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UNIVERSITY OF OULU P .O. Box 8000 F I -90014 UNIVERSITY OF OULU FINLAND
A C T A U N I V E R S I T A T I S O U L U E N S I S
University Lecturer Tuomo Glumoff
University Lecturer Santeri Palviainen
Senior research fellow Jari Juuti
Professor Olli Vuolteenaho
University Lecturer Veli-Matti Ulvinen
Planning Director Pertti Tikkanen
Professor Jari Juga
University Lecturer Anu Soikkeli
Professor Olli Vuolteenaho
Publications Editor Kirsti Nurkkala
ISBN 978-952-62-2439-8 (Paperback)ISBN 978-952-62-2440-4 (PDF)ISSN 0355-3221 (Print)ISSN 1796-2234 (Online)
U N I V E R S I TAT I S O U L U E N S I S
MEDICA
ACTAD
D 1547
AC
TAM
adhura Patankar
OULU 2019
D 1547
Madhura Patankar
MODELING AND HISTOPATHOLOGICAL RECOGNITION OF ANOIKIS RESISTANCE IN COLORECTAL CARCINOMA
UNIVERSITY OF OULU GRADUATE SCHOOL;UNIVERSITY OF OULU,FACULTY OF MEDICINE
ACTA UNIVERS ITAT I S OULUENS I SD M e d i c a 1 5 4 7
MADHURA PATANKAR
MODELING AND HISTOPATHOLOGICAL RECOGNITION OF ANOIKIS RESISTANCE IN COLORECTAL CARCINOMA
Academic dissertation to be presented with the assent ofthe Doctoral Training Committee of Health andBiosciences of the University of Oulu for public defence inAuditorium P117 (Aapistie 5B), on 13 Decamber 2019, at12 noon
UNIVERSITY OF OULU, OULU 2019
Copyright © 2019Acta Univ. Oul. D 1547, 2019
Supervised byProfessor Tuomo J. KarttunenDocent Sinikka Eskelinen
Reviewed byAssistant Professor Pekka TaimenDocent Keijo Viiri
ISBN 978-952-62-2439-8 (Paperback)ISBN 978-952-62-2440-4 (PDF)
ISSN 0355-3221 (Printed)ISSN 1796-2234 (Online)
Cover DesignRaimo Ahonen
JUVENES PRINTTAMPERE 2019
OpponentDocent Juha Klefström
Patankar, Madhura, Modeling and histopathological recognition of anoikisresistance in colorectal carcinoma. University of Oulu Graduate School; University of Oulu, Faculty of MedicineActa Univ. Oul. D 1547, 2019University of Oulu, P.O. Box 8000, FI-90014 University of Oulu, Finland
Abstract
Colorectal carcinoma (CRC) is an important cause of cancer-associated deaths. About 30–50% ofCRCs show KRAS or BRAF mutation. In many cancers, anoikis, i.e. apoptosis induced by loss ofextracellular matrix (ECM) contact, is disturbed. Anoikis resistance is essential for the formationof metastases, and since anoikis resistance assessment is based on in vitro cell cultures, theprognostic value of anoikis resistance is largely unknown. We aimed to identify thehistopathological features indicating anoikis resistance in CRC and analyze their prognostic value.The roles of BRAF and KRAS mutations and survivin in anoikis resistance were analyzed and 3-Dcell culture was used to model the histopathology of anoikis resistant (AR) structures.
The two cohorts of CRC cases used in the study consisted of 62 (series 1) and 137 patients(series 2). Immunohistochemistry for ECM proteins enabled identification of tumor cells with andwithout ECM contact, and in both populations, apoptosis was determined with staining forcaspase-cleaved keratin 18. Based on absence of ECM contact and decreased apoptosis rate, weidentified micropapillary (MIP), cribriform and solid structures to represent the putative ARpopulations. High areal density of AR structures associated independently with short survival andwas an independent prognostic factor. MIPs showed lower survivin expression, proliferation andapoptosis rates than non-MIP cells, and low apoptosis rate was associated with poor prognosis instage I and II cases. For 3-D in vitro model of AR structures, we transfected Caco-2 cells withmutated KRAS or BRAF genes; both induced anoikis resistance as measured with Annexin V testin suspension culture. In 3-D cultures, native Caco-2 cells formed polarized cysts. In contrast,mutated cell lines formed partially filled cysts or solid structures, and inverted polarity in KRASmutant cells.
In conclusion, it is possible to identify putative AR structures by conventional histopathologyand their number is associated with poor prognosis. MIPs represent a distinct subpopulation ofCRC cells with features of quiescence. KRAS and BRAF mutations induce anoikis resistance inCaco-2 cells. In 3-D cultures, oncogenes KRAS and BRAF induce solid structures and cell piling,with structural resemblance to putative AR structures observed by histopathology. The mutatedCaco-2 cells thus serve as a model to study the manifestation of anoikis resistance as a distincthistological feature with oncological significance.
Keywords: anoikis resistance, apoptosis, BRAF, carcinoma, colon, extracellular matrix,KRAS, proliferation, survivin
Patankar, Madhura, Anoikisresistenssin mallintaminen ja histopatologinen tunnis-taminen kolorektaalisyövässä. Oulun yliopiston tutkijakoulu; Oulun yliopisto, Lääketieteellinen tiedekuntaActa Univ. Oul. D 1547, 2019Oulun yliopisto, PL 8000, 90014 Oulun yliopisto
Tiivistelmä
Paksu- ja peräsuolisyöpä on yleinen syöpäkuoleman aiheuttaja. KRAS- tai BRAF-geenien mutaa-tio todetaan 30–50 prosentissa suolisyövistä. Anoikis tarkoittaa apoptoosia, jonka käynnistää solun irtoaminen soluväliaineesta. Anoikisresistenssi on etäpesäkkeen synnyn edellytys. Anoi-kisresistenssiä voidaan todeta vain soluviljelyssä, joten sen merkitystä syövässä in vivo ei ole aiemmin arvioitu. Tässä työssä pyrittiin tunnistamaan anoikisresistenssiin viittaavat muutokset histopatologisista suolisyöpänäytteistä ja selvittämään niiden vaikutusta potilaan ennusteeseen. Lisäksi tutkittiin BRAF- ja KRAS-mutaatioiden yhteyttä anoikisresistenssiin ja mallinnettiin anoikisresistenttejä (AR) rakenteita kolmiulotteisessa soluviljelmässä.
Potilasaineisto koostui 199 suolisyöpäpotilaasta. Kudosleikkeistä värjättiin soluväliaineen komponentteja sekä määritettiin apoptoottiset ja jakautuvat solut (M30- ja Ki-67-värjäykset). AR-solupopulaatioiden tunnistamisessa käytettiin kriteereinä soluväliainekontaktin puuttumista ja vähentynyttä apoptoositiheyttä. AR-populaatioiksi osoittautuivat mikropapillaariset (MIP), seulamaiset ja solidit rakenteet. Näiden rakenteiden korkea kokonaisesiintyvyys osoittautui itse-näiseksi huonon ennusteen tekijäksi. MIP-rakenteissa surviviinin ilmentyminen ja apoptoosi- ja proliferaatiotiheys olivat vähentyneet muihin kasvainsoluihin verrattuna. Lisäksi apoptoottisten solujen pieni määrä MIP-rakenteissa liittyi huonoon ennusteeseen paikallisessa syövässä. Mal-linnusta varten Caco-2 solut transfektoitiin mutatoiduilla KRAS- tai BRAF-geeneillä. Onkogee-nien transfektion todettiin indusoivan anoikisresistenssiä. Kolmiulotteisessa soluviljelyssä polarisoituneet Caco-2 solut muodostivat säännöllisiä rauhasmaisia rakenteita. Onkogeeneillä transfektoidut solut muodostivat puolestaan osittain tai kokonaan täyttyneitä rakenteita ja KRAS-transfektio aiheutti solujen polariteetin kääntymistä.
Havainnot osoittavat, että anoikisresistenssiä edustavat rakenteet voidaan tunnistaa kudos-leikkeestä ja niiden runsas määrä viittaa huonoon ennusteeseen. MIP-rakenteissa todettiin lepoti-lan (quiescence) piirteitä. KRAS- ja BRAFmutaatiot aiheuttavat Caco-2 soluissa anoikisresistens-siä. Kolmiulotteisissa soluviljelmissä onkogeenien vaikutus näkyy solujen pinoutumisena, mikä muistuttaa syöpäkudosnäytteissä todettuja AR-rakenteita. Tulosten perusteella modifioituja Caco-2 soluja voidaan hyödyntää anoikisresistenssin mallintamiseen ja tarkempien mekanismi-en tutkimiseen.
Asiasanat: anoikisresistanssi, apoptoosi, BRAF, karsinooma, kooolon, KRAS, proliferaatio, soluväliaine
To Aai
There is no greater Tapasya (penance) than peace, there is no greater happiness than satisfaction, there is no
greater disease than greed, and there is no greater dharma (religion) than mercy.
– Chanakya.
“Neither money pays, not name, nor fame, nor learning; it is CHARACTER than can cleave through adamantine
walls of difficulties.” – Swami Vivekananda.
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Acknowledgements
The study was conducted at the Department of Pathology, Cancer and Translational
Medicine Research Unit at University of Oulu under the expert supervision of
Professor Tuomo J. Karttunen.
I would like to start with thanking my mentor, Professor Tuomo J. Karttunen
for his strong support and expert guidance. From him, I have learned the importance
of keeping one eye on the details and the other on the larger picture. He has been a
patient coach with a very clear vision, and, to top it all, his kind attitude,
commitment to science and constant availability, made this journey of science
possible and enjoyable for me.
I am thankful to Professor Markus Mäkinen for providing scientific guidance
and support for my thesis. I am very grateful to Docent Sinikka Eskelinen, my co-
supervisor, for introducing me to the interesting field of experimental cell biology,
for sharing her scientific knowledge and for her kind and loving support all these
years.
I am thankful to Assistant Professor Pekka Taimen and Docent Keijo Viiri for
their careful review and expert comments on the thesis. I am grateful to Anna
Vuolteenaho for her excellent linguistic editing of the thesis and making time for
this work.
I wish to thank my former and current thesis follow-up group, Professor Tuomo
Glumoff, Docent Jussi Koivunen, Johanna Mäkinen, MD, PhD, Kristian Koski,
PhD, Irina Raykhel, PhD for their encouragement and guidance towards the
completion of my thesis. I would like to thank former Medical Research Center
(MRC-Oulu) coordinator Mirja Peltola for her kind support. Sincere thanks to
senior colleagues of my department, Docent Anne Tuomisto for her kind support
and troubleshooting experimental halts, and Docent Katja Porvari and Dr Helena
Kaija, DMD, PhD, for their friendship and kind support.
I sincerely thank Professor Pentti Nieminen and Risto Bloigu, MA, for
introducing me to the essentials of medical statistics and their help with data
analysis. I would like to thank Professor Aki Manninen for providing the
infrastructure and his expert guidance on viral-mediated cell culture work. I express
my gratitude to Docent Virpi Glumoff for walking me through flow cytometry
experimentation and analysis. I would like to thank Veli-Pekka Ronkainen, PhD,
for his expert advice on imaging acquisition and analysis. Many thanks to Antti
Viklund and Mika Kaakinen, PhD, for helping with and fixing unexpected
experimental encounters.
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I want to thank my co-authors Professor Jrki Mäkelä, Sara Väyrynen, MD, PhD,
Taneli Mattila, MD, Vesa-Matti Pohjanen, MD, PhD, Juha Väyrynen, MD, PhD,
Kai Klintrup, MD. I wish to thank former and current friends and colleagues Janne
Capra, Päivi Sirniö, Siina Vaarala, Ilkka Minkkinen, Anne-Mari Moilanen, and
Tiina Kantola; it has been a pleasure to share office space and work with you. I am
grateful to Riitta Vuento, Mirja Mäkeläinen and Erja Tomperi for their technical
expertise and kind support all these years. Sincere thanks to Jaana Träskelin and
Riitta Jokela for their technical help with viral mediated work.
I acknowledge the financial support from the Cancer and Translational
Medicine Research Unit, Medical Research Center Oulu, Oulu University Hospital,
Scholarship fund of University of Oulu and Thelma Mäkikyrö Foundation.
I want to thank my dear friend Sara Väyrynen for her friendship, optimism,
and unconditional support. Humble thanks to Hanna-Riikka Teppo and Laura
Luukkainen for their friendship and optimistic point of view. Heartfelt thanks also
to Susanna Kaisto and Lea Rahtu-Korpela for their caring friendship and being
there! My warm thanks to Virve Pääkkonen, Cynthia Paulin, Satu Myllymäki and
Salla Kangas for kind friendship and thoughtful scientific-non-scientific
discussions. Many thanks to Seija Leskelä for her friendship and teaching me tricks
and tips in graphic design software. I would like to thank Miia Hillilä, Julia
Kniazeva and Päivi Taskila, friends from outside work, for their caring and kind
friendship,
My Mother, Bharati Patankar, has been a rock for us and has beautifully juggled
the multiple roles of mother, father and friend all these years. Her optimism,
kindness and integrity are contagious and enriching. To thank my parents, Vikram
and Bharati Patankar, is similar to thanking God and there aren’t enough words to
do that. Warmest thanks to my little sister Mayura for her unconditional love,
support and believing in me. Finally, extending my warm affection to li’l
munchkins Legolas and Frodo, my sister’s kittens, for their innocent mischief that
kept all the nightmares at bay, and my humble thanks and regards to all the elders
of my family for their love and blessings.
14.11.2019 Madhura Patankar
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Abbreviations
AI Apoptosis index
AJC Apical Junctional Complex
Akt Protein kinase B
APC Adenomatous polyposis coli
AR Anoikis resistant
Bak Bcl-2 homologous antagonist/killer
BCL-2 B-cell lymphoma 2
BCL-XL B-cell lymphoma-extra large
BH3 Bcl-2 homology domain 3
Bid BH3 interacting-domain death agonist
Bim Bcl-2-like protein 11
BIR Baculovirus inhibitor of apoptosis protein repeat
BRAF v-Raf murine sarcoma viral oncogene homolog B
Caco-2 Human colon carcinoma cell line
CD3 Cluster of differentiation 3
CD8 Cluster of differentiation 8
CD147 Extracellular matrix metalloproteinase inducer
Cdc-42 Cell division control protein 42 homolog
CIMP CpG island methylator phenotype
CIMP-H CpG island methylator phenotype-High
CIN Chromosomal instability
CPT1A Carnitine Palmitoyltransferase 1A
CRC Colorectal carcinoma
CSC Cancer Stem cells
CSS Cancer specific survival
CTC Circulating tumor cells
DFS Disease-Free Survival
DISC Death-inducing signaling complex
DMEM Dulbecco Modified Eagle Medium
DNA Deoxyribonucleotide Acid
E-cadherin Epithelial cadherin
ECM Extracellular matrix
EDTA Ethylenediaminetetraacetic Acid
EGFR Epidermal growth factor receptor
EMT Epithelial Mesenchymal Transition
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ER Endoplasmic Reticulum
ERK Extracellular signal-regulated kinase
FACS Fluorescence-activated cell sorter
FAK Focal adhesion kinase
GCHP Goblet cell-rich hyperplastic polyp
GFP Green Fluorescent Protein
HIF1α Hypoxia-inducible factor 1-alpha
HP Hyperplastic polyp
HRP Horseradish peroxidase
IAP Inhibitor of Apoptosis Proteins
IBD Inflammatory bowel disease
ICC Interclass correlation coefficient
ILK Integrin-linked kinase
KRAS Kristen rat sarcoma viral oncogene homolog
MCF10A Human breast cancer cells
MCL-1 Induced Myeloid Leukemia Cell Differentiation Protein
MDCK Madine-Darby Canine Kidney cells
MEK Mitogen-activated extracellular signal regulated kinase
MEM Minimal Essential Medium Eagle
MGMT O (6)-methylguanine-DNA-methyl transferase
MIP Micropapillary structures
miRNA Micro-ribonucleic acid
MLH1 MutL homolog 1 gene
MPHP Mucin-poor hyperplastic polyp
MSI-L Microsatellite instable-low
MSS Microsatellite stable
MVHP Microvesicular hyperplastic polyp
N-Cadherin Neural cadherin
Non-MIP Non-micropapillary epithelium
Nox 4 NADPH oxidase 4
PBS Phosphate buffer saline
PIK3CA Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit
alpha
PI3K Phosphoinositide 3-kinases
PIP2 Phosphatidylinositol-4-5-bisphosphate
PIP3 Phosphatidylinositol-3-4-5- triphosphate
poly-HEMA Poly (2-hydroxyethyl methacrylate)
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PTEN Phosphatase and tensin homolog gene
RIPA Radioimmunoprecipitation assay buffer
ROC Receiver operating characteristic curve
ROS Reactive oxygen species
RTK Receptor tyrosine kinase
SDS-PAGE Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis
snail Zinc finger protein SNAI1
SNORA 42 Box H/ACA small nucleolar RNAs
Sox2 Sex determining region Y-box 2
Src Proto-oncogene tyrosine-protein kinase
SSA Sessile serrated adenoma
TBS Tris-buffered saline
TGFβ Transforming growth factor-beta
TIL Tumor infiltrating lymphocytes
TNF Tumor necrosis Factor
TMA Tissue microarray
TNM Tumor, Node, Metastasis staging
TP53 Tumor protein p53
TrKB Tyrosine kinase B
TSA Traditional Serrated Adenoma
WHO World Health Organization
Wnt Wingless-related integration site
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Original publications
This thesis is based on the following publications cited by their Roman numerals:
I Patankar M, Väyrynen S, Tuomisto A, Mäkinen M, Eskelinen S and Karttunen TJ. (2018). Micropapillary structures in colorectal cancer: An anoikis-resistant subpopulation. Anticancer Research 38, 2915-2921.
II Patankar M, Mattila T, Väyrynen JP, Klintrup K, Mäkelä J, Tuomisto A, Nieminen P, Mäkinen M J, Karttunen TJ. (2019). Histopathological assessment of anoikis resistance in colorectal carcinoma: Abundance of putative anoikis resistant subpopulations indicate poor prognosis. Manuscript.
III Patankar M, Eskelinen S, Tuomisto A, Mäkinen M, Karttunen TJ. (2019). KRAS and BRAF mutations induce anoikis resistance in Caco-2 cells and characteristic 3D phenotypes in Caco-2 cells. Molecular Medicine Reports, 20: 4634-4644.
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Contents
Abstract
Tiivistelmä
Acknowledgements 9
Abbreviations 11
Original publications 15
Contents 17
1 Introduction 21
2 Review of Literature 23
2.1 Colon and Rectum ................................................................................... 23
2.1.1 Anatomy and physiology of the colon and rectum ....................... 23
2.1.2 Histology ...................................................................................... 24
2.2 Colorectal cancer ..................................................................................... 25
2.2.1 Conventional carcinoma ............................................................... 26
2.2.2 Serrated carcinoma ....................................................................... 27
2.2.3 Colorectal premalignant lesions ................................................... 27
2.2.4 Prognostic factors in colorectal carcinoma ................................... 29
2.3 Apoptosis ................................................................................................ 34
2.3.1 Pathways of apoptosis .................................................................. 34
2.3.2 Anoikis ......................................................................................... 35
2.4 Mechanism of anoikis resistance ............................................................ 36
2.4.1 Integrin signaling and cell survival .............................................. 36
2.4.2 Cell-cell contacts .......................................................................... 37
2.4.3 Activation of anti-apoptotic pathways .......................................... 38
2.4.4 Apical-basal polarity aberration ................................................... 39
2.4.5 Survivin ........................................................................................ 40
2.4.6 Other factors ................................................................................. 41
2.5 Anoikis resistance in cancer .................................................................... 42
2.5.1 Anoikis resistance and formation of metastasis ............................ 43
2.5.2 Anoikis resistance and prognosis in carcinoma ............................ 43
2.6 Assessment and modeling of anoikis resistance ..................................... 44
2.6.1 Anti-adhesion tests ....................................................................... 44
2.6.2 3-D in vitro culture ....................................................................... 44
2.6.3 Biomarkers associated with anoikis resistance .............................. 45
3 Aims of the study 47
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4 Materials and Methods 49
4.1 Histopathology ........................................................................................ 49
4.1.1 Patients and tumors ....................................................................... 49
4.1.2 Histopathological analysis ............................................................ 51
4.1.3 Immunohistochemical stainings ................................................... 53
4.1.4 Immunohistochemical analysis ..................................................... 53
4.2 In vitro experiments ................................................................................ 55
4.2.1 Cell culture, staining and imaging ................................................ 55
4.2.2 Image collection and analysis ....................................................... 55
4.2.3 Paraffin embedding of 3-D cultures ............................................. 58
4.2.4 Protein expression analysis ........................................................... 58
4.3 Statistical analyses .................................................................................... 59
5 Results 61
5.1 Identification and quantification of putative AR structures in
carcinomas (I, II) ..................................................................................... 61
5.2 Immunohistochemical assessment of ECM proteins, apoptosis
and proliferation rates and survivin expression ....................................... 62
5.2.1 Expression of type IV collagen and laminin (II) .......................... 62
5.2.2 Proliferation and Apoptosis indexes (I, II) ................................... 62
5.2.3 Survivin expression (I) ................................................................. 63
5.3 Areal density of putative AR structures and their association with
clinical features of carcinomas (II) .......................................................... 66
5.3.1 Putative AR structures and clinicopathological features .............. 66
5.3.2 Putative AR structures associate with prognosis (II) .................... 66
5.4 Effects of BRAF and KRAS mutations on anoikis resistance in
vitro (III) .................................................................................................. 67
5.4.1 Transfection of Caco-2 cells with mutant KRAS or BRAF
genes ............................................................................................. 67
5.4.2 Anoikis resistance assessment with Annexin V test ..................... 68
5.4.3 Cell cycle stage estimation in different Caco-2 cell forms ........... 69
5.4.4 Bim expression in AR cells .......................................................... 70
5.5 3-D in vitro modeling of AR cell subpopulations ................................... 70
5.5.1 Live monitoring: evolution of 3-D structures ............................... 71
5.5.2 Organization and polarization of Caco-2 cells in 3-D
structures: influence of KRAS and BRAF mutations ................... 71
5.5.3 Paraffin embedment of 3-D cultures ............................................. 73
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6 Discussion 75
6.1 Identification of putative AR subpopulations .......................................... 76
6.2 Putative AR structures and prognosis of carcinoma ................................ 77
6.3 Survivin, an anti-apoptotic protein influencing tumorigenesis ............... 78
6.4 3-D in vitro model with mutated KRAS and BRAF oncogenes
transfected Caco-2 cells to model anoikis resistance .............................. 79
6.5 KRAS and BRAF mutations induce anoikis resistance in adhesion
free culture in Caco-2 cells ..................................................................... 82
6.6 Anoikis-resistant cells and putative AR cells present in
carcinomas show features of dormancy or quiescence ........................... 84
6.7 A model untangling the fates of AR subpopulations in cancer
formation ................................................................................................. 84
6.8 Future perspectives ................................................................................. 85
7 Conclusions 89
List of references 91
Original publications 107
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1 Introduction
Colorectal cancer (CRC) is the third most common cause of cancer-related deaths.
CRC usually develops slowly, and tumor formation involves many steps comprised
of genetic, epigenetic, histological and morphological changes that accumulate
over a long time. This often results in presentation of symptoms quite late when the
tumor is of considerable size, affecting the passage of feces, along with cramps and
bleeding. Surgery is the main treatment option for non-metastatic CRC (Haddad,
Eid, Kourie, Barouky, & Ghosn, 2018; Simon, 2016). Thorough clinical evaluation
with imaging and histological assessment of surgical resections allows
determination of stage and estimation of other factors for outcome assessment and
consideration of possible adjuvant therapy. However, the benefits of adjuvant
therapy after surgery are debatable, since it is difficult to identify the patients at risk
of recurrence (Tyrrell & Kerr, 2018). Therefore, there is a need for identification
and validation of prognostic and predictive markers to assess tumor recurrence in
stage II CRC patients to enable appropriate decision for adjuvant treatment course
(Eriksen et al., 2018; Haddad et al., 2018). For example, a low number of CD3+
and CD8+ tumor infiltrating lymphocytes (TILs) at the invasive front represents
poor prognosis for stage II CRC patients (Eriksen et al., 2018). Some other
predictive and prognostic markers, such as aberrant miRNA expression, mutations
of KRAS or BRAF genes, and high proportions of Ki-67 expressing cells are
promising, but they require thorough clinical testing and reproducibility validation
for decision of optimal treatments.
In normal healthy tissues, unwanted or faulty cells are removed by a process
called cellular apoptosis in order to maintain tissue homeostasis. Anoikis is a form
of apoptosis induced when a cell loses its contact with the extracellular matrix.
Anoikis was described in the year 1994 by Frisch and Francis (Frisch & Francis,
1994). Resistance to anoikis is important in the formation of cancer metastases, as
otherwise, cells detached to circulation would die by induction of apoptosis.
Anoikis resistance can be a result of disturbed integrin signaling, faulty cell death
mechanism, disrupted apical-basal cell polarity, epithelial-mesenchymal transition,
cellular dormancy, hypoxia or others factors.
Related to the essential role of anoikis resistance in metastasis, identification
of features indicating it would likely be important in the assessment of prognosis
and selection of optimal therapy of malignant tumors, and therefore, likely to be
important in routine clinical assessment of malignant tumors. So far, detection of
anoikis resistance has been limited to anti-adhesion in vitro cell culture-based tests.
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Conventional histopathological methods have not been adopted to assess anoikis
resistance. To address this issue, we aimed to identify and quantitate cells with
anoikis resistance by conventional histopathological methods based on the basic
premise of anoikis resistance, survival of tumor cells without contact with the ECM.
To get indirect support for the concept, we evaluated the prognostic significance of
the amount of anoikis-resistant tumor cell subpopulations. Finally, we tested
whether corresponding putative anoikis resistant (AR) structures can be formed by
an in vitro 3-D model.
Firstly, we identified micropapillary (MIP) structures representing a
subpopulation of putative AR structures in a series of colorectal polyps and
carcinomas. In the same study, we assessed proliferation and apoptosis rates and
survivin expression in polyps and cancers in MIPs and non-MIP epithelium.
Built on the same idea, we extended our search of putative AR subpopulations
to other subpopulations besides MIPs by analyzing another series of CRC and
evaluated the prognostic significance of these subpopulations.
To study AR structures similar to actual carcinomas, we generated an in vitro
model with a modified Caco-2 colorectal cancer cell line by transfecting the cells
with mutated KRAS and BRAF oncogenes and assessed the growth pattern. In
addition, we investigated anoikis resistance ability by anti-adhesion tests and
studied the survival mechanisms in AR subpopulations.
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2 Review of Literature
2.1 Colon and Rectum
2.1.1 Anatomy and physiology of the colon and rectum
The lower gastrointestinal tract consists of the large intestine, appendix and anus.
The large intestine is further divided into the first section, i.e. the caecum, followed
by the ascending and transverse colon. After the splenic flexure, the colon continues
as descending colon, and when the intestine enters the pelvis, it turns into the S-
shaped sigmoid colon, followed by the rectum, and ends at the anus, which opens
to the exterior (Ponz de Leon & Di Gregorio, 2001) (Figure 1). The surface area of
the large intestinal mucosa of an adult human is about 2 m2 (Helander & Fandriks,
2014). In contrast to the small intestine, the large intestine lacks
Fig. 1. Anatomy of the large bowel adapted from (Ponz de Leon & Di Gregorio, 2001).
villi and large volume of contents, and it absorbs fluids, processes luminal contents,
and acts as a reservoir (San Roman & Shivdasani, 2011).
The main functions are absorption and storage. The colon and rectum absorb
water and nutrients, including those remaining after absorption in the small
intestine and those formed by microbes. They store indigestible food residue before
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it can be eliminated from the body via the anus in the form of feces (Cheng et al.,
2010; Greenwood-Van Meerveld, Johnson, & Grundy, 2017).
The blood supply to the colon derives from the superior mesenteric artery (caecum
to splenic flexure) and the inferior mesenteric artery (descending colon, sigmoid
colon and rectum) (San Roman & Shivdasani, 2011) whereas the middle and
inferior artery along with the internal iliac artery supply blood to the lower rectum.
2.1.2 Histology
The most luminal part of the colon is the mucosa, which consists of epithelial cells
and the supportive lamina propria. The epithelial component consists of a single
columnar epithelium lining the surface and crypts opening to the surface. The
epithelium is comprised of goblet cells, absorptive cells, undifferentiated cells, and
endocrine cells. At the base of the intestinal crypt lies a stem cell pool that divides
continuously; the daughter cells differentiate into new specialized cells of the
intestinal epithelium (Barker et al., 2009) The lamina propria contains pericryptal
cells supporting the epithelial cells, occasional smooth muscle cells, blood and
lymphatic vessels, nerves and the cells of innate and acquired immune system.
Fig. 2. Colon and rectum histology.
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A thin smooth muscle layer, muscularis mucosae, separates the mucosa from the
submucosa composed mainly of loose connective tissue with fibrocytes and
supportive extracellular matrix (ECM), nerves, occasional lymphocytes, and mast
cells. Smooth muscle layers known as muscularis interna and externa extend from
the submucosa to the serosa and form the main bulk of the wall. (Ponz de Leon &
Di Gregorio, 2001) (Figure 2).
2.2 Colorectal cancer
In general, carcinogenesis may result from inactivation of tumor suppressor genes
including gatekeepers that regulate tumor growth by inhibiting cell proliferation or
enhancing death (e.g. APC or TP53 in CRC), caretakers that maintain genomic
stability and, in their absence, cause increased mutation in other genes (MLH1) or
landscapers which influence cellular microenvironment (e.g. PTEN loss). On the
other hand, cancer could also be a result of activation of pro-tumorigenic oncogenes
(e.g. KRAS) which are altered or transformed by mutation, chromosomal
translocation or gene amplification, enhancing expression or causing structural
changes in protein product that functions in proliferation, differentiation, growth
and apoptosis (De Rosa et al., 2015; Nguyen & Duong, 2018).
The development of CRC begins when normal colorectal epithelium transforms
into premalignant lesions composed of genetic alterations and some alterations in
their microscopic structure enabling their recognition. Premalignant lesions include
aberrant crypt foci and adenomas, and progress into cancer by accumulative genetic
alterations (mutation or amplification of gene) or epigenetic alterations, i.e.
inheritable changes (chromatin modification, aberrant DNA methylation, histone
modification and noncoding RNAs) modifying gene expression without changes in
the DNA sequence (Grady & Carethers, 2008; Pancione, Remo, & Colantuoni,
2012). CRC arises through a sporadic or hereditary pathway, the latter accounting
for about 5% of CRCs including Lynch syndrome (mutation in mismatch repair
genes resulting in accumulative DNA mutations) or familial adenomatous
polyposis (a syndrome caused by a mutation in adenomatous polyposis coli (APC))
gene essential for Wnt signaling (Nguyen & Duong, 2018).
Hereditary pathway to CRC results from germline mutations via the two-hit
hypothesis where a germ cell mutation in a tumor suppressor gene causes the first
hit followed by a second hit at somatic progenitor cells in target tissues (DA Silva,
Wernhoff, Dominguez-Barrera, & Dominguez-Valentin, 2016; Jass, 2007). CRC
may also develop via sporadic pathway by a somatic genetic or epigenetic change
26
during tumor initiation. By definition, sporadic cancers occur in patients without
history suggesting familial CRC and with no germline mutation (Mundade,
Imperiale, Prabhu, Loehrer, & Lu, 2014; Raskov, Pommergaard, Burcharth, &
Rosenberg, 2014).
Sporadic pathway can lead to three types of colorectal carcinoma: conventional
carcinoma (CAC) via adenoma-carcinoma sequence, serrated CRC (SAC) that
evolves via serrated pathway, and inflammatory bowel disease (IBD) associated
pathway (Beaugerie & Itzkowitz, 2015; Leggett B & Whitehall V, 2010).
2.2.1 Conventional carcinoma
For many decades, it was thought that colon cancer can only form by the adenoma-
carcinoma sequence, which is mostly initiated by chromosomal instability (CIN)
leading to cumulative genomic alterations. Fearon and Vogelstein proposed a
multistage model for colon cancer progression in 1990 (Fearon & Vogelstein, 1990).
In a normal colon epithelial cell, the Wnt signaling pathway is activated when the
APC gene undergoes mutation (due to frameshift or point mutation). The activation
results in accumulation of beta-catenin, which supports the maintenance of
undifferentiated stem cell phenotype with restricted migration ability (Armaghany,
Wilson, Chu, & Mills, 2012; Leslie et al., 2003). As a result, the accumulated
undifferentiated cells may lead to development of adenomas (early adenoma),
which in turn, via additional mutations (such as activation of proto-oncogene
KRAS), form late adenomas including aberrant cell adhesion and proliferative
signaling network (Armaghany et al., 2012).
According to the model, a late adenoma turns into carcinoma when it
encounters mutation in tumor suppressor genes such as TP53, inactivation of
PIK3CA oncogene, or loss of heterozygosity (e.g. loss of long arm of chromosome
18) mutation occurring in the remaining allele (Borowsky et al., 2018; Leslie et al.,
2003; Pinto, Jacobsen, & Horwitz, 2011).
Cancers forming through conventional adenomas often harbor chromosomal
instability (CIN) and are CpG island methylator phenotype (CIMP) negative and
microsatellite stable (MSS) (Figure 3). Mutated APC is common in CAC compared
to serrated malignancy; however, non-APC-related Wnt signaling has been
implicated in the serrated pathway (Borowsky et al., 2018).
27
2.2.2 Serrated carcinoma
SAC develops via serrated neoplasia pathway with molecular aberrations partially
distinct from the conventional adenoma-carcinoma sequence. This type of
carcinoma is more common in women, particularly in older age, possibly through
the post-menopause effect (low estrogen and folate level) (Noffsinger, 2009).
Histologically, these are glands with serrations, accompanied by frequent mucin
pools, no necrosis and large eosinophilic cytoplasm (Makinen, 2007; Tuppurainen
et al., 2005).
SACs may originate by respective serrated polyps via genetic and epigenetic
mutations. One route involves traditional serrated adenoma where early change
involves KRAS or BRAF mutation accompanied by O6-methyl guanine-DNA-
methyl transferase (MGMT) activation and methylation of other genes, eventually
giving rise to CIMP-High, chromosomally stable, MSI-Low or MSS SAC
predominantly found in the distal colon and rectum. Another route involves sessile
serrated adenomas with early BRAF mutation along with mutations in p16, a tumor
suppressor protein and Insulin-like growth factor-binding protein (IGFBP) 7
promoter hypermethylation and mutL homolog 1 (MLH1) epigenetic alteration
leading to CIMP-High phenotype. Such SACs have BRAF mutations, are
chromosomally stable and MSS, and are predominantly found in the proximal
colon. (De Palma et al., 2019; Makinen, 2007) (Figure 3).
Another route to formation of SAC may arise from adenomatous polyps or
serrated polyps with mutation in the KRAS oncogene. These cancers are CIMP-
Low, chromosomally unstable, harbor MGMT methylation, KRAS mutation and are
MSI-Low or MSS (Leggett B & Whitehall V, 2010; Snover, 2011; Tuppurainen et
al., 2005).
2.2.3 Colorectal premalignant lesions
CAC arises from conventional adenoma (CA) with characteristic features such as
variable dysplasia of epithelium and is more common in males and in patients over
50 years of age. Macroscopically, CAs appear polypoid or sessile, and
histologically, they comprise three subtypes: tubular adenoma (composed of
tubular/gland like structures), tubulovillous adenoma (combination of tubular
structures and villous projections at surface), and villous adenoma (predominantly
villous projections).
28
SAC mostly has a different set of precursor lesions, serrated polyps, which are
comprised of traditional serrated adenomas (TSA), sessile serrated adenomas
(SSA), and hyperplastic polyps (HP). HPs, considered to have less malignant
Fig. 3. Developmental pathways of colorectal cancer adapted from (Armaghany et al.,
2012; Leggett B & Whitehall V, 2010; Noffsinger, 2009)
potential than other serrated polyp types, mainly associate with polyps in the
proximal to sigmoid colon (Yang, Mitchell, Sepulveda, & Sepulveda, 2015). TSAs
are formed of cells with eosinophilic cytoplasm lining the glands and villous
structures. They often have ectopic crypts, i.e. crypts that have lost contact with the
muscularis mucosae, perpendicular to the longitudinal axis of villous projections
(Kalimuthu, Chelliah, & Chetty, 2016). TSA are accompanied by either KRAS or
BRAF mutation and may show features of cellular senescence (Fleming, Ravula,
Tatishchev, & Wang, 2012; Kalimuthu et al., 2016).
29
SSAs typically have crypts with serrated epithelium broadened bases
accompanied by basal branching and are often accompanied by dysplasia (admixed
polyp), a precursor of CRC with MSI (Makinen, 2007). HPs show non-dysplastic
saw tooth-like serrations on the epithelial folds of the upper parts of the crypt and
narrow, non-branching crypt bases. HPs are further divided into goblet cell
hyperplastic polyps (GCHP), microvesicular hyperplastic polyps (MVHP), and
mucin poor hyperplastic polyps (MPHP). GCHP are composed of abundant goblet
cells, lack BRAF mutation, and include less serrations in the upper half compared
to other subtypes. MVHP presents characteristic features of mucin in the cytoplasm
of epithelial cells and often harbor BRAF mutation. Therefore, it is speculative
whether MVHP progress into SSA/P and eventually serrated carcinoma, or whether
the cancer originates directly from MVHP without any intermediary phase (Groff,
Nash, & Ahnen, 2008; Rosty, Hewett, Brown, Leggett, & Whitehall, 2013). Finally,
MPHP are a HP type with the absence of cytoplasmic mucin (Fleming et al., 2012;
Sweetser, Smyrk, & Sinicrope, 2013).
2.2.4 Prognostic factors in colorectal carcinoma
Prognostic factors are defined as measurements showing associations with clinical
outcome either in the absence of therapy or upon standard therapy received by the
patient (Clark, 2008). In addition to estimating overall outcome, prognostic factors
are used to optimize treatment. Currently, in CRC, one of the main objectives is to
find prognostic markers to identify those patients with stage II disease who are at
increased risk of recurrence after surgery and who would benefit from adjuvant
therapies, such as adjuvant chemotherapy (van de Velde et al., 2014).
TNM class and stage
Classification based on the anatomical extent of the tumor is based on the widely
accepted TNM classification system and comprises the extent of local growth of
carcinoma (T; Figure 4), presence of distant metastases (M), and involvement of
lymph nodes (N). The AJCC and UICC TNM classification systems are reviewed
and updated constantly and the latest 8th edition was released in 2017.
Determination of stage provides information about prognosis and is very useful
from the viewpoint of surgical aspects. In addition to detailed TNM class,
anatomical extent can be summarized by translating TNM class to stages I-IV.
30
Stages I and II represent local carcinomas limited to the intestinal wall and adjacent
tissues. Stages III and IV are more advanced carcinomas with local lymph node
metastasis (stage III) or with distant metastases (stage IV). For colon cancer, 5-year
survival in stages I-II is 90%, in stage III 71%, and in stage IV, 14% (Carroll &
Zhao, 2019). (Table 1)
Fig. 4. Histological image showing invasion of colorectal cancer into mucscularis
propria, indicating TNM stage T2.
Histopathological prognostic factors
The characteristics determined by the differentiation of a tumor are recorded as a
histological grade. This is based on WHO standards (Bosman, Carneiro, Hruban,
& Theise, 2010) and the percentage of well-differentiated glands in the tumor as
follows: well-differentiated tumors (> 95% gland forming) are classified as grade
1, moderately differentiated (50–95% gland forming) as grade 2, poorly
differentiated (< 50% gland forming) as grade 3, and undifferentiated as grade 4
tumors (Derwinger, Kodeda, Bexe-Lindskog, & Taflin, 2010). Determination of
grade has rather poor reproducibility and limited prognostic value, but higher
31
Table 1. Tumor staging of colorectal carcinoma
Stage Main pathological and clinical features
Stage I T1 (Tumor invading submucosa), T2 (Tumor invading muscularis
propria)
Absence of lymph node metastasis
No distant metastasis
Stage II T3 (Tumor invading subserosa or into pericolic or perirectal
tissues), T4 (tumor directly invading organ or structures and/ or
perforates visceral peritoneum)
Absence of lymph node metastasis
No distant metastasis
Stage III Any tumor class
Presence of lymph node metastasis
No distant metastasis
Stage IV Any tumor class
Presence or absence of lymph node metastasis
Presence of distant metastasis
grade has rather poor reproducibility and limited prognostic value, but higher
grades predict less favorable prognosis (Barresi, Reggiani Bonetti, Ieni, Caruso, &
Tuccari, 2015).
Blood vessel and lymphatic vessel invasion are directly associated with nodal
metastasis and poor prognosis. Lymphatic vessel invasion alone displays strong
association with lymph node metastasis and poor outcome (Barresi et al., 2012; Lin
et al., 2010). Most importantly, lymphatic invasion in CRC is a stage-independent
prognostic factor and crucial for determining adjuvant therapy for stage II patients
(Harris et al., 2008).
Tumor budding comprises small discrete clusters of less than 5 tumor cells
mainly detected and assessed at the invasive front. In addition to being associated
with poor prognosis, the presence of buds is an indicator of epithelial mesenchymal
transition (EMT) and invasive phenotype (Lugli et al., 2017; Marks, West, Morris,
& Quirke, 2018). Moreover, Dawson et al. (Dawson et al., 2015) suggested that
based on low apoptosis rate and expression of a pro-survival molecule, anoikis
resistance might be related with the prognostic significance of budding. Detection
of tumor budding is currently an important prognostic feature.
32
Detection of poorly differentiated clusters (PDC) or solid cancer cell nests is a
relatively new feature. Their abundance is a better indicator of poor prognosis than
the assessment of conventional grade. PDC are defined as five or more cancer cells
that form clusters and are completely devoid of gland-like structures (Reggiani
Bonetti, Barresi, Bettelli, Domati, & Palmiere, 2016; Ueno et al., 2014). The
biology of PDC is not known.
Increased inflammatory cell response at the invasive border associates with
better outcome (Klintrup et al., 2005). The quality of immune response is
determined by immune cell profiling based on IHC assessment (Marks et al., 2018;
Vayrynen et al., 2013; Vayrynen et al., 2014). Tumor infiltrating lymphocyte (TIL)
response is also known to be associated with primary and metastatic colorectal
cancer (Kong et al., 2019). In addition, systemic level inflammation as detected by
blood C reactive protein level and albumin level associates with less favorable/poor
prognosis (Kantola et al., 2012; Proctor et al., 2011). Similarly, systemic
inflammation assessed by blood neutrophil-to-lymphocyte ratio (NLR) has
prognostic value, low NLR favoring poor survival (M. X. Li et al., 2014). NLR
combined with serum albumin concentration gives a systemic inflammation score
(SIS) and this score represents a prognostic factor (Shibutani et al., 2018).
Apoptosis and proliferation
Estimation of proliferation by detecting Ki-67 antigen-positive cells with
immunohistochemistry is a well-known independent prognostic factor, high rates
associating with disease progression and poor clinical outcome (Luo et al., 2019;
Melling et al., 2016). Additionally, low cellular apoptosis rate as shown by a low
number of cells expressing cleaved caspase 3 or caspase-cleaved Keratin 18
associates with poor prognosis (Reimers et al., 2014; Saigusa et al., 2014).
Molecular prognostic factors
Along with efforts to understand the mechanism of diseases and find effective
diagnosis and treatment, several genetic and epigenetic markers have been reported.
Genetic alterations in oncogenes are associated with patient outcome. For drugs
targeting the EGFR pathway, mutational analysis of BRAF, KRAS and NRAS
oncogenes is necessary to predict treatment response.
Mutations in KRAS oncogene are found in about 40% of CRCs and commonly
harbor at codon 12 or 13. Such mutations constitutively activate the EGFR pathway,
33
leading to resistance to anti-EGFR therapies (Lievre et al., 2006). KRAS-mutated
carcinomas are less likely to display MSI but associate with less favorable
prognosis among microsatellite stable (MSS) carcinomas (Phipps et al., 2013;
Taieb et al., 2016). Mutations in the BRAF oncogene are present in about 10% of
CRCs, and in MSS carcinomas they are associated with increased risk of disease
progression. BRAF mutation is a negative prognostic marker independent of stage
that is often observed in recurrent colorectal cancer (De Divitiis et al., 2014;
Haddad et al., 2018; Sepulveda et al., 2017).
Mutations of the TP53 gene are linked to poor patient outcome, but its
usefulness as a clinical biomarker has not been validated (V. D. Li, Li, & Li, 2019;
Nguyen & Duong, 2018). Microsatellite instability status (MSI) predicts improved
clinical outcome in colorectal cancer patients (Kang et al., 2018). Whether MSI-H
patients (i.e. patients with high instability) with stage II tumors should receive
adjuvant chemotherapy is still controversial (Nazemalhosseini Mojarad et al., 2016;
Saridaki, Souglakos, & Georgoulias, 2014).
Other biomarkers in blood, plasma and tissues
With extensive demand and ongoing research in the field of diagnostics, new
biomarkers for CRC are reported for clinical utility. At the same time, continuous
efforts are made to validate the prognostic/predictive value of already known
markers. These markers include genetic, epigenetic, and proteomic markers studied
biochemically as well as with histological and cell biological techniques utilizing
samples from tissues and body fluids. Due to the extensive amount of literature,
systematic review of the topic is not possible. As an example of the growing field
of markers are microRNA (miRNA) members of the non-coding RNA family. In
colorectal cancer, miRNA species may act as tumor suppressors or have oncogenic
effects as well as prognostic value (Yiu & Yiu, 2016).
Of the body fluids, blood is a valuable source of novel biomarkers, including
genetic material from CRC (such as cell-free circulating tumor DNA), various
protein markers, and circulating tumor cells. In the quest of easily accessible and
non-invasive tests, detection of biomarkers from blood, plasma and other body
fluids is of great potential value in the future (Fung et al., 2015; Hauptman &
Glavac, 2017; J. J. Jones et al., 2016; Nikolaou et al., 2018).
34
2.3 Apoptosis
Apoptosis is a form of programmed cell death enabling cellular homeostasis and
tissue organization. Two distinct pathways can trigger the complex process of
apoptosis via activation of caspases, leading to fragmentation of DNA with the help
of endonucleases. The process results in elimination of cells, often leaving cell
fragments in the form of small membrane-enclosed apoptotic bodies (Elmore,
2007).
2.3.1 Pathways of apoptosis
Cellular apoptosis may result via two main pathways, intrinsic and extrinsic
pathway. The intrinsic pathway is triggered by DNA damage or as a result of
endoplasmic reticulum stress. In this pathway, mitochondrial disturbance or
detachment of cells from the extracellular matrix induces a direct cascade of events,
including activation of activator BH3 proteins. These proteins promote Bax-Bak
oligomerization, permeabilization of mitochondrial membrane, and release of
cytochrome C from the mitochondrial pores into cytosol. These proteins form the
apoptosome complex leading to caspase activation and cell death. On the other
hand, sensitizer BH3 proteins can also indirectly activate the pathway by
counteracting the anti-apoptotic functions of Bcl-2 protein, leading to Bax-Bak
oligomerization and caspase-activated cell death (Jin & El-Deiry, 2005; Paoli,
Giannoni, & Chiarugi, 2013).
Another route, an alternative to the sequential activation of caspase-mediated
cellular apoptosis, is the extrinsic pathway initiated by ligand binding to death
receptor (member of TNF superfamily). The binding leads to formation of death-
inducing signaling complex (DISC) and activation of caspase-8. Alternately,
extrinsic and intrinsic pathways may link via caspase-8 activation mediated Bid
cleavage and activation resulting in apoptotic cascade (Figure 5) (Paoli et al., 2013).
35
Fig. 5. Schematic summary of the main apoptosis pathways.
2.3.2 Anoikis
Anoikis is a form of programmed cell death induced by loss of attachment of
cells to an appropriate matrix (Frisch & Francis, 1994). Anoikis contributes to
36
developmental processes such as hollowing of the glands and the involution
process and is often disturbed in cancer. Anoikis ensures elimination of misplaced
for development of metastasis (Gilmore, 2005). Both the intrinsic and extrinsic
apoptosis pathway are involved in the initiation and execution of anoikis (Paoli,
Giannoni, & Chiarugi, 2013). Furthermore, during anoikis, death signal receptor
activity may be modified by interaction with regulatory factors, such as their
known ligands promoting the progression of anoikis. (Bunek, Kamarajan, &
Kapila, 2011; Laguinge et al., 2008; Paoli et al., 2013).
2.4 Mechanism of anoikis resistance
After detachment of malignant cells from their original location, inhibition of
anoikis is an essential mechanism for the formation of metastases. Alterations in
cell death mechanism, faulty integrin signaling or epithelial-mesenchymal
transition (EMT) may result in anchorage-independent survival of tumor cells (Y.
N. Kim, Koo, Sung, Yun, & Kim, 2012; Paoli et al., 2013).
2.4.1 Integrin signaling and cell survival
Integrins are main mediators of anoikis, as these cell surface receptors support anti-
apoptotic and pro-survival signaling when associated with relevant matrix proteins.
In adherent cells, anoikis is inhibited by specific integrin activation and
downstream signaling mediators including integrin linked kinase (ILK), non-
receptor tyrosine kinase (Src), and focal adhesion kinases (FAK). The latter may
contribute to suppression of anoikis in undifferentiated cells as well as to EMT.
Unligated integrins in adherent cells may induce death receptor-independent
(caspase-mediated) cellular death. However, when integrins are ligated, the
integrin-caspase complex is disrupted, enabling cell survival (Stupack, Puente,
Boutsaboualoy, Storgard, & Cheresh, 2001). Integrins can be subdivided based on
their function and location. For instance, some integrins are essential for cell-cell
crosstalk while others contribute to adhesive forces between cells and ECM. The
most common and vital integrins in mammalian cells are fibronectin binding
integrin α5β1, collagen-binding integrin α2β1, and laminin-binding integrin
α3β1 receptors (Desgrosellier & Cheresh, 2010; Paoli et al., 2013; Vachon, 2011).
Basement membrane components maintain structural integrity, function in
tissues, and include type IV collagen, laminin, and other ECM components, as well
as growth factors. In addition to other receptors, integrins link epithelial cells to
37
basement membrane components. The absence of integrin signaling leads to
hyperactive survival and proliferation cascade. In addition, it leads to changed cell
shape as the shape is controlled in normal conditions by the cytoskeleton through
its connection with integrin at cell/ECM and cell/cell junctions.
Integrin α2β1 depletion is implicated in anoikis resistance of tumor cells via
Akt downregulation. Inhibition of α2β1 in melanoma cells grown on non-
adhesive surface leads to upregulation of p53, decreased Bcl-2, and increase in cell
cycle inhibitors, all of which are essential for the proliferation and survival of cells
(Kozlova, Morozevich, Ushakova, & Berman, 2019).
Interestingly, α3β1 is important for glandular phenotype in 3-D matrigel
cultures of intestinal epithelial cells. Lack of β1 Integrin instantly inhibits
glandular morphology along with disturbed cytoskeletal organization, whereas
integrin α3 induces glandular phenotype during the course of development of cyst
in 3-D environment (Zhang, Cromwell, Kunjummen, Yee, & Garcia-Aguilar, 2003).
2.4.2 Cell-cell contacts
Intercellular contacts play a key role in establishing many cellular functions
including proliferation, survival and apoptosis, to maintain tissue homeostasis.
These contacts enable transport of signals and factors to maintain exchange and
normal function. Actin and tubulin polymers responsible for organizing
cytoplasmic organelles, define cell polarity and intact intracellular
compartmentalization in epithelial cells. They determine cell shape and polarity
and promote stability in contact between cells or with ECM via cadherins and
integrins (Hall, 2009).
Cell-cell contact is supported by the adherens junctions located on the lateral
sides of the cells. These junctions provide plasticity and adhesion to cell groups,
allowing tolerance to mechanical stress along with supporting intercellular
transport ions, enzymes and other molecules. Cadherins are essential components
of adherens junctions and are involved in the control of tumor growth (Delva &
Kowalczyk, 2009). A cadherin type identified in epithelial cells is termed E-
Cadherin. It’s decreased expression associates with cancer metastasis and is one of
the hallmarks of EMT (Kourtidis, Lu, Pence, & Anastasiadis, 2017).
Desmosomes employ cadherin binding to intermediate filaments such as
keratins providing mechanical resilience (Garcia, Nelson, & Chavez, 2018).
Hemidesmosomes have very different molecular organization and are structurally
dissimilar from desmosomes. Via conjugation to integrins, they form a link between
38
the cell and the ECM (Garcia et al., 2018; Green & Jones, 1996; J. C. Jones, Yokoo,
& Goldman, 1986). Tight junctions, on the other hand, line the apical part of the
lateral membranes and create a strong bond without any extracellular space to
attach to actin filament networks (Anderson & Van Itallie, 2009). Tight junctions
also regulate a tumor suppressor protein, Scribble, which is important for the
plasticity and function of the intestinal epithelium (Ivanov et al., 2010).
Along with integrins and growth factors, contact and communication between
cells are key in terms of survival and proliferation. Furthermore, this contact
between cells is supported by E-cadherins, and a loss of E-cadherin expression
therefore indicates a loss of cell-cell contact. Thus, in primary or metastatic cancer
cell populations, decreased E-cadherin expression is indicative of active anoikis
resistance-based survival (Fouquet et al., 2004; Hofmann et al., 2007; Taddei,
Giannoni, Fiaschi, & Chiarugi, 2012).
2.4.3 Activation of anti-apoptotic pathways
In cancers, several signaling players promote cell survival and proliferation, in turn
counteracting the induction of apoptosis. Activation of pro-survival signaling
pathways such as Ras-Raf-MEK-ERK and PI3K/Akt enable abnormal regulation
of growth factor receptor-based pro-survival and pro-proliferation signaling and
promotes anoikis resistance (Y. N. Kim et al., 2012). The roles of these signaling
cascades are well acknowledged in the establishment and progression of
malignancy. Furthermore, these pathways are known to be a potential mechanism
towards resistance to chemo, radiation or hormone therapy and may cause cellular
drug resistance (Knickelbein & Zhang, 2015; Saif & Chu, 2010).
RAS-RAF-ERK pathway
In normal condition, mitogen-activated protein kinases (MAPK) are regulated by
phosphatases and can function as tumor suppressor or pro-oncogenic signals, which
is determined by activated signal in the respective context/tissue or can depend on
the strength of the signal. The MAPK pathway is essential for human cell survival,
dissemination and drug resistance and interacts with several other pathways. DNA
damage and metabolic stress may trigger the pathway in conjunction with cellular
contact with the matrix, other cells or external growth factors. Mutations may occur
upstream at receptor (EGFR), transducer (RAS) or regulatory player level
(McCubrey et al., 2007). Post MAPK/ERK activation, ERK detaches from
39
cytoplasm and translocates to the nucleus for transcriptional regulation. The effects
of the pathway in a carcinogenic situation enables anoikis resistance and lead to
metastasis depending on the intensity, duration and localization of the signal
(McCubrey et al., 2007).
The MAPK/ERK pathway is very active during proliferation and invasion,
driving further cell proliferation, dissemination and survival. The pathway
activation can occur upstream at receptor level (receptor tyrosine kinase) or at
downstream targets such as PI3K, Src or RAS. It is rare for two mutations to occur
within the same tumor at once in the RAS/RAF/MEK/ERK pathway (McCubrey et
al., 2007).
PI3K/Akt Pathway
The PI3K pathway can be positively regulated by gain-of-function mutations of
PIK3CA gene whereas loss-of-function mutation triggers negative regulation of
PI3K. Alternatively, overexpression of receptor tyrosine kinase (RTK) or mutation
of downstream effector (e.g. Akt) can lead to activation of PI3K cascade.
Modulators of the pathway include hormones, vitamins, growth factors, integrin,
ras-dependent MAPK pathway, and intracellular calcium (Martini, De Santis,
Braccini, Gulluni, & Hirsch, 2014).
When growth factor binds to receptor tyrosine kinase, it recruits the P85
regulatory subunit to the intracellular part. This results in the formation of a dimer
with the p110 catalytic subunit, leading to subsequent enzymatic activation of PI3K
and generation of PIP3. (Osaki, Oshimura, & Ito, 2004). Negative regulators of
PI3K involve dephosphorylating of PI3K to inactive PIP2 form via phospholipid
phosphatases. The PI3K/Akt pathway is crucial for anoikis suppression mediated
cell survival and Phosphatase and tensin homolog (PTEN), tumor suppressor
frequently mutated in many human cancers and inducer of anoikis, negatively
regulate the PI3K/Akt pathway (Y. N. Kim et al., 2012). Additionally,
immunohistochemical studies have shown Akt upregulation in cancers and
association of phosphorylation of AKT at serine 473 with poor prognosis in many
cancer (Martini et al., 2014).
2.4.4 Apical-basal polarity aberration
Correct apical-basal polarity and mitotic division are essential for tissue integrity
and cellular homeostasis. Epithelial cells establish apical domain already at first
40
cell division between two daughter cells, and this apical domain is maintained
during the course of growth (Jaffe, Kaji, Durgan, & Hall, 2008). Cell division
control protein 42 homolog (Cdc42) is implicated in controlling mitotic spindle
orientation during cell division, and this process regulates epithelial cell
morphogenesis in 3-D cultures.
An aberration of such polarity may lead to uncontrolled cell division in random
direction. Epithelial cells connect apical junction proteins to actin filaments. Apical
junction complex formation enables epithelial phenotype and regulates gene
transcription via apical polarity proteins (Lelievre, 2010).
Nuclear localization of apical protein dictates cell-cell junctional integrity. A
disturbed AJC results in free movement, turning nuclear repressors to promoters,
which drives claudin-2 mediated colon tumorigenesis (Buchert et al., 2010;
Coradini, Casarsa, & Oriana, 2011). A study with mouse gut organoids showed that
tissue polarity was lost in the early stages; however, apical-basal polarity was
initially maintained and changed only during later stages (Fatehullah, Appleton, &
Nathke, 2013). Absence of some integrin receptor proteins has been shown to alter
apical-basal polarity in colon cancer cells resulting in mispositioning of the apical
domain and piling of cells upon proliferation (Zhang, Cromwell, Kunjummen, Yee,
& Garcia-Aguilar, 2003). When cells are attached to ECM, integrins play important
role in controlling anoikis by regulating cell-ECM crosstalk. In the absence of such
contact in detached cells, anoikis can be overcome by cytoskeletal rearrangements
with the help of inside-out mechanism aided by signaling molecules. (Guadamillas,
Cerezo, & Del Pozo, 2011). When cells detach due to stress, lack of integrin
partners or in the absence of matrix stiffness, the inside-out signal is induced to
control anoikis (Debnath, 2010). Not surprisingly, loss of cell polarity and anoikis
resistance have been implicated in the formation of solid carcinomas (Halaoui et
al., 2017; Leung & Brugge, 2012).
2.4.5 Survivin
Survivin is classified as the smallest member of the inhibitor of apoptosis (IAP)
family with Baculovirus IAP Repeat (BIR). Survivin is often upregulated in several
cancer types, yet its role in apoptosis in a stressed cell is not completely understood.
Furthermore, survivin is essential for chromosomal segregation during mitosis
(Altieri, 2008).
The localization of survivin in different cell compartments may deliver
different functions. For example, when expressed in nuclei, survivin implies cell
41
division (Gianani et al., 2001; Mita, Mita, Nawrocki, & Giles, 2008), whereas
cytoplasmic localization is associated with cytoprotective role (Stauber RH, Mann
W, & Knauer SK, 2007). In one study, cytoplasmic survivin levels were inversely
correlated with anoikis in colorectal cancer cell lines, suggesting a role in anoikis
resistance. In carcinoma specimens, high cytoplasmic survivin levels associated
with lymph node and distant metastasis, suggesting that cytoplasmic survivin is a
possible biomarker for metastatic disease (Hori et al., 2013).
2.4.6 Other factors
Epithelial-mesenchymal transition
EMT associates with several aspects of tumor progression, including increased
metastatic potential and anoikis resistance (Frisch, Schaller, & Cieply, 2013). A
combination of events and forces may contribute to disruption of epithelial tissue
organization and acquisition of EMT. EMT is vital for many processes such as
embryonic development, wound repair and tissue remodeling. Indicators of EMT
include loss of epithelial characteristics along with disturbed apical-basal polarity,
loose cell-cell contacts, and acquisition of mesenchymal phenotype, often detected
by mesenchymal markers such as vimentin and N-cadherin (Macara & McCaffrey,
2013).
Suppression of epithelial marker E-cadherin by the transcriptional suppressors
Slug and Snail is often associated with cancer progression and drug resistance in
CRC (Bolos et al., 2003; Vu & Datta, 2017). Along with EMT, a single carcinoma
cell transitioned to a mesenchymal phenotype and showing features resembling
those in the stem cells may enter into lymphatic or blood stream. At a suitable
ectopic site the cell can extravasate, colonize and form metastasis (Macara &
McCaffrey, 2013).
During active EMT, members of integrin families such as αvβ6 are detected at
the cell-ECM junction. Expression of αvβ6 and TGFβ are indicators of invasion
and poor prognosis (Bates & Mercurio, 2005). A recent report by Fessler and
colleagues showed that TGFβ can induce EMT in early serrated pathway lesions
with BRAF mutation, but not in conventional adenomas (Fessler et al., 2016).
EMT has also been extensively studied in circulating tumor cells (CTC) as
CTCs are shown to present mesenchymal phenotype complemented with
overexpression of EMT transcriptional factors (Zeb1, Snail and Slug). Cell surface
42
vimentin detection in CTC from blood of CRC patients is a promising biomarker
for EMT (Satelli et al., 2015).
Reactive oxygen species (ROS)
Solid tumors are often accompanied by oxidative stress and reactive oxygen species
(ROS) that elicit pro-survival signals in tumor cells. Anoikis resistance
accompanied by Ras-induced ERK and Akt activation occurs via ROS induced Src
activation with phosphorylation of epidermal growth factor receptors in ligand-
independent manner (Guadamillas, Cerezo, & Del Pozo, 2011; Y. N. Kim, Koo,
Sung, Yun, & Kim, 2012). However, Ras is not an absolute requirement for ROS-
activated ERK pathway because without any ligand, it can still induce activation of
a growth factor (PDGF) leading to Ras activation and increased ERK1/2 activity
(Y. N. Kim et al., 2012). Studies show that MEK inhibitors can block oxidative
stress-induced ERK activation by inactivating upstream targets (Tan & Chiu, 2013).
Hypoxia
Carcinomas are often comprised of areas with insufficient oxygen supply, which in
normal cells would lead to apoptosis. However, cancer cells acquire anoikis
resistance in hypoxic conditions. HIF-1α induction occurs in tumor cells during
hypoxia (Y. N. Kim et al., 2012) and it seems to promote anoikis resistance through
several mechanisms, including upregulation of integrin α5 (Rohwer et al., 2008),
modulation of autophagy, and activation of nuclear factor-κB (NFκB) (Paoli et
al., 2013). As an alternative to independent effects of HIF1α activation on anoikis
resistance, it is possible that oncogene-induced signaling aberrations lead to both
HIF pathway activation and simultaneous anoikis resistance through separate
mechanisms (Paoli et al., 2013).
2.5 Anoikis resistance in cancer
Anoikis resistance is a key feature enabling cancer cells to survive during formation
of metastasis. Anoikis resistance in cancer cells can be acquired in many ways
including disturbed apoptotic mechanisms, integrin disengagement and EMT.
During stress, induced by detachment of cells from neighboring cells or from ECM,
other survival mechanisms providing anoikis resistance may appear. For example,
autophagy, which can provide resistance to metabolic stress, may support tumor
43
growth by replenishing nutrient loss and increasing energy production. Another
mechanism is entosis, a non-phagocytic process in which a cell that has lost contact
with the ECM can invade into another cell. The host cell may either kill the
invading cell by lysosomal mechanisms or keep the cell alive and release it later.
Although this is a potential mechanism to avoid anoikis, there is so far no evidence
of its significance in the formation of metastasis (Guadamillas et al., 2011; Lugini
et al., 2006).
2.5.1 Anoikis resistance and formation of metastasis
Formation of metastasis involves many steps beginning with cancer cell
detachment from the primary site, followed by migration and survival within the
lymphatic or blood system, attachment, extravasation and invasion to the secondary
site, and finally, proliferation in the distant organ (Bates & Mercurio, 2005). For
survival, the detached cancer cell without any support or signaling from the matrix
must escape the natural defense system and anoikis (Y. N. Kim et al., 2012).
Without anoikis resistance, a detached cancer cell undergoes anoikis, preventing
colony formation elsewhere (Paoli et al., 2013).
Studies on circulating tumor cells support the importance of anoikis resistance
in the formation of metastasis. Human studies have shown that several anoikis
resistance mechanism are activated in circulating tumor cells (Strilic & Offermanns,
2017; Wang et al., 2018) while animal studies suggest that metastatic efficiency
correlates with the activation of anoikis resistance mechanisms (Strilic &
Offermanns, 2017).
2.5.2 Anoikis resistance and prognosis in carcinoma
There are no clinical studies showing a direct association between anoikis
resistance levels and outcome. The expression levels of some biomarkers
functionally associated with anoikis resistance have been assessed for prognostic
value (as shown in 2.6.2). For example, tumor buds show features consistent with
anoikis resistance (such as low apoptosis rate and low expression of caspase-3) and
associate with poor prognosis (Dawson et al., 2014).
44
2.6 Assessment and modeling of anoikis resistance
Anoikis resistance has been addressed by several in vitro cell culture methods. The
methods include culturing of cells in suspension, by plating them on anchorage-
resistant surfaces or by culturing cells in soft gel assays, and by measuring the
apoptosis rate of the cells. Assessment of dysregulated anoikis in gut
pathophysiology has been reported in detail (Vachon, 2018). A colorimetric method
was further developed to monitor anoikis resistance in ovarian cancer cells (He,
Chien, & Shridhar, 2013).
2.6.1 Anti-adhesion tests
Anoikis resistance assessment for single cancer cells or for cells in aggregates has
been performed by different anti-adhesion tests (J. L. Chen et al., 2017). One such
test involves culturing the cells at single cell confluency on anti-adhesive surfaces.
To obtain such a surface, one can coat the cell culture dish with material such as
Poly-HEMA-ethanol solution. This can be complemented by a hypoxic chamber or
by addition of specific substrates such as laminin or poly-L-lysine (Attwell,
Roskelley, & Dedhar, 2000; Bozzo et al., 2006).
Another rigorous and widely utilized method is coating culture plates with agar
solution and employment of colony forming assay. However, this method has
limitations, such as heat stress if the solution is too hot, as well as difficulties in
cell plating and cell retrieval (Borowicz et al., 2014).
2.6.2 3-D in vitro culture
Cell culture in 3-dimension (3-D) is a promising model that mimics several features
of in vivo conditions better compared to 2-dimensional culture (2-D) (Pereira,
Lechanteur, & Sarmento, 2018), including studies for drug permeability, invasion
and migration properties (N. Li et al., 2013; Pereira et al., 2018). 3-D cultures are
generated by growing cells in semisolid media composed of basement membrane
extracts containing laminin, and growth factors or collagen gel, or mix of both.
Hydrogels are another alternative employed for spheroid cultures (Dosh, Essa,
Jordan-Mahy, Sammon, & Le Maitre, 2017; Dosh, Jordan-Mahy, Sammon, & Le
Maitre, 2019).
When epithelial cells such as MDCK cells, MCF10A cells or Caco-2 cells
achieve polarization cue from laminin-rich media, they form well-polarized round
45
cysts with lumen formation at the center via clearing of cells through active anoikis
(Andrew & Ewald, 2010; N. Li et al., 2013). The cysts resemble glandular
structures in vivo (Magudia, Lahoz, & Hall, 2012; Makrodouli et al., 2011; Martin-
Belmonte et al., 2008; Zhang et al., 2003). Due to physiological resemblances to
normal intestinal epithelium, Caco-2 cells are commonly used for studies involving
epithelial transport and permeability (Anabazhagan et al., 2017; Liang et al., 2001).
Lumen formation in epithelial 3-D cysts occurs by either cavitation or hollowing.
Cavitation involves apoptosis of cells trapped within large cell clusters and their
eventual clearance into the lumen, and polarity acquisition occurs post proliferation
and cavitation (Debnath et al., 2002). Hollowing is a mechanism where lumen is
formed through exocytosis and separation of membrane. In this mechanism, cells
acquire apical-basal polarity and intercellular junctions form between the cells.
Released vacuoles then fuse at apical surfaces, forming a small lumen, which
subsequently expands by addition of apical membranes (Lubarsky & Krasnow,
2003; Martin-Belmonte et al., 2008).
2.6.3 Biomarkers associated with anoikis resistance
Several in vitro studies have dissected the regulation of anoikis resistance and found
putative key regulatory molecules. The prognostic value of these molecules has
been assessed in several carcinoma types, and association with poor prognosis has
been constantly shown. Some of these biomarkers and their prognostic/predictive
values are presented in Table 2.
46
Table 2. Biomarkers associated with anoikis resistance in cancer.
Biomarker Putative effect Prognosis References
BCLXL expression
maintains anoikis
resistance
unfavorable prognosis in
ovarian cancer
(Frankel, Rosen,
Filmus, & Kerbel,
2001)
miRNA 451
downregulation
enables anoikis resistance poor prognosis in non-small
cell lung cancer (NSCLC)
(Bian, Pan, Yang,
Wang, & De, 2011)
CD147 upregulation
acquisition of anoikis
resistance
Metastasis of hepatocellular
carcinoma cells
(Ke, Li, Dong, &
Chen, 2012)
RAD21 overexpression
anoikis resistance feature
not studied
poor prognosis in KRAS
mutant CRC
(Deb et al., 2014)
Sox2 expression
induces anoikis resistance
poor prognosis in colorectal
cancer with increased
metastatic capacity
(Lundberg et al.,
2014)
TrKB (Tyrosine kinase
receptor) overexpression
promotes anoikis
resistance
poor prognosis in colorectal
cancer
(Dawson et al.,
2015)
miR-181a
increases anoikis
resistance
poor prognosis in CRC
(Niu et al., 2016)
SNORA42 overexpression
increases anoikis
resistance
poor prognosis in colorectal
cancer with increased
metastatic capacity
(Okugawa et al.,
2017)
MiR10a upregulation
increases anoikis
resistance
poor prognosis in metastatic
breast cancer
(Liu et al., 2017)
NOX4 (NADPH oxidase 4)
overexpression
promotes anoikis
resistance
poor prognosis in CRC
critical for metastatic
progression of gastric
cancer
(Du et al., 2018)
CPT1A-mediated fatty
acid oxidation
increases anoikis
resistance
promotes colorectal cancer
cell metastasis
(Wang et al., 2018)
47
3 Aims of the study
The main aim of the present study was to adopt the concept of anoikis resistance to
histopathological analysis of CRC. For this aim, morphological and
immunohistochemical criteria for putative anoikis-resistant (AR) carcinoma cell
subpopulations were constructed, and an in vitro model was developed. We also
assessed the role of some potential biological mechanisms of anoikis resistance by
immunohistochemistry and by using anti-adhesion cell culture-based tests. Finally,
the clinical significance of the concept was assessed by evaluating the prognostic
significance of the amount of the putative AR subpopulations present within the
tumors.
The specific aims were the following:
I To identify and quantify putative AR tumor cell subpopulations in
histopathological colorectal cancer specimens and to analyze their prognostic
significance (I, II).
II To study the mechanisms behind anchorage-independent survival of AR
subpopulations in colorectal cancer cells in vitro and in tissues using patient
samples (I, II, III).
III To generate a 3-D in vitro model corresponding to the multicellular structures
of putative AR structures as seen in carcinoma tissue specimens (III).
48
49
4 Materials and Methods
4.1 Histopathology
4.1.1 Patients and tumors
Study I included a case series consisting of 59 samples of normal mucosa, 56 benign
polyps and 62 carcinomas (1986–1996; Cohort 1) collected from the Department of
Pathology, Oulu University Hospital (Table 3). We obtained a representative series of
serrated carcinomas (n = 30) and a comparable number of unselected conventional
carcinomas (n = 32) matched by gender, location, Dukes’ stage and WHO histological
grade. The research project was approved by the Ethical Council of Oulu University
Hospital (25/2002, 58/2005, 184/2009).
Study II included a prospectively recruited series of 149 CRC patients who had
signed a written informed consent to participate and had been operated on in Oulu
University Hospital during 2006–2010 (Cohort 2; Table 3). Out of 149 cases, 12
(8%) were excluded from the study due to insufficiency of the sample material
available, leaving 137 cases for the assessment of anoikis resistance. The research
project was approved by the Ethical Council of Oulu University Hospital (58/2005,
184/2009). The latter study included TMAs constructed previously (Vayrynen et
al., 2012).
For the colorectal carcinoma series (I, II), we obtained clinical data such as age,
gender, treatment, and recurrence, from the clinical records and questionnaires. The
Finnish Cancer Registry provided survival data with 60-month follow-up.
A total of 56 colorectal polyps and polyps adjacent to carcinoma were selected
to represent different types of polyps (I) including 21 CAs (tubular adenomas and
tubulovillous adenomas), 20 SAs, and 10 HPs. In addition, we also assessed 5
adenomas next to the cancer area in specimens collected during 2006–2010 (Table
4).
50
Table 3. Colorectal cancer cohorts in studies I and II
Variable Cohort 1 (n = 62) Cohort 2 (n = 147)
Age, mean (SD) 66.49 (11.65) 66.8 (11.19)
Gender, n (%)
Male
32 (51.6%)
80 (53.69%)
Female 30 (48.38%) 69 (46.30%)
Tumor location, n(%)
Proximal colon 31 (50.8%) 49 (32.8%)
Distal colon 13 (21.3%) 28 (18.7%)
Rectum 18 (29.03%) 72 (48.3%)
WHO grade, n (%)
G1 (well) 27 (44.2%) 21 (14.3%)
G2 (moderately) 25 (40.9%) 108 (72.4%)
G3 (high) 10 (16.1%) 20 (13.6%)
TNM stage, n (%)
Stage I 9 (14.7%) 27 (18.1%)
Stage II 27 (44.2%) 55 (36.9%)
Stage III 18 (29.03%) 44 (29.5%)
Stage IV 8 (13.1%) 22 (14.7%)
T class, n (%)
T 1 5 (3.35%)
T 2 29 (19.46%)
T 3 103 (69,1)
T 4 11 (7.38%)
Lymphatic invasion, n (%)
Yes 61 (44.06%)
No 85 (57.04%)
Infiltrating border, n (%)
Yes 43 (29.05%)
No 105 (70.94%)
Metastasis, n (%)
Yes 19 (12.9%)
No 129 (87.16%)
Cancer type, n (%)
Serrated 30 34 (22.81%)
Conventional 32 115 (77.18%)
In some cases, the following information was missing: Cancer stage (n = 1), T class (n = 1), lymphatic
invasion (n = 3), presence of infiltrating borders (n = 1), metastasis (n = 1).
51
Table 4. Colorectal polyps in study I
Lesion Type N (%) Mean age(range), years
Serrated polyps
35 (62.5%)
63 (45-85)
Sessile serrated adenomas (SSA) 20 (35.7%) 66 (45-81)
Hyperplastic polyps (HP)
Serrated adenomas adjacent to cancer
10 (17.85%)
5 (8.92%)
62 (48-85)
60 (47-72)
Conventional adenomas
Tubular adenomas (TA) and tubulovillous
adenomas (TVA)
Conventional adenomas adjacent to
cancer
21 (37.5%)
16 (28.57%)
5 (8.92 %)
67(45-81)
65 (45-81)
68 (54-77)
4.1.2 Histopathological analysis
Carcinomas and polyps were classified according to WHO 2010 criteria (Bosman
et al., 2010).
Hematoxylin-eosin stained sections from formalin-fixed, paraffin-embedded
specimens were used in studies I and II for stage and grade determination and for
classification of polyp carcinomas. In study II, a TMA was constructed and the
most optimal tumor blocks used for TMAs were selected based on hematoxylin-
eosin stained diagnostic slides. One to four cores of 3.0 mm diameter were
manually sampled from the tumor bulk region in each case (Paarnio et al., 2019).
Stage and Grade
Staging and grades of differentiation were determined by TNM 6 (Greene & Sobin,
2002) and WHO criteria (Bosman et al., 2010), respectively.
52
Recognition and quantitation of the putative AR carcinoma cell
subpopulations
For carcinoma cases, we identified carcinoma cell populations in contact with the
ECM or with stromal areas of the tumors, and cells without such contact. The first
subpopulation included cells of single-layered columnar epithelium and the
outermost layer of multilayered epithelium. The latter subpopulations were defined
as putative AR tumor cell subpopulations, and included cells in micropapillary
structures (MIPs), cribriform structures and solid structures as shown below. In
Study I, only MIPs were identified while in Study II, all three types of putative AR
subpopulations were identified.
Criteria for putative AR tumor cell subpopulations
1. Micropapillary structures. These are composed of piled cells, the minimum
thickness of the pile being one cell (at least one cell piled over the basal cell
layer). The lateral extent may be two or more cells. Basal cells have contact
with the ECM, and as they are in contact with the ECM or stromal areas, are
not included in the putative AR subpopulation.
2. Cribriform structures. Inner cells in confluent groups of cells at least four cells
thick with the innermost cells not forming solid sheets; instead, there are
scattered, seemingly empty, spaces without cells. The outermost cells have
contact with the ECM or stromal areas and are not included in the putative AR
subpopulation.
3. Solid islands. Inner cells in the groups of cells forming solid sheets, with a
minimum thickness of four cells (at least one cell should be without contact
with ECM or stromal area). The outermost cells have contact with the ECM or
stromal area and are not included in the putative AR subpopulation.
For quantitation of the putative AR tumor cell subpopulations (II) we first measured
the area occupied by the tumor in each TMA core representing tumor bulk by using
the virtual microscope software Imagescope (Leica Aperio, Germany). Then, each
occurrence of AR subpopulations was determined in each core and areal density
(structures/mm2) determined.
In the first study (cohort 1), we assessed cells in MIPs and cells with contact
to ECM or stromal areas (non-MIP cells) separately in tumor bulk and at the
invasive front area. In the second study (cohort 2), we studied all three AR
53
subpopulations (i.e. cribriform and solid structures) and cells in contact with ECM
or stromal areas (non-AR cells).
4.1.3 Immunohistochemical stainings
Immunohistochemical stainings were performed on 4 µm sections cut from
respective tumor tissue on Superfrost slides followed by de-paraffinization in
xylene and rehydration through graded alcohol. After rinsing with distilled water
and PBS-Tween, the slides were immunohistochemically stained for the respective
proteins using the reagents and methods described in Table 5. All staining protocols
comprised treatment of sections for antigen retrieval. This was done with Tris-
EDTA or citrate buffer in microwave oven at 800W for 2 min followed by 150W
for 15 min in respective buffers or with pepsin for 30 min at 37°C (Table 5). After
washes, the sections were incubated with primary antibodies as specified in Table
5. Bound antibodies were detected with polymer-based detection reagents (Table 5)
using diaminobenzidine (DAB) as a color reagent. The sections were
counterstained with Hematoxylin and cover-slipped.
4.1.4 Immunohistochemical analysis
Staining patterns were assessed separately in the putative AR subpopulations, including
suprabasal cells of the MIPs (I and II), inner cells of cribriform and solid structures
(II) if present, and tumor cell populations in contact with the ECM or stromal areas (I,
II).
In the first study (I), we assessed survivin expression separately in the cytoplasm
and nucleus. Both the percentage of positively stained cells (0–100%) and intensity of
staining (negative: 0; weak: 1; moderate: 2; strong: 3) were recorded. Due to absence
of significant variation in the intensity of staining, only proportion of positively stained
cells was used for this study. Proliferation and apoptosis indexes were based on the
percentage of cells with positive nuclear Ki-67 staining and cytoplasmic cleaved
keratin-18 (M30) staining, respectively. The scoring was performed manually by
two independent observers blinded to clinical and pathological information. For
each polyp case, the superficial half and deep half of the lesion were scored
separately, and in carcinomas, the invasive front and bulk were scored separately.
For each case, a minimum of five of each subpopulation types was evaluated. Cases
with more than 30% disagreement between evaluators were evaluated jointly and
54
an agreement score was determined. For other cases, the average values of the
immunohistochemistry scores from both observers were used for statistical analysis.
Table 5. Details of immunohistochemical staining methods
Antigen Antigen
retrieval
Antibody Clone Manufacturer Dilution Incubation
time
Detection Paper
Survivin Citrate
buffer
Rabbit
polyclonal
Abcam469 Abcam,
Cambridge, UK
1:1000 30 min Envision I
Ki67 Tris-EDTA Mouse
monoclonal
NCL-Ki67-
MM1
Leica
Biosystems,
UK
1:50 30 min Envision I, II
M30 Tris-EDTA Mouse
monoclonal
M30
Cytodeath
Enzo Life
Sciences,
Lausen,
Switzerland
1:1000 30 min Envision I, II
Collagen
IV
0.4%
Pepsin
Monoclonal
mouse anti-
human
CIV 22 Dako,
Copenhagen,
Denmark
1:50 1 h Ultravision
Large
Volume
Detection
system TP-
125-HL
II
Laminin Leica Bond
Epitope
Retrieval
Solution 1
anti-
LAMC1
Atlas
Antibodies,
Stockholm,
Sweden
1:150 2h Leica Bond
Polymer
Refine
detection kit
DS 9800
II
The second study (II) involved assessment of Ki-67 stained slides, scanned with
Leica Aperio microscope scanner (Leica Biosystems, Nussloch, Germany) by using
the automated digital image analysis platform QuPath (Bankhead et al., 2017). The
putative AR cell subpopulations and tumor cells in contact with ECM or stromal
areas were identified and annotated. We aimed to annotate at minimum 10
subpopulations of each type. This was followed by image analysis workflow
composed of TMA dearraying, cell segmentation, identification, and counting of
positive and negative tumor cells in each annotated area. Mean proportion (%) of
Ki-67 positive cells for each tumor cell subpopulation was determined for each case.
For the assessment of interobserver agreement, a pilot series of ten cases was
studied by three observers. Otherwise, the assessment was shared by three
investigators. Apoptosis index assessment was carried out with scanned sections
stained for M30 by using the Aperio ImageScope program. Positive and negative
55
cells were manually counted from representative areas of each of the putative AR
subpopulation types and similarly from the cell populations with ECM contact. For
M30, one investigator (MP) carried out the initial analysis and an expert pathologist
(TJK) contributed to evaluation of cases with inconclusive staining patterns.
To assess the presence of ECM protein immunoreactivity within the putative
AR tumor cell groups (II), virtual images of sections stained for laminin and type
IV collagen were analyzed using the Aperio ImageScope program, and extracellular
immunoreaction within MIPs, cribriform or solid structures was recorded as
positive or negative. One investigator (MP) performed the assessment, and cases
with inconclusive staining patterns were assessed together with a pathologist (TJK),
who also analyzed a random subset of 30 cases.
4.2 In vitro experiments
We used Caco-2 colon cancer cells known to form well-polarized cysts when
cultured in Matrigel to generate an in vitro 3-D cell culture model for anoikis-
resistant structures.
4.2.1 Cell culture, staining and imaging
We generated Caco-2 cell lines with KRAS G12V and BRAF V600E mutations by
retroviral transfection at the Biocenter Viral Core Facility, Oulu, Finland. Prof. Alan
Hall (Sloan Kettering Institute, New York, USA) kindly gifted us plasmids with
GFP-tagged KRAS G12V and BRAF V600E mutations (Magudia et al., 2012).
Generation of cell lines, assessment of anoikis resistance by anchorage independent
assay, and performance of 3-D cultures is summarized in Table 6, and the reagents
used in these assays in Table 7.
4.2.2 Image collection and analysis
For live cell imaging, Zeiss Cell Observer Spinning Disk confocal microscope set
at 37°C was used. We collected images with 0.6 um step size using 40X objective
and excitation wavelengths of 405 nm, EC Plan NeoFluar 40X/0.75 DIC air
objective and BP 450/50nm (blue) emission filters. We collected images from 5–
15 cysts from each sample using spinning disk confocal microscope and each
experiment was repeated three times.
56
Table 6. In vitro cell manipulation and culture methods
Experiments
Generation of mutated cell lines
Retrovirus production with plasmids PQCXIP-GFP, pQCXIP-KRAS-GFP, pQCFLAP-
BRAF-GFP.
Transfection by Lipofectamine 2000.
Enhancement of viral titer by ultracentrifugation.
Infections to Caco-2 cells with respective retroviruses.
Selection of transfected cells:
Antibiotic selection for 2 days-Caco-2 control and Caco-2 KRAS
cells by Puromycin (4 ug/mL) and for Caco-2 BRAF cells by
G418 (0.8 mg/mL)
Sorting of GFP-positive clones by flow cytometry based sorting
Anchorage independent assay
-Anti-adhesion plate preparations: Poly-HEMA-ethanol solution (0.5 g Poly-HEMA /25
mL 95% Ethanol) plated to 10 cm bacterial cell culture dish.
- Cells at single cell suspension were plated on each 10 cm poly-HEMA coated dish
and cultured at 37°C for 24 and 48 hours, respectively.
- Anoikis-resistant (non-apoptotic) subpopulations were determined with Annexin V
flow cytometric assay with Annexin-negative cell population representing living cells.
3D culture
- 70,000 cells per well were plated on pre-coated (80% matrigel + 20% collagen I)
4-well chambered slides, grown for 10 days, and finally fixed and stained.
- Cultures for live imaging: 10,000 cells were plated on pre-coated (80% matrigel +
20% collagen I) 35 mm glass bottom well dish.
- To provide non-stressed cells for imaging, 3 dishes were initially plated with each cell
line simultaneously. One dish was imaged for 3 days, followed by the second dish for
the next 3 days and third dish for the last four days.
57
Table 7. Cell visualization and characterization methods
Experiment Dye Concentration/
dilution
Incubation
time
Manufacturer Detection Analysis
program
3-D culture
(Live
imaging)
Hoechst,
CellMask TM
plasma
membrane
stain
1:1000 30 min Thermo
Scientific
Zeiss cell
observer
spinning
disk
confocal
microscope
Hygen Pro
Zen
Fixed 10-
day old 3-D
structures
TRITC-
phalloidin
1:10 1 h Invitrogen Olympus
flow-view
confocal
microscope
Zen 2012
Fixed 10-
day old 3-D
structures
Dapi 1:1000 1 h Invitrogen Olympus
flow-view
confocal
microscope
Zen 2012
Anchorage
independent
assay
Annexin V 500 5ul/
100 ul cells
15 min BD
Biosciences
BD LSR
Fortessa
FACS diva
version 7.2
FlowJo X
Cell cycle
phase
estimation
ReadiDropTM
Propidium
Iodide
a few drops/
100 ul cells
15 min Bio-RAD BD LSR
Fortessa
FACS diva
version 7.2
FlowJo X
We viewed fixed 3-D culture specimens with Olympus Flow-view confocal
microscope and collected z-stack images using UPLSAPO 60x/1.35 oil immersion
objective. The excitation wavelengths of 405 and 543 nm and appropriate emission
filters were used for dapi and TRITC-phalloidin, respectively.
3-D cell growths were classified as cysts if they had an outer wall formed by a
single layer of cells and had a lumen without cells or cell debris. Structures filled
completely or partially with cells without a clear lumen as present in cysts, were
identified as solid growth or filled structures. We manually quantified the structures
using 20X objective, classifying and counting 145–212 structures from the fixed 3-
D specimens. A minimum of three independent experiments was performed and the
average proportion was used for graphical representation.
58
Fig. 6. Embedding of 3-D cultures in paraffin adaptation from (Pinto et al., 2011)
4.2.3 Paraffin embedding of 3-D cultures
3-D cultures were generated similarly as for fixed 3-D specimens for 8 days and
transferred to agarose, fixed and embedded in paraffin (Figure 6).
4.2.4 Protein expression analysis
We sorted annexin-negative cells with flow cytometry (BD FACS Aria) and lysed
them by sonication in 1 ml of radio immunoprecipitation assay (RIPA) buffer
59
(consisting of 50 mM Tris-HCL (pH 7.4), 150 mM NaCl, 4 mM EDTA, 1% Nonidet
NP-40 and 0.1% SDS in 200 mL dH2O) with a cocktail of proteinase inhibitors.
Lysates were incubated on ice for 30 min with vortexing every 5 min and cleared
by centrifugation (10,000g, 2min, +4°C). We measured protein concentration with
Bradford Protein assay (Bio-Rad). For western blot analysis, equal amounts (20 ug)
of protein samples were separated on 15% SDS-PAGE and electro-blotted to
nitrocellulose membrane (2 h). We blocked the membrane in 5% skim milk in TBS-
Tween buffer (1 h) followed by washes in 1X TBS-tween buffer, incubated with
primary antibody [Bim rabbit mAb (C34C5, Cell Signaling Technology, USA),
1:1,000; Tubulin mouse mAb (MS-719-P1, Neomarkers, Fremont, CA), 1:5,000;
rabbit polyclonal anti GFP (Ab11122, Invitrogen, UK), 1:1,000 and mouse
monoclonal anti-BRAFV600E (VE1, Roche Diagnostics, Indianapolis, IN, USA),
1:1,000] overnight at +4°C. After washing, the membranes were incubated in HRP
conjugated secondary antibody [goat anti-rabbit IgG (sc-2004, Santa Cruz
Biotechnology, Dallas, USA), 1:5,000; goat anti-mouse IgG (sc2005), Santa Cruz
Biotechnology, Dallas, USA) 1:10,000 for 1.5 h. Antibodies were detected by
incubating the membranes in a detection solution comprising 250 mM Luminol, 90
mM Cumoric and 3 uL H2O2 in 10 mL 0.1 M Tris-HCL (pH 8.3) for 2 min and
chemiluminescence was detected using Fuji-Las-3000 system. Bands were
quantified for presentation with Quantity One (Bio-Rad, Hercules, CA, USA)
software.
4.3 Statistical analyses
IBM SPSS 22 and 25 (IBM Corp., Armonk, NY, USA) software was used for
statistical analyses (Table 8). Reproducibility of the assessments was evaluated by
using interclass correlation coefficient (ICC) based on a mean-rating (k = 2),
absolute-agreement, two-way mixed-effects model. For all the tests, two-tailed
exact p values less than 0.05 were considered statistically significant.
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Table 8. Statistical methods used
Assessment Test
To assess different parts of same lesion Wilcoxon matched pair test
To assess association of two independent variables Mann-Whitney test
To assess association of three or more independent
variables
To assess correlation between
different AR structures
To assess association to cancer-specific survival or
disease-free survival
To test for independent prognostic factors
To find cutoff value discriminating survival and non-survival
to assess capacity of AR quantification
To compare cell lineages for anoikis resistance and 3-D
growth patterns and for protein expression
Kruskal-Wallis test
Spearman correlation test
Kaplan-Meir curve method or
Hazard plot
Cox regression test: univariate and bivariate
ROC curve
ANOVA (Tukey for post hoc comparisons)
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5 Results
5.1 Identification and quantification of putative AR structures in
carcinomas (I, II)
We assessed the numbers of putative AR structures: MIPs, cribriform and solid
structures from Cohort 2 material with image analysis techniques as described in
Materials and Methods.
From a total of 137 cases analyzed, 126 (92.0%) cases showed at least one MIP
structure, 125 (91.2%) a cribriform structure, and 121 (88.3%) a solid structure,
respectively. Furthermore, 104 (75.9%) cases presented all three types of the
putative AR subpopulations, 27 (18.7%) cases showed at least two structures, and
6 cases (4.4%) presented only one subtype with solid structures alone in four cases
and MIPs in two cases.
Fig. 7. The figure panel shows collagen IV staining in cribriform (left), solid (center) and
MIP (right) structures in colorectal carcinoma. Positive staining (brown) can be seen in
the interface of tumor cell islands and stroma, surrounding some of the spindle-shaped
stromal cells, and in the walls of blood vessels. No positive staining is present within
the putative AR structures.
We found that areal densities (structures/mm2) of each putative AR subpopulation
type correlated with the total areal density of all AR structures (II; p < 0.001). The
areal density of cribriform structures correlated positively with the densities of
solid structures (II; p = 0.017; rho = 0.204) whereas MIP areal density correlated
inversely with that of solid structures (II; p = 0.006; rho = 0.234).
62
5.2 Immunohistochemical assessment of ECM proteins, apoptosis
and proliferation rates and survivin expression
5.2.1 Expression of type IV collagen and laminin (II)
We assessed the presence of ECM proteins collagen IV and laminin in the tumors
(Cohort 2; II). Positive staining, often discontinuous, was seen along the outer
borders of cancer cell islands of all subtypes (Figure 7). However, putative AR
subpopulations in MIPs, cribriform and solid structures showed no extracellular
positivity, suggesting the absence of organized ECM within these structures (Figure
7).
5.2.2 Proliferation and Apoptosis indexes (I, II)
Proliferation index (PI) and apoptosis index (AI) were based on the counts of Ki-
67 and M30 positive cells (I: Figure 2), respectively. As expected, in normal
colorectal mucosa (I) epithelial cells in the upper half of the crypts showed lower
PI (p < 0.001) and higher AI as compared with lower half (p < 0.001).
In carcinomas (I, II) AI and PI were separately determined in different tumor
cell subpopulations, including cells in contact with the ECM, and different
populations of the putative AR cells without such contact (putative AR structures,
Table 3). In Study I, only MIPs were studied whereas in Study II, all AR
subpopulations were analyzed. Additionally, MIPs were analyzed in polyps (I). AI
was lower in all three putative AR structures as compared with cells in contact with
ECM (Table 9A and 9B, p < 0.001; II: Figure 4), suggesting that these
subpopulations are resistant to anoikis. Proliferation rates were mostly similar in
different subpopulations. Only suprabasal cells in the MIPs presented lower
proliferation rates than the tumor cells with ECM contact (Table 9A and 9B) (I, II).
Serrated and conventional colorectal carcinoma did not show any differences for
PI or AI in MIP and non-MIP epithelium (I, II). When comparing precursor lesion
subtypes, PI and AI rates in MIPs in serrated polyps (I, Table II; PI, 25 (0-75); AI, 0 (0-
4)) were significantly lower than in conventional adenomas (PI, 38 (10-75), p = 0.045;
AI, 1 (0-3), p = 0.045). A similar difference was seen in non-MIP epithelium with lower
PI in SPP than CA (SPP, 28 (7-50); CA, 42 (16-52), p = 0.002), but for AI no significant
difference emerged. In addition, when precursor lesions (combined) were compared to
malignant ones (combined) AI was lower in non-MIP epithelium of polyps compared,
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but this difference was not present for MIPs in the compared lesion types (Figure 8).
Table 9 A. Distribution of AI and PI in different tumor cell subpopulations in CRC. AI and
PI represent proportion (%) of cells positive for M30 and Ki-67, respectively.
Tumor subpopulations AI (%) median (range) PI (%) median (range)
MIP 2.6 (0-15.23) 41 (0-100)
Cribriform 6.40 (0.43-35.40) 61 (0-100)
Solid 2.59 (0-11.92) 63.5 (0-100)
Total AR 4.57 (1.3-9.07) 56.38 (1-100)
Non-AR cells 12 (2.50- 54.31) 65 (1-100)
Table 9 B. Statistical comparison of PI and AI in different subpopulations in CRC (refers
to Table 9 A).
Compared subpopulations AI (p values) PI (p values)
Putative AR vs. non-AR cells
MIP vs. non-AR cells
p < 0.001 [<]
p < 0.001 [<]
Cribriform vs. non-AR cells p < 0.001 [<] p = 0.287 [=]
Solid AR vs. non-AR cells p <0.001 [<] p = 0.875 [=]
AR subpopulation comparison
MIP vs. Cribriform p < 0.001 [<] p < 0.001 [<]
MIP vs. Solid p = 0.842 [=] p = 0.001 [<]
Cribriform vs. Solid p < 0.001 [>] p = 0.718 [=]
<, > or = in brackets indicates apoptosis or proliferation rates compared between subpopulations
Total AR indicates sum of areal densities of MIPs, cribriform and solid structures.
Non-AR cells refer to tumor cells in contact with ECM or stromal areas.
5.2.3 Survivin expression (I)
We assessed nuclear and cytoplasmic survivin expression in the upper and lower
halves of normal colon mucosa (I). Nuclear survivin staining was higher
(proportion of positively stained cells) in the lower half of the crypts (p < 0.001)
whereas cytoplasmic survivin expression was significantly higher in the upper half (p
< 0.001) (I: Figure 2).
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Fig. 8. Proliferation and apoptosis indexes in polyps and cancers. Significant differences
are represented by p-values in the graph. The symbols (asterisk) are outliers.
Nuclear survivin expression in MIP structures was significantly higher in cancers
than in polyps (p < 0.001, Figure 9) but there was no such difference in non-MIP
epithelium. In addition, survivin expression in MIPs was lower than in non-MIP
65
Fig. 9. Survivin expression in polyps and cancers. Significant differences between MIP and
non-MIP epithelium are represented by p-values in the graph.
epithelium in both cancers (nuclear survivin, p = 0.026; cytoplasmic survivin, p =
0.012) and in polyps (nuclear survivin, p < 0.001; cytoplasmic survivin, p < 0.001;
Figure 9). In subgroup analysis, polyp subtypes showed similarly lower survivin
66
expression in MIPs than in the non-MIP epithelium [nuclear survivin, SPP, p <
0.001; CA, p < 0.001; cytoplasmic survivin: SPP, p < 0.001; CA, p < 0.001].
5.3 Areal density of putative AR structures and their association
with clinical features of carcinomas (II)
5.3.1 Putative AR structures and clinicopathological features
Low tumor grade associated with high areal density of MIPs (II, Table 3; p = 0.005)
and high tumor grade with that of solid structures (p = 0.029). ). Although BRAF
or KRAS mutations did not associate with total areal density of AR structures, KRAS
mutation associated significantly with low abundance of solid structures (p = 0.048)
whereas BRAF mutation tended to associate with solid structures (p = 0.102). MIPs,
cribriform, solid structures, independently or combined, did not associate with
tumor stage (II: Table 3). No association was seen between putative AR structures
and tumor type (serrated vs. conventional).
5.3.2 Putative AR structures associate with prognosis (II)
We determined cutoff values for low and high areal densities of different AR types
and their sum by ROC curve analysis. Areal densities of MIPs did not associate
with prognosis in the whole case series. However, in subgroup analysis comprised
of only stage I and II tumors cases there was a trend for association of high MIP
areal density with worse survival (p = 0.058). Interestingly, areal densities of
cribriform structures associated with poor cancer-specific survival (CSS, p = 0.004,
II: Figure 5) and poor disease-free survival (DFS; p=0.015, II: Supplementary
figure 1). Similarly, for solid structures, areal density presented a strong association
with worse CSS (p = 0.017, II: Figure 5); however, the association was not
significant for DFS. High total putative AR areal density showed a significant
association with poor prognosis (CSS; p = 0.001; II, Figure 5; Figure 10).
67
Fig. 10. Hazard plot showing cancer survival (60 months; log rank) in patients (n = 138)
with high and low areal density (structure/mm2) of putative AR structures (total AR
count/mm2).
To investigate the independent prognostic value of areal densities of putative AR
structures, we used a multivariate analysis modification described by Kleinbaum
and Klein, since the number of cases in some subgroups was low (Kleinbaum &
Klein, 2012). Accordingly, we assessed prognostic value against one variable at a
time, and found that the total AR count based on MIP, cribriform and solid counts
was an independent prognostic factor when tested against several clinical features
such as age, location, stage, grade and others (II; Table 4). Such total putative AR
areal density was a stronger factor than the combined areal density of cribriform
and solid structures (II).
5.4 Effects of BRAF and KRAS mutations on anoikis resistance in
vitro (III)
5.4.1 Transfection of Caco-2 cells with mutant KRAS or BRAF genes
Caco-2 colorectal carcinoma cells natively not having KRAS or BRAF mutations
were transfected with retroviral vectors encoding GFP-tagged KRAS G12V, BRAF
V600E or GFP only as a control (III). The success of the transfection was confirmed
68
by flow cytometric detection of GFP and by showing the presence of mutant BRAF
protein and GFP-KRAS composite protein by western blotting (III; Supplementary
Figure 1). Control cells, transfected with GFP, were similarly shown to express GFP
(III).
5.4.2 Anoikis resistance assessment with Annexin V test
To assess if mutations have any effect on anchorage-independent survival ability of
colon cancer cells, we cultured control Caco-2 cells and Caco-2 cells transfected
with mutated KRAS or BRAF oncogenes on poor attachment (poly-HEMA coated)
surfaces (III). Annexin V500 FACS assay showed a significantly lower apoptosis
rate in Caco-2 KRAS and Caco-2 BRAF cells when compared to control cells at 24
h (Figure 11). On the contrary, cells grown in suspension for 48 h presented higher
apoptosis rates independent of the vector used (Figure 11).
Fig. 11. Proportions of Annexin V negative (non-apoptotic) cells among control Caco-2
cells and Caco-2 cells transfected with KRAS G12V or BRAF V600E. Cells were cultured
in non-adhesion conditions for 24 h or 48 h.
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5.4.3 Cell cycle stage estimation in different Caco-2 cell forms
To assess the cell cycle phase of anoikis-resistant cell populations, we cultured
Caco-2 control cells and cells transfected with KRAS G12V or BRAF V600E
mutated oncogenes in suspension for 24 h and 48 h. Propidium iodide assay was
performed on fixed and permeabilized cells. At G0/G1 (pre-replicative) phase,
Caco-2 KRAS cells showed a strong peak with the highest proportion of cells,
followed by Caco-2 BRAF cells, Caco-2 control cells showing clearly the lowest
proportion at both time points, at 24 h and 48 h (Figure 12). In contrast, S-phase
fractions in Caco-2 KRAS, Caco-2 BRAF, and Caco-2 control cells were similar at
both time points (Figures 12 and 13).
Fig. 12. Cell cycle phase plots from annexin-negative sorted Caco-2 control cells (left),
Caco-2 cells transfected with mutated KRAS (center), and Caco-2 cells transfected with
mutated BRAF (right) oncogene. The upper row represents results from 24 h
suspension culture and the lower row results from 48 h suspension cultures.
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Fig.13. Proportions of anoikis-resistant cells in different cell cycle phases in anchorage-
independent assays (24 h). Readings for native Caco-2 cells are based on one
experiment, and those for Caco-2 KRAS and Caco-2 BRAF are from three identical
experiments. Median (horizontal line), interquartile range (box) and range are shown.
5.4.4 Bim expression in AR cells
To survey possible mechanisms behind anchorage-independent survival in annexin
negative sorted cells, we assessed the expression of Bim, a pro-apoptotic protein
and a member of BCL-2 family. Quite unexpectedly, based on three experimental
replicates, we found a trend for overexpression of Bim in the Caco-2 BRAF and
Caco-2 KRAS cell lysates when compared to Caco-2 control lysates but the
differences was not statistically significant (III; Figure 7).
5.5 3-D in vitro modeling of AR cell subpopulations
To study the effect of KRAS and BRAF mutations in multicellular glandular
formation in vitro we generated a 3-D model with Caco-2 colon cancer cells and
Caco-2 cells transfected with either KRAS G12V or BRAF V600E (III). For 3-D
cultures, we used a mixture of basement membrane extract (Matrigel) plus collagen
I gel and grew the respective cells in the mixture for 10 days.
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5.5.1 Live monitoring: evolution of 3-D structures
We followed the cells in the 3-D cultures by staining with DNA dye (Hoechst) (III).
Although such live imaging provided a close to normal environment for the cells,
the specimens were still prone to some toxicity induced by the dye after 3 days.
Therefore, cells were grown on three parallel sets and each set was only monitored
for a sequence of 3 to 4 days.
During the initial days, cells proliferated and formed round cell clusters
growing and expanding within the matrix, whereas later, i.e. post 8th day, most
Caco-2 control cells formed round cysts with epithelial cell lining around a fluid-
filled lumen (III; Figure 1). The structures formed by Caco-2 KRAS and Caco-2
BRAF cell lines were larger than those formed by the control cells. In addition,
some structures formed from Caco-2 KRAS cells were cysts like those in Caco-2
controls (III; Figure 2) with a clear lumen while others formed cystic structures
partially filled with cells. Finally, some cysts formed by Caco-2 KRAS cells
showed focal cell piling (Figure 14) or apoptotic cells in the luminal space adjacent
to the cyst wall. In contrast, Caco-2 BRAF cells dominantly formed solid structures
with cells filling up the lumen, resembling solid tumor cell clusters seen in some of
the clinical carcinoma specimens. Growth patterns were consistent in terms of cyst
formation or solid growth from early on and remained consistent after Day 7 in
culture for both control and mutated 3-D cultures (Figure 14).
5.5.2 Organization and polarization of Caco-2 cells in 3-D structures:
influence of KRAS and BRAF mutations
To understand the organization and polarization of cells in 3-D cultures, we imaged
10-day-old fixed cultures and stained the specimens for actin with TRITC-
phalloidin and dapi (III). We noted well-polarized 3-D cysts with regular apical-
basal polarity formed by control Caco-2 cells as indicated by regular apically
polarized localization of actin stress fibers (Figure 14). On the other hand, Caco-2
KRAS cells formed partially filled structures with irregular polarity of actin fibers
or structures with inverted cell polarity, with the apical surface pointing out of the
clusters (III: Figure 2). There was also irregularity in cell polarity present in the
piling cell clusters towards the luminal side. In contrast, Caco-2 BRAF cells
predominantly formed filled structures with irregular cell polarity as indicated by
irregular actin fibers between the cells within the clusters, but no clear inversion of
polarity (III).
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Since the cystic or solid growth patterns did not entirely relate to the cell
lineage, we quantitated growth patterns in the 10-day-old fixed culture specimens
at 20X magnification. The majority (about 70%) of the structures formed by the
Fig.14. 3-D cultures of conventional and modified Caco-2 cells assessed by different
techniques. A) Nuclear DNA was stained with Hoechst (blue) and Caco-2-control cells
and Caco-2 BRAF cells additionally stained with CellMask TM plasma membrane stain
(orange) to show actin filaments. B) Formalin-fixed cultures were sectioned and stained
with hematoxylin and eosin. In this particular experiment, only a few cyst-like structures
were found in paraffin blocks of Caco-2 BRAF cells. C) Formalin fixed cultures were
sectioned and stained with Ki-67. In this experiment Ki-67 staining show proliferating
cells in the growing cysts, images representing 3-D structures such as Caco-2 control
might appear solid but this could be outermost layer of the cyst. Scale bar represents
20 µm.
control Caco-2 cells were polarized cysts with occasional solid structures (Figure
15). In Caco-2 KRAS 3-D cultures, about half of the structures were solid and the
other half were like those observed in control Caco-2 cysts with occasional cell
73
piling. In contrast, the Caco-2 BRAF cultures consisted predominantly (> 80%) of
solid structures and these differences were found to be statistically significant
(Figure 15).
Fig. 15. Proportions (%) of filled (solid) structures of all multicellular clusters formed by
Caco-2 control cells (Caco-2 GFP cells) and Caco-2 cells transfected with KRAS G12V
or BRAF V600E. Cells were cultured for 10 days. About 145–212 structures/experiments
were quantified from fixed specimens. Mean proportions (SD) based on three
experiments are shown.
5.5.3 Paraffin embedment of 3-D cultures
Preservation of samples in paraffin and possibility for conventional
immunohistochemical assessment would yield advantage over the storage of 3-D
samples and their use in research. Therefore, we adapted a protocol by Pinto et al.
with some changes (Pinto et al., 2011) (III). We analyzed the specimens for
architectural differences with H&E stainings. Reasonably, the structures formed by
the respective cell lines were similar and well preserved, as noted earlier from fixed
or live cell imaging (Figure 14). In addition, the Ki-67 stainings showed functional
utility of immunohistochemical applications of these specimens (Figure 14).
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6 Discussion
By definition, anoikis is a form of cell death induced when cells lose contact with
the ECM (Gilmore, 2005), and resistance to anoikis is essential for cancer
metastasis (Wang et al., 2018). Anoikis resistance has direct links to poor prognosis,
as shown by prognostic marker reports functionally linked to anoikis resistance (F.
Chen et al., 2018; Dawson et al., 2015). However, so far it has only been possible
to evaluate anoikis resistance by using various anchorage-independent in vitro cell
cultures (Frisch & Francis, 1994). We aimed at identification and understanding of
anoikis resistance as a set of histopathological features by employing
histopathological tools and cell biology with 3-D modeling approaches. In addition,
the roles of some factors, including KRAS and BRAF mutations and anti-apoptotic
protein survivin in anoikis resistance were evaluated. The main hypothesis was that
a carcinoma cell’s ability to resist anoikis manifests as histopathologically
characteristic features. More specifically, we presumed that anoikis resistance
would allow generation of multicellular tumor cell clusters with cells surviving
without contact with the ECM. Such features have not been identified before by
using the anoikis resistance paradigm. However, they might have prognostic and
predictive value as anoikis resistance enables metastasis formation.
For the identification of putative anoikis-resistant (AR) subpopulations in
histopathological specimens, we searched for tumor cell subpopulations without
contact with the ECM, and then evaluated apoptosis rates in cell populations with
and without ECM contact. The absence of increased apoptosis rate in the latter
would imply the presence of anoikis resistance. With such a strategy, we were able
to identify subpopulations of tumor cells fulfilling the set criteria, and these
subpopulations were defined as putative AR populations. Supporting the validity
of the concept, high areal density of such subpopulations associated with adverse
prognosis in CRC.
To gain additional evidence to conceptualize the structural manifestations and
mechanistic information of anoikis resistance, we used genetically modified Caco-
2 cells. Transfection of the cells with mutated KRAS or BRAF oncogenes induced
anoikis resistance as assessed with a classical anchorage-independent survival test
(I), and in 3-D culture, oncogene transfection induced the formation of solid
clusters instead of crypts, suggestive of putative AR structures seen in
histopathology.
These observations potentially define new histopathological criteria with
prognostic value. If validated in large external cohorts, criteria based on a well-
76
defined biological paradigm, anoikis resistance, may provide clinically useful
prognostic and even predictive information. It is possible that such a paradigm can
be adopted to carcinomas of other organs as well.
6.1 Identification of putative AR subpopulations
For identification of putative AR subpopulations, we first spotted carcinoma cells
in contact with mesenchymal areas of the tumors and cells without such contact.
The latter included suprabasal cells of micropapillary structures (MIP) and inner
cells from cribriform and solid structures. The rationale for this was the reported
presence of basement membrane or interstitial collagens in the stromal interface.
Although many studies have evaluated the expression of basement membrane
proteins at the tumor stroma interface in CRC, there was lack of studies
commenting on the presence of intercellular basement membrane protein
expression within the clusters formed by carcinoma cells, such as between the inner
cells of solid or cribriform structures. Therefore, we used immunohistochemistry
to evaluate the presence of ECM proteins in these structures. Stainings for collagen
IV and laminin showed that although the tumor stroma interface encloses these
proteins, they are absent from regions between the cells of the putative AR
structures. We used M30 staining to access cellular apoptosis. M30 antibody binds
to the caspase-cleaved epitope of cytokeratin 18 and is confined to the cytoplasm
of apoptotic cells (Saigusa et al., 2014; West, Courtney, Poullis, & Leicester, 2009).
Our assessment showed decreased apoptosis rates in all putative AR structures as
compared with tumor cells in contact with mesenchymal areas. Additionally, MIPs,
a subpopulation in which we identified features supporting the presence of anoikis
resistance, also presented lower proliferation rates than cells in contact with ECM.
As non-dividing cells do not express Ki-67 antigen, lower PI could possibly be
indicative of features of quiescence in these cells.
In summary, we were able to identify subpopulations of carcinoma cells in
CRC characterized by the absence of ECM contact and showing decreased
apoptosis rate, and therefore representing putative AR cells. One should note that
all these subpopulations are multicellular clusters of cells and always next to tumor
cells in contact with the ECM. Based on our experience, identification of the
putative AR structures in tissue sections was straightforward, and by using image
analysis, it was convenient to define their areal density for quantification and
further analysis. For convenient and accurate quantification of the putative AR
subpopulation in histological sections, it might be possible to generate an
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automated image analysis system based on recognition of tumor cell islands and
their characteristics, which could provide faster means for histopathological
evaluation.
6.2 Putative AR structures and prognosis of carcinoma
With the aim to extend understanding of the biology and importance of putative AR
subpopulations, we assessed if the quantities of single AR subpopulation types or
total quantity of all AR subpopulation types associated with carcinoma prognosis.
We found that high areal density of both cribriform and solid structures shows an
independent association with poor prognosis. The sum of areal densities of all three
types of AR subpopulations showed the strongest association with poor prognosis.
Such associations are plausible considering the significance of anoikis resistance
in the formation of metastasis, and indirectly support the current concept of
evaluating anoikis resistance by histopathological analysis.
There are no previous prognostic studies in any human carcinoma type based
on the concept of histopathological evaluation of anoikis resistance. In CRC, only
few studies have assessed the prognostic value of histopathological features related
with the current concepts of putative AR subpopulations. Cribriform carcinoma is
a rare type of CRC (Lino-Silva et al., 2015) presenting with unspecified abundance
of cribriform structures and association with poor prognosis. This is consistent with
our finding of association between abundance of cribriform structures and poor
prognosis. Additionally, our results provide evidence that even lesser abundance of
cribriform structures not fulfilling the criteria of cribriform carcinoma may
associate with poor survival.
Solid structures, another putative AR structure type, were associated with high
conventional tumor grade (Bosman et al., 2010), as expected based on conventional
grading criteria. Solid structures as defined in our study may be partially analogous
to poorly differentiated clusters in the recent grading system by Ueno et al. (Ueno
et al., 2012). A marker of poor prognosis, poorly differentiated clusters were
defined to be solid clusters comprised of a minimum five cells and lacking any
glandular phenotype. Accordingly, larger poorly differentiated clusters might
contain cells without contact with ECM and thereby fulfill the current criteria of
putative AR cells in solid clusters. Ueno did not consider any biological
mechanisms for the prognostic effect of poorly differentiated clusters. Based on our
observations, anoikis resistance would be a plausible mechanism.
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MIPs showed no general association with prognosis. However, in grade 1 and
2 tumors, there was a trend (p = 0.058) for association with poor prognosis, and
interestingly, inclusion of MIP areal density into the total putative AR areal density
strengthened the association with poor prognosis. These findings suggest that MIPs
contribute to the prognostic effect of anoikis resistance. There are no previous
studies about prognostic effect of MIPs in CRC. In another non-invasive carcinoma,
ovarian borderline carcinoma, micropapillary architecture is associated with poor
prognosis (Hannibal et al., 2017).
We found both decreased proliferation rates and apoptosis rates in MIPs as
compared with cells in contact with the ECM, suggesting that these cells are at least
partly quiescent. Anoikis resistance and quiescence are potential cell escape
mechanisms; together, they may interfere with responses to chemotherapy and
radiotherapy (Kyle, Baker, & Minchinton, 2012; Masunaga & Ono, 2002).
Our study indicates that the current concept of histopathological assessment of
anoikis resistance provides new, biologically plausible criteria and a new system
for prognostic assessment in CRC. However, putative AR subpopulations
including MIPs should be explored further to understand their biology. Prognostic
value should be confirmed based on independent case series. In addition, being
functionally distinct subpopulations, the possible roles of the putative AR
populations as predictive markers warrant exploring. Finally, as tumor cell
subpopulations analogous to the current putative AR cells are found the most in
many other carcinoma types, it may be possible to expand the concept to those
malignancies as well.
6.3 Survivin, an anti-apoptotic protein influencing tumorigenesis
Survivin is a classified member of the inhibitor of apoptosis family and possesses
dual function in both proliferation and apoptosis (Altieri, 2008; Mita et al., 2008).
Although survivin is a short-lived protein with T1/2 of 30 minutes, it is essential for
chromosomal segregation and present in all stages of mitosis (Altieri, 2008). The
physiological role of survivin in colorectal mucosa has been a matter of controversy
(ref see II). Our detailed analysis of the subcellular localization of survivin in
normal colorectal mucosa showed heavy nuclear survivin expression in the cells
located in basal parts of the crypts of normal colon mucosa, indicating survivin’s
role in cell proliferation (Gianani et al., 2001; Mita et al., 2008). There is strong
cytoplasmic survivin expression in the cells in the superficial parts of crypt
epithelium, a location in the colon where cells mature, and eventually undergo
79
apoptosis and shed into lumen. This observation could indicate a pro-apoptotic role
of survivin contrary to the cyto-protective role decoded when survivin is localized
in the cytoplasm (Stauber, Mann, & Knauer, 2007). In summary, our results suggest
that in normal colorectal epithelium, survivin plays a role in both proliferation and
apoptosis depending on its subcellular location in cells.
Based on the suggested anti-apoptotic role of survivin (Mita et al., 2008) we
were interested to analyze its role in MIPs, a type of putative AR subpopulation.
Both nuclear and cytoplasmic expression were lower in the cells of MIPs as
compared with other tumor cells. Survivin expression, however, did not correlate
with apoptosis or proliferation rates in the tumor subpopulation types, and
accordingly, the functional role of survivin in anoikis resistance remains
speculative and warrants additional studies.
In line with earlier reports (Parfitt & Driman, 2007), we observed a bottom-
heavy staining pattern of nuclear survivin in serrated polyps whereas in
conventional adenomas, survivin expression was most abundant in the upper half
of the lesion. This distribution correlates with cell proliferation in these polyp types
and is consistent with the role of survivin in cell proliferation (Altieri, 2008). The
characteristic difference in the staining patterns suggests that survivin staining
might provide some, albeit minor, help in the classification of polyps.
The overall expression pattern of survivin was in line with previous findings
in CRC, illustrating higher cytoplasmic survivin and lower nuclear survivin in
cancer than in normal colon mucosa or benign polyps (Fang YJ et al., 2009; Gianani
et al., 2001). An association between high expression of survivin and adverse
prognosis has been previously reported (Fang YJ et al., 2009). Our finding of
absence of association with prognosis could be related to the limited number of
patients and selection bias related to emphasis on serrated carcinomas.
6.4 3-D in vitro model with mutated KRAS and BRAF oncogenes
transfected Caco-2 cells to model anoikis resistance
3-D culture has been developed for many decades and it holds advantages over
conventional 2-D cultures. 3-D culturing of normal or cancer cells in basement
membrane extract (matrigel), rat-tail collagen I or synthetic hydrogels has been
utilized to study the pathogenesis of several diseases. Moreover, this system allows
assessment of biological and functional properties of cells in an environment close
to that of actual in vivo situation.
80
We aimed to create an in vitro model for the putative AR subpopulations seen
in actual carcinomas to get additional evidence of association between anoikis
resistance and the histopathological features identified to represent it, including
MIPs, solid and cribriform structures.
3-D culture was prepared by plating Control-Caco2 cells and Caco-2 cells with
KRAS or BRAF mutations in a mixture of Matrigel and collagen as described
previously (Debnath, Muthuswamy, & Brugge, 2003; Magudia et al., 2012).
Monitoring and imaging of 3-D live cultures for 10 days showed that by Day 7, all
cell lineages had grown to constant patterns of cysts or filled structures, with no
visible changes in the distribution of these patterns at later time points. At Day 10,
well-polarized cysts with a clear lumen were formed by Caco-2 control cells as
expected (Magudia et al., 2012; Makrodouli et al., 2011). However, Caco-2 cells
with mutant KRAS formed filled structures (partial or complete solid cysts) with
inverted polarity shown by actin staining (Hall, 2009) at the apical pole outside of
the cell clusters. In addition, Caco-2 KRAS cells formed cysts with some cell piling
at the luminal side with disorganized cytoskeletal organization marked by
fragments of actin strands. Quite recently, inverted polarity was reported to be the
mechanism enabling survival and dissemination of cancer cell clusters during
peritoneal metastasis especially in serrated CRC (Zajac et al., 2018). Therefore,
solid structures formed by Caco-2 KRAS cells with inverted polarity might serve
as a useful model to provide additional mechanistic knowledge of inverted polarity
and anoikis resistance. Caco-2 BRAF cells, on the other hand, predominantly
formed solid structures with irregular polarity in the inner cells. The formation of
solid structures or intraluminal piling by Caco-2 cells with KRAS and BRAF
mutations is structurally reminiscent of the putative AR subpopulations seen in
histopathological sections of CRC (I, II, III, Figure 16), mostly with solid islands
and micropapillary structures, respectively. Emergence of these structures in vitro
along with emergence of anoikis resistance in adhesion-free cultures supports the
concept that the formation of these structures in vitro is a manifestation of anoikis
resistance. Further supporting this concept is the finding that the inner cells in the
cell clusters in vitro clearly survive without contact with the ECM. However, to
confirm the occurrence of anoikis resistance, detailed comparisons of inner and
outer cells of these multicellular cluster are needed to see whether there is any
suppression of apoptosis in the inner cells. In addition, functional studies would be
needed to identify the anti-apoptotic mechanisms involved in survival in such
organized multicellular clusters.
81
Fig. 16. Comparison of histopathology of CRC cases (left column; Hematoxylin & eosin
staining) and confocal images of 3-D cultures of different Caco-2 cell lines (right column;
DNA stained with dapi; actin with TRITC-phalloidin) to illustrate similarities between
putative non-AR (1st row) and AR (2nd and 3rd row) subpopulations in CRC cases, and
corresponding non-AR (1st row) and AR (2nd and 3rd rows) cells in 3-D in vitro cultures.
To provide possibilities for a more comprehensive comparison of in vitro 3-D
structures and actual tumors, we adapted a method by Pinto et al. by transferring 3-
D cultures into an agarose sandwich followed by embedding in paraffin. The
method not only allows preservation of experimental samples for long duration but
also provides an opportunity to study markers related to anoikis resistance and
progression by using conventional immunohistochemistry (Figure 14).
82
6.5 KRAS and BRAF mutations induce anoikis resistance in
adhesion free culture in Caco-2 cells
There are several methods for in vitro assessment of anoikis resistance. These
methods include anti-adhesion tests such as soft agar hanging drop cultures, utilized
to study colony formation, whereas cultures grown in suspension alone or with
additives such as poly-L lysine, collagen or other cell adhesion molecules are used
to study anchorage-independent mechanisms. The most frequently applied tool for
suspension cultures involves using commercially manufactured low attachment
dishes or cell culture dishes coated with poly HEMA-ethanol solution providing an
anchorage-independent surface. We utilized this cost-effective and robust method
to study anoikis resistance in suspension environment.
We used Caco-2 cells, a well-characterized colon cancer cell line that does not
harbor KRAS or BRAF oncogene mutations, which are commonly spotted in CRC.
Additional Caco-2 cells form cysts with a regular lumen and polarized cells around
in 3-D matrigel, resembling glandular structures of normal intestinal mucosa
(Magudia et al., 2012; Makrodouli et al., 2011). Caco-2 cells are adherent cell
lines and not resistant to anoikis (Kozlova, Morozevich, Chubukina, & Berman,
2001). To modify the cells we selected KRAS G12V and BRAF V600E mutations,
since mutations in KRAS G12V and BRAF V 600E are common in CRC and hold
prognostic significance in CRC (Richman et al., 2009; Taieb et al., 2016). We
modified Caco-2 cells with these oncogenic mutations. The Caco-2 cells with
KRAS or BRAF mutations have been shown to alter polarized cysts formation.
(Magudia et al., 2012; Makrodouli et al., 2011).
We noted a significant increase in the number of anoikis-resistant (Annexin
negative) cells in Caco-2 KRAS and Caco-2 BRAF cells compared to Caco-2
control cells in serum-free suspension cultures. KRAS G12V-mutated Caco-2 cells
showed higher resistance to anoikis than BRAF V600E-mutated Caco-2 cells; this
difference was more evident at 24 h and less pronounced at 48 h, possibly due to
stress induced by the culture conditions (i.e. cells in suspension). These
observations indicate, for the first time, that KRAS G12V and BRAF V600E induce
anoikis resistance in Caco-2 cells. In support of this observation, earlier literature
indicated the presence of anoikis resistance in all reported (n = 4) intestinal
carcinoma cell lines with either inherent KRAS G12V or BRAF V600E mutation
(III: Table 1).
Since Caco-2 cells harbor APC mutation (De Bosscher, Hill, & Nicolas, 2004;
Magudia et al., 2012), it is important to consider whether APC mutation contributes
83
to induction of anoikis resistance by KRAS or BRAF mutations. Extension of our
literature survey of CRC cell lines with inherent mutation of KRAS or BRAF and
either anoikis resistance or in vitro growth as solid structures in 3-D (III; Table 1)
indicated that all these cell lines except for HCT116 have APC mutation (Heinen,
Richardson, White, & Groden, 1995; Ilyas, Tomlinson, Rowan, Pignatelli, &
Bodmer, 1997). The latter reports provide experimental evidence that the combined
effect of APC mutation together with KRAS or BRAF may contribute to anoikis
resistance. However, we are not aware of studies confirming, for example by RNA
interference, that APC mutation has any essential role in anoikis resistance, and this
warrants additional studies. Biologically, combined effects of two mutations in the
generation of anoikis resistance seem plausible, as there is previous experimental
evidence indicating the existence of regulatory links between WNT and ERK
signaling (Jeong, Ro, & Choi, 2018). Furthermore, indirectly supporting the
concept, animal model studies have shown cumulative effects of APC and KRAS
on metastasis development (Sakai et al., 2018). Finally, in our clinical series, we
did not find clear associations between KRAS or BRAF mutation and the extent of
putative anoikis resistant subpopulations, suggesting that mutations additional to
KRAS or BRAF might be involved in anoikis resistance in CRC. Accordingly, it
would be interesting to assess the role of the combined effects of APC and KRAS
or BRAF mutations on the formation of putative anoikis resistant populations in a
clinical series of CRC.
To get some insight into the mechanisms behind anoikis resistance related to
transfection of mutated KRAS or BRAF, we studied Bim protein expression in our
three Caco-2 cell lineages surviving in adhesion-free conditions. Bim is a well-
characterized pro-apoptotic protein, which blocks anti-apoptotic proteins and
induces caspase-mediated apoptosis (Boisvert-Adamo & Aplin, 2008; Goldstein et
al., 2009). We found a non-significant trend for increased expression of Bim in the
cells with mutant oncogenes, suggesting an anti-apoptotic role for this protein.
Although the observation is in disagreement with the well-addressed pro-apoptotic
role of Bim protein, a prosurvival role of Bim has also been identified (Gogada et
al., 2013). Obviously, dissection of the mechanisms of anoikis resistance induced
by oncogene transfections requires additional research.
84
6.6 Anoikis-resistant cells and putative AR cells present in
carcinomas show features of dormancy or quiescence
Among several factors that may aid or induce anoikis resistance in cancer cells,
tumor quiescence stands strong. Cellular quiescence is represented when a cell is
detected at G0 phase. It can be reversible (quiescent stage) or irreversible
(senescent and differentiated, non-dividing). This phenomenon is commonly
explored in stem cell research and cancer research. Quiescence can be detected in
tissues by Ki-67 immunohistochemical staining, in cells by estimation of cell cycle
phase with Propidium iodide FACS assay (J. H. Kim et al., 2015), and with label
retention experiments using bromodeoxyuridine (BrdU) (Glauche et al., 2009).
We found that the majority of Annexin-negative (anoikis-resistant) cells from
Caco-2 cells transfected with mutant KRAS or BRAF oncogenes in suspension were
arrested at G0/G1 phase compared to control Caco-2 cells. This difference was
present in the 24 h suspension cultures and became stronger in the 48 h cultures. In
histopathological studies (I, II) we found that cells in the MIP structures showed
lower Ki-67 protein expression as compared to tumor epithelium in contact with
ECM, possibly indicating features of quiescence. Importantly, quiescent cancer
stem cells (CSCs) often present higher chemo resistance and tumor formation
ability than non-quiescent CSCs (Kojima et al., 2017), which is why their efficient
identification and elimination would be beneficial (Becker, 2018).
Further studies are needed to assess whether MIPs contain quiescent cells and
whether Caco-2 cells with BRAF or KRAS mutation serve as a model for quiescence.
6.7 A model untangling the fates of AR subpopulations in cancer
formation
Identification and assessment of cancer subpopulations with anoikis resistance
from human cancer tissues might provide vital information improving our
understanding of the mechanism for acquisition of this feature and its link to
survival and progression in cancer. We present here a theoretical model proposing
different fates AR cells might encounter (Figure 17). With the current knowledge
deciphered in this thesis, we have displayed possible routes of progression by any
anoikis resistant tumor cell population. MIPs were used here as example, since
they seem to present both anoikis resistance and cellular quiescence. There could
be three prospective fates they might run into. 1) Cells might remain quiescent at
the primary location for decades without being detected or removed, as has been
85
reported for cells of breast cancer. 2) Alternately, in response to a stimulus, these
cells might proliferate extensively towards the luminal space and, complemented
by decreased apoptosis, fill up the gland, resulting in formation of partially
(cribriform) or completely filled (solid) structures, contributing to poorly
differentiated cancer with poor clinical outcome. Accordingly, speculatively, MIPs
could be the origin of formation of other AR structures. 3) It is possible that
utilizing their anoikis resistance, cells from MIPs and other anoikis resistant
subpopulations might disseminate and travel through the blood and lymphatic
vessel system, resulting in the formation of metastases.
Although such sequences are still speculative, if real, any of these fates may
lead to poor clinical outcome and should therefore be investigated to confirm or
exclude any such possibility. An elaborate understanding of such cells and/or
structures, including a deeper understanding of the molecular mechanism by which
KRAS or BRAF mutations contribute to cancer metastasis via anoikis resistance and
associated aberrations, would be helpful in improving patient survival. The ways
for such improvement might include development of reliable methods for detection
of features indicating anoikis resistance and the concomitant risks as well as
development of drugs and other treatment modalities effective for elimination of
AR cells.
6.8 Future perspectives
In Study II, we identified and assessed putative AR structures in colorectal cancer
tissues with histopathology and immunohistochemