et al., 2003; Zhao et al.,
2005), an experimental measure of the transformation hallmark of anchorage-
independent growth (Hanahan and Weinberg, 2011). Activation of PI3K by expression of
myristoylated p110g or p110く, or mutant alleles of p110g found in cancers, transforms
these cells (Zhao et al., 2003; Zhao et al., 2005).
To address whether decreased PIK3R1 expression might play a role in the
transformation of mammary tissue, we generated polyclonal DDp53-HMEC lines with
stable RNAi-mediated knockdown of PIK3R1 (Figure 2.2 A). Two different shRNAs
targeting PIK3R1 reduced p85g protein levels by 76.6 ± 0.7% and 77.3 ± 2.9% in
comparison to the shControl (N = 3 for all) (Figure 2.2 B). While the positive control cells
expressing oncogenic p110g-H1047R (Zhao et al., 2003) showed dramatically increased
activation of AKT even after 4 hours of serum and growth factor starvation, with a fold
increase of 35.1 ± 9.0 in phosphorylation of AKT at S473 as compared to the shControl
line, PIK3R1 knockdown only slightly increased AKT S473 phosphorylation, by a fold
increase of 2.7 ± 0.4 and 4.0 ± 0.9 (N = 3 for all) (Figure 2.2 D). Although this increase
was statistically significant, it is clear that partial loss of p85g does not increase
constitutive PI3K pathway activation under un-stimulated conditions to a similar extent
57
Figure 2.2: Generation of DDp53-HMECs with stable RNAi-mediated PIK3R1 knockdown. Human mammary epithelial cells (HMECs) expressing a dominant negative p53 mutant (DDp53) were infected with lentivirus containing a negative control scrambled shRNA or one of two distinct shRNAs targeting PIK3R1, or with retrovirus containing the cancer-associated p110g-H1047R mutant as a positive control. Following selection for stable polyclonal lines, cells were starved of serum and growth factors for 4 hours; protein lysates were collected and subjected to immunoblotting for PI3K pathway components. Membranes were stripped and re-probed for total proteins and vinculin as a loading control. (A) Representative immunoblot. (B-D) Bands from immunoblots of three independent sets of protein lysates were quantified by densitometry; protein levels were normalized first to the vinculin loading control (for p85g and PTEN) or the total unphosphorylated protein (for phospho-AKTS473), then to the corresponding mean value for the shControl. Means ± SEM are shown; N = 3 for each. Statistical significance was determined by unpaired t-test. Significance for comparison to the shControl is shown. *, P < 0.05; **, P < 0.01; ****, P < 0.0001; ns, not significant.
58
as oncogenic mutant p110g.
Next we investigated whether PIK3R1 knockdown was sufficient to induce
transformation of DDp53-HMECs. It has previously been shown that DDp53-HMECs are
unable to form colonies in agar, but become transformed upon activation of PI3K (Zhao
et al., 2006; Zhao et al., 2003). We plated single-cell suspensions of our HMEC lines in
fully supplemented growth medium containing 0.3% agar and allowed them to grow for 4
weeks before scoring colonies. Consistent with previous reports, the shControl line was
unable to form colonies in agar, with only 16 ± 0.6 colonies per 50,000 cells plated, while
the positive control line expressing p110g-H1047R formed abundant colonies, with 909.7
± 35.0 colonies per 50,000 cells plated (N = 3 for both) (Figure 2.3 A). In comparison,
both shPIK3R1 lines readily formed colonies when grown in agar, with 633.7 ± 7.9 and
1,229 ± 39.0 colonies per 50,000 cells plated, respectively (N = 3 for both) (Figure 2.3
A). These results demonstrate that PIK3R1 knockdown is sufficient to transform DDp53-
HMECs in vitro.
To further assess the effects of PIK3R1 knockdown on PI3K signaling, we evaluated
activation of downstream effectors of this pathway in response to acute growth factor
stimulation. Cells were synchronized via a 4 hour serum and growth factor starvation,
and then stimulated with 20ng/ml EGF for timepoints up to 60 minutes; protein lysates
were collected and subjected to immunoblotting for phosphorylation at activation sites of
AKT and S6 ribosomal protein. Compared to the control line, PIK3R1 knockdown lines
exhibited both increased and sustained phosphorylation of AKT at activating residues
T308 and S473, and of S6 ribosomal protein at S235/236 (Figure 2.3 B). Comparable
increases in EGF-stimulated PI3K/AKT pathway activation were seen in DDp53-HMECs
expressing other shRNAs targeting PIK3R1, and a similar effect was seen upon
59
Figure 2.3: PIK3R1 knockdown transforms DDp53-HMECs and increases growth factor-stimulated PI3K/AKT activation. (A) DDp53-HMECs with stable expression of shControl, shPIK3R1, or p110g-H1047R were tested for anchorage-independent growth. Single-cell suspensions were plated in 0.3% agar and grown for 4 weeks. 50,000 cells were plated per 6cm plate. The number of colonies was counted for three independent experiments of at least 3 plates each. Means ± SEM are shown; N = 3 for each group. Statistical significance was determined by unpaired t-test. Significance for comparison to the shControl is shown. ****, P < 0.0001. (B) The indicated cell lines were starved of serum and growth factors for 4 hours and then stimulated with 20ng/ml EGF for the indicated amounts of time. Protein lysates were collected and subjected to immunoblotting. Membranes were stripped and re-probed for total proteins and vinculin as a loading control. Bands were quantified by densitometry and normalized first to the corresponding total protein, then to the most intense band for the shControl. One representative experiment is shown.
60
stimulation with insulin (data not shown). These results indicate that partial reduction of
p85g increases PIγK/AKT signaling in DDp5γ-HMECs, and that this increase is most
pronounced upon stimulation with growth factors.
To establish that the increased PI3K signaling seen in our PIK3R1 knockdown DDp53-
HMEC lines was specifically from decreased p85g expression and not an off-target
effect of stable shRNA introduction, we sought to rescue p85g protein levels in our
knockdown lines. For shRNAs targeting the γ’ UTR of PIK3R1, including shPIK3R1 #1, a
wildtype flag-tagged PIK3R1 construct was used; for shRNAs targeting the coding region
of PIK3R1, including shPIK3R1 #2, we introduced silent wobble mutations rendering
resistance to specific shRNAs into this wildtype construct. Stable expression of these
constructs in our PIK3R1 knockdown DDp53-HMECs restored p85g protein expression
to levels comparable to the shControl line (Figure 2.4 and data not shown). We then
evaluated PI3K/AKT pathway activation in shControl, shPIK3R1, and rescue cell lines in
response to acute growth factor stimulation. Cells were starved for 4 hours and then
stimulated with 20ng/ml EGF for timepoints up to one hour; protein lysates were
collected and subjected to immunoblotting for PI3K/AKT pathway components. As
expected, compared to the shControl line, shPIK3R1 cells exhibited increased and
sustained phosphorylation of AKT and S6 ribosomal protein; rescue of p85g protein
levels in our shPIK3R1 cells reduced AKT and S6 phosphorylation to levels comparable
to the shControl line (Figure 2.4). Similar results were seen with other shPIK3R1 rescue
DDp53-HMECs (data not shown). This data indicates that the augmented PI3K/AKT
signaling seen in our knockdown lines is likely due to decreased expression of p85g.
PIK3R1 knockdown augments HMEC transformation mediated by oncogenes
Because the increased PI3K/AKT signaling in PIK3R1 knockdown DDp53-HMECs was
61
Figure 2.4: Augmented PI3K/AKT activation in PIK3R1 knockdown DDp53-HMECs is rescued by ectopic expression of PIK3R1. Silent wobble mutations were introduced into a wildtype, flag-tagged PIK3R1 construct to specifically render resistant to shPIK3R1 #2. This construct was stably introduced into DDp53-HMECs expressing shPIK3R1 #2 to rescue expression levels of p85g. The cell lines indicated were starved of serum and growth factors for 4 hours and then stimulated with 20ng/ml EGF for timepoints up to one hour. Protein lysates were collected and subjected to immunoblotting. Membranes were stripped and re-probed for total proteins and vinculin as a loading control. Bands were quantified by densitometry and normalized first to the corresponding total protein, then to the most intense band for the shControl. One representative experiment is shown.
62
dependent on growth factors to initiate PI3K signaling, we were interested to know
whether reduced p85g could also cooperate with PIγK-activating oncogenes to augment
PI3K output and transformation. To address this, we generated DDp53-HMECs stably
expressing neuT, an activated rat form of HER2/neu, in addition to shRNA targeting
PIK3R1 (Figure 2.5 A). Similar to the DDp53-HMEC lines, shRNAs targeting PIK3R1
reduced p85g protein levels in neuT-expressing lines by 80.3 ± 0.4% and 70.6 ± 3.9%
compared to the shControl (N = 3 for all) (Figure 2.5 B). Expression of neuT increased
PI3K/AKT pathway activation even following overnight starvation, and as expected,
expression of p110g-H1047R further augmented AKT activation as assessed by S473
phosphorylation by 3.8 ± 0.5 fold, as compared to the shControl; both PIK3R1
knockdown lines also exhibited increased AKT S473 phosphorylation over the shControl
line, by 1.6 ± 0.1 and 1.6 ± 0.2 fold respectively (N = 3 for all) (Figure 2.5 D). These
results suggest that partial p85g loss may be able to cooperate with activated HER2/neu
to increase PI3K/AKT activation.
To study the potential synergy between activated HERβ/neu and reduced p85g, we
examined whether PIK3R1 knockdown could increase the in vitro transformation of
DDp53-HMECs by neuT. We plated single-cell suspensions of these HMEC lines in fully
supplemented growth medium containing 0.3% agar and allowed them to grow for 3
weeks before scoring colonies. While the neuT shControl line was able to form colonies
in agar, with 821.1 ± 69.2 colonies per 25,000 cells plated, additional expression of
p110g-H1047R increased colony formation, with 1,330 ± 190.3 colonies per 25,000 cells
plated (N = 4 for both) (Figure 2.6 A). Similarly, both neuT shPIK3R1 lines exhibited
significantly augmented colony formation over the neuT shControl line, with 1,227 ± 79.3
and 1,321 ± 125.6 colonies per 25,000 cells plated, respectively (N = 4 for both) (Figure
2.6 A). These results indicate that partial p85g loss can cooperate with oncogenic
63
Figure 2.5: Generation of DDp53-HMECs with activated HER2/neu and RNAi-mediated PIK3R1 knockdown. DDp53-HMECs stably expressing neuT were infected with lentivirus containing a negative control scrambled shRNA or one of two distinct shRNAs targeting PIK3R1, or with retrovirus containing the cancer-associated p110g-H1047R mutant as a positive control. Following selection for stable polyclonal lines, cells were starved of serum and growth factors overnight; protein lysates were collected and subjected to immunoblotting for PI3K pathway components. Membranes were stripped and re-probed for total proteins and vinculin as a loading control. (A) Representative immunoblot. (B-D) Bands from immunoblots of three independent sets of protein lysates were quantified by densitometry; protein levels were normalized first to the vinculin loading control (for p85g and PTEN) or the total unphosphorylated protein (for phospho-AKTS473), then to the corresponding mean value for the shControl. Means ± SEM are shown; N = 3 for each. Statistical significance was determined by unpaired t-test. Significance for comparison to the shControl line is shown. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001; ns, not significant.
64
Figure 2.6: PIK3R1 knockdown increases transformation and PI3K/AKT signaling driven by activated HER2/neu in DDp53-HMECs. (A) DDp53-HMECs with stable expression of neuT and shControl, shPIK3R1, or p110g-H1047R were tested for anchorage-independent growth. Single-cell suspensions were plated in 0.3% agar and grown for 3 weeks. 25,000 cells were plated per 6cm plate. The number of colonies was counted for four independent experiments of at least 3 plates each. Means ± SEM are shown; N = 4 for each group. Statistical significance was determined by unpaired t-test. Significance for comparison to the shControl is shown. *, P < 0.05; **, P < 0.01. (B) The indicated cell lines were starved of serum and growth factors overnight and then stimulated with 20ng/ml EGF for the indicated amounts of time. Protein lysates were collected and subjected to immunoblotting. Membranes were stripped and re-probed for total proteins and vinculin as a loading control. Bands were quantified by densitometry and normalized first to the corresponding total protein, then to the most intense band for the shControl line. One representative experiment is shown.
65
HER2/neu to increase transformation of DDp53-HMECs.
We also assessed the ability of reduced p85g expression to increase PIγK/AKT
signaling in DDp53-HMECs with activated HER2/neu. DDp53-HMECs expressing neuT
and control or PIK3R1-targeting shRNAs were synchronized via overnight serum and
growth factor starvation, then stimulated with 20ng/ml EGF for timepoints up to 24 hours;
protein lysates were collected and subjected to immunoblotting for phosphorylation of
activation sites on AKT and S6 ribosomal protein. Compared to the shControl cells,
DDp53-HMECs expressing neuT and shPIK3R1 had increased phosphorylation of AKT
at both T308 and S473, and of S6 at S235/236, throughout the timecourse of EGF
stimulation (Figure 2.6 B). Similar results were seen with DDp53-HMECs expressing
neuT and other shRNAs targeting PIK3R1 (data not shown).Together this data indicates
that reduced p85g synergistically augments PIγK signaling driven by the pathway-
activating oncogenic HER2/neu in starved or growth factor-stimulated conditions.
To further explore the ability of partial p85g loss to synergize with oncogenes common to
breast cancer, we generated DDp53-HMECs stably expressing oncogenic p110g-
H1047R in addition to stable knockdown of PIK3R1. Compared to DDp53-HMECs
expressing p110g-H1047R and shControl, both PIK3R1 knockdown cell lines formed
approximately 4 fold more colonies when grown in 0.3% agar for 3 weeks (Figure 2.7
A). We also examined PI3K/AKT activation in these cells in response to EGF stimulation
following overnight starvation. In DDp53-HMECs expressing p110g-H1047R, PIK3R1
increased phosphorylation of AKT at both T308 and S473 in comparison to the
shControl (Figure 2.7 B). Together this data demonstrates that partial loss of p85g can
further augment transformation mediated by PI3K-activating oncogenes clinically
relevant to breast cancer, including HERβ/neu and p110g-H1047R.
66
Figure 2.7: PIK3R1 knockdown increases transformation and PI3K/AKT signaling driven by p110g-H1047R in DDp53-HMECs. (A) DDp53-HMECs with stable expression of p110g-H1047R and shControl or shPIK3R1 were tested for anchorage-independent growth. Single-cell suspensions were plated in 0.3% agar and grown for 3 weeks. 25,000 cells were plated per 6cm plate. The number of colonies was counted for one independent experiment of at least 3 plates per cell line. Means ± SD are shown; N ≥ γ for each. (B) The indicated cell lines were starved of serum and growth factors overnight and then stimulated with 20ng/ml EGF for the indicated amounts of time. Protein lysates were collected and subjected to immunoblotting. Membranes were stripped and re-probed for vinculin as a loading control.
67
Transformation driven by PIK3R1 knockdown is mediated by signaling through p110g
The PI3K catalytic isoforms play divergent roles in physiological and pathophysiological
signaling. Knowing which isoforms are functionally critical in different contexts can inform
future clinical use of isoform-selective inhibitors. Accordingly, we used pan-PI3K and
isoform-selective inhibitors to determine the contribution of different p110 isoforms to the
transformation of HMECs mediated by PIK3R1 knockdown. We plated DDp53-HMECs
expressing control or PIK3R1-targeting shRNAs in 0.3% agar, and grew cells for 4
weeks in the presence of either pan-PI3K or isoform-selective PI3K inhibitors. Either the
pan-PI3K inhibitor GDC0941 (Folkes et al., 2008) or the p110g-selective inhibitor
BYL719 (Furet et al., 2013) effectively inhibited colony formation of PIK3R1 knockdown
lines in a dose-dependent manner (Figure 2.8 A-B). Treatment with the p110く-selective
inhibitor TGX221 did not have a substantial effect on colony growth, even at doses well
above the IC50 of this compound (Jackson et al., 2005) (Figure 2.8 C). These results
suggest that transformation of DDp53-HMECs with partial p85g is mediated by PIγK
signaling through p110g and not p110く.
While it has been demonstrated that similar to our findings with PIK3R1 knockdown
DDp53-HMECs, HER2/neu-driven transformation is dependent on p110g (Utermark et
al., 2012), recent work has also demonstrated that the presence of co-existing
oncogenic events can shift PI3K isoform dependency (Schmit et al., 2014). Therefore,
we were interested to determine the isoform dependency of HER2/neu-driven
transformation in the context of partial p85g loss. We plated single-cell suspensions of
DDp53-HMECs with stable expression of neuT and either shControl, shPIK3R1, or
p110g-H1047R in 0.3% agar and allowed cells to grow for 3 weeks with different PI3K
inhibitors. Treatment with the pan-PIγK inhibitor GDC0941 or the p110g-selective
inhibitor BYL719 effectively inhibited colony formation of these cells (Figure 2.9 A-B),
68
Figure 2.8: Transformation of PIK3R1 knockdown DDp53-HMECs is blocked by p110g-selective pharmacological inhibition. DDp53-HMECs with stable expression of shControl or shPIK3R1 were plated as single-cell suspensions in 0.3% agar and grown for 4 weeks. 9,000 cells were plated per well of a 12-well plate. Fresh growth medium containing either the pan-PI3K inhibitor GDC0941 (A), the p110g-selective inhibitor BYL719 (B), or the p110く-selective inhibitor TGX221 (C) was given every three days. Means ± SD are shown for triplicate wells from representative experiments.
69
Figure 2.9: Transformation of PIK3R1 knockdown DDp53-HMECs with activated HER2/neu is blocked by p110g-selective inhibition. DDp53-HMECs with stable expression of neuT and shControl, shPIK3R1, or p110g-H1047R were plated as single-cell suspensions in 0.3% agar and grown for 3 weeks. 4,500 cells were plated per well of a 12-well plate. Fresh growth medium containing either the pan-PI3K inhibitor GDC0941 (A), the p110g-selective inhibitor BYL719 (B), or the p110く-selective inhibitor KIN193 (C) was given every three days. Means ± SD are shown for triplicate wells from representative experiments.
70
while treatment with the p110く-selective inhibitor KIN193 did not substantially effect
colony growth (Figure 2.9 C), even at concentrations that completely block AKT
activation in PTEN-null cancer cell lines (Ni et al., 2012). Consistent with these findings,
either GDC0941 or BYL719 blocked PI3K/AKT pathway activation in DDp53-HMECs
expressing neuT and shPIK3R1 in a dose-dependent manner, while KIN193 only slightly
reduced AKT and S6 phosphorylation at the highest doses (Figure 2.10). We would note
that these inhibitor experiments are missing an important positive control for the p110く
inhibitors: to demonstrate that TGX221 and KIN193 are acting as expected, we plan to
carry out similar experiments using the PTEN null breast cancer cells HCC70, MDA-MB-
468, and BT-549; signaling in and transformation of these cells has been shown to be
largely reliant on p110く (Jia et al., 2008; Ni et al., 2012; Torbett et al., 2008; Wee et al.,
2008). Nonetheless, the results presented here indicate that the augmented PI3K/AKT
signaling in and transformation of PIK3R1 knockdown DDp53-HMECs with or without
expression of neuT is primarily mediated by p110g.
PIK3R1 knockdown does not affect PTEN levels or lipid phosphatase activity
Next we were interested in determining the molecular mechanism by which decreased
p85g levels could increase PIγK/AKT output and mediate transformation. Recent studies
have reported that p85g may directly bind PTEN (Chagpar et al., 2010; Rabinovsky et
al., 2009) and increase its phosphatase activity (Chagpar et al., 2010); this binding was
found to be dependent on EGF stimulation in one study (Chagpar et al., 2010). Other
publications have suggested that p85g may be important for PTEN stability at the mRNA
or protein level (Cheung et al., 2011; Taniguchi et al., 2010). We hypothesized that if
p85g had a stabilizing or activating function on this negative regulator of the PIγK/AKT
pathway, then partial p85g loss may lead to reduced levels or activity of PTEN, thereby
increasing PI3K/AKT signaling.
71
Figure 2.10: PI3K/AKT signaling in PIK3R1 knockdown DDp53-HMECs with activated HER2/neu is blocked by p110g-selective inhibition. DDp53-HMECs stably expressing neuT and shPIK3R1 #2 were starved of serum and growth factors overnight, then stimulated with starvation medium containing 20ng/ml EGF and the indicated concentrations of PI3K inhibitors for 15 minutes. Protein lysates were collected and subjected to immunoblotting. Membranes were stripped and re-probed for total proteins and vinculin as a loading control. Bands were quantified by densitometry and normalized first to the corresponding total protein, then to the corresponding band for the DMSO control. One representative experiment is shown.
72
Figure 2.11: Endogenous p85g and PTEN do not appear to interact in DDp53-HMECs. DDp53-HMECs with stable expression of scrambled control or PIK3R1-targeting shRNAs were starved of serum and growth factors for 4 hours and then given either fresh starvation medium or 20ng/ml EGF for the indicated amounts of time. Protein lysates were collected and subjected to immunoprecipitation reactions for either endogenous PTEN (A) or endogenous p85g (B). Samples were then analyzed by immunoblotting. Membranes were stripped and re-probed for vinculin as a loading control.
73
We first sought to determine whether an interaction between endogenous p85g and
PTEN proteins occurred in our DDp53-HMECs. We synchronized shControl and
shPIK3R1 DDp53-HMECs by a 4 hour serum and growth factor starvation, stimulated
half of the cells with 20ng/ml EGF, collected protein lysates, and carried out
immunoprecipitation reactions for PTEN. Although we were able to achieve reliable
immunoprecipitation of endogenous PTEN from both cell lines, we could not detect any
evidence of p85g co-immunoprecipitation either under starved or stimulated conditions
(Figure 2.11 A). We also carried out similar experiments with immunoprecipitation of
p85g from synchronized or EGF-stimulated DDp53-HMECs. We consistently
immunoprecipitated endogenous p85g from shControl and shPIK3R1 cell lines, but while
we observed co-immunoprecipitation of endogenous p110g in these experiments, we did
not detect endogenous PTEN in immunoprecipitations from either starved or stimulated
cells (Figure 2.11 B). Despite altering a number of conditions for these
immunoprecipitation reactions, including the antibodies and buffers used, similar results
were seen across multiple experiments (data not shown). Thus we could not positively
demonstrate an interaction between endogenous p85g and PTEN in our HMECs.
We considered that a p85g-PTEN interaction might be easier to demonstrate in certain
cell types over others. Neither of the publications showing this interaction used HMECs;
however, both studies used HeLa cells among other cell types in their
immunoprecipitation experiments (Chagpar et al., 2010; Rabinovsky et al., 2009). We
therefore used HeLa cells in addition to wildtype HMECs without p53 inactivation. These
cell lines were starved of serum and growth factors for 4 hours, and then half of the cells
were stimulated with 20ng/ml EGF. Protein lysates were collected and subjected to
immunoprecipitation for endogenous p85g. Although p85g and p110g were reliably co-
immunoprecipitated from both cell lines, PTEN was not detected in these samples under
74
Figure 2.12: PTEN and p85g do not appear to interact in a variety of cell types. (A) HeLa cells and HMECs without p53 inactivation were starved of serum and growth factors for 4 hours before being stimulated with 20ng/ml EGF for the indicated amounts of time. Protein lysates were collected and used in immunoprecipitation reactions for endogenous p85g or PTEN. (B) 293T cells were either mock transfected or transiently transfected with wildtype PIK3R1. Protein lysates were collected and subjected to immunoprecipitation for PTEN or p85g. Membranes were stripped and re-probed for vinculin as a loading control.
75
either starved or stimulated conditions (Figure 2.12 A). Based on these results we were
unable to conclude that p85g and PTEN interact in HeLa cells.
Finally, we speculated that the amount of interacting p85g and PTEN might be a small
fraction of the total amount of these proteins, potentially making it difficult to detect
endogenous co-immunoprecipitation. We therefore transiently transfected 293T cells
with a wildtype PIK3R1 construct, collected protein lysates from these cells, and
subjected them to immunoprecipitation for either PTEN or p85g. Compared to the mock
transfected cells, transient transfection with PIK3R1 led to substantial overexpression of
p85g (Figure 2.12 B). Although immunoblots revealed a small amount of p85g present
in PTEN immunoprecipitates, a comparable amount of p85g was detected in the beads
only control, suggesting that when p85g was highly overexpressed it bound at a low,
non-specific level to the beads used for immunoprecipitation (Figure 2.12 B). Similar
results were seen in multiple independent experiments (data not shown). Consistent with
this conclusion, we did not observe any co-immunoprecipitated PTEN along with p85g in
PIK3R1-transfected 293T cells, despite achieving co-immunoprecipitation of both p110g
and p110く (Figure 2.12 B). Taken together, we were unable to satisfactorily
demonstrate an interaction between p85g and PTEN in a variety of cell types and
conditions.
While we were unable to positively shown an interaction between p85g and PTEN in our
experiments, it has been also been reported that mutation or loss of PIK3R1 might
destabilize PTEN, either at the level of transcription or translation (Cheung et al., 2011;
Taniguchi et al., 2010). To explore this possibility, we first examined PTEN protein levels
in our HMECs with PIK3R1 knockdown. We collected three independent sets of protein
lysates from cells synchronized by serum and growth factor starvation, subjected them
76
to immunoblotting for PTEN, and used densitometry to quantify the intensity of each
band relative to the vinculin loading control. In DDp53-HMECs, stable PIK3R1
knockdown did not have a consistent effect on the steady-state PTEN levels; only one of
the shPIK3R1 lines had significantly reduced PTEN protein levels, of 29.8 ± 4.1%
compared to the shControl (N = 3 for both) (Figure 2.2 C). We also assessed PTEN
protein levels in our neuT-expressing DDp53-HMECs: compared to the shControl, only
one shPIK3R1 line showed a significant reduction in PTEN protein levels of 32.9 ± 4.0%;
the p110g-H1047R line also had a significant reduction of 17.1 ± 1.7% in PTEN levels (N
= 3 for all) (Figure 2.5 C). These results suggest that in HMECs, partial reduction of
p85g does not necessarily lead to destabilization of PTEN protein.
We also sought to confirm that PTEN transcripts were not affected by PIK3R1
knockdown in our HMEC lines. We used quantitative PCR (qPCR) to assess the levels
of PTEN mRNA in extracts from DDp53-HMECs stably expressing shControl or
shPIK3R1. As an additional control, we also examined mRNA levels of the INPP4B
phosphatase; INPP4B is a lipid phosphatase that removes phosphorylation of the 4’
hydroxyl group of PtdIns(3,4)P2, and has been identified as a tumor suppressor in breast
cancer in a screen using HMECs (Gewinner et al., 2009). Compared to the shControl
line, both shPIK3R1 lines had somewhat increased levels of INPP4B transcripts (Figure
2.13 A). In addition, while one shPIK3R1 line had somewhat decreased PTEN
transcripts compared to the shControl line, the other shPIK3R1 line showed slightly
elevated PTEN mRNA levels (Figure 2.13 A). Together these qPCR results suggest that
PIK3R1 expression is not a reliable predictor of the mRNA levels for either the INPP4B
or PTEN tumor suppressor genes.
Although we were unable to reproduce a p85g-PTEN interaction in our experiments, and
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Figure 2.13: PIK3R1 knockdown does not affect PTEN mRNA levels or lipid phosphatase activity in DDp53-HMECs. (A) Quantitative PCR (qPCR) was used to determine the levels of INPP4B and PTEN mRNA in extracts from DDp53-HMECs stably expressing scrambled control or PIK3R1-targeting shRNAs. Means ± SD are shown for one experiment performed in triplicate. Levels were normalized to the corresponding mean for shControl. (B-C) In vitro lipid phosphatase assays for PTEN immunoprecipitated from shControl or shPIK3R1 DDp53-HMECs. A malachite green reagent was used to detect phosphate in prepared standards (B) or released upon incubation of PtdIns(3,4,5)P3 substrate with PTEN immunoprecipitates. Three negative controls were used: PIP3 Only, assay performed using substrate but no source of PTEN; PTEN Only, assay performed using PTEN immunoprecipitated from shControl cells but with no substrate added; and Beads Only, assay performed using precipitates from shControl cells in which beads but no PTEN antibody was used. The amount of phosphate released in in vitro assays was interpolated from comparison to the phosphate standards. For (B), means ± SD are shown for standards in triplicate. For (C), means ± SEM are shown for assays performed using three independent immunoprecipitation reactions per group. Statistical analysis was performed using unpaired t-test as compared to the shControl. *, P < 0.05; ns, not significant.
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we did not find a consistent effect of PIK3R1 knockdown on the levels of PTEN mRNA or
protein, the possibility remained that partial p85g loss might affect PTEN lipid
phosphatase activity. To assess PTEN activity in our HMEC lines, we carried out PTEN
immunoprecipitations and performed in vitro lipid phosphatase assays using
PtdIns(3,4,5)P3 as a substrate. In these assays, a malachite green reagent was used to
detect phosphate liberated by lipid phosphatase activity towards the provided substrate.
We used three negative controls, consisting of assays performed either without PTEN
added (“PIPγ Only,” using substrate but no source of PTEN, and “Beads Only,” using
precipitate from shControl cells with beads but no antibody), or without substrate added
(“PTEN Only,” using PTEN immunoprecipitated from shControl cells). These controls
produced negligible phosphate release (Figure 2.13 C). Compared to these controls,
PTEN immunoprecipitated from shControl DDp53-HMECs was able to convert 25.0 ±
0.6% of the PtdIns(3,4,5)P3 substrate provided to PtdIns(4,5)P2 (N = 3) (Figure 2.13 C).
PTEN immunoprecipitated from one of the shPIK3R1 lines converted significantly more
substrate, with 30.5 ± 1.8% conversion, while PTEN immunoprecipitated from the other
shPIK3R1 line was similar to the control, with 25.2 ± 1.0% substrate conversion (N = 3
for both) (Figure 2.13 C). Admittedly, the conclusions from this experiment are limited by
the inability to control for the exact amount of immunoprecipitated PTEN in each in vitro
lipid phosphatase assay; however, previous experiments from these same cell lines
produced a comparable amount of PTEN protein in immunoprecipitation reactions
(Figure 2.11 A). These results suggest that in DDp53-HMECs, partial p85g loss does
not lead to reduced PTEN lipid phosphatase activity.
PIK3R1 knockdown does not increase RTK activation or alter RTK trafficking
Because we were unable to demonstrate an interaction between p85g and PTEN, and
did not find that PIK3R1 knockdown significantly impacted PTEN levels or lipid
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phosphatase activity, we looked for a mechanism of transformation mediated by partial
p85g loss that did not involve PTEN. To determine whether the augmented growth
factor-mediated PI3K signaling in PIK3R1 knockdown cells was due to increased
receptor activation, we assessed EGFR phosphorylation in response to EGF stimulation
using two different methods. First, we synchronized shControl and shPIK3R1 DDp53-
HMECs by a 4 hour serum and growth factor starvation, stimulated the cells with
20ng/ml EGF for timepoints up to 1 hour, and collected protein lysates. We then
performed immunoblotting using an antibody specific to EGFR phosphorylated on
Y1068, one of the three major activating autophosphorylation sites (Downward et al.,
1984). Although PIK3R1 knockdown cells exhibited significantly increased and sustained
phosphorylation of AKT and S6 ribosomal protein, phosphorylation of EGFR at Y1068
was largely unchanged (Figure 2.14 A). While Y1068 is one of the main residues
phosphorylated during EGFR activation, other phosphorylated tyrosines also contribute
to activation of this receptor (Downward et al., 1984). To completely assess EGFR
phosphorylation status, we next carried out the same EGF stimulation timecourse,
performed immunoprecipitations for tyrosine-phosphorylated proteins, and subjected
these samples to immunoblotting for total EGFR. Following EGF stimulation, PIK3R1
knockdown cells showed a similar or even slightly reduced amount of total tyrosine-
phosphorylated EGFR when compared to control cells (Figure 2.14 B). Together, these
results indicate that the increase in growth factor-stimulated PI3K signaling in PIK3R1
knockdown cells likely occurs at a step in pathway activation that is downstream of
receptor autophosphorylation and activation.
Following activation, RTKs are internalized in endosomes, and are then either recycled
back to the cell surface or targeted to lysosomes for degradation (Miaczynska, 2013).
Intracellular trafficking of receptors can control the magnitude and duration of signaling
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Figure 2.14: PIK3R1 knockdown does not increase growth factor-stimulated RTK phosphorylation in DDp53-HMECs. (A) The indicated cell lines were starved of serum and growth factors for 4 hours and then stimulated with 20ng/ml EGF for the indicated amounts of time. Protein lysates were collected and subjected to immunoblotting. Membranes were stripped and re-probed for vinculin as a loading control. One representative experiment is shown. (B) Growth factor stimulation was performed as in (A); protein lysates were collected and subjected to immunoprecipitation using beads conjugated to the 4G10 antibody recognizing tyrosine-phosphorylated residues. Immunoprecipitates were subjected to immunoblotting for phosphorylated tyrosines using the 4G10 antibody; membranes were stripped and re-probed for total EGFR and vinculin as a loading control. One representative experiment is shown.
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(Miaczynska, 2013), and is regulated by a number of Rab small GTPases (Jean and
Kiger, 2012; Stenmark, 2009). The BH domain of p85g reportedly has GAP activity
towards select small GTPases, including Rab4 and Rab5 (Chamberlain et al., 2004),
and disruption of this activity leads to increased PI3K/AKT activation and cellular
transformation (Chamberlain et al., 2004; Chamberlain et al., 2008), apparently due to
more rapid and sustained internalization and reduced degradation of RTKs
(Chamberlain et al., 2008; Chamberlain et al., 2010). Therefore, we were interested to
know whether the increased PI3K signaling and transformation in our PIK3R1
knockdown cells could be due to altered intracellular trafficking of receptors, as a
consequence of reduced p85g Rab-GAP function.
To assess effects of PIK3R1 knockdown on RTK trafficking, we used biotin labeling to
track both internalization and degradation of surface proteins. First, to analyze receptor
internalization, shControl and shPIK3R1 cells were synchronized by overnight serum
and growth factor starvation, and then all surface proteins were labeled with biotin. Cells
were stimulated with 20ng/ml EGF to initiate receptor internalization, remaining surface
biotin was cleaved, and cells were lysed and subjected to immunoprecipitation with
streptavidin beads to capture internalized biotinylated proteins. Immunoblotting was then
used to assess the amount of total EGFR in the samples. Both shControl and shPIK3R1
cells had similar rates of EGFR internalization (Figure 2.15 A). Next, to analyze receptor
degradation, all surface proteins of synchronized shControl and shPIK3R1 cells were
labeled with biotin, cells were stimulated with EGF, and cells were lysed and subjected
to immunoprecipitation with streptavidin beads to capture all remaining biotinylated
proteins. Immunoblotting for total EGFR revealed that PIK3R1 knockdown cells had a
rate of EGFR degradation comparable to that of the control cells (Figure 2.15 B). These
experiments indicate that in DDp53-HMECs, partial loss of p85g does not have a
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Figure 2.15: PIK3R1 knockdown does not affect growth factor-stimulated RTK trafficking in DDp53-HMECs. (A) EGFR internalization in response to EGF. The indicated cell lines were starved of serum and growth factors overnight. Surface proteins were labeled with biotin, cells were stimulated with 20ng/ml EGF for the indicated amounts of time to initiate receptor internalization, and remaining surface biotin was cleaved. Protein lysates were generated and used in streptavidin immunoprecipitation to capture internalized biotinylated proteins. Immunoblotting was used to determine the amount of tyrosine-phosphorylated EGFR in the samples. Membranes were stripped and re-probed for total EGFR and vinculin as a loading control. T.S., total surface protein prior to stimulation. (B) EGFR degradation in response to EGF. The indicated cell lines were starved as in (A). Surface proteins were biotinylated, and then cells were stimulated with 20ng/ml EGF for the indicated amounts of time. Protein lysates were generated and then subjected to streptavidin immunoprecipitation to capture all remaining biotinylated proteins. Immunoblotting was used to determine the amount of total EGFR in the samples. Membranes were stripped and re-probed for vinculin as a loading control. T.S., total surface protein prior to stimulation. Representative experiments for (A) and (B) are shown.
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substantial effect on EGFR trafficking.
PIK3R1 knockdown increases the amount of p85-p110g bound to activated RTKs
Binding to the p85 regulatory subunit is required for p110 catalytic subunit stability (Yu et
al., 1998b). Furthermore, p85 serves as a necessary adaptor for recruiting p110 to
activated RTKs, where the p85-p110 heterodimer becomes activated (Rameh et al.,
1995; Yu et al., 1998a; Yu et al., 1998b). Research from the lab of Dr. Cantley has
suggested that in some tissues, p85 may be present in excess of p110, and that free
p85 might function as a negative regulator of PI3K signaling by competing with p85-p110
heterodimers for binding to phosphorylated RTKs (Luo and Cantley, 2005; Ueki et al.,
2003; Ueki et al., 2002b). Therefore, we were interested to know whether PIK3R1
knockdown in DDp53-HMECs might selectively reduce free p85g, allowing more p85-
p110 heterodimers to bind activated RTKs, thereby increasing PI3K/AKT signaling.
To test whether partial loss of p85 in our cells augments PI3K activation by selectively
depleting free p85, we generated polyclonal DDp53-HMEC lines with stable expression
of flag-tagged, activated ErbB3 (Flag-TEL-ErbB3) along with shRNA targeting PIK3R1.
Expression of Flag-TEL-ErbB3 lead to low-level colony formation of DDp53-HMECs, with
150.7 ± 18.8 colonies per 50,000 cells, while additional expression of p110g-H1047R
robustly increased transformation of these cells, to 891.5 ± 16.6 colonies per 50,000
cells (N = 3 for both) (Figure 2.16). Consistent with our previous data, knockdown of
PIK3R1 in these cells increased colony formation to a similar extent as p110g-H1047R,
with 685.8 ± 20.4 and 725.2 ± 53.9 colonies per 50,000 cells (N = 3 for both) (Figure
2.16). These findings suggest that in DDp53-HMECs, the expressed Flag-TEL-ErbB3 is
weakly activated and transforming, and can cooperate with partial p85g loss.
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Figure 2.16: PIK3R1 knockdown increases transformation of DDp53-HMECs expressing activated ErbB3. DDp53-HMECs stably expressing flag-tagged, activated ErbB3 (Flag-TEL-ErbB3) were infected with lentivirus containing a negative control scrambled shRNA or one of two distinct shRNAs targeting PIK3R1, or with retrovirus containing the cancer-associated p110g-H1047R mutant as a positive control. Following selection for stable polyclonal lines, these cells were tested for anchorage-independent growth. Single-cell suspensions were plated in 0.3% agar and grown for 4 weeks. 50,000 cells were plated per 6cm plate. The number of colonies was counted for three independent experiments of at least 3 plates each. Means ± SEM are shown; N = 3 for each group. Statistical significance was determined by unpaired t-test. Significance for comparison to the shControl is shown. ***, P < 0.001; ****, P < 0.0001.
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To assess the effect of PIK3R1 knockdown on binding of p85 and p110 to activated
RTKs in DDp53-HMECs, we starved the cells of serum and growth factors to limit RTK
activation to just the Flag-TEL-ErbB3, then used the Flag tag to immunoprecipitate this
activated receptor. Immunoblotting and densitometric quantification was then used to
determine the amounts of pan-p85 and p110g bound to Flag-TEL-ErbB3 (Figure 2.17
A). Compared to the shControl, both shPIK3R1 lines had significantly reduced pan-p85
levels, by 68.6 ± 3.7% and 69.3 ± 1.7% (N = 4 for all) (Figure 2.17 E). PIK3R1
knockdown reduced the amount of pan-p85 bound to Flag-TEL-ErbB3 by 43.6 ± 14.7%
and 53.4 ± 4.2% compared to the shControl (N = 4 for all) (Figure 2.17 B). Both
shPIKγR1 lines also exhibited a slight but significant reduction in p110g protein in whole
cell lysates as compared to the shControl line, of 20.9 ± 7.1% and 32.2 ± 6.4% (N = 4 for
all) (Figure 2.17 F); despite this, the amount of p110g associated with Flag-TEL-ErbB3
was actually increased in shPIK3R1 lines, with fold increases of 1.5 ± 0.3 and 1.4 ± 0.1
as compared to the shControl (N = 4 for all) (Figure 2.17 C). The net result was that
knockdown of PIK3R1 in DDp53-HMECs increased the ratio of p110g:pan-p85 bound to
activated ErbB3 by a fold of 3.7 ± 0.4 and 2.5 ± 0.1 as compared to the shControl (N = 4
for all) (Figure 2.17 D). These ratios correlated well with the fold increase in AKT
activation in these cells, as determined by phosphorylation at S473, of 2.4 ± 0.4 and 1.7
± 0.2 as compared to the shControl line (N = 4 for all) (Figure 2.17 G). These findings
were recapitulated with two additional PIK3R1 knockdown DDp53-HMEC lines, and also
confirmed using a different pan-p85 antibody (data not shown).
Together, the data presented in this chapter is consistent with the model of increased
PI3K/AKT signaling and transformation mediated by partial p85g loss depicted in Figure
2.18: in mammary epithelial cells with normal p85 levels, p85 is present in excess of
p110, and activated sites on receptors are able to be bound by both non-signaling free
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Figure 2.17: PIK3R1 knockdown increases the amount of p85-p110g bound to activated RTKs in DDp53-HMECs. DDp53-HMECs stably expressing Flag-TEL-ErbB3 and either shControl, shPIK3R1, or p110g-H1047R were starved of serum and growth factors for 4 hours; protein lysates were collected and subjected to immunoprecipitation for ErbB3 using beads conjugated to anti-flag antibody. (A) Representative immunoblot. Membranes were stripped and re-probed for total proteins and vinculin as a loading control. (B-D) Bands for proteins in ErbB3 immunoprecipitates from immunoblots were quantified by densitometry. For (B-C), protein levels were normalized first to the amount of ErbB3 in the immunoprecipitates, then to the corresponding mean for the shControl. For (D), protein levels of p110g were normalized to the levels of pan-p85 in immunoprecipitates, then to the corresponding mean for the shControl. (E-G) Bands for proteins in whole cell lysates from immunoblots were quantified by densitometry. Protein levels were normalized first to the vinculin loading control (for pan-85 and p110g) or the total unphosphorylated protein (for phospho-AKTS473), then to the corresponding mean value for the shControl. For (B-G), means ± SEM are shown for four independent experiments, N = 4 for each. Statistical significance was determined by unpaired t-test. Significance for comparison to the shControl is shown. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001; ns, not significant.
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Figure 2.18: Model: partial p85g loss leads to increased PI3K/AKT signaling and transformation. The data presented in Chapter 2 is consistent with a model in which p85 monomers compete with p85-p110 heterodimers to negatively regulate RTK-mediated PI3K/AKT signaling. Top: In mammary epithelial cells with normal p85g levels, p85 is present in excess of p110. Both monomeric p85 and heterodimeric p85-p110 can compete for binding to sites on activated RTKs, but only p85-p110 is capable of signaling. Bottom: In mammary epithelial cells with partial p85g reduction, the pool of monomeric p85g is selectively depleted, since p85 is required for p110 stability; more binding sites on activated RTKs are available for p85-p110 heterodimers, allowing for upregulated RTK-mediated PI3K signaling. While it is likely that reduced p85g levels similarly affect p110g and p110く, the p110く isoform has a minimal role in RTK-mediated signaling, possibly due to lower RTK-associated lipid kinase activity of p110く in comparison to p110g (Utermark et al., 2012).
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p85 and signaling-capable p85-p110 heterodimers; under conditions of partial p85g loss,
the pool of free p85 is selectively reduced, allowing for more p85-p110 heterodimers to
bind activated receptors, resulting in increased PI3K signal output. Although we expect
p85g reduction to similarly affect RTK signaling through p110g and p110く, since the
p110く isoform contributes little to PI3K signaling downstream of RTKs (Utermark et al.,
2012), it likely plays a minor role in this context. By this model, a balance between p85
and p110 subunits is expected to be critical for regulation of PI3K signaling in response
to inputs from activated RTKs.
Summary and discussion
In this chapter, we find that heterozygous deletion of PIK3R1 is frequent in human breast
cancers, and that furthermore PIK3R1 expression is significantly reduced in breast
tumors when compared to normal breast tissue. We show that RNAi-mediated
downregulation of p85g in DDp5γ-HMECs augments PI3K/AKT signaling in response to
growth factor stimulation, and increases colony formation in agar. PIK3R1 knockdown
also augments PI3K/AKT signaling and transformation driven by oncogenes common in
breast cancer, including p110g-H1047R and activated HER2/neu. Studies using pan-
PI3K and isoform-selective inhibitors suggest that HMEC transformation driven by partial
p85g loss is primarily mediated by signaling through p110g. Contrary to reports linking
p85g to PTEN stability or activity, we find that PIK3R1 downregulation in HMECs does
not substantially change steady-state PTEN mRNA or protein levels, or in vitro PTEN
lipid phosphatase activity. In addition, although p85g has been reported to have GAP
activity towards the Rab5 GTPase important for intracellular trafficking, we find that RTK
internalization and degradation is largely unchanged in PIK3R1 HMECs. Instead, we find
that partial reduction of p85g increases the amount of p85-p110g associated with
activated RTKs, suggesting a model where excess p85 monomers compete with p85-
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p110 heterodimers to negatively regulate RTK-mediated PI3K signaling.
The data presented in Chapter 2 strongly suggest that partial loss of p85g leads to an
increase in growth factor-stimulated PI3K/AKT pathway activation. However, a number
of additional experiments will help to confirm these findings. We have shown that
PIK3R1 knockdown increases phosphorylation of AKT at both activation sites in
response to growth factors, and while AKT phosphorylation is in general a good readout
for PI3K pathway activation, a more direct measure will be to assess production of
PtdIns(3,4,5)P3. We expect that in our HMECs, PtdIns(3,4,5)P3 levels will correlate well
with AKT phosphorylation, but in certain contexts it seems that this is not always the
case (Vora et al., 2014) and (J.A. Engelman, unpublished observations), so this will be
important to confirm. We also plan to extend our immunoblot experiments (Figure 2.2,
Figure 2.3, Figure 2.4, Figure 2.5, and Figure 2.6) to include other activated
downstream components of this pathway, in particular 4EBP1 phosphorylated at S65,
S6K phosphorylated at T389, PRAS40 phosphorylated at Tβ46, and GSKγく
phosphorylated at S9, to further confirm PI3K/AKT pathway upregulation in our PIK3R1
knockdown cells. Finally, we will expand on our pharmacological inhibition experiments
(Figure 2.8, Figure 2.9, and Figure 2.10) by using AKT-selective inhibitors such as the
ATP-competitive small molecule inhibitor GSK690693 (Rhodes et al., 2008) or the
allosteric inhibitor MK2206 (Hirai et al., 2010) to treat our PIK3R1 knockdown HMECs. If
transformation of these cells is indeed driven by PI3K/AKT pathway upregulation, we
expect that these agents will effectively block signaling in and transformation of these
cells in a manner similar to PI3K-selective inhibitors. Together, these proposed
experiments will further confirm that partial p85g loss transforms HMECs by increasing
PI3K/AKT pathway activation.
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Although the data presented in Chapter 2 are consistent with the competition model we
propose (Figure 2.18), additional experiments may substantially strengthen the
argument for this model. Using immunoblotting techniques, we have shown that PIK3R1
knockdown in HMECs increases the amount of p85-p110g bound to activated RTKs
(Figure 2.17 D). We plan to verify this result using mass spectrometry to determine the
number of p85 and p110 molecules bound to these activated RTKs. It will also be critical
to use in vitro lipid kinase assays to demonstrate that in these same cells, the PI3K
activity associated with activated RTKs is increased upon PIK3R1 knockdown. Our
model also relies on p85 being present in excess of p110 in HMECs. We performed
immunodepletion experiments similar to those published by other groups (Geering et al.,
2007; Mauvais-Jarvis et al., 2002; Ueki et al., 2002a) which indicated that this may in
fact be the case (data not shown), but technical difficulties precluded a definitive
conclusion from these results. An alternative approach will be to perform size-exclusion
chromatography on whole cell lysates from control and PIK3R1 knockdown HMECs,
followed by immunoblotting of fractions for p85 and p110 isoforms. We expect that if p85
is present in excess of p110, p85g will be detected in two distinct sets of fractions:
monomeric p85g without p110 will be found in earlier fractions of smaller molecular
weight, while heterodimeric p85g with p110 will be found in later fractions of higher
molecular weight. We additionally expect that compared to the control cells, PIK3R1
knockdown HMECs will have a reduced amount of monomeric p85g detected in earlier
fractions of lower molecular weight. Finally, to determine the absolute amounts of PI3K
subunits in our cells, we plan to perform mass spectrometry or immunoblotting of total
cell lysates in comparison to known amounts of recombinant p110 and p85 proteins.
Together, these experiments may strengthen the argument for the competition model we
have proposed here.
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One caveat to the immunoprecipitation experiments presented in this chapter to support
this competition model is the use of Flag-TEL-ErbB3 as an activated RTK probe for
bound PI3K isoforms. HER3/ErbB3 is generally considered to be a pseudokinase
because it lacks residues conserved among other HER/ErbB family RTKs thought to be
required for autophosphorylation and catalytic function (Guy et al., 1994; Jura et al.,
2009; Shi et al., 2010; Sierke et al., 1997); it instead propagates RTK signals by forming
heterodimers with other HER/ErbB family members, in particular EGFR/ErbB1 and
HER2/ErbB2 (Pinkas-Kramarski et al., 1996; Tzahar et al., 1996), and does not naturally
form homodimers (Berger et al., 2004). Here we use a fusion of ErbB3 to a TEL domain
that facilitates homodimerization and activation of RTKs (Carroll et al., 1996; Golub et
al., 1994; Jousset et al., 1997). Although it might be expected that ErbB3
homodimerization would therefore not activate RTK signaling, a recent report indicated
that ErbB3 might in fact retain weak catalytic activity (Shi et al., 2010). Our data
demonstrating that ectopic expression of Flag-TEL-ErbB3 in HMECs modestly increases
AKT phosphorylation under starvation conditions (Figure 2.17 A compared to Figure 2.2
A) and augments colony formation (Figure 2.16 compared to Figure 2.3 A) are
consistent with this report. Because ErbB3 possess direct p85-binding YXXM motifs
(Hellyer et al., 1998; Prigent and Gullick, 1994; Soltoff et al., 1994) while EGFR/ErbB1
and HER2/ErbB2 require adaptors to interact with p85 (Baselga and Swain, 2009), it
was an ideal probe for bound p85 and p110 in our system.
In addition to the competition model favored here, we explored other possible
explanations for the augmented PI3K/AKT signaling and transformation seen in HMECs
with reduced PIK3R1 expression. The BH domain of p85g has been reported to have
GAP activity towards Rab4 and Rab5, small GTPases critical for endosomal trafficking
(Chamberlain et al., 2004). Disruption of the Rab-GAP function of p85g leads to
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increased growth factor-stimulated PI3K/AKT activation and cellular transformation as a
result of more rapid and sustained Rab-mediated RTK internalization (Chamberlain et
al., 2004; Chamberlain et al., 2008; Chamberlain et al., 2010). Furthermore, a recent
report demonstrated that in MEFs, RNAi-mediated PIK3R1 knockdown increased the
amount of active GTP-bound Rab5, augmented PI3K/AKT pathway activation, and
induced autophagy (Dou et al., 2013). Accordingly, we examined whether p85g
downregulation affected growth factor-stimulated trafficking of RTKs in our HMEC lines.
We found that PIK3R1 knockdown did not have a substantial effect on EGFR
internalization or degradation in response to EGF stimulation (Figure 2.15). However,
we did not examine intracellular trafficking of EGFR by additional means, for example
immunofluorescence using fluorophore-conjugated EGF and known markers for different
intracellular compartments. We also did not explore whether PIK3R1 knockdown in
HMECs affected activation of Rab GTPases. Therefore, while our work suggests that the
increased growth factor-stimulated PI3K/AKT activation in these cells is likely not due to
altered RTK trafficking, we cannot completely rule out an effect on Rab GTPase
activation or function.
Based on published reports implicating p85g in PTEN binding (Chagpar et al., 2010;
Rabinovsky et al., 2009), stability (Cheung et al., 2011; Taniguchi et al., 2010), or lipid
phosphatase activity (Chagpar et al., 2010; Taniguchi et al., 2006), we also explored the
possibility that PIK3R1 knockdown had an effect on PTEN. Despite repeated attempts,
we were unable to confirm interaction of either endogenous or ectopically expressed
p85g with PTEN in HMECs or in a number of other cell types (Figure 2.11, Figure 2.12,
and data not shown). We also did not find that PIK3R1 knockdown substantially affected
PTEN mRNA or protein levels at the steady state (Figure 2.2 C, Figure 2.5 C, and
Figure 2.13 A). In addition, based on reports that in some contexts p85g is translocated
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to the nucleus (Chiu et al., 2014; Park et al., 2010; Winnay et al., 2010) and a multitude
of publications demonstrating a poorly-understood role for nuclear PTEN (reviewed in
(Planchon et al., 2008)), we examined whether PIK3R1 knockdown in HMECs affected
the subcellular localization of PTEN. Cellular fractionation experiments indicated that
p85g downregulation did not affect the proportion of PTEN associated with lipid
membrane, cytosolic, or nuclear fractions in either quiescent or EGF-stimulated HMECs
(data not shown). This is consistent with a recent study suggesting that p85g and PTEN
nuclear localization are not related (Chiu et al., 2014). Together our findings suggest that
in HMECs with PIK3R1 knockdown, upregulated PI3K/AKT signaling and transformation
may not be mediated by an effect of p85g directly on PTEN.
In summary, the data presented in this chapter demonstrates that the levels of p85g
modulate PI3K/AKT activation in mammary epithelial cells. RNAi-mediated PIK3R1
downregulation increases growth factor-stimulated PI3K signaling in and transformation
of HMECs. Partial reduction of p85g also synergizes with oncogenes common in breast
cancer, including p110g-H1047R and oncogenic HER2/neu. Both pan-PIγK and p110g-
selective pharmacological inhibitors are equally effective at blocking PI3K/AKT signaling
and colony formation mediated by PIK3R1 knockdown. Data from immunoprecipitation
of activated RTKs are consistent with a model where p85 is in excess of p110, and
monomeric p85 can compete with p85-p110 heterodimers for binding to RTKs to fine-
tune PIγK output. While others have reported a role for p85g in regulation of Rab-
mediated receptor trafficking, we find that PIK3R1 knockdown does not affect EGFR
internalization or degradation in HMECs. In contrast to published reports, we also do not
find that partial p85g reduction directly affects PTEN levels or lipid phosphatase activity.
The current literature on this topic, and the implications our work in this context, are
discussed in further detail in Chapter 4 of this dissertation.
Chapter 3: PI3K regulatory subunit p85alpha plays a tumor suppressive role in
a genetically engineered mouse model of mammary tumorigenesis
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Acknowledgements
The HMS Rodent Histopathology Core prepared slides of fixed tissue for histological
analysis and performed hematoxylin and eosin (H&E) staining of these slides. Carolynn
Ohlson performed mammary tumor transplants, daily drug administrations, and
immunohistochemical staining of fixed tissue samples. Lauren Thorpe performed all
other experiments and data analysis.
I would additionally like to thank Lewis Cantley for the generous contribution of floxed
Pik3r1 mice, and William Muller for the generous contribution of MMTV-NIC mice. Thank
you to Thanh Von for sharing his extensive knowledge of in vivo techniques. Thank you
to Roderick Bronson of the HMS Rodent Histopathology Core for help in pathological
analysis. Thank you to Qi Wang for sharing protocols for mouse mammary epithelial cell
(MMEC) isolation, and Hailing Cheng for sharing protocols and reagents for the isolation
and culture of mouse tumor cells. Finally, I would like to thank Stephanie Santiago for
sharing tips and tricks for mouse mammary gland whole mount preparation.
96
Preface
In this chapter, we use genetically engineered mouse models (GEMMs) to explore the
consequences of Cre/loxP-mediated conditional Pik3r1 ablation in the mouse mammary
epithelium. We find that p85g expression is not required for normal mouse mammary
gland development during puberty, pregnancy, or lactation. We then use a GEMM of
HER2/neu-driven breast cancer to demonstrate that Pik3r1 ablation significantly reduces
the latency of mammary tumor onset. When transplanted into recipient mice, the growth
of these tumors is blocked by treatment with pan-PIγK or p110g-selective inhibitors.
Together, these findings demonstrate the in vivo importance of p85g as a tumor
suppressor in the mammary epithelium, and suggest that isoform-selective PI3K
therapies may be effective in breast cancers characterized by a decrease in p85g.
Introduction
Genetically engineered mouse models are a convenient system in which to study
contributions of specific genes to both normal mammary gland development and
mammary tumorigenesis. Both mice and humans have three main stages of mammary
development: embryonic, pubertal, and adult (Watson and Khaled, 2008) (Figure 3.1).
During mouse embryonic development, five pairs of mammary buds form and undergo
limited initial branching, forming a rudimentary ductal tree. Following birth, terminal end
buds (TEBs) appear at the tips of the ducts and begin to invade the mammary fat pad;
during puberty, estrogen and other signals stimulate TEB proliferation and clefting,
resulting in ductal elongation and branching. By approximately 12 weeks after birth, the
mammary fat pad is filled, TEBs disappear, and ductal growth ceases. Adult mammary
glands undergo further change during pregnancy and lactation: progesterone and
prolactin induce side-branching and alveolar bud formation, differentiation into alveoli,
and milk secretion. After weaning, cell death, alveolar collapse, and remodeling occur
97
Figure 3.1: Schematic of mammary gland development in the mouse. Mouse mammary gland development progresses through several distinct stages and is tightly regulated by a number of hormones and signaling pathways. At birth, a few rudimentary ducts surround the nipple. During puberty, these ducts undergo pronounced outgrowth and branching; at the end of puberty, the mammary fat pad is filled with a ductal network. During pregnancy, additional ductal branching occurs, along with extensive lobular-alveolar development; in preparation for lactation, the secretory epithelium undergoes functional differentiation, allowing milk to be produced and secreted. Following weaning, the alveolar compartment undergoes remodeling, termed involution, and the mammary gland returns to a pre-pregnancy-like state. Hormones and growth factors known to be important for transition from one state to another are indicated above blue arrows. Signaling pathways known to be important during certain stages are indicated above that stage. Adapted from (Hennighausen and Robinson, 2001) and (Hennighausen and Robinson, 1998).
98
during a process called involution, returning the mammary gland to a pre-pregnancy-like
state (Hennighausen and Robinson, 1998). In addition to hormone signals, the different
stages of mammary gland development are tightly regulated by a number of other
signaling pathways (Hennighausen and Robinson, 2001; Hynes and Watson, 2010;
Watson and Khaled, 2008).
Several studies have established the important role of the PI3K pathway in mouse
mammary gland development and tumorigenesis. Conditional ablation of Pten in the
mammary epithelium led to accelerated ductal outgrowth and precocious lobulo-alveolar
development during puberty and pregnancy; these mice also frequently developed
mammary tumors with heterogeneous pathology as early as 2 months (Li et al., 2002).
Mice with mammary-specific expression of an inducible oncogenic p110g-H1047R
transgene developed mammary tumors with a mean latency of 7 months (Liu et al.,
2011), whereas Pik3ca ablation in the mammary epithelium significantly impaired
pubertal mammary gland branching and outgrowth and post-partum lactation, and also
blocked mammary tumor development driven by polyoma middle T antigen (pyMT) or
oncogenic HER2/neu (Utermark et al., 2012). Surprisingly, mammary-specific deletion of
Pik3cb resulted in modestly hypermorphic mammary gland development, with
precocious lobulo-alveolar growth and increased ductal branching, and moderately
accelerated pyMT- or HER2/neu-driven mammary tumor development (Utermark et al.,
2012). The distinct roles of p110g and p110く in the mammary gland were explained by a
proposed model in which p110g may have higher RTK-associated kinase activity than
p110く, allowing p110く to compete with p110g for binding sites on RTKs to regulate
PI3K output (Utermark et al., 2012) (Figure 1.6). This model was supported by extensive
biochemical experiments demonstrating increased RTK-bound p110g and RTK-
associated PIγK activity in mouse mammary epithelial cells with p110く knockout
99
(Utermark et al., 2012). Together, these studies demonstrate that in mouse models,
genetic alterations that increase PI3K/AKT signaling lead to accelerated mammary gland
development and tumorigenesis, while alterations that reduce PI3K/AKT signaling
impede mammary gland development and block tumorigenesis in certain contexts.
A number of publications have suggested that in vivo, p85g expression levels modulate
PI3K/AKT activation. Mice with genetic ablation of the p85g isoform only (Terauchi et al.,
1999), of all three regulatory isoforms arising from Pik3r1 (p85g, p55g, and p50g)
(Fruman et al., 2000), or of p55g and p50g only (Chen et al., 2004) exhibited
hypoglycemia, increased insulin sensitivity, and increased PI3K/AKT pathway activation
upon insulin stimulation. Conversely, mice with increased p85g expression displayed
increased insulin resistance and reduced PtdIns(3,4,5)P3 production (Barbour et al.,
2005). Expression levels of p85g have also been shown to modulate pathophysiological
signals in mice. Heterozygous deletion of Pik3r1 increased the incidence of prostatic
intraepithelial neoplasia induced by heterozygous Pten knockout (Luo et al., 2005c) and
the number of lung tumors in a GEMM of lung cancer driven by oncogenic KRAS
(Engelman et al., 2008). Mice with liver-specific Pik3r1 ablation developed hepatitis and
dysplastic liver nodules by 6 months of age, and liver tumors resembling hepatocellular
carcinoma by 14 to 20 months (Taniguchi et al., 2010). In this study, liver lysates from
Pik3r1 knockout mice demonstrated upregulated PI3K/AKT activation and
PtdIns(3,4,5)P3 accumulation; liver tumors were found to have significantly reduced Pten
mRNA and protein levels (Taniguchi et al., 2010). This work indicates that reduced p85g
expression can increase PI3K/AKT signaling in vivo, and that additionally in some
tissues p85g downregulation augments tumorigenesis.
In this chapter, we examine the specific role of p85g in the mammary gland. We use
100
conditional knockout techniques to determine the consequences of Pik3r1 ablation on
normal mouse mammary gland development. We then combine mammary-specific
Pik3r1 ablation with an established GEMM of HER2/neu-driven breast cancer to
examine the role of p85g in mammary tumor development. Finally, we explore the ability
of pan- and isoform-selective PI3K inhibitors to block in vivo mammary tumorigenesis in
the context of reduced p85g. As some of these agents are currently in early clinical trials
(Table 1.2 and Table 1.4), this work has important implications for therapeutic targeting
of breast cancers with reduced p85g expression.
Results
Pik3r1 expression is not required for mouse mammary gland development
The data presented in Chapter β indicates a tumor suppressive role for p85g in the in
vitro transformation of mammary epithelial cells. To determine whether these
observations hold true in vivo, we used GEMMs to evaluate the physiological and
pathophysiological consequences of p85g loss in this tissue. In mice, embryonic Pik3r1
knockout is lethal (Fruman et al., 2000). Therefore, we took advantage of the Cre/loxP
recombination system to conditionally ablate Pik3r1 in the mammary epithelium (Figure
3.2). Mice bearing a floxed Pik3r1 allele (Luo et al., 2005b) were backcrossed more than
ten generations to the FVB/N wildtype background to eliminate variations in mammary
development (MacLennan et al., 2011) and mammary tumor latency (Davie et al., 2007)
arising from different genetic backgrounds. To study the role of p85g in mouse
mammary gland development, these Pik3r1 floxed mice were then crossed with MMTV-
Cre transgenic mice, in which expression of the Cre recombinase is under control of the
MMTV LTR promoter and occurs in the secretory epithelium, including the mammary
gland, beginning at early stages of development (Wagner et al., 1997). The resulting
MMTV-Cre; Pik3r1+/loxP and MMTV-Cre; Pik3r1loxP/loxP mice have mosaic ablation of one
101
Figure 3.2: Schematic of Pik3r1 conditional knockout allele and breeding scheme for mammary-specific Pik3r1 ablation. In mice, Pik3r1 generates three regulatory isoforms, p85g, p55g, and p50g, by alternative transcription initiation and splicing. The full-length isoform p85g has N-terminal SH3 and BH domains encoded by exons 1A through 6, while p55g and p50g have the unique first exons 1C and 1B, respectively. The first exon common to all three isoforms arising from Pik3r1 is exon 7. The conditional Pik3r1 knockout mouse used in these studies have knock-in of an engineered Pik3r1 allele in which exon 7 is flanked by loxP sites (Luo et al., 2005b); Cre recombinase mediates recombination of the loxP sites, resulting in deletion of exon 7. Transcription of the recombined gene produces a truncated p85g consisting of the SHγ and BH domains, but lacking the domains necessary for binding to p110g or activated RTKs, and essentially does not produce any p55g or p50g (Luo et al., 2005b). These floxed Pik3r1 mice were interbred with MMTV-Cre mice (Wagner et al., 1997), which express the Cre transgene under control of the MMTV LTR promoter, to achieve mammary-specific Pik3r1 ablation.
102
or both Pik3r1 alleles mainly in luminal mammary epithelial cells, and will hereafter be
referred to as MMTV-Cre; Pik3r1+/- and MMTV-Cre; Pik3r1-/-.
To confirm the successful ablation of Pik3r1 in these mice, we isolated mouse mammary
epithelial cells (MMECs) from resected mammary glands of adult nulliparous female
MMTV-Cre; Pik3r1+/- and MMTV-Cre; Pik3r1-/- mice, generated protein lysates from
these cells, and used immunoblotting to determine expression of PI3K catalytic and
regulatory isoforms. Lysates of MMECs isolated from adult nulliparous female MMTV-
Cre mice were used as a wildtype control. MMECs derived from MMTV-Cre; Pik3r1+/-
and MMTV-Cre; Pik3r1-/- mice exhibited dramatically reduced p85g protein levels in
comparison to the MMTV-Cre control MMECs (Figure 3.3). In addition, as p85 is known
to be required for the stability of p110 (Fruman et al., 2000; Luo et al., 2005b; Yu et al.,
1998b), we were not surprised to find a reduction in p110g protein levels in MMTV-Cre;
Pik3r1+/- and MMTV-Cre; Pik3r1-/- MMECs. We also found that the level of p85g protein
varied slightly in each individual mouse, likely due to the mosaic nature of MMTV-Cre
expression (Wagner et al., 1997). Nonetheless, this protein analysis confirmed that this
GEMM could be used to determine the consequences of p85g loss in the mouse
mammary epithelium.
We then used whole mount techniques to analyze the effects of p85g loss in these mice
on the different stages of mammary gland development. The fourth inguinal mammary
glands from control and Pik3r1 floxed female mice were excised, fixed on slides, and
prepared with Carmine staining. Mammary gland development was assessed during
puberty in nulliparous female mice at 6 weeks of age, at the completion of puberty in 12-
week-old nulliparous females, during pregnancy at 14 days, and during lactation at 2
days postpartum (Figure 3.4). We found that there was no appreciable difference in the
103
Figure 3.3: Transgenic MMTV-Cre ablates Pik3r1 expression in mouse mammary epithelial cells. MMECs were derived from the mammary glands of individual nulliparous MMTV-Cre, MMTV-Cre; Pik3r1+/-, and MMTV-Cre; Pik3r1-/- females. Protein lysates were prepared from these MMECs and subjected to immunoblotting for PI3K isoforms. The membrane was stripped and re-probed for vinculin as a loading control.
104
Figure 3.4: Pik3r1 expression is not required for mouse mammary gland development. Whole mounts were prepared from the fourth inguinal mammary glands of MMTV-Cre; Pik3r1+/-, and MMTV-Cre; Pik3r1-/- female mice during puberty (A-C), at the end of puberty (D-F), during pregnancy (G-I), and during lactation (J-L). Mammary glands were stained with Carmine red to visualize ducts. Representative images from each genotype and stage are shown.
105
mammary gland development of MMTV-Cre; Pik3r1+/- and MMTV-Cre; Pik3r1-/- mice as
compared to the MMTV-Cre control at all developmental stages examined. Halfway
through puberty, at 6 weeks of age, the duct outgrowth of all three genotypes was similar
relative to the lymph node (Figure 3.4 A-C). At the end of puberty at 12 weeks, the ducts
had completely filled the mammary fat pads in all three genotypes, and ductal branching
was comparable (Figure 3.4 D-F). Heterozygous or homozygous Pik3r1 ablation had no
substantial effect on lobulo-alveolar development during pregnancy (Figure 3.4 G-I) or
lactation (Figure 3.4 J-L). Together, these findings demonstrate that p85g is not
required for these stages of mammary gland development in the mouse.
Mammary-specific Pik3r1 ablation leads to spontaneous mammary tumor development
Although deletion of Pik3r1 did not have a substantial effect on mouse mammary gland
development, over a longer time frame nulliparous MMTV-Cre; Pik3r1+/- and MMTV-Cre;
Pik3r1-/- females eventually developed focal or multifocal spontaneous mammary
tumors. These tumors formed with an average latency of 14.1 months, an average
survival of 14.4 months, and a penetrance of 90% (9/10) (Table 3.1). In addition, we
found metastasis of the primary mammary tumor to the lungs in 11% (1/9) of the mice
with spontaneous mammary tumors. Many of the characteristics of mammary tumor
development in Pik3r1 knockout mice are comparable to those of other established
mouse models of breast cancer (Table 3.2).
To determine the expression of PI3K isoforms and activation of the PI3K/AKT pathway in
Pik3r1 knockout spontaneous mammary tumors, we generated protein lysates from
tumor tissue and subjected them to immunoblotting. Compared to whole mammary
gland lysates from MMTV-Cre nulliparous females, mammary tumors from MMTV-Cre;
Pik3r1+/- and MMTV-Cre; Pik3r1-/- mice had reduced p85g protein levels; tumors from
106
Ta
ble
3.1
: N
ull
ipa
rou
s f
em
ale
mic
e w
ith
ma
mm
ary
-sp
ecif
ic P
ik3
r1 a
bla
tio
n
de
ve
lop
sp
on
tan
eo
us
ma
mm
ary
tu
mo
rs
Ge
no
typ
e
Mo
us
e ID
T
um
or
La
ten
cy
(mo
nth
s)
Su
rviv
al
(mo
nth
s)
Pri
ma
ry T
um
or
Pa
tho
log
y
Lu
ng
M
eta
sta
sis
?
Co
mm
en
ts
MM
TV
-Cre
; P
ik3
r1+
/-
A6
59
10
.7
11
.6
Un
diffe
ren
tia
ted
a
de
no
ca
rcin
om
a, sa
rco
ma
No
Fo
ca
l m
am
ma
ry tu
mo
r (1
)
MM
TV
-Cre
; P
ik3
r1+
/-
A6
09
12
.7
15
.9
Un
diffe
ren
tia
ted
a
de
no
ca
rcin
om
a, sa
rco
ma
No
Mu
ltifo
ca
l m
am
ma
ry tu
mors
(3
)
MM
TV
-Cre
; P
ik3
r1+
/-
A6
03
13
.5
14
.9
Un
diffe
ren
tia
ted
a
de
no
ca
rcin
om
a, sa
rco
ma
No
Mu
ltifo
ca
l m
am
ma
ry tu
mors
(2
)
MM
TV
-Cre
; P
ik3
r1+
/-
A6
05
17
.1
17
.8
ND
N
o
Mu
ltifo
ca
l m
am
ma
ry tu
mors
(2
)
MM
TV
-Cre
; P
ik3
r1+
/-
A6
07
17
.9
ND
N
D
No
MM
TV
-Cre
; P
ik3
r1-/
- A
66
0
ND
1
0.7
U
nd
iffe
ren
tia
ted
a
de
no
ca
rcin
om
a, sa
rco
ma
Ye
s
Fo
ca
l m
am
ma
ry tu
mo
r (1
)
MM
TV
-Cre
; P
ik3
r1-/
- A
60
6
12
.2
14
.1
Un
diffe
ren
tia
ted
a
de
no
ca
rcin
om
a, sa
rco
ma
No
Mu
ltifo
ca
l m
am
ma
ry tu
mors
(3
)
MM
TV
-Cre
; P
ik3
r1-/
- A
60
2
13
.9
15
.2
Ma
mm
ary
ade
noca
rcin
om
a,
ma
mm
ary
hyp
erp
lasia
N
o
Fo
ca
l m
am
ma
ry tu
mo
r (1
)
MM
TV
-Cre
; P
ik3
r1-/
- A
59
7
14
.7
14
.9
Un
diffe
ren
tia
ted
a
de
no
ca
rcin
om
a, sa
rco
ma
No
Mu
ltifo
ca
l m
am
ma
ry tu
mors
(2
)
MM
TV
-Cre
; P
ik3
r1-/
- A
61
8
NA
N
A
NA
N
A
Sa
cri
fice
d m
ou
se
at 2
2 m
on
ths
du
e t
o s
evere
de
rma
titis;
did
no
t h
ave
tu
mo
rs
ND
, not
de
term
ined;
NA
, no
t ap
plic
able
.
107
Ta
ble
3.2
: C
om
pa
ris
on
of
ma
mm
ary
tu
mo
r d
ev
elo
pm
en
t in
Pik
3r1
k
no
ck
ou
t m
ice
to
oth
er
es
tab
lis
he
d G
EM
Ms
of
bre
as
t c
an
ce
r
Ge
no
typ
e
Tu
mo
r L
ate
nc
y
Tu
mo
r P
en
etr
an
ce
P
rim
ary
Tu
mo
r P
ath
olo
gy
Lu
ng
M
eta
sta
sis
?
Re
fere
nc
e
MM
TV
-Cre
; P
ik3
r1+
/- a
nd
M
MT
V-C
re;
Pik
3r1
-/-
14
.1 m
on
ths
9
0%
(9
/10
)
Mix
ed
(sa
rco
ma
, m
am
ma
ry
ad
en
oc
arc
ino
ma
)
11
% (
1/9
)
L.M
. T
ho
rpe
an
d J
.J. Z
hao
, u
np
ub
lis
he
d o
bs
erv
ati
on
s
MM
TV
-rtT
A; te
tO-P
ik3
ca
H1
04
7R
6.8
mo
nth
s
95
%
Mix
ed
ma
mm
ary
(a
den
oca
rcin
om
a,
ad
en
osq
ua
mo
us c
arc
ino
ma
)
NR
(L
iu e
t a
l., 2
01
1)
K1
4-C
re; p
53
-/- ;
Brc
a1
-/-
7.0
mo
nth
s
10
0%
M
am
mary
and
skin
(ID
C-n
os,
ca
rcin
osa
rcom
a,
ad
en
om
yo
ep
ith
elio
ma)
NR
(L
iu e
t a
l., 2
00
7)
MM
TV
-Cre
; E
rbB
2K
I 1
3.8
mo
nth
s
83
%
Fo
ca
l m
am
ma
ry c
om
ed
o-
ad
en
oca
rcin
om
as
6%
(A
nd
rech
ek e
t a
l., 2
00
0)
MM
TV
-NIC
6
.4 m
on
ths
10
0%
M
ultifo
ca
l, s
olid
no
du
lar
ma
mm
ary
ca
rcin
om
a
56
%
(Scha
de
et a
l., 2
00
9)
MM
TV
-Cre
; P
ten
+/-
15
.5 m
on
ths
75
%
So
lid n
od
ula
r m
am
mary
ca
rcin
om
a
18
% (
2/1
1)
(Do
urd
in e
t a
l., 2
00
8)
MM
TV
-Cre
; P
ten
-/-
11
mo
nth
s
75
%
Mix
ed
(fib
road
en
om
a,
ad
en
oca
rcin
om
a)
NR
(L
i e
t a
l., 2
00
2)
MM
TV
-Cre
; E
rbB
2K
I ; P
ten
+/-
6.5
mo
nth
s
10
0%
Mix
ed
ma
mm
ary
(so
lid n
odu
lar
ma
mm
ary
ca
rcin
om
a,
ad
en
om
yo
ep
ith
elio
ma
, a
de
no
sq
ua
mo
us c
arc
ino
ma
)
35
% (
6/1
7)
(Do
urd
in e
t a
l., 2
00
8)
N
R, not
rep
ort
ed.
108
MMTV-Cre; Pik3r1-/- mice also generally had a greater reduction in total p85 levels when
compared to tumors from MMTV-Cre; Pik3r1+/- mice (Figure 3.5). Interestingly, though
PTEN loss has been reported in spontaneous liver tumors of mice with Pik3r1 knockout
(Taniguchi et al., 2010), we did not observe a pattern of PTEN protein reduction in
Pik3r1 knockout mammary tumors. In addition, we found that PI3K/AKT pathway
activation in these mammary tumors as assessed by phosphorylation of AKT and S6
ribosomal protein was highly variable (Figure 3.5). Thus while we find that mice with
mammary-specific Pik3r1 ablation develop spontaneous mammary tumors, our data is
inconclusive as to whether these tumors arise due to upregulated PI3K/AKT signaling.
We were further interested to know the pathology of spontaneous mammary tumors from
Pik3r1 knockout mice. Analysis of formalin-fixed tumor tissue by hematoxylin and eosin
(H&E) staining revealed that these tumors ranged in pathology, from sarcoma to
mammary adenocarcinoma (Figure 3.6 A-F). In addition, metastasis of the primary
mammary tumor to the lung was observed in 11% (1/9) of the mice with spontaneous
tumors (Figure 3.6 G-I). We also used whole mount techniques to examine the adjacent
mammary glands from Pik3r1 knockout mice with spontaneous mammary tumors.
Interestingly, non-tumor-bearing mammary glands from these mice displayed a slightly
hypermorphic phenotype with apparent lobulo-alveolar development and excessive
ductal branching (Figure 3.7) resembling mammary glands from pregnant females
(Figure 3.4 G-I). Together these findings suggest that Pik3r1 ablation alone is sufficient
for mammary tumor development in mice.
Pik3r1 ablation reduces the latency of HER2/neu-driven mouse mammary tumors
To further study the contribution of p85g loss to in vivo mammary tumorigenesis, we
combined a well-defined GEMM of HER2/neu-driven breast cancer with our conditional
109
Figure 3.5: PI3K/AKT pathway activation in spontaneous mammary tumors from Pik3r1 knockout mice. Mammary tumor tissue was collected from random-fed MMTV-Cre; Pik3r1+/- and MMTV-Cre; Pik3r1-/- female mice. As a control, normal mammary gland tissue was collected from MMTV-Cre mice (“MG”). Protein lysates were generated and subjected to immunoblotting for PI3K/AKT pathway components and activation of PI3K/AKT pathway effectors. Membranes were stripped and re-probed for total proteins and vinculin as a loading control.
110
Figure 3.6: Pathology of primary spontaneous mammary tumors and lung metastases from Pik3r1 knockout mice. (A-F) Representative images of formalin-fixed primary mammary tumor tissue from MMTV-Cre; Pik3r1+/- and MMTV-Cre; Pik3r1-/-
females stained with hematoxylin and eosin (H&E). These spontaneous tumors display a range of pathologies, from sarcoma and undifferentiated adenocarcinoma (A-C) to mammary hyperplasia and mammary adenocarcinoma (D-F). White arrowheads designate areas of the tumor where duct-like formations occur. Scale bars = 50たm. (G-I) Representative images of formalin-fixed lung tissue from one mouse in (A-F) stained with H&E. Black arrows designate metastases. Scale bars = 100たm.
111
Figure 3.7: Adjacent mammary glands from Pik3r1 knockout mice with spontaneous mammary tumors have a hypermorphic phenotype. Mammary gland tissue from an approximately 1 year old nulliparous MMTV-Cre; Pik3r1-/- female with palpable mammary tumors was excised, fixed, and subjected to Carmine staining. The hypermorphic phenotype of these mammary glands, with what appears to be lobular-alveolar development and ductal branching similar to that occurring during pregnancy, can be seen clearly in (C) and (D), magnified images taken from the white boxes shown in (A) and (B) respectively.
112
Pik3r1 knockout mice. We bred Pik3r1 floxed mice with MMTV-NIC mice, which express
a bicistronic transgene consisting of an activated HER2/neu allele and Cre recombinase
under control of the MMTV promoter (Schade et al., 2009; Ursini-Siegel et al., 2008)
(Figure 3.8). The resulting MMTV-NIC; Pik3r1+/loxP and MMTV-NIC; Pik3r1loxP/loxP mice
have ablation of one or both Pik3r1 alleles in the same luminal mammary epithelial cells
that express oncogenic HER2/neu. MMTV-NIC mice were used as a control. These mice
will hereafter be referred to as NIC, NIC; Pik3r1+/-, and NIC; Pik3r1-/-.
We monitored female cohorts of these mice for progression of mammary tumors. All
three genotypes developed multifocal mammary tumors with 100% penetrance. NIC
mice developed palpable tumors with a mean latency of 140 days (range 97-191, N =
25), consistent with other published information for this strain (Schade et al., 2009;
Ursini-Siegel et al., 2008; Utermark et al., 2012). Either heterozygous or homozygous
Pik3r1 ablation significantly reduced the time to tumor onset: NIC; Pik3r1+/- and NIC;
Pik3r1-/- mice developed tumors with mean latencies of 125 days (range 101-162, N =
38) and 126 days (range 86-155, N = 43), respectively (Figure 3.5 A). We additionally
determined the average number of mammary tumors, total tumor mass, and number of
lung metastases per mouse for all three genotypes five weeks after the onset of the first
palpable tumor. NIC mice developed on average 9.4 ± 1.5 tumors (N = 16), while NIC;
Pik3r1+/- mice had a significantly higher number of tumors, with on average 16.0 ± 1.2
tumors per mouse (N = 20); NIC; Pik3r1-/- mice developed a comparable number of
tumors to the NIC control, with on average 10.4 ± 4.3 tumors per mouse (N = 20)
(Figure 3.9 B). All three genotypes had comparable total tumor weight; NIC mice had an
average total tumor mass of 4.6 ± 0.8 grams (N = 16), while NIC; Pik3r1+/- and NIC;
Pik3r1-/- mice had an average total tumor mass of 5.4 ± 0.5 grams and 4.7 ± 0.4 grams,
respectively (N = 20 for both) (Figure 3.9 C). To determine the number of lung
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Figure 3.8: Schematic of the transgenic NIC allele and breeding scheme for mammary-specific HER2/neu expression and Pik3r1 ablation. MMTV-NIC mice are a well established genetically engineered model of HER2/neu-driven breast cancer (Schade et al., 2009; Ursini-Siegel et al., 2008). These mice express a bicistronic transgene consisting of a HER2/neu allele containing an activating in-frame deletion (Schade et al., 2009; Siegel et al., 1999; Ursini-Siegel et al., 2008) and the Cre recombinase gene, linked by an internal ribosomal entry site (IRES). This transgene is expressed under the control of the MMTV LTR promoter. MMTV-NIC mice develop multifocal mammary tumors with 100% penetrance and an average latency of 198 ± 43 days. Approximately 60% of MMTV-NIC mice also develop lung metastases. In this study, we interbred MMTV-NIC and conditional Pik3r1 knockout mice to achieve expression of activated HER2/neu and deletion of Pik3r1 in the same luminal mammary epithelial cells.
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Figure 3.9: Pik3r1 ablation reduces the latency of HER2/neu-driven mammary tumor development. (A) Cohorts of NIC, NIC; Pik3r1+/-, and NIC; Pik3r1-/- female mice were observed every three days for mammary tumor onset as determined by first palpation. Median tumor-free survival: NIC, 140 days (N = 25); NIC; Pik3r1+/-, 125 days (N = 38); NIC; Pik3r1-/-, 126 days (N = 43). Statistical significance was determined by Log-rank (Mantel-Cox) test. (B) The total number of mammary tumors per mouse was determined for NIC (N = 16), NIC; Pik3r1+/- (N = 20), and NIC; Pik3r1-/- (N = 20) females. (C) The total wet weight of mammary tumors plus associated mammary gland tissue per mouse was determined for NIC (N = 16), NIC; Pik3r1+/- (N = 20), and NIC; Pik3r1-/- (N = 20) females. (D) The number of lung metastases per mouse was determined for NIC, NIC; Pik3r1+/-, and NIC; Pik3r1-/- females (all groups N = 8). For (B-D), numbers were determined exactly 5 weeks after tumor onset. Means ± SEM are shown. Statistical significance was determined by unpaired t-test. Significance for NIC; Pik3r1+/- and NIC; Pik3r1-/- in comparison to the NIC control is shown. **, P < 0.01; ***, P < 0.001; ****, P < 0.0001; ns, not significant.
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metastases per mouse, we examined H&E-stained lung sections by microscopy.
Although the difference was not statistically significant, there was a trend towards higher
incidence of lung metastasis in mice with Pik3r1 ablation, with NIC mice having an
average of 2.7 ± 0.5 mets, and NIC; Pik3r1+/- and NIC; Pik3r1-/- having an average of 5.6
± 2.2 mets and 6.1 ± 4.9 mets, respectively (N = 8 for all groups) (Figure 3.9 D).
Together these results indicate that partial p85g loss reduces the latency of HER2/neu-
driven mammary tumorigenesis in mice, and may contribute to the severity of the
disease.
To analyze PI3K isoform expression and PI3K/AKT pathway activation in these tumors,
we isolated primary tumor tissue from random-fed mice, generated protein lysates, and
subjected them to immunoblotting (Figure 3.10). We also quantified the bands from
these blots by densitometry (Figure 3.11). Although there was some mouse-to-mouse
variation, likely owing to the mosaic expression of the MMTV LTR promoter (Wagner et
al., 1997), NIC; Pik3r1+/- mammary tumors had a 25.8 ± 15.1% reduction in p85g protein
levels, while NIC; Pik3r1-/- mammary tumors had a 83.9 ± 2.2% reduction in p85g protein
levels (N = 4 for both) (Figure 3.11 A). Expression of PI3K catalytic isoforms correlated
with the protein levels of p85g: NIC; Pik3r1+/- mammary tumors had a 46.5 ± 14.0%
reduction in p110g protein levels and a 9.8 ± 10.8% reduction in p110く levels, while
NIC; Pik3r1-/- mammary tumor cells had a 69.8 ± 4.8% reduction in p110g protein levels
and a 55.8 ± 5.4% reduction in p110く levels (N = 4 for all) (Figure 3.11 D-E). Notably,
although others have reported that p85g may important for the stability of PTEN
(Cheung et al., 2011; Taniguchi et al., 2010), we did not observe a significant change in
PTEN protein levels in NIC; Pik3r1+/- or NIC; Pik3r1-/- mammary tumors as compared to
the NIC control (Figure 3.11 F). Finally, we did not observe a significant difference in
activation of the PI3K/AKT pathway, as determined by phosphorylation of AKT and S6
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Figure 3.10: Effect of Pik3r1 ablation on PI3K/AKT pathway activation in HER2/neu-driven mammary tumors. Mammary tumor tissue was collected from random-fed NIC, NIC; Pik3r1+/-, and NIC; Pik3r1-/- female mice. Protein lysates were generated and subjected to immunoblotting for PI3K/AKT pathway components and activation of PI3K/AKT pathway effectors. Membranes were stripped and re-probed for total proteins and vinculin as a loading control.
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Figure 3.11: Quantification of the effect of Pik3r1 ablation on PI3K/AKT pathway activation in HER2/neu-driven mammary tumors. Bands in the immunoblots of NIC, NIC; Pik3r1+/-, and NIC; Pik3r1-/- mammary tumor lysates from Figure 3.10 were quantified by densitometry. Levels of p85g, pan-p85, p110g, p110く, and PTEN were normalized to the corresponding vinculin loading control on the re-probed membrane, then to the corresponding NIC control mean. Levels of phosphorylated HER2/neu, AKT, and S6 were normalized to the corresponding total proteins on the re-probed membrane, then to the corresponding NIC control mean. Means ± SEM are shown; N = 4 for each group. Statistical significance was determined by unpaired t-test. Significance is shown for NIC; Pik3r1+/- and NIC; Pik3r1-/- compared to the NIC control. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ns, not significant.
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ribosomal protein (Figure 3.11 G-I). Thus although we have shown that partial p85g loss
reduces the latency of HER2/neu-driven mammary tumors, it is not clear from this data
whether PI3K signaling is upregulated in Pik3r1 knockout tumors.
We additionally examined the histology of formalin-fixed tumor tissue of each genotype.
Immunohistochemical (IHC) staining for p85g revealed that in NIC tumors, p85g was
mainly cytoplasmic, with strong and uniform signal throughout the tumor and perhaps
slightly elevated levels at the tumor edge (Figure 3.12 A); NIC; Pik3r1+/- tumors showed
a reduction in p85g, while NIC; Pik3r1-/- tumors had very little signal for p85g (Figure
3.12 B-C), correlating well with the immunoblot results (Figure 3.11 A). H&E staining of
tumor tissue showed that tumors from mice of all three genotypes had similar solid
nodular carcinoma histology (Figure 3.12 D-F); it is unsurprising that Pik3r1 ablation had
no effect on tumor pathology, since it has been shown previously that Pten ablation also
does not change the pathology of MMTV-NIC tumors (Schade et al., 2009). Finally, IHC
was used to stain for Ki67, a nuclear protein associated with cellular proliferation. Ki67
IHC revealed that compared to NIC tumors, which had 9.3 ± 0.9% proliferating cells,
NIC; Pik3r1+/- and NIC; Pik3r1-/- tumors had nearly double the proliferation indices, with
16.5 ± 2.1% and 17.5 ± 1.5% proliferating cells respectively (N = 12 for all groups)
(Figure 3.12 G-J). Together these results demonstrate that in mice, reduced p85g
expression significantly increases the proliferation of HER2/neu-driven mammary tumor
cells, correlating with a significant reduction in the latency of tumor onset.
Growth of Pik3r1 knockout tumors is blocked by p110g-selective inhibitors
Since mammary epithelial cell transformation driven by p85g loss is blocked in vitro by
pan-PI3K or p110g-selective inhibitors, we were interested to know whether these
agents could block growth of HER2/neu-driven mammary tumors with p85g loss in vivo.
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Figure 3.12: Effect of Pik3r1 ablation on tumor pathology and proliferation of HER2/neu-driven mammary tumors. Formalin-fixed tissue from NIC, NIC; Pik3r1+/-, and NIC; Pik3r1-/- mammary tumors was subjected to immunohistochemical staining for p85g (A-C), staining with hematoxylin and eosin (H&E) (D-F), or subjected to immunohistochemical staining for the proliferation marker Ki67 (G-I). The percentage of Ki67-positive nuclei (J) was calculated by dividing the number of positively-stained nuclei by the total number of nuclei in the field of view. Means ± SEM are shown; all groups N = 12. Statistical significance was determined by unpaired t-test. Significance is shown for NIC; Pik3r1+/- and NIC; Pik3r1-/- compared to the NIC control. **, P < 0.01; ***, P < 0.001. Scale bars = 50たm.
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Primary tumors were excised from a NIC; Pik3r1+/- donor female and orthotopically
transplanted into eight week old NcrNu female recipients. Recipient mice were randomly
assigned to four cohorts, and treated daily with methylcellulose vehicle, the pan-PI3K
inhibitor GDC0941 (125mg/kg), the p110g-selective inhibitor BYL719 (45mg/kg), or the
p110く-selective inhibitor KIN193 (20mg/kg); tumor size was measured every three days
using calipers. All agents were administered by oral gavage with the exception of
KIN193, which was administered by intraperitoneal injection. Compared to the vehicle
control, which had an average final tumor volume of 942.6 ± 222.9 mm3, KIN193 did not
have a substantial effect on tumor growth, with an average final tumor volume of 801.6 ±
111.1 mm3; treatment with either GDC0941 or BYL719 significantly blocked the growth
of transplanted tumors, with average final volumes of 299.5 ± 66.8 mm3 and 293.2 ±
85.0 mm3 respectively (N ≥ 10 for all cohorts) (Figure 3.13 A). Similar results were
obtained upon treatment of transplanted NIC; Pik3r1-/- tumors (data not shown).
Although all treatment groups maintained good body weight, signifying that none of the
drugs were excessively toxic over the course of treatment (Figure 3.13 B), it should be
noted that compared to the vehicle control, treatment with GDC0941 did lead to a slight
but significant percent decrease in body weight at later time points (Figure 3.13 C).
Together, these results indicate that pan-PIγK and p110g-selective inhibitors are
similarly able block in vivo tumor growth in the context of p85g loss.
To further study the effects of pan- and isoform-selective PI3K inhibitors on Pik3r1
ablated tumors in vivo, we analyzed activation of the PI3K pathway in tumors under each
treatment condition. Recipient mice were treated for four days, and tumors were excised
from recipient mice one hour after the last administration. A portion of each tumor was
used to generate protein lysates, which were then subjected to immunoblotting to assess
activation of components downstream of PI3K. Acute treatment with either
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Figure 3.13: Pan-PI3K or p110g-selective inhibitors block the growth of transplanted HER2/neu tumors with Pik3r1 ablation. NIC; Pik3r1+/- mammary tumors were orthotopically transplanted into female NcrNu mice. Recipients were randomly assigned to cohorts for once daily treatment with the pan-PI3K inhibitor GDC0941 (1β5mg/kg, oral gavage), the p110g-selective inhibitor BYL719 (45mg/kg, oral gavage), the p110く-selective inhibitor KIN193 (20mg/kg, intraperitoneal injection), or the vehicle control (methylcellulose, oral gavage). Tumor size was measured with calipers (A) and body weight was determined (B) every three days. Percent change in body weight (C) was calculated for each mouse relative to its weight at the start of treatment (day 0). Means ± SEM are shown; all treatment groups N ≥ 10. Statistical significance was determined by two-way ANOVA with Tukey’s multiple comparisons test. In (A), only significance for comparison of the final tumor volumes (day 18) of each treatment group to the vehicle control is shown. In (C), significance is shown for comparison of GDC0941 treatment to the vehicle control for days 12, 15, and 18; no other comparisons were statistically significant. *, P < 0.05; **, P < 0.01; ****, P < 0.0001; ns, not significant.
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GDC0941 or BYL719, but not KIN193, substantially reduced phosphorylation of AKT at
both activation sites and phosphorylation of S6 ribosomal protein at activation residues
S235/236 (Figure 3.14 A). The other portion of the excised treated tumor tissue was
fixed in formalin and used to assess histopathology. H&E staining revealed that the
transplanted tumors retained similar histology to the primary tumors (Figure 3.14 B-E).
IHC staining for AKT phosphorylated at S473 showed that tumors treated with vehicle or
KIN193 had moderate to strong nuclear and cytoplasmic AKT activation in most cells,
while tumors treated with GDC0941 or BYL719 had only slight AKT activation in a limited
number of cells (Figure 3.14 F-I). Similarly, IHC staining for S235/236-phosphorylated
S6 ribosomal protein showed strong cytoplasmic activated S6 signal in most cells of
tumors treated with vehicle or KIN193, while tumors treated with GDC0941 or BYL719
showed strong cytoplasmic S6 activation in only a few select cells (Figure 3.14 J-M).
These results demonstrate that pan-PI3K or p110g-selective inhibition, but not p110く-
selective inhibition, effectively decreases PI3K/AKT pathway signals in transplanted
HER2/neu-driven tumors with reduced p85g.
Finally, IHC staining was used to assess cellular proliferation and apoptosis in
transplanted tumors treated with pan-PI3K or isoform-selective inhibitors. Ki67 IHC was
used to visualize the nuclei of proliferating tumor cells. Compared to the vehicle-treated
sample with 34.2 ± 2.7% Ki67-positive nuclei, either GDC0941 or BYL719 treatment
significantly reduced the percentage of Ki67-positive nuclei to 9.7 ± 1.1% and 14.3 ±
1.4%, respectively, while KIN193 treatment had no effect on the proliferation index of
tumor cells, with 33.6 ± 2.9% Ki67-positive nuclei (N = 8 for all groups) (Figure 3.15 A-D
and Figure 3.15 I). IHC using the TUNEL method was performed to visualize the
fragmented DNA of cells undergoing apoptosis. While vehicle treatment did not induce
apoptosis of tumor cells, with only 1.2 ± 0.3% TUNEL-positive nuclei, either GDC0941
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Figure 3.14: Pan-PI3K or p110g-selective inhibitors suppress PI3K/AKT activation in transplanted HER2/neu tumors with Pik3r1 ablation. NIC; Pik3r1+/- mammary tumors orthotopically transplanted into NcrNu females and treated with the pan-PI3K inhibitor GDC0941, the p110g-selective inhibitor BYL719, the p110く-selective inhibitor KIN193, or the vehicle control as described in Figure 3.13. One hour after treatment on day 4, recipients were sacrificed and tumor tissue was collected. (A) Protein lysates from tumors in each treatment group were subjected to immunoblotting for PI3K/AKT pathway activation. Membranes were stripped and re-probed for total proteins and vinculin as a loading control. (B-M) Formalin-fixed tumor tissue was stained with hematoxylin and eosin (H&E) (B-E), or subjected to immunohistochemical staining for AKT phosphorylated at S473 (F-I) or S6 ribosomal protein phosphorylated at S235/236. Scale bars = 50たm.
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Figure 3.15: Pan-PI3K or p110g-selective inhibitors suppress proliferation and induce apoptosis in transplanted HER2/neu tumors with Pik3r1 ablation. NIC; Pik3r1+/- mammary tumors were orthotopically transplanted into NcrNu females. Recipients were treated with the pan-PI3K inhibitor GDC0941, the p110g-selective inhibitor BYL719, the p110く-selective inhibitor KIN193, or the vehicle control as described in Figure 3.13. One hour after treatment on day 4, recipients were sacrificed and tumor tissue was collected. Formalin-fixed tissue was subjected to immunohistochemical staining for the proliferation marker Ki67 (A-D) or for fragmented DNA using the TUNEL method (E-H). The percentage of Ki67-positive (I) or TUNEL-positive (J) nuclei was calculated by dividing the number of positively-stained nuclei by the total number of nuclei in the field of view. Means ± SEM are shown; all groups N = 8. Statistical significance was determined by unpaired t-test. Significance is shown for each treatment group compared to the vehicle control. **, P < 0.01, ****, P < 0.0001; ns, not significant. Scale bars = 50たm.
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or BYL719 treatment significantly increased the percentage of TUNEL-positive nuclei to
5.8 ± 1.0% and 4.8 ± 0.5%, respectively, while KIN193 treatment had no effect on tumor
cell apoptosis with 0.9 ± 0.3% TUNEL-positive nuclei (N = 8 for all groups) (Figure 3.15
E-H and Figure 3.15 J). Together this data demonstrates that pan-PI3K or p110g-
selective inhibitors, but not p110く-selective inhibitors, effectively block PI3K pathway
activation in mammary tumors in vivo in the context of p85g loss, and furthermore
reduce proliferation and induce apoptosis of mammary tumor cells.
Summary and discussion
In this chapter, we use Cre/loxP-mediated conditional deletion to study the effects of
Pik3r1 ablation on the mouse mammary gland. We find that Pik3r1 expression is not
required for mammary development during puberty, pregnancy, or lactation. However,
mice with mammary-specific Pik3r1 knockout develop spontaneous mammary tumors
with a mean latency of 14.1 months. We furthermore show that when combined with an
established GEMM of HER2/neu-driven breast cancer, mammary-specific Pik3r1
ablation significantly reduces the latency and increases the cellular proliferation of
mammary tumors. Growth of these tumors is equally and effectively blocked by pan-
PIγK or p110g-selective pharmacological inhibitors. Pan-PIγK or p110g-selective
therapeutics also block PI3K/AKT signaling, reduce proliferation, and induce apoptosis in
mammary tumors with Pik3r1 knockout. These findings help elucidate the previously
unstudied role of p85g in the mammary epithelium, and also have important implications
for therapeutic targeting of breast cancers with decreased p85g.
Because PI3K signaling is known to be important for mouse mammary gland
development, we were surprised to find that Pik3r1 ablation did not have an appreciable
effect on the morphology of this tissue. Previous studies have shown that increased
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PI3K activation via Pten ablation leads to hypermorphic mammary gland development
during puberty and pregnancy (Li et al., 2002), while reduced PI3K signaling due to
Pik3ca ablation significantly impairs pubertal mammary development and post-partum
lactation (Utermark et al., 2012). Based on our data in Chapter 2 demonstrating that
partial p85g loss leads to upregulated PIγK signaling, we expected to find mildly
accelerated mammary gland development in mice with conditional Pik3r1 ablation.
Although we do not have a definitive explanation for our observations, we propose that
because partial p85g loss has a subtle effect on PIγK activation in comparison to strong
oncogenes such as p110g-H1047R (Figure 2.2 D), it may not upregulate PI3K signaling
strongly enough in this tissue during development to substantially affect its morphology.
This idea is supported by the published result that Pten ablation leads to tumor
development in mice as early as 2 months (Li et al., 2002), while we find that the earliest
onset of spontaneous tumors in mice with mammary-specific Pik3r1 ablation is about
10.7 months (Table 3.1). Analysis of adjacent mammary glands from these mice using
whole mount techniques suggested that by the time spontaneous mammary tumors
developed, the remaining mammary glands without tumors showed signs of alveolar
differentiation (Figure 3.7) similar to normal mammary gland development during
pregnancy (Figure 3.4 G-I). It is likely that in mice with mammary-specific Pik3r1
ablation, PI3K/AKT signaling upregulation is modest and does not substantially affect
mammary gland development during puberty or pregnancy, but over a longer time period
leads to a slightly hypermorphic phenotype and spontaneous tumor development.
An additional confounding factor to our examination of the effect of conditional Pik3r1
ablation on mammary gland development is the levels of other PI3K regulatory and
catalytic isoforms. Although we were unable to identify an antibody capable of selectively
recognizing murine p85く by immunoblot (data not shown), we expect that MMTV-Cre;
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Pik3r1+/- and MMTV-Cre; Pik3r1-/- mice should have comparable levels of p85く to the
MMTV-Cre control. Retained Pik3r2 expression is expected to be critical for the normal
mammary gland morphology in our conditional Pik3r1 knockout mice, as p85く is
necessary to sustain PIγK signaling in conditions of p85g depletion (Ueki et al., 2002a);
ablation of both Pik3r1 and Pik3r2 would likely lead to substantially impaired mammary
gland development. This hypothesis is supported by the finding that conditional Pik3r1
ablation increases insulin-stimulated PI3K/AKT activity in the heart, while double Pik3r1
and Pik3r2 knockout largely blocks PI3K signaling (Luo et al., 2005a). Although Pik3r1
ablation should not affect p85く levels, we do find that it leads to significant reductions in
protein levels of both the p110g and p110く catalytic isoforms (Figure 3.3, Figure 3.5,
Figure 3.10, and Figure 3.11 D-E). Since it has previously been demonstrated that
Pik3ca ablation impairs mammary gland development during puberty and pregnancy,
while Pik3cb ablation leads to precocious lobulo-alveolar development (Utermark et al.,
2012), p110g and p110く downregulation likely contribute to the mammary phenotype of
mice with Pik3r1 ablation. The overall effect of mammary-specific Pik3r1 ablation on
PI3K/AKT activation and mammary gland development in these mice is probably a
combination of the changes to all class IA PI3K isoforms in this tissue.
Although Pik3r1 ablation does not have a substantial impact on mouse mammary gland
development, we find that 90% of MMTV-Cre; Pik3r1+/- and MMTV-Cre; Pik3r1-/- females
develop spontaneous mammary tumors by an average of 14.1 months (Table 3.1). This
timeline to spontaneous tumor development is comparable to the 14 to 20 month latency
for development of spontaneous liver tumors resembling hepatocellular carcinoma in
mice with liver-specific Pik3r1 ablation (Taniguchi et al., 2010), and to other GEMMs of
breast cancer (Table 3.2). While tumor lysates prepared from random-fed mice were
confirmed to have reduced p85g protein levels by immunoblotting, they exhibited
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variable PI3K/AKT activation (Figure 3.5). While we believe that these spontaneous
tumors likely arose due to persistent low-level upregulation of PI3K, which may be
difficult to demonstrate in tumor tissue from random-fed mice, it will also be interesting to
determine whether these tumors are prone to the accumulation of other genetic
alterations, as has been observed with other GEMM models of breast cancer (Liu et al.,
2011). Further study of these spontaneous Pik3r1 knockout mammary tumors using
RNA sequencing techniques will provide insight into this question.
Another puzzling result from our in vivo studies is the finding that in mice, heterozygous
or homozygous Pik3r1 ablation has a nearly identical effect on the latency of HER2/neu-
driven mammary tumors (Figure 3.9). Because heterozygous PIK3R1 loss is much more
frequent than homozygous deletion in human breast cancers (Figure 2.1 A), we
expected that in our mouse model heterozygous Pik3r1 ablation would be more
tumorigenic. While a number of studies have shown that either heterozygous (Mauvais-
Jarvis et al., 2002) or homozygous (Fruman et al., 2000; Terauchi et al., 1999) Pik3r1
ablation leads to hypoglycemia and enhanced insulin sensitivity as compared to wildtype
controls, few have made direct comparisons between the consequences of
heterozygous or homozygous loss of this gene on PI3K/AKT signaling. One publication
compared wildtype, heterozygous Pik3r1 knockout, and homozygous Pik3r1 knockout
MEFs, and found that while heterozygous knockout increased IGF1-stimulated PI3K
activity associated with p110g or tyrosine-phosphorylated proteins and robustly
enhanced IGF1-stimulated PtdIns(3,4,5)P3 production in comparison to wildtype MEFs,
homozygous Pik3r1 knockout had a less pronounced effect (Ueki et al., 2002a). Thus it
was unclear from the literature why heterozygous or homozygous Pik3r1 ablation would
similarly increase tumorigenesis in the mouse mammary gland.
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To explain our observations, we considered that based on our model from Chapter 2
(Figure 2.18) heterozygous Pik3r1 ablation in the mouse mammary epithelium might
partially reduce free p85g, while homozygous Pik3r1 ablation may completely reduce
free p85g and also partially reduce p85g-p110 heterodimers. Conceivably these two
scenarios could result in similar levels of PI3K/AKT signaling upregulation (Figure 3.16).
We sought to address this by immunoprecipitating endogenous HER3/ErbB3 from NIC,
NIC; Pik3r1+/-, and NIC; Pik3r1-/- mammary tumor lysates, and using immunoblotting to
assess the amount of p85 and p110 bound to these RTKs. Unfortunately, we found that
although we could achieve robust HER3/ErbB3 immunoprecipitation from tumor lysates,
the tissue homogenization process apparently disrupted all protein-protein interactions,
as no PI3K isoforms were detectable in the immunoprecipitates by immunoblot (data not
shown). We also cultured cells from these mammary tumors, generated protein lysates,
and again performed HER3/ErbB3 immunoprecipitations; this protocol resulted in
successful p85 and p110 pulldown, but the background on these immunoblots was too
high to reliably quantify the protein bands (data not shown). Verification of this proposed
explanation for our findings will likely require the use of other techniques such as mass
spectrometry.
In summary, the data presented in this chapter demonstrates the important role of p85g
in the mammary epithelium. While p85g expression is not required for normal mouse
mammary gland development during puberty, pregnancy, or lactation, mammary-specific
Pik3r1 ablation leads to spontaneous mammary tumor development accompanied by a
hypermorphic mammary gland phenotype within about one year. Pik3r1 ablation also
significantly reduces the latency of mammary tumor development driven by HER2/neu in
an established GEMM. Either pan-PIγK or p110g-selective inhibitors effectively block
growth of transplanted HER2/neu-driven mammary tumors with Pik3r1 ablation and
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Figure 3.16: Model: heterozygous or homozygous Pik3r1 ablation has a similar effect on HER2/neu-driven tumorigenesis. Pik3r1 ablation reduces the latency of HER2/neu-driven mammary tumor development in the NIC mouse model. Surprisingly, NIC; Pik3r1+/- and NIC; Pik3r1-/- female mice have nearly identical average time to tumor development. Here we show one possible explanation for these observations. Top: In NIC mice, p85 is present in excess of p110; p85 monomers and p85-p110 heterodimers compete for binding to activated RTKs, but only p85-p110 heterodimers can signal. Middle: Heterozygous Pik3r1 ablation partially depletes the pool of free p85, but some monomers remain. Bottom: Homozygous Pik3r1 ablation completely depletes the pool of free p85, but also reduces the number of p85-p110 heterodimers. By this model, heterozygous or homozygous Pik3r1 ablation could result in similar low-level upregulation of RTK-mediated PI3K signaling. While we expect that partial p85g loss similarly affects signaling by p110g and p110く, the p110く isoform is believed to have minimal contribution to RTK-mediated PI3K signaling due to substantially lower RTK-associated lipid kinase activity (Utermark et al., 2012).
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PI3K/AKT signaling in these tumors. The implications of these findings, along with the
data presented in Chapter 2, for the clinical application of PI3K-targeted therapies in
breast cancers with reduced p85g are discussed in Chapter 4 of this dissertation.
Chapter 4: Summary, discussion, and future directions
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Summary
Research in the past decade has established that PI3K isoforms play critical but
divergent roles in both normal cellular signaling and in cancer. Chapter 1 discusses the
current state of this field: the distinct roles of PI3K isoforms in different signaling
contexts, the ways in which different PI3K isoforms are altered in cancer, and the
promise of emerging isoform-selective therapeutics in the clinic. The roles of class I PI3K
catalytic isoforms in cancer are relatively well studied; oncogenic mutation of p110g is
frequent in human cancers, while p110く, p110h, and p110け are rarely mutated but can
be overexpressed (Table 1.1 and Appendix A). Although PI3K regulatory isoforms had
not previously been considered to contribute to oncogenesis, recent studies have
converged to implicate p85g mutation or loss of expression in certain cancers. In this
dissertation we find that heterozygous deletion of PIK3R1 is a frequent event in human
breast cancers, and furthermore that PIK3R1 expression is significantly reduced in
breast tumors when compared to normal breast tissue. Based on these findings, we use
both in vitro and in vivo approaches to explore the role of p85g as a tumor suppressor in
the transformation of mammary epithelial cells.
In Chapter 2, we use RNAi-mediated knockdown of PIK3R1 to assess the effects of
p85g loss on human mammary epithelial cells (HMECs) in vitro. We find that partial
p85g reduction leads to increased growth factor-stimulated PI3K signaling in and
transformation of these cells. We further show that PIK3R1 knockdown augments HMEC
transformation by oncogenes, including activated HER2/neu. Using pharmacological
inhibitors, we demonstrate that the increased PI3K signaling and transformation driven
by partial p85g loss is largely mediated by p110g, and can be equally blocked by either
the pan-PI3K inhibitor GDC0941 or the p110g-selective inhibitor BYL719. Although
others have reported a role for p85g in the stabilization or activation of the PTEN
134
phosphatase opposing PI3K, we were unable to demonstrate an effect of PIK3R1
knockdown on PTEN mRNA or protein levels, or on in vitro PTEN lipid phosphatase
activity. We also did not detect a change in RTK endocytosis or degradation, counter to
reports that p85g plays an important role in activation of Rabs critical for intracellular
trafficking. Instead, we find that partial loss of p85g increases the amount of p85-p110g
bound to activated RTKs. This result is consistent with a model in which p85 is in excess
of p110 in wildtype HMECs, allowing monomeric p85 to compete with p85-p110 for
binding to activated RTKs and negatively regulate PI3K signaling. PIK3R1 knockdown
might selectively reduce the pool of monomeric p85g, allowing more p85-p110
heterodimers to bind RTKs, increasing PI3K signaling and transformation (Figure 2.18).
In Chapter 3, we use the Cre/loxP system to study the effects of mammary-specific
Pik3r1 deletion on both normal mouse mammary gland development and mammary
oncogenesis. Surprisingly, we find that Pik3r1 expression is not required for mouse
mammary gland development during puberty, pregnancy, or lactation. However, mice
with mammary-specific Pik3r1 ablation develop spontaneous mammary tumors of
heterogeneous pathology with a mean latency of 14.1 months. Furthermore, Pik3r1
ablation significantly reduces the latency and increases the cellular proliferation of
mammary tumors in a mouse model of HER2/neu-driven breast cancer. Either the pan-
PI3K inhibitor GDC0941 or the p110g-selective inhibitor BYL719 effectively blocked
growth of transplanted Pik3r1 knockout tumors. Treatment of these tumors with
GDC0941 or BYL719 also considerably reduced PI3K/AKT activation, and significantly
reduced cellular proliferation and increased apoptosis. These findings indicate an
important role for p85g as a tumor suppressor in mammary tumor formation in vivo, and
furthermore suggest that pan-PI3K or p110g-selective inhibitors might be effective
therapeutics in breast cancers characterized by p85g loss.
135
Discussion and future directions
In this dissertation, we present in vitro data using HMECs and in vivo data using GEMMs
demonstrating a tumor suppressive role for PIγK regulatory subunit p85g in mammary
epithelial cells. Our data is consistent with a model where p85 is present in excess of
p110 in normal mammary epithelial cells, allowing p85 monomers to compete with p85-
p110 heterodimers for binding sites on activated RTKs to modulate PI3K signaling. We
additionally show that in the context of transformation mediated by partial p85g loss, the
efficacy of p110g-selective inhibitors is comparable to that of pan-PI3K inhibitors. Our
findings have several important implications for the current literature regarding p85g-
mediated transformation, the regulation of RTK-mediated PIγK signals by p85g, and the
therapeutic targeting of breast cancers characterized by partial p85g loss. They also
raise interesting questions about the role of differential p85g expression in various
tissues and metabolic contexts. These concepts will be important to address in
continuing work on this project.
Transformation mediated by partial p85g loss does not appear to be through PTEN
A number of recent reports link p85g to PTEN stability or lipid phosphatase activity, and
some studies have demonstrated an interaction between these two proteins. This
proposed connection between p85g and PTEN has been invoked to explain increased
PI3K/AKT signaling and transformation in the context of p85g mutation or
downregulation (Cheung et al., 2011; Taniguchi et al., 2006; Taniguchi et al., 2010). The
results presented in this dissertation suggest that further study is needed to conclude
whether PTEN contributes to transformation mediated by partial reduction of p85g. At a
minimum, our data suggest that these reported effects of p85g on PTEN may not be
operative in all tissues.
136
An interaction between p85g and PTEN has been reported by two separate groups. In
one study p85g, p85く, and p110く were found to participate in a complex with
unphosphorylated PTEN (Rabinovsky et al., 2009); a second study demonstrated direct
binding between the C-terminal SHγ and BH domains of p85g and PTEN that was
dependent on EGF stimulation only in certain cell types (Chagpar et al., 2010). Thus the
exact nature of the proposed p85g-PTEN interaction and the contexts in which these
proteins bind are still not clear. Although we were unable to positively show co-
immunoprecipitation of p85g and PTEN in a number of different cell types and conditions
(Figure 2.11, Figure 2.12, and data not shown), we cannot absolutely rule out this
interaction. It is possible that the antibodies we used for our co-immunoprecipitation
assays obscured protein domains necessary for binding; although we tried many of the
antibodies used in these two publications, at least one was not a commercial reagent
(D.H. Anderson, personal communication). However, we would note that at least one
other study reported being unable to demonstrate binding of p85g and PTEN (Taniguchi
et al., 2006).
Other publications have indicated that p85g is important for PTEN mRNA or protein
stability. Ectopic expression of the cancer-associated truncation mutant p85g-E160*
reportedly led to PTEN protein destabilization via ubiquitin-mediated proteasomal
degradation, while overexpression of wildtype p85g was shown to stabilize PTEN protein
levels (Cheung et al., 2011). In another study, mice with liver-specific Pik3r1 ablation
developed liver tumors resembling hepatocellular carcinoma within 14 to 20 months;
compared to liver lysates from these mice at 6 months of age, livers from mice aged 16
to 18 months exhibited upregulated AKT phosphorylation and PtdIns(3,4,5)P3
production, and a corresponding reduction in both PTEN protein and mRNA levels
(Taniguchi et al., 2010). In HMECs, we found that RNAi-mediated PIK3R1 knockdown
137
did not have a substantial effect on steady-state PTEN mRNA levels (Figure 2.13 A) or
protein levels (Figure 2.2 C and Figure 2.5 C). We also did not find that ablation of one
or both Pik3r1 alleles had a consistent effect on PTEN protein levels either in
spontaneous mammary tumors as compared to wildtype mammary glands (Figure 3.5)
or in mammary tumors driven by HER2/neu (Figure 3.10 and Figure 3.11 F). These
findings corroborate a report that liver-specific Pik3r1 ablation had no effect on PTEN
protein levels in this tissue (Taniguchi et al., 2006). Together our results indicate that
p85g may not be important in the regulation of PTEN mRNA or protein levels in
mammary epithelial cells. Our data furthermore suggests that PTEN mRNA and protein
reduction found in spontaneous Pik3r1 knockout liver tumors may be a secondary event
that is not necessarily linked to p85g downregulation.
Finally, p85g has been reported to regulate PTEN lipid phosphatase activity. In liver
extracts from mice with liver-specific Pik3r1 ablation, PtdIns(3,4,5)P3 production and
AKT activation were found to be upregulated; although Pik3r1 knockout had no effect on
PTEN protein levels, it significantly reduced both basal and insulin-stimulated PTEN lipid
phosphatase activity (Taniguchi et al., 2006). Another study reported that in in vitro
assays, addition of purified p85g increased PTEN lipid phosphatase activity in a
concentration-dependent manner (Chagpar et al., 2010). However, we did not find a
difference in the in vitro lipid phosphatase activity associated with PTEN
immunoprecipitates from shControl and shPIK3R1 HMEC lines (Figure 2.13 C). This
data suggests that at least in this cell type, p85g may not modulate PTEN activity.
Together our results indicate that in both mouse and human mammary epithelial cells,
partial p85g loss does not substantially alter PTEN levels. They also suggest that in
HMECs, p85g may not have a significant effect on PTEN activity. We conclude it is
138
unlikely that the observed transformation mediated by p85g downregulation in our model
systems is due to reduced PTEN function. It would be especially interesting to carry out
experiments examining the ability of partial p85g loss to increase transformation of
PTEN-null mammary epithelial cells. One approach would be to use RNAi techniques to
silence PIK3R1 in PTEN-null breast cancer cell lines or in HMECs with CRISPR-
mediated PTEN deletion. A parallel approach would be to use Cre/loxP-mediated
conditional ablation to knock out both Pik3r1 and Pten in the mouse mammary
epithelium. The ability of reduced p85g to augment transformation and tumorigenesis in
the complete absence of PTEN would further support the idea that this mechanism is
independent of proposed effects of p85g on PTEN stability or activity.
Implications of the competition model for transformation mediated by p85g loss
We present data demonstrating that in HMECs, PIK3R1 knockdown increases PI3K/AKT
pathway signaling in response to growth factors, cellular transformation, and the amount
of p85-p110g associated with activated RTKs. Our results are consistent with a model
where partial p85g loss selectively reduces a pool of monomeric p85 which competes
with p85-p110 heterodimers for binding activated RTKs to negatively regulate PI3K/AKT
signaling downstream of RTKs (Figure 2.18). While there are a number of remaining
experiments that would more conclusively support this model, discussed in Chapter 2 of
this dissertation, it has several important implications for p85-mediated regulation of
PI3K signaling, and the general role of p85 regulatory isoforms in transformation.
Although our work here has focused on PIK3R1, there are three genes encoding class
IA regulatory isoforms: PIK3R1, encoding p85g and its splicing variants p55g and p50g,
PIK3R2, encoding p85く, and PIK3R3, encoding p55け. These five isoforms are
collectively called p85 type regulatory subunits. All p85 isoforms possess the iSH2
139
domain responsible for binding class IA catalytic isoforms, and the SH2 domains
responsible for binding to phosphorylated YXXM motifs on activated RTKs or their
adaptors (Figure 1.1). The experiments presented in this dissertation reduced or ablated
expression of all three p85 isoforms arising from PIK3R1, leaving expression of PIK3R2
and PIK3R3 intact. We expect that the remaining p85 isoforms are necessary to sustain
PI3K signaling in the context of reduced PIK3R1 expression.
Our model predicts that modulation of the ratio of p85 monomers to p85-p110
heterodimers might produce a range of RTK-mediated PI3K activity (Figure 4.1). When
p85 is present in excess of p110, p85 monomers might negatively regulate RTK-
mediated PI3K output. According to this model, PI3K signaling downstream of RTKs
would be maximal when p85 isoform expression is reduced exactly to the level where
the number of p85 subunits is equal to the number of p110 subunits; further reduction in
p85 expression would decrease the number of signaling-capable p85-p110
heterodimers, reducing RTK-mediated PI3K signaling. Consistent with this idea, others
have shown that ablation of both Pik3r1 and Pik3r2 significantly impairs PI3K lipid kinase
activity and AKT phosphorylation in mouse cardiac tissue (Luo et al., 2005b). In a
separate study using a GEMM of KRAS-driven lung cancer, Pik3r1+/-; Pik3r2-/- mice
developed a greater number of lung tumors in comparison to Pik3r2-/- mice, while tumor
development was nearly completely blocked in Pik3r1-/-; Pik3r2-/- mice (Engelman et al.,
2008). These results support the idea that a balance between p85 and p110 isoforms is
critical for regulation of PI3K signaling.
If our model is correct, it might also be expected that partial loss of any p85 isoforms
could increase RTK-mediated PI3K signaling. We have performed preliminary
experiments indicating that in HMECs, RNAi-mediated PIK3R2 knockdown increases
140
Fig
ure
4.1
: M
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PI3
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012
).
141
growth factor-stimulated PI3K/AKT activation and anchorage-independent growth (data
not shown). Others have shown that Pik3r2-/- mice display increased insulin sensitivity,
and cells derived from these mice showed heightened insulin-stimulated AKT
phosphorylation (Ueki et al., 2003; Ueki et al., 2002b). However, two recent publications
demonstrated that PIK3R2 overexpression in chicken embryo fibroblasts (CEFs) or
immortalized murine fibroblasts (NIH 3T3) increases PI3K/AKT activation and cellular
transformation (Cortes et al., 2012; Ito et al., 2014). Furthermore, these studies
suggested that PIK3R2 is overexpressed in human breast, colon, and ovarian cancers
(Cortes et al., 2012; Ito et al., 2014). It has been proposed that p85く-p110g has greater
kinase activity towards PtdIns(3,4,5)P3 than p85g-p110g (Cortes et al., 2012) or that
p85く is a less effective inhibitor of p110 catalytic activity (Ito et al., 2014). We queried
https://www.oncomine.org and http://www.cbioportal.org, the same online databases we
used to detect significant PIK3R1 underexpression in breast cancers (Figure 2.1 and
Table 2.1), to determine whether PIK3R2 alterations were a common event in human
cancers. However, we did not identify a significant trend towards either overexpression
or underexpression of PIK3R2 (data not shown). We conclude that further study is
needed to clarify the role of PIK3R2 expression in transformation.
Our model also relies on an imbalance in the number of class IA p85 regulatory and
p110 catalytic subunits. The presence of free p85 is currently a source of controversy in
the field, with publications arguing both for and against the existence of p85 monomers.
One study used quantitative mass spectrometry to determine the absolute number of
p85 and p110 molecules in murine B lymphocytes (WEHI-231), murine fibroblasts (NIH
3T3), and various homogenized mouse tissues (Geering et al., 2007). This work
demonstrated that in WEHI-231 and NIH 3T3 cells, and in mouse muscle, liver, fat, and
spleen tissue, p85 and p110 are present in approximately equal amounts; only in the
142
mouse brain was p85 found to be present in excess (Geering et al., 2007). In this study,
it was concluded that class IA PI3Ks are obligate p85-p110 heterodimers.
In contrast, two studies from the Cantley and Kahn groups used immunodepletion
techniques on wildtype and Pik3r1 ablated mouse cells and tissues to demonstrate the
presence of p85 monomers (Mauvais-Jarvis et al., 2002; Ueki et al., 2002a). From these
results it was estimated that the ratio of p85-p110 dimers to p85 monomers was 2:1 in
wildtype MEFs, 3:1 in heterozygous Pik3r1 knockout MEFs, and 7:1 in homozygous
Pik3r1 knockout MEFs (Ueki et al., 2002a); in mouse livers, the ratio of p85-p110 dimers
to p85 monomers was estimated to be 2:1 in wildtype mice and 4:1 in heterozygous
Pik3r1 knockout mice (Mauvais-Jarvis et al., 2002). However, none of these studies
examined mammary cells or tissues. We used similar immunodepletion techniques in
our HMECs, but while these results suggested that p85 might be in excess in these
cells, our findings were inconclusive (data not shown). It is possible that the relative
levels of p85 and p110 may vary depending on the cell type or tissue. In fact, in
preliminary studies we found that RNAi-mediated downregulation of p85g in MCF10A
human mammary epithelial cells or in HC11 murine mammary epithelial cells increased
PI3K/AKT signaling in response to EGF or insulin, while Pik3r1 knockdown in wildtype
MEFs had no effect on growth factor-stimulated PI3K/AKT activation (data not shown). It
will be critical to assess the relative numbers of p85 and p110 isoforms in different cell
and tissue types using sensitive techniques such as quantitative mass spectrometry.
If correct, our model also has several implications for RTKs relative to PI3K subunits.
First, the ratio of available RTKs to PI3K molecules will be important. It is likely that in
mammary epithelial cells, the number of p85 monomers plus p85-p110 heterodimers is
in excess in comparison to the number of RTKs, even when Flag-TEL-ErbB3 is
143
ectopically expressed. If instead RTKs were in excess, we would expect that partial
reduction of p85g would have no effect on PIγK/AKT signaling, since all p85-p110
heterodimers would already be able to complex with activated RTKs in this instance.
Second, our model makes the assumption that p85 monomers and p85-p110
heterodimers bind to RTKs with approximately the same affinity, allowing monomers and
heterodimers to compete for the same active sites. We could begin to address this by
performing immunoprecipitations of Flag-TEL-ErbB3 similar to those shown in Chapter
2, and comparing the ratio of p85 to p110 in immunoprecipitates in comparison to the
non-immunoprecipitated supernatant; in this experiment, we would expect the ratio of
p85 to p110 to be similar in both the immunoprecipitate and supernatant fractions.
However, a more definitive demonstration will require careful biochemical experiments
with purified proteins.
Finally, our data indicates that increased PIγK/AKT signaling in contexts of partial p85g
reduction may be specific to RTK inputs. Our model predicts that p85g downregulation
might only affect PI3K signaling downstream of receptors for which p85 serves as a
necessary binding adaptor for the PI3K heterodimer. Growth factor-stimulated PI3K
signaling relies on binding of the SH2 domains of p85 subunits to phosphorylated motifs
on activated RTKs, recruiting class IA p110 catalytic subunits and activating their lipid
kinase activity (Figure 1.2). A number of studies have demonstrated that p110g is the
primary catalytic subunit involved in growth factor-stimulated PI3K activation (Foukas et
al., 2006; Graupera et al., 2008; Knight et al., 2006; Utermark et al., 2012; Zhao et al.,
2006). Consistent with this, we find that increased signaling and transformation mediated
by partial p85g loss is blocked by p110g-selective pharmacological inhibition. It is likely
that p85g depletion similarly affects both p110g and p110く, but since p110く plays a
minor role in RTK-mediated PIγK signaling, effects on p110く are difficult to detect.
144
Interestingly, of the class IA catalytic isoforms only p110く has been shown to also
mediate GPCR-activated PI3K signaling (Ciraolo et al., 2008; Guillermet-Guibert et al.,
2008; Jia et al., 2008). A recent study demonstrated that a unique region of p110く
directly binds GPCR-associated Gくけ subunits, facilitating p110く-mediated PI3K signaling
downstream of GPCRs (Figure 1.5) (Dbouk et al., 2012). This suggests that p85
subunits may not function as adaptors for PI3K signaling downstream of GPCRs,
consistent with our data demonstrating that p110く-selective inhibition does not suppress
PI3K/AKT signaling and transformation brought about by a partial reduction in p85g. It
may be that p85g downregulation uniquely synergizes with RTK-activating signals. It will
be interesting to test this idea using GPCR agonists such as LPA to stimulate our control
and PIK3R1 knockdown HMECs. If correct, we would expect to see no difference in
LPA-stimulated PI3K/AKT activation between these cell lines.
Implications for therapeutic targeting of PI3K in cancers with p85g loss
The discovery of frequent PI3K activation in cancers has made this pathway an
attractive target for small-molecule therapeutics. The first PI3K inhibitors to enter clinical
trials were pan-PI3K inhibitors (Table 1.2) and dual pan-PI3K/mTOR inhibitors (Table
1.3). Unfortunately, many of these drugs have had only modest single-agent success in
the clinic (Rodon et al., 2013). This is in part due to compensatory feedback signaling
networks which facilitate the development of resistance to targeted therapies; one major
focus in the field is to identify these resistance pathways and develop rational
combination therapy strategies to circumvent them (Figure 1.8). Another limiting aspect
of many pan-PI3K inhibitors is their broad spectrum of off-target effects on PI3K-related
kinases and other cellular components (Fruman and Rommel, 2014). This is likely
because inhibitors targeting the active site of all class I PI3Ks will necessarily be
promiscuous (Knight and Shokat, 2005). Isoform-selective PI3K inhibitors are now
145
emerging in clinical trials (Table 1.4), and should theoretically have both fewer off-target
effects on molecules outside the PI3K family, and fewer on-target toxicities by sparing
PI3K isoforms that are not contributing to tumorigenesis. Some p110g-selective
inhibitors have shown promising success in early clinical trials (Juric et al., 2013b), and
the p110h-selective inhibitor idelalisib has recently become the first FDA-approved PI3K
therapy due to its significant success in patients with B cell malignancies. Thus another
major focus of the field is to identify the contexts in which isoform-selective PI3K
inhibitors will be successful (Figure 1.7).
Using isoform-selective PI3K inhibitors, we demonstrate that the transformation of
mammary epithelial cells with partial p85g loss is primarily mediated by catalytic isoform
p110g. Either the pan-PI3K inhibitor GDC0941 or the p110g-selective inhibitor BYL719
effectively inhibited colony formation of PIK3R1 knockdown DDp53-HMECs, while
p110く-selective inhibition had no effect (Figure 2.8). GDC0941 and BYL719 also
substantially reduced PI3K/AKT activation in and colony formation of DDp53-HMECs
expressing oncogenic HER2/neu in conjunction with knockdown of PIK3R1 (Figure 2.9
and Figure 2.10). Pan-PIγK or p110g-selective pharmacological inhibition of p110g
blocked the in vivo growth of transplanted tumors with Pik3r1 ablation, while the p110く-
selective inhibitor KIN193 did not affect tumor growth (Figure 3.13). IHC and
immunoblot analysis of tumor tissue revealed that GDC0941 or BYL719 treatment
suppressed PI3K/AKT pathway activation in Pik3r1 knockout tumors, while the effect of
KIN193 treatment on PI3K/AKT signaling was indistinguishable from that of the vehicle
control (Figure 3.14). Pan-PIγK and p110g-selective inhibition also significantly reduced
cellular proliferation and increased the percentage of cells undergoing apoptosis in
transplanted tumors (Figure 3.15). These results demonstrate that in mammary
epithelial cells with partial p85g loss, the efficacy of p110g-selective pharmacological
146
inhibition at blocking transformation and tumorigenesis is comparable to that of a pan-
PI3K agent.
It is perhaps unsurprising that transformation in this context is governed by PI3K
signaling through p110g. If our model for increased PIγK signaling mediated by partial
p85g loss (Figure 2.18) is correct, downregulation of p85g should only augment PIγK
signaling through RTKs, and not through other inputs such as GPCRs. A number of
studies using pharmacological inhibition and genetic inactivation or ablation have
demonstrated that PI3K signaling in response to growth factors is principally through
p110g (Foukas et al., 2006; Graupera et al., 2008; Knight et al., 2006; Sopasakis et al.,
2010; Utermark et al., 2012; Zhao et al., 2006) and not p110く (Ciraolo et al., 2008;
Guillermet-Guibert et al., 2008; Jia et al., 2008). Furthermore, Pik3ca ablation or p110g-
selective inhibition was sufficient to block mouse mammary tumorigenesis driven by
HER2/neu in a recent study from our group (Utermark et al., 2012). These findings were
explained by a proposed model where p110g may have higher RTK-associated lipid
kinase activity than p110く, making p110g the primary catalytic isoform mediating PI3K
signaling downstream of RTKs (Utermark et al., 2012) (Figure 1.6). Based on this
model, oncogenic lesions activating RTK signaling will be effectively targeted by p110g-
selective inhibitors (Figure 1.7).
Early clinical data has reported promising activity of p110g-selective agents BYL719 or
GDC00γβ in advanced breast tumors with p110g activation (Juric et al., 2013b). The
data presented in this dissertation suggests that such inhibitors may also be successful
in treatment of breast tumors with reduced expression of PIK3R1. Furthermore, another
preclinical study has demonstrated that p110g- but not p110く-selective inhibitors block
both PI3K/AKT signaling in and cellular transformation of cells with ectopic expression of
147
cancer-associated p85g mutants (Sun et al., 2010). Together this work highlights the
potential for use of p110g-selective agents in treatment of cancers with p85g loss or
mutation. Since loss of PIK3R1 expression is common in breast cancers (Figure 2.1 and
Table 2.1) (Cizkova et al., 2013) and certain other cancer types (Taniguchi et al., 2010),
and PIK3R1 mutation is a frequent event particularly in endometrial and pancreatic
cancers (Table 1.1 and Appendix A), our findings along with other recent publications
emphasize the need to consider alterations in PIK3R1 as a diagnostic marker in
cancers, and underline the importance of evaluating p110g-selective agents in the
treatment of cancers with PIK3R1 alterations in a clinical setting.
Potential role of differential p85g expression in various metabolic contexts
The work presented in this dissertation supports the concept that modulation of p85g
levels could provide a mechanism to fine-tune activation of the PI3K/AKT pathway
(Figure 4.1). We and others have shown that reduced p85g expression leads to
enhanced growth factor-stimulated PI3K/AKT activation (Fruman et al., 2000; Mauvais-
Jarvis et al., 2002; Taniguchi et al., 2010; Terauchi et al., 1999; Ueki et al., 2002a), while
several publications have demonstrated that increased p85g expression reduces
PI3K/AKT output (Barbour et al., 2005; Luo et al., 2005a; Ueki et al., 2000). Together
these findings suggest that differential p85g expression could serve as a physiological
mechanism to control the extent of PI3K/AKT signaling.
One potential application for PIγK/AKT pathway regulation by p85g levels might be in
different metabolic contexts. Under conditions of glucose elevation, for example as a
result of ingested nutrients, reduced p85g expression could increase sensitivity to insulin
and reduce blood glucose levels. Conversely, in conditions of reduced glucose, such as
during nutrient deprivation, elevated p85g levels could reduce insulin sensitivity and
148
favor fatty acid metabolism. Consistent with these ideas, one publication found that in
GEMMs of genetic insulin resistance via heterozygous deletion of IR or IRS1,
heterozygous Pik3r1 ablation improved insulin sensitivity and glucose homeostasis, and
protected mice from the development of diabetes (Mauvais-Jarvis et al., 2002). A second
study demonstrated that Pik3r1 expression was highly induced in adipose tissue from
mice with obesity induced by a high fat diet; heterozygous Pik3r1 ablation preserved
insulin sensitivity in these mice (McCurdy et al., 2012). Thus it will be especially
interesting to explore whether p85g expression levels are dynamic, particularly in those
tissues critical for metabolism, depending on nutrient conditions and disease states.
It will also be important to identify the mechanisms governing p85g expression. Several
recent publications have identified microRNAs (miRNAs) which functionally regulate
Pik3r1 expression (Huang et al., 2014; Huang et al., 2012; Nicoli et al., 2012; Peng et
al., 2013; Tian et al., 2013; Zheng et al., 2012). A separate study reported PIK3R1
transcriptional upregulation in adipocytes by direct binding of peroxisome proliferator-
activated receptor gamma (PPARけ) to two peroxisome proliferator response elements
(PPREs) in the PIK3R1 promoter (Kim et al., 2014). However, the regulation of PIK3R1
expression remains an underexplored area of study. If dynamic changes in p85g levels
in fact contribute to physiological processes such as regulation of metabolism, it will be
critical to identify the different mechanisms which control expression of PIK3R1.
Conclusions and perspective
A tremendous amount of work using RNAi-mediated gene silencing, genetically
engineered mouse models, and emerging isoform-selective pharmacological inhibitors
has begun to elucidate the distinct roles of PI3K catalytic isoforms in different signaling
contexts. Large-scale sequencing efforts in the past decade have also identified
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frequently occurring oncogenic mutations in catalytic isoform p110g in a range of human
cancers; catalytic isoforms p110く, p110h, and p110け are rarely mutated but can be
overexpressed. While the roles of PI3K catalytic isoforms in signaling and cancer are
beginning to be understood, the roles of the regulatory isoforms are less well studied.
The work presented in this dissertation adds to a growing number of recent publications
indicating that PIγK regulatory isoform p85g may also contribute to tumorigenesis.
Frequent mutations in PIK3R1 have been identified in certain cancer types; studies have
shown that some of these cancer-associated p85g mutants can still bind but not inhibit
p110, leading to enhanced PI3K/AKT activation. One preclinical study has also indicated
a potential role for p85g as a tumor suppressor in the liver. Here we show that partial
reduction of p85g increases PIγK/AKT signaling in and transformation of human
mammary epithelial cells in vitro and contributes to mammary tumor formation in vivo.
Our findings are consistent with a model in which excess monomeric p85 competes with
p85-p110 heterodimers to negatively regulate PI3K signaling downstream of RTKs. This
work begins to address the role of p85g in different physiological and pathophysiological
PI3K signaling contexts, and highlights the potential for PIK3R1 mutation or
underexpression as a diagnostic and therapeutic marker for breast cancer.
Materials and Methods
151
Publically available clinical data
The Oncomine database version 4.4.4.3 (https://www.oncomine.org/) was queried for
expression of PIK3R1 in breast cancer microarray studies. The data from each study
was converted to raw expression levels of PIK3R1 by taking the inverse log2, and then
normalized to the mean raw PIK3R1 expression level of the normal breast tissue from
that specific study.
Vectors
Lentiviral pLKO.1-puromycin shRNA vectors were obtained from the RNAi Consortium at
the Broad Institute, Cambridge, MA. The sequences for these vectors were as follows:
shControl scrambled vector 5’-TCC TAA GGT TAA GTC GCC CTC G-γ’, shPIKγR1 #1
(TRCN0000039903, targeting the γ’ UTR of PIK3R1) 5’-GCG CTA TGC AAT TCT TAA
TTT-γ’, and shPIK3R1 #2 (TRCN0000033284, targeting the coding sequence of
PIK3R1) 5’-CCT TCA GTT CTG TGG TTG AAT-γ’. Retroviral vectors were as follows:
pWZL-blasticidin-p53DD, pBabe-neomycin-p53DD, pBabe-blasticidin-neuT, pWZL-
neomycin-HA-PIK3CAH1047R, pBabe-puromycin-HA-PIK3CAH1047R, and pWZL-neomycin-
Flag-tel-ErbB3. To generate constructs for rescue of PIK3R1 knockdown, a pCMV6
entry vector containing the cDNA ORF of wildtype human PIK3R1 with C-terminal Myc
and Flag tags was obtained from Origene (RC210544) and cloned into the pWZL-
blasticidin retroviral vector. This vector was used for rescue of shPIK3R1 #1. For rescue
of shPIK3R1 #2, the QuikChange II XL site-directed mutagenesis kit (Agilent) was used
to make wobble point mutations T1197C and G1203A with primers 5'-CTC TGA CCC
ATT AAC CTT CAG CTC TGT AGT TGA ATT AAT AAA CCA CTA CC-3' and 5’-GGT
AGT GGT TTA TTA ATT CAA CTA CAG AGC TGA AGG TTA ATG GGT CAG AG-γ’.
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Cell culture and transduction
hTERT-immortalized HMECs were cultured in HMEC Growth Medium (DMEM/F12
GlutaMAX [Gibco] supplemented with 0.01たg/ml EGF [Sigma], 10たg/ml insulin [Gibco],
0.0β5たg/ml hydrocortisone [Sigma], 1ng/ml cholera toxin [Sigma], 0.6% FBS [Gibco],
penicillin/streptomycin [Gibco], and antimycotic [Gibco]). 239T and phoenix cells used for
virus production were cultured in DMEM 10% FBS (DMEM supplemented with 5% FBS,
penicillin/streptomycin, and antimycotic, all from Gibco). All cells were maintained at
37°C and 5% CO2.
VSV lentivirus was produced by transfecting 293T cells with the pMD2-VSV-G and
pCMV-〉R8.91 packaging vectors along with a pLKO.1 vector encoding the shRNA of
interest. Retrovirus was produced by transfecting phoenix cells with the retroviral vector
encoding the gene of interest. All transfections were carried out for 20 minutes at room
temperature using the FuGene6 transfection reagent (Promega) in Opti-MEM reduced
serum media (Gibco). Virus was harvested by passing culture supernatants through a
0.45たm filter β-3 days post-transfection.
Stable HMEC lines were generated by infecting cells with lentiviral or retroviral
supernatants in the presence of 4たg/ml polybrene (Milipore) overnight. After infection,
successfully transduced stable polyclonal lines selected for several days in HMEC
Growth Medium containing the appropriate antibiotic (β50たg/ml neomycin [Gibco],
β.5たg/ml blasticidin [Invitrogen], or 1.5たg/ml puromycin [Calbiochem]) until a control
plate of non-transduced cells were completely killed.
Growth factor stimulation timecourse assays
Cells were rinsed twice with PBS (Gibco) and starved in HMEC Starvation Medium
153
(DMEM/F12 GlutaMAX with penicillin/streptomycin and antimycotic [all from Gibco]) for
either 4 hours or overnight as indicated. For EGF timecourses, human recombinant EGF
(Sigma) was prepared in HMEC Starvation Medium to a final concentration of 20mg/ml,
and used to stimulate cells at 37°C and 5% CO2 for the indicated amounts of time.
Protein lysate preparation and immunoblotting
All protein lysates were prepared by scraping plates of cells on ice using NP40 lysis
buffer (137mM NaCl, 20mM Tris-HCl [pH 8.0], 0.2mM EDTA, 10% glycerol, 1% NP40)
with protease inhibitors (Roche) and phosphatase inhibitors (Thermo Scientific). Whole
cell lysates were prepared by taking the supernatant following centrifugation at
14000rpm and 4°C. Protein concentrations of total cell lysates were determined by
Bradford assay (Bio-Rad) and then 4X SDS/DTT sample buffer (40% glycerol, 250mM
Tris-HCl [pH 6.8], 8% SDS, 0.04% bromophenol blue) was added to a final concentration
of 1X. Samples were boiled at 100°C for 10 minutes and stored at -80°C.
For immunoblotting, proteins in the samples were separated by SDS-PAGE on 8%,
10%, or 1β% polyacrylamide gels and electrotransferred onto 0.45たm NitroBind
nitrocellulose membranes (Maine Manufacturing). Membranes were blocked for 1 hour
at room temperature in a solution of 5% nonfat dry milk (Bio-Rad) in TBS (50mM Tris-
HCl [pH 7.5], 150mM NaCl). Primary antibodies were diluted in a solution of 5% BSA
(Research Products International) in TBST (50mM Tris-HCl [pH 7.5], 150mM NaCl,
0.15% Tween-20) and incubated with membranes at 4°C overnight. The following
primary antibodies were used for immunoblotting at the dilutions specified: vinculin
(Sigma V9131 1:10000), pan-p85 (Millipore Absβγ4 1:600), p85g (Millipore 05β1β
1:1000), p85g (Millipore 0440γ 1:600), p85く (Santa Cruz sc569γ4 1:100), p110g (Cell
Signaling 4β49 1:1000), p110く (Cell Signaling γ011 1:1000), p110く (Santa Cruz sc60β
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1:100), Flag (Origene TA50011 1:1000), Flag (Sigma F1804 1:1000), HA (Cell Signaling
2367 1:1000), ErbB2 (Calbiochem OP15 1:100), ErbB3 (Cell Signaling 4754 1:1000),
PTEN (Cell Signaling 9552 1:1000), phospho-AKTT308 (Cell Signaling 4056 1:1000),
phospho-AKTS473 (Cell Signaling 9271 1:1000), total AKT (Cell Signaling 9271 1:1000),
phospho-ERKT202/Y204 (Cell Signaling 9101 1:1000), total ERK (Cell Signaling 9102
1:1000), phospho-S6S235/236 (Cell Signaling 2211 1:1000), total S6 (Cell Signaling 2217
1:1000), phospho-EGFRY1068 (Cell Signaling 3777 1:1000), and EGFR (Cell Signaling
4267 1:1000). Anti-mouse IgG IRDye800-conjugated (Rockland) and anti-rabbit IgG
AlexaFluor680-conjugated (Invitrogen) secondary antibodies were used at a dilution of
1:5000 in a solution of 1.36% nonfat dry milk (Bio-Rad) and 0.01% SDS (Invitrogen) in
TBST, and were incubated with membranes for 1 hour at room temperature. Fluorescent
protein signals were detected and quantified using a LI-COR Odyssey CLx imaging
system and the accompanying ImageStudio software, version 3.1.4.
Anchorage-independent growth assays
Single-cell suspensions were plated in a solution of 0.3% agar in HMEC Growth Medium
on top of a base layer of 0.6% agar in DMEM (Gibco). To prevent agar from drying out,
HMEC Growth Medium with or without PI3K inhibitors was added fresh every 3 days.
For HMECs stably expressing neuT, 2.5x104 viable cells were plated per 60mm dish or
4.5x103 viable cells per well of a 12-well plate, and grown for 3 weeks at 37°C and 5%
CO2; for all other HMEC lines, 5.0x104 viable cells were plated per 60mm dish or 9.0x103
viable cells per well of a 12-well plate, and grown for 4 weeks at 37°C and 5% CO2.
Pictures of unstained colonies were taken at 2X magnification using a Nikon SMZ-U
dissecting microscope with a SPOT Flex 15.2 64Mp Shifting Pixel camera (Diagnostic
Instruments) and the accompanying SPOT advanced software, version 4.5.9.1. Plates
were then stained overnight at 37°C and 5% CO2 with a solution of 0.5mg/ml
155
iodonitrotetrazolium chloride (Sigma) in HMEC Growth Medium; pictures of stained
plates were taken using visualized using an AlphaImager EP transilluminator (Alpha
Innotech) and the accompanying AlphaView software, version 1.3.0.7.
Proliferation assays
Single-cell suspensions in HMEC Growth Medium were generated, and 1.25x104 viable
cells were plated per well of 24-well plates and allowed to attach overnight. For cells
grown under minimal growth conditions, wells were washed once with PBS (Gibco) and
then given Minimal Growth Medium (HMEC Growth Medium with 0.5% of the normal
growth factor and serum supplements). Fresh HMEC Growth Medium or Minimal Growth
Medium was given every other day. At each time point, wells were washed once with
PBS, cells were fixed for 15 minutes at room temperature with 10% phosphate-buffered
formalin (Fisher), washed twice with ddH2O, stained for 30 minutes with 0.1% crystal
violet (Sigma), washed three times with ddH2O, and allowed to dry completely. Cell-
associated dye was extracted with 1ml of 10% acetic acid per well, and optical density at
590nm was read using a Benchmark Plus microplate spectrophotometer (Bio-Rad) and
the accompanying Microplate Manager III software, version 1.133 for Mac OSX.
Immunoprecipitation assays
For immunoprecipitation of Flag-ErbB3 from HMECs, cells were rinsed twice with PBS
and starved for 4 hours in HMEC Starvation Medium before being lysed in NP40 lysis
buffer. For each reaction, 40たl of anti-Flag beads (Sigma) were washed 3 times with
NP40 lysis buffer, and then mixed with 1mg total protein from the appropriate whole cell
lysate in a total volume of 500たl NP40 lysis buffer. Reactions were carried out on a
rotator at 4°C for 1 hour. Beads were washed γ times with β50たl NP40 lysis buffer and
then resuspended in 2X SDS/DTT sample buffer and boiled at 100°C for 10 minutes.
156
For immunoprecipitation of endogenous ErbB3 from cultured mouse mammary tumor
cells, cells were rinsed twice with PBS and starved overnight in DMEM containing
penicillin/streptomycin and antimycotic before being lysed in NP40 lysis buffer. For each
reaction, 500たg total protein from the appropriate whole cell lysate was mixed with 4たg
anti-ErbB3 antibody (Millipore 05-390) and incubated on a rotator at 4°C for 1 hour.
Then, 40たl of Protein A/G beads (Santa Cruz) were added and reactions were carried
out on a rotator at 4°C for an additional 1 hour. The beads were washed 3 times with
β50たl NP40 lysis buffer and then resuspended in βX SDS/DTT sample buffer and boiled
at 100°C for 10 minutes.
For immunoprecipitation of phospho-tyrosine-containing proteins, HMECs were rinsed
twice with PBS and given HMEC Starvation Medium for 4 hours before being lysed in
NP40 lysis buffer. Each reaction consisted of 10たl 4G10 anti-phospho-tyrosine
sepharose bead slurry (Millipore) and 100たg total protein from the appropriate whole cell
lysate in a final volume of β50たl. Reactions were carried out on a rotator overnight at
4°C, and then the beads were washed γ times with β50たl NP40 lysis buffer and then
resuspended in 2X SDS/DTT sample buffer and boiled at 100°C for 10 minutes.
PTEN lipid phosphatase activity assay
HMECs were grown to confluency in 15cm tissue culture dishes. Asynchronous cells
were lysed in NP40 lysis buffer. Endogenous PTEN was immunoprecipitated from cell
lysates in triplicate reactions. For “Beads Only” reaction, 2mg total protein from
shControl whole cell lysate was diluted to a final volume of 400たl in NP40 lysis buffer.
For “PTEN Only” reaction, 2mg total protein from shControl whole cell lysate was mixed
with 8たl anti-PTEN antibody (Cell Signaling 9559) and diluted to a final volume of 400たl
in NP40 lysis buffer. For all other reactions, 2mg total protein from the appropriate whole
157
cell lysate was mixed with 8たl anti-PTEN antibody (Cell Signaling 9559) and diluted to a
final volume of 400たl in NP40 lysis buffer. All tubes were incubated on a rotator
overnight at 4°C. Then, 40たl of Protein A/G beads (Santa Cruz) were added to each
tube, and reactions were incubated on a rotator for 3 hours at 4°C. The beads were
washed 3 times with 400たl NP40 lysis buffer and then washed once with PTEN Reaction
Buffer (TBS [25 mM Tris-HCl (pH 7.5), 140mM NaCl, 2.7mM KCl] with 10mM DTT added
fresh). The beads were resuspended in γ0たl PTEN Reaction Buffer and used in in vitro
PTEN lipid phosphatase assays (Echelon Biosciences, method adapted from provided
documents and (Song et al., 2011)). Briefly, phosphate standards from 0-2,000pmol
were prepared using provided reagents. Then βたl of 1mM diC8PtdIns(3,4,5)P3 was
added to each of the standards, a “PIPγ Substrate Only” control (consisting of PTEN
Reaction Buffer only), and the immunoprecipitation reactions and accompanying
controls, and brought to a final volume of 50たl with PTEN Reaction Buffer. Reactions
were incubated at γ7°C for γ0 minutes, and then 100たl Malachite Green Reagent was
added to each reaction and incubated for 10 minutes at room temperature. The optical
density at 620nm, corresponding to phosphate released by PTEN enzymatic activity,
was read using a Benchmark Plus microplate spectrophotometer (Bio-Rad) and the
accompanying Microplate Manager III software, version 1.133 for Mac OSX.
Receptor internalization and degradation assays
To track internalization of EGFR, HMECs were rinsed with PBS and starved overnight in
HMEC Starvation Medium. Plates were washed with PBS-CM (PBS with 1mM MgCl2
and 0.1mM CaCl2 added), then incubated on a rocker for 40 minutes at 4°C with 5ml
PBS-CM containing 0.5mg/ml Sulfo-NHS-SS-Biotin (Pierce) to label surface proteins.
Plates were washed with PBS-CM, then incubated on a rocker for 10 minutes at 4°C
with 10ml PBS-CM containing 50mM NH4Cl (Sigma) to inactivate excess unbound sulfo-
158
NHS-SS-biotin. Plates were washed with PBS-CM. One plate per cell line was then
lysed with TritonX100 Lysis Buffer (200mM NaCl, 75mM Tris-HCl [pH 7.5], 15mM NaF,
2.5mM EDTA, 2.5mM EGTA, 1.5% TritonX100, 0.75% NP40, 0.1% SDS) for
determination of total surface EGFR. The remaining plates were stimulated with
20mg/ml human recombinant EGF (Sigma) in HMEC Starvation Medium at 37°C and 5%
CO2 for the indicated amounts of time to induce receptor internalization. At the
appropriate time, plates were rinsed with PBS-CM, washed twice with 10ml Glutathione
Buffer (90mM NaCl, 1mM MgCl2, 0.1mM CaCl2, 50mM reduced glutathione, 60mM
NaOH) to cleave any sulfo-NHS-SS-biotin remaining on the cell surface, and rinsed with
10ml PBS-IAA (50mM iodoacetamide in PBS-CM) on a rocker at 4°C for 15 minutes, to
quench excess glutathione. After rinsing with PBS-CM, plates were lysed with
TritonX100 lysis buffer and protein samples were prepared as described above. A
portion of these samples was reserved for whole cell lysates, and the rest was used in
Streptavidin immunoprecipitation. First, 1mg total protein per sample was pre-cleared by
incubating with pansorbin (Calbiochem) on a rotator at 4°C for 1 hour. The pansorbin
was removed by centrifugation, and 40ul Streptavidin beads (Pierce) were added for
overnight immunoprecipitation reactions. Beads were rinsed 4 times with TritonX100
lysis buffer before being boiled in 2X SDS/DTT sample buffer for 10 minutes. Samples
were then subjected to electrophoresis and immunoblotting as described above.
To track degradation of EGFR, HMECs were rinsed with PBS and starved overnight in
HMEC Starvation Medium. Plates were washed with PBS-CM, then incubated on a
rocker for 40 minutes at 4°C with 5ml PBS-CM containing 0.5mg/ml Sulfo-NHS-LC-LC-
Biotin (Pierce) to label surface proteins. Plates were washed with PBS-CM, then
incubated on a rocker for 10 minutes at 4°C with 10ml PBS-CM containing 50mM NH4Cl
(Sigma) to inactivate excess unbound sulfo-NHS-LC-LC-biotin. Plates were washed with
159
PBS-CM. One plate per cell line was then lysed with TritonX100 Lysis Buffer for
determination of total surface EGFR. The remaining plates were stimulated with
20mg/ml human recombinant EGF (Sigma) in HMEC Starvation Medium at 37°C and 5%
CO2 for the indicated amounts of time to induce receptor internalization. At the
appropriate time, plates were rinsed with PBS-CM and lysed with TritonX100 lysis buffer,
and protein samples were prepared as described above. A portion of these samples was
reserved for whole cell lysates, and the rest was used in Streptavidin
immunoprecipitation. First, 1mg total protein per sample was pre-cleared by incubating
with pansorbin (Calbiochem) on a rotator at 4°C for 1 hour. The pansorbin was removed
by centrifugation, and 40ul Streptavidin beads (Pierce) were added for overnight
immunoprecipitation reactions. Beads were rinsed 4 times with TritonX100 lysis buffer
before being boiled in 2X SDS/DTT sample buffer for 10 minutes. Samples were then
subjected to electrophoresis and immunoblotting as described above.
Animal husbandry and breeding strategy
MMTV-Cre (Wagner et al., 1997), NIC (Schade et al., 2009; Ursini-Siegel et al., 2008),
and Pik3r1 floxed (Luo et al., 2005b) mice were backcrossed to the FVB/N wildtype
background at least 10 generations. To generate the female mice used in these studies,
male MMTV-Cre or NIC mice heterozygous for the floxed Pik3r1 allele were crossed with
female mice heterozygous for the floxed Pik3r1 allele. For orthotopic tumor
transplantations, eight-week-old NCrNu female mice (Harlan) were used. Transplant
recipient mice were treated daily with vehicle control (0.5% [w/V] methylcellulose
[Sigma], administered by oral gavage at 1ml/kg body weight), BYL719 (in 0.5%
methylcellulose, administered by oral gavage at 45mg/kg), GDC0941 (in 0.5%
methylcellulose, administered by oral gavage at 125mg/kg), or KIN193 (in a solution of
7.5% NMP [1-methyl-2-pyrrolidinone, Sigma] and 40% PEG400 [Sigma], administered
160
by intraperitoneal injection at 20mg/kg). All animals were housed and treated in
accordance with protocols approved by the Institutional Animal Care and Use
Committees of Dana-Farber Cancer Institute and Harvard Medical School.
Genotyping
Genomic DNA was extracted from 2-3mm of tail tissue by boiling in 150ul of an alkaline
buffer containing 2mM EDTA and 25mM NaOH at 100C for 60 minutes, followed by
neutralization with 150ul of a buffer containing 40mM Tris Base. PCR was then
performed on the DNA extracts using GoTaq DNA polymerase (Promega) as follows for
each gene: Pik3r1, primers 5'-CAC CGA GCA CTG GAG CAC TG-3' and 5'-CCA GTT
ACT TTC AAA TCA GCA CAG-3', wildtype Pik3r1 allele generates a fragment of 252bp,
while floxed Pik3r1 allele generates a 301bp fragment; NIC transgene, primers 5'-TTC
CGG AAC CCA CAT CAG GCC-3' and 5'-GTT TCC TGC AGC AGC CTA CGC-3',
transgene generates a 630bp fragment; MMTV-Cre transgene, primers 5’-CTG ATC
TGA GCT CTG AGT G-γ’, 5’-CAT CAC TCG TTG CAT CGA CC-γ’, transgene
generates a 250bp fragment. PCR samples were then resolved by electrophoresis
through a 2% agarose gel with SYBR Safe (Invitrogen) and visualized under UV light
using an AlphaImager EP transilluminator (Alpha Innotech) and the accompanying
AlphaView software, version 1.3.0.7.
Mammary whole mount preparation
The fourth mammary gland tissue was excised, spread on glass slides, and fixed
overnight in Carnoy’s Fixative (a 1:γ [V/V] solution of glacial acetic acid and 100%
ethanol). Slides were then washed for 30 minutes in 70% ethanol and 30 minutes in
ddH2O, and then stained overnight in Carmine Alum (1g carmine [Sigma] dissolved in
500ml ddH2O). Slides were then washed for 30 minutes in 70% ethanol, 30 minutes in
161
95% ethanol, and 30 minutes 100% ethanol before being immersed in toluene. All steps
were carried out at room temperature. Images of fixed mammary tissue were taken with
a Nikon SMZ-U dissecting microscope with a SPOT Flex 15.2 64Mp Shifting Pixel
camera (Diagnostic Instruments) and the accompanying SPOT advanced software,
version 4.5.9.1.
Mouse mammary epithelial cell isolation
For each mouse, the third and fourth mammary glands were excised, washed in PBS
(Gibco), finely chopped, combined, and digested overnight at 37°C and 5% CO2 in 5ml
Digestion Medium (DMEM/F12 GlutaMAX [Gibco] with penicillin/streptomycin [Gibco]
and collagenase/hyaluronidase [Stem Cell Technologies] added to a final concentration
of 1X). Following digestion, the tissue was pelleted by centrifugation, the supernatant
removed, and the tissue resuspended in Red Blood Cell Lysis Buffer (a 1:4 [V/V] solution
of cold HF Solution [Hank’s Balanced Salt Solution (Stem Cell Technologies) with β%
FBS (Gibco) and penicillin/streptomycin (Gibco)] and ammonium chloride [Stem Cell
Technologies]). The tissue was then pelleted by centrifugation, the supernatant
removed, and the pellet resuspended in 2ml pre-warmed 0.25% Trypsin-EDTA (Gibco)
for 1-3 minutes, followed by addition of 3ml FBS and 10ml cold HF Solution. The tissue
was then pelleted by centrifugation, the supernatant removed, the pellet resuspended in
1ml Dispase and 100たl DNAseI (both Stem Cell Technologies) for 1 minute followed by
addition of 5-10ml cold HF Solution, and then passed through a 40たm cell strainer.
Analysis of mammary tumors and lung metastases
Cohorts of female mice were examined every 3 days for the onset of tumors, defined by
the first palpation. Five weeks after tumor onset, the mice were sacrificed by CO2 in
accordance with protocols approved by the Institutional Animal Care and Use
162
Committees of Dana-Farber Cancer Institute and Harvard Medical School. The total
tumor burden per mouse was determined by taking the wet weight of excised mammary
tissue and associated tumors. The total number of tumors per mouse was determined by
counting the number of distinct excised tumors with a diameter of at least 3mm. To
determine the total number of lung metastases per mouse, lungs were excised and fixed
overnight in 10% phosphate-buffered formalin (Fisher). All lung lobes were embedded in
paraffin, and three sections 50たm apart were mounted on slides and stained with
hematoxylin and eosin. Metastases were visualized and quantified using a Nikon Eclipse
E600 microscope. For each mouse, the total number of lung metastases was taken to be
that of the section with the highest count.
Histology and immunohistochemistry
Tissue was fixed overnight in 10% phosphate-buffered formalin (Fisher) and then
transferred to 70% ethanol. Formalin-fixed tissue was embedded in paraffin blocks and
mounted on slides by the HMS Rodent Histopathology Core. Hematoxylin and eosin
staining was performed by the HMS Rodent Histopathology Core. Immunohistochemical
staining of tissue sections was performed using a sodium citrate antigen retrieval
method. Slides were deparaffinized in xylene and hydrated in ethanol washes of
decreasing concentration. Antigen retrieval was then performed by boiling slides in
10mM sodium citrate (pH 6.0) (Boston BioProducts) for 20 minutes, followed by 30
minutes of cooling. Endogenous peroxidases were blocked by soaking the slides in 3%
hydrogen peroxide (Sigma) for 10 minutes at room temperature, and then slides were
further blocked by a 1 hour incubation with 5% serum in IHC-TBST (50mM Tris-HCl [pH
7.5], 150mM NaCl, 0.1% Tween-20) at room temperature. Slides were then incubated
with primary antibodies overnight. Antibodies from Cell Signaling were diluted in the
buffer provided by Cell Signaling, and all other antibodies were diluted in 5% serum in
163
IHC-TBST. The following primary antibodies were used: p85g (EMD Millipore 04403
1:500), phospho-AKTS473 (Cell Signaling 3787 1:50), phospho-ERKT202/Y204 (Cell
Signaling 4376 1:400), phospho-S6S235/236 (Cell Signaling 4858 1:400), and Ki67 (Vector
Laboratories VPK451 1:1000). Slides were then incubated for 30 minutes at room
temperature with biotinylated goat anti-rabbit IgG secondary antibody (Vector
Laboratories BA1000 1:250-1:2000) followed by a 30-minute incubation at room
temperature with ABC reagent (Vector Laboratories). Antibody signal was then
developed by brief incubation with DAB horseradish peroxidase substrate (Vector
Laboratories) and slides were counterstained with hematoxylin (Vector Laboratories).
For TUNEL, the ApopTag Plus Peroxidase In Situ Apoptosis Detection Kit was used
(EMD Millipore) followed by a counterstain with methyl green (Vector Laboratories).
Tissue sections were then dehydrated by washes in increasing concentrations of ethanol
followed by washes in xylene. Coverslips were mounted using Cytoseal XYL (Thermo
Scientific) and slides were visualized using a Nikon Eclipse E600 microscope, and
images were obtained with a SPOT Flex 15.2 64Mp Shifting Pixel camera (Diagnostic
Instruments) and the accompanying SPOT advanced software, version 4.5.9.1.
Preparation of mouse tissue protein lysates
Tissue pieces were snap frozen in liquid nitrogen. To generate protein lysates, tissue
was homogenized in NP40 lysis buffer using 0.5mm zirconium oxide beads (Next
Advance Inc.) in an air-cooling bullet blender (Next Advance). Once homogenized,
lysates were cleared and analyzed as described above.
Isolation and culture of mouse mammary tumor cells
Mouse mammary tumor cells were cultured in DMEM 5% FBS (DMEM supplemented
with 5% fetal bovine serum, penicillin/streptomycin, and antimycotic, all from Gibco) at
164
37°C and 5% CO2. To isolate cells for culture, tumor pieces of approximately 0.5cm3
were finely chopped, resuspended in 6-8ml DMEM 5% FBS containing 1mg/ml
collagenase (Roche), and incubated on a rotator for 20 minutes at 37°C. Cells were then
pelleted by a 5 minute centrifugation at 1200rpm, washed with PBS, pelleted again,
resuspended in 10ml DMEM 5% FBS, and plated in 10cm tissue culture dishes.
Graphing software and statistical analysis
All graphs and statistical analysis were done using GraphPad Prism 6.0 for Mac OS X.
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191
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192
Appendix A: Supplemental table of class I PI3K alterations in cancer, with complete references
Alteration Type Cancer Type Frequency of
Alteration Sample Size Range
References
Class IA
PIK3CA (p110g) Mutation Endometrial 10.3-53.0% 29-232 1, 2 Breast 7.1-35.5% 65-507 3-9 Ovarian (CC) 33.0% 97 10 Colorectal 16.9
†-30.6%
72-195 11, 12
Bladder 5.0-20.0% 20-130 13-16 Lung (SCC) 20.0% 5 17 Lung (SQCC) 2.9-16.8% 35-178 17, 18 Lung (LCC) 11.9% 9 17 Lung (ADC) 0.6-4.3% 57-183 3, 17, 19, 20 Cervical 13.6% 22 2 Glioblastoma 4.3-11.0% 91-291 21-24 Head and neck 8.1-9.4%
32-74 25, 26
Esophageal 5.5%
145 27 Melanoma 5.0%
121
28
Prostate 1.3-3.6%
55-156 3, 29-31 Sarcoma 2.9%
207 32
Renal (CC) 1.0-2.9%
98-417 33, 34 Liver (HCC) 1.6% 125 35 Megalencephaly
‡ 48.0% 50 36
Copy number Head and neck 9.1-100% 11-117 37-39 gain/amplification Cervical 9.1-76.4% 22-55 2, 40 Lung (SQCC) 42.9-69.6% 28-52 17, 41, 42 Lung (SCC) 33.3-66.7% 3-12 17, 41 Lung (LCC) 16.7-37.5% 6-16 17, 41 Lung (ADC) 9.5-19.1% 47-74 17, 41 Lung (NSCLC) 12.0% 92 43 Lymphoma (MCL) 68.2% 22 44 Lymphoma (DLBCL) 16.7% 60 45 Ovarian 39.8% 93 46 Ovarian (Serous) 13.3-24.3% 60-74 47, 48 Gastric 36.4% 55 49 Thyroid 30.0% 110 50 Prostate 28.1% 32 16 Breast 8.7-13.4% 92-209 8, 9 Glioblastoma 1.9-12.2% 139-206 21, 22 Endometrial 10.3% 29 2 Thyroid 9.4% 128 51 Esophageal 5.7% 87 52 Leukemia (CLL) 5.6% 161 53
Increased expression Prostate 40.0% 25 16
193
Appendix A: Supplemental table of class I PI3K alterations in cancer, with complete references (continued)
Alteration Type Cancer Type Frequency of
Alteration Sample Size Range
References
Class IA
PIK3CB (p110く) Mutation Breast 0.5% 183 3, 54
Copy number Lung (SQCC) 56.5% 46 42 gain/amplification Thyroid 42.3% 97 50 Ovarian 5-26.9% NA-93 46, 55
Lymphoma (DLBCL) 20.0% 60 45
Glioblastoma 5.8% 103 56 Breast 4.9-5% NA-81
55, 57
Increased expression Prostate 46.7% 30 58 Glioblastoma 3.9% 103 56
PIK3CD (p110h) Copy number gain Glioblastoma 40.0% 10 59
Increased expression Neuroblastoma 52.6% 19 60 Glioblastoma 5.8% 103 56
PIK3R1 (p85g, p55g, p50g) Mutation Endometrial 19.8-32.8% 108-243 1, 61, 62 Pancreatic 16.7% 6 63 Glioblastoma 7.6-11.3% 91-291 22-24 Colorectal 4.6
†-8.3% 108-195 11, 63
Melanoma 4.4% 68 64 Ovarian 3.8% 80 65 Esophageal 3.4%
145 27
Breast 1.1-2.8% 62-507 3, 4, 63, 66 Colon 1.7% 60 65
Decreased expression Breast 61.8% 458 66 Prostate 17-75%* NA 67 Lung 19-46%* NA 67 Ovarian 22%* NA 67 Breast 18%* NA 67 Bladder 18%* NA 67
Copy number loss Ovarian 21.5% 93 46
PIK3R2 (p85く) Mutation Endometrial 4.9% 243 61 Colorectal 0.9% 108 63 Megalencephaly
‡ 22.0% 50 36
Amplification Lymphoma (DLBCL) 23.3% 60 45
Increased expression Colon 55.0% 20 68 Breast 45.7% 35 68
PIK3R3 (p55け) Copy number gain Ovarian 15.0% 93 46
194
Appendix A: Supplemental table of class I PI3K alterations in cancer, with complete references (continued)
Alteration Type Cancer Type Frequency of
Alteration Sample Size Range
References
Class IB
PIK3CG (p110け) Copy number gain Ovarian 19.3% 93 46
Increased expression Breast 77.5% 40 69
Prostate 72.4% 29 70
Medulloblastoma 52.9% 17 71
PIK3R5 (p101)
Mutation Melanoma 38.2% 68 64 Gastric 2.7% 37 63
CC, clear cell; SCC, small cell carcinoma; SQCC, squamous cell carcinoma; ADC, adenocarcinoma; LCC, large cell carcinoma; NSCLC, non-small cell lung carcinoma; MCL, mantle cell lymphoma; CLL, chronic lymphocytic leukemia; DLBCL, diffuse large B cell lymphoma; HCC, hepatocellular carcinoma. ‡ Megalencephaly syndromes are a collection of sporadic overgrowth disorders characterized by enlarged
brain size and other distinct features. † Combined number of hypermutated and non-hypermutated colon and colorectal patient samples with
mutations in the indicated gene. * Represents the percent reduction in gene expression. NA Sample size not available for this study.
195
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9. Wu, G. et al. Somatic mutation and gain of copy number of PIK3CA in human breast cancer. Breast Cancer Res 7, R609-16 (2005).
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196
17. Okudela, K. et al. PIK3CA mutation and amplification in human lung cancer. Pathol Int 57, 664-71 (2007).
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27. Dulak, A.M. et al. Exome and whole-genome sequencing of esophageal adenocarcinoma identifies recurrent driver events and mutational complexity. Nat Genet 45, 478-86 (2013).
28. Hodis, E. et al. A landscape of driver mutations in melanoma. Cell 150, 251-63 (2012).
29. Taylor, B.S. et al. Integrative genomic profiling of human prostate cancer. Cancer Cell 18, 11-22 (2010).
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35. Guichard, C. et al. Integrated analysis of somatic mutations and focal copy-number changes identifies key genes and pathways in hepatocellular carcinoma. Nat Genet 44, 694-8 (2012).
36. Riviere, J.B. et al. De novo germline and postzygotic mutations in AKT3, PIK3R2 and PIK3CA cause a spectrum of related megalencephaly syndromes. Nat Genet 44, 934-40 (2012).
37. Fenic, I., Steger, K., Gruber, C., Arens, C. & Woenckhaus, J. Analysis of PIK3CA and Akt/protein kinase B in head and neck squamous cell carcinoma. Oncol Rep 18, 253-9 (2007).
38. Pedrero, J.M. et al. Frequent genetic and biochemical alterations of the PI 3-K/AKT/PTEN pathway in head and neck squamous cell carcinoma. Int J Cancer 114, 242-8 (2005).
39. Woenckhaus, J. et al. Genomic gain of PIK3CA and increased expression of p110alpha are associated with progression of dysplasia into invasive squamous cell carcinoma. J Pathol 198, 335-42 (2002).
40. Ma, Y.Y. et al. PIK3CA as an oncogene in cervical cancer. Oncogene 19, 2739-44 (2000).
41. Massion, P.P. et al. Early involvement of the phosphatidylinositol 3-kinase/Akt pathway in lung cancer progression. Am J Respir Crit Care Med 170, 1088-94 (2004).
42. Massion, P.P. et al. Genomic copy number analysis of non-small cell lung cancer using array comparative genomic hybridization: implications of the phosphatidylinositol 3-kinase pathway. Cancer Res 62, 3636-40 (2002).
43. Kawano, O. et al. PIK3CA gene amplification in Japanese non-small cell lung cancer. Lung Cancer 58, 159-60 (2007).
44. Psyrri, A. et al. Phosphatidylinositol 3'-kinase catalytic subunit alpha gene amplification contributes to the pathogenesis of mantle cell lymphoma. Clin Cancer Res 15, 5724-32 (2009).
45. Cui, W. et al. Frequent copy number variations of PI3K/AKT pathway and aberrant protein expressions of PI3K subunits are associated with inferior survival in diffuse large B cell lymphoma. J Transl Med 12, 10 (2014).
46. Huang, J. et al. Frequent genetic abnormalities of the PI3K/AKT pathway in primary ovarian cancer predict patient outcome. Genes Chromosomes Cancer 50, 606-18 (2011).
47. Nakayama, K. et al. Sequence mutations and amplification of PIK3CA and AKT2 genes in purified ovarian serous neoplasms. Cancer Biol Ther 5, 779-85 (2006).
48. Nakayama, K. et al. Amplicon profiles in ovarian serous carcinomas. Int J Cancer 120, 2613-7 (2007).
49. Byun, D.S. et al. Frequent monoallelic deletion of PTEN and its reciprocal associatioin with PIK3CA amplification in gastric carcinoma. Int J Cancer 104, 318-27 (2003).
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50. Liu, Z. et al. Highly prevalent genetic alterations in receptor tyrosine kinases and phosphatidylinositol 3-kinase/akt and mitogen-activated protein kinase pathways in anaplastic and follicular thyroid cancers. J Clin Endocrinol Metab 93, 3106-16 (2008).
51. Wu, G. et al. Uncommon mutation, but common amplifications, of the PIK3CA gene in thyroid tumors. J Clin Endocrinol Metab 90, 4688-93 (2005).
52. Miller, C.T. et al. Gene amplification in esophageal adenocarcinomas and Barrett's with high-grade dysplasia. Clin Cancer Res 9, 4819-25 (2003).
53. Brown, J.R. et al. Integrative genomic analysis implicates gain of PIK3CA at 3q26 and MYC at 8q24 in chronic lymphocytic leukemia. Clin Cancer Res 18, 3791-802 (2012).
54. Dbouk, H.A. et al. Characterization of a tumor-associated activating mutation of the p110beta PI 3-kinase. PLoS One 8, e63833 (2013).
55. Brugge, J., Hung, M.C. & Mills, G.B. A new mutational AKTivation in the PI3K pathway. Cancer Cell 12, 104-7 (2007).
56. Knobbe, C.B. & Reifenberger, G. Genetic alterations and aberrant expression of genes related to the phosphatidyl-inositol-3'-kinase/protein kinase B (Akt) signal transduction pathway in glioblastomas. Brain Pathol 13, 507-18 (2003).
57. Crowder, R.J. et al. PIK3CA and PIK3CB inhibition produce synthetic lethality when combined with estrogen deprivation in estrogen receptor-positive breast cancer. Cancer Res 69, 3955-62 (2009).
58. Zhu, Q. et al. Phosphoinositide 3-OH kinase p85alpha and p110beta are essential for androgen receptor transactivation and tumor progression in prostate cancers. Oncogene 27, 4569-79 (2008).
59. Mizoguchi, M., Nutt, C.L., Mohapatra, G. & Louis, D.N. Genetic alterations of phosphoinositide 3-kinase subunit genes in human glioblastomas. Brain Pathol 14, 372-7 (2004).
60. Boller, D. et al. Targeting the phosphoinositide 3-kinase isoform p110delta impairs growth and survival in neuroblastoma cells. Clin Cancer Res 14, 1172-81 (2008).
61. Cheung, L.W. et al. High frequency of PIK3R1 and PIK3R2 mutations in endometrial cancer elucidates a novel mechanism for regulation of PTEN protein stability. Cancer Discov 1, 170-85 (2011).
62. Urick, M.E. et al. PIK3R1 (p85alpha) is somatically mutated at high frequency in primary endometrial cancer. Cancer Res 71, 4061-7 (2011).
63. Jaiswal, B.S. et al. Somatic mutations in p85alpha promote tumorigenesis through class IA PI3K activation. Cancer Cell 16, 463-74 (2009).
64. Shull, A.Y. et al. Novel somatic mutations to PI3K pathway genes in metastatic melanoma. PLoS One 7, e43369 (2012).
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66. Cizkova, M. et al. PIK3R1 underexpression is an independent prognostic marker in breast cancer. BMC Cancer 13, 545 (2013).
67. Taniguchi, C.M. et al. The phosphoinositide 3-kinase regulatory subunit p85alpha can exert tumor suppressor properties through negative regulation of growth factor signaling. Cancer Res 70, 5305-15 (2010).
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70. Edling, C.E. et al. Key role of phosphoinositide 3-kinase class IB in pancreatic cancer. Clin Cancer Res 16, 4928-37 (2010).
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200
Appendix B: Supplemental table of genetically engineered mouse models of PI3K isoforms in cancer, with complete references.
Genotype Phenotype Ref
PIK3CA (p110g)
KRasLA2
; Pik3caRBD/RBD Protected from KRas-induced lung
tumors 1
Rosa26-Cre; KRasLA2
; Pik3caRBD/flox
Partial regression of KRas-induced lung tumors
2
MMTV-Neu-IRES-Cre; Pik3caflox/flox
Protected from Her2/neu-driven mammary tumors
3
Pb-Cre; Ptenflox/flox
; Pik3caflox/flox No effect on high-grade PIN driven by
Pten loss 4
Mx1-Cre; KRasG12D
; Pik3caflox/flox Protection from MPN induced by
oncogenic KRas 5
Mx1-Cre, LSL-Shp2GOF/+
; Pik3caflox/flox No effect on MPN induced by Shp2
GOF 6
Pten−/+
; Pik3caKD/+
Increased endometrial hyperplasia; reduced pheochromocytoma and thyroid tumors
7
CCSP-rtTA; Tet-op-PIK3CAH1047R
Develop lung tumors within 3 months 8
MMTV-rtTA; tetO-PIK3CAH1047R
Develop mammary tumors within 7 months
9
MMTV-Cre; LSL-PIK3CAH1047R Surviving mice develop mammary
tumors within 7 months 10
MMTV-Cre; Pik3cae20H1047R/+ Develop mammary tumors within 16
months 11
WAP-Cre; LSL-PIK3CAH1047R Develop mammary tumors within 36
days post-partum 10
WAP-Cre; LSL-PIK3CAE545K
Develop mammary tumors within 80 days post-partum
12
MMTV-Cre; p53flox/+
; Rosa26-Pik3caH1047R
Develop mammary tumors within 5 months
13
MMTV-rtTA; tetO-Cre; ErbB3flox/flox
; tetO-PIK3CAH1047R
Delayed mammary hyperplasia but no effect on mammary tumor formation driven by PIK3CA
H1047R
14
MMTV-rtTA; MMTV-Her2; tetO-PIK3CAH1047R
Accelerated mammary tumor formation and increased lung metastasis compared to Her2 or PIK3CA
H1047R alone
15
Ptenflox/flox
; Pik3caLat-H1047R/+ Develop ovarian tumors within 16
weeks 16
Gpa33-CrePR2; APCLOF/LOF
; Pik3caLat-H1047R/+
Accelerated development of intestinal tumors compared to Pik3ca
H1047R or
APCLOF
alone 17
Fabp1-Cre; ApcMin/+
; Rosa26-Pik3ca*
Increased number and size of intestinal tumors compared to Pik3ca* or Apc
Min/+ alone
18
Fabp1-Cre; Apcflox/+
; Rosa26-Pik3ca*
Increased number and size of intestinal tumors compared to Pik3ca* or Apc
flox/+ alone
18
201
Appendix B: Supplemental table of genetically engineered mouse models of PI3K isoforms in cancer, with complete references (continued).
Genotype Phenotype Ref
PIK3CB (p110く)
MMTV-Her2/neuT; Pik3cbKD/KD
Reduced number of mammary tumors driven by Her2/neuT
19
Pb-Cre; Ptenflox/flox
; Pik3cbflox/flox Protection from high-grade PIN driven
by Pten loss 4
Pten−/+
; Pik3cbKD/+ Reduced PIN and prostate cancer
driven by Pten loss 7
(ARR)2PB-Pik3cbCA Develop VP PIN by 10 weeks and
DLP PIN by 60 weeks 20
MMTV-Neu-IRES-Cre; Pik3cbflox/flox
Accelerated mammary tumor formation and increased tumor burden driven by Her2/neu
3
PIK3CA (p110g) and PIK3CB (p110く)
K14-Cre; Ptenflox/flox
; Pik3caflox/flox
; Pik3cbflox/flox
Loss of ¾ alleles of Pik3ca and Pik3cb blocks skin lesions and mammary hyperplasia driven by Pten loss
21, 22
PIK3CD (p110h)
Pik3cdKD
Reduced trafficking of NK cells; reduced NK cell extravasation to tumor cells
23
Mx1-Cre, LSL-Shp2GOF/+
;Pik3cdKD/KD
Reduced MPN induced by Shp2 GOF 6
Lck-Cre; Ptenflox/flox
; Pik3cd−/−
No effect on development of T-ALL driven by Pten loss
24
PIK3CG (p110け)
Lck-Cre; Ptenflox/flox
; Pik3cg−/−
No effect on development of T-ALL driven by Pten loss
24
PIK3CD (p110h) and PIK3CG (p110け)
Lck-Cre; Ptenflox/flox
; Pik3cd−/−
; Pik3cg−/−
Delayed development of T-ALL driven by Pten loss
24
PIK3R1 (p85g, p55g, p50g)
CD19-Cre; Pik3r1flox/flox
Reduced B-cell leukemia development driven by ex vivo infection with BCR-ABL
25
Albumin-Cre; Pik3r1flox/flox
Develop liver tumors within 20 months 26
Pten−/+
; Pik3r1−/+ Increased intestinal polyps but no
change in PIN driven by Pten loss 27
PIK3R2 (p85く)
Pik3r2−/− Decreased number of colon tumors
induced by AOM/DSS 28
Pten−/+
; Pik3r2−/− No change in intestinal polyps or PIN
driven by Pten loss 27
CD19-Cre; Pik3r2−/−
No effect on B-cell leukemia development driven by ex vivo infection with BCR-ABL
25
202
Appendix B: Supplemental table of genetically engineered mouse models of PI3K isoforms in cancer, with complete references (continued).
Genotype Phenotype Ref
PIK3R1 (p85g, p55g, p50g) and PIK3R2 (p85く) CCSP-rtTA; tetO-KRas
G12D; Pik3r1
flox/flox; Pik3r2
−/−
LSL-KRasG12D
; Pik3r1flox/flox
; Pik3r2−/−
Decreased incidence of lung tumors driven by KRas
8
CD19-Cre; Pik3r1flox/flox
; Pik3r2−/−
Blocked B-cell leukemia development driven by ex vivo infection with BCR-ABL
25
CCSP-rtTA; tetO-KRasG12D
; Pik3r1flox/+
; Pik3r2−/−
LSL-KRasG12D
; Pik3r1flox/+
; Pik3r2−/−
Increased incidence of lung tumors driven by KRas
8
PIK3C2A (PI3K-Cβg)
Cdh5(PAC)-CreERT2
; Pik3c2aflox/flox Decreased microvessel density and
tumor burden of implanted tumors 29
RBD, Ras binding domain mutant; KD, kinase dead mutant; CA, constitutively active; Tg, transgene; PIN, prostate intraepithelial neoplasia; AOM/DSS, azoxymethane/dextran sodium sulfate; LOF, loss of function; GOF, gain of function; VP, ventral prostate; DLP, dorsal/lateral prostate; MPN, myoproliferative neoplasia.
203
Appendix B references:
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4. Jia, S. et al. Essential roles of PI(3)K-p110beta in cell growth, metabolism and tumorigenesis. Nature 454, 776-9 (2008).
5. Gritsman, K. et al. Hematopoiesis and RAS-driven myeloid leukemia differentially require PI3K isoform p110alpha. J Clin Invest 124, 1794-809 (2014).
6. Goodwin, C.B. et al. PI3K p110delta uniquely promotes gain-of-function Shp2-induced GM-CSF hypersensitivity in a model of JMML. Blood 123, 2838-42 (2014).
7. Berenjeno, I.M. et al. Both p110alpha and p110beta isoforms of PI3K can modulate the impact of loss-of-function of the PTEN tumour suppressor. Biochem J 442, 151-9 (2012).
8. Engelman, J.A. et al. Effective use of PI3K and MEK inhibitors to treat mutant Kras G12D and PIK3CA H1047R murine lung cancers. Nat Med 14, 1351-6 (2008).
9. Liu, P. et al. Oncogenic PIK3CA-driven mammary tumors frequently recur via PI3K pathway-dependent and PI3K pathway-independent mechanisms. Nat Med 17, 1116-20 (2011).
10. Meyer, D.S. et al. Luminal expression of PIK3CA mutant H1047R in the mammary gland induces heterogeneous tumors. Cancer Res 71, 4344-51 (2011).
11. Yuan, W. et al. Conditional activation of Pik3ca(H1047R) in a knock-in mouse model promotes mammary tumorigenesis and emergence of mutations. Oncogene 32, 318-26 (2013).
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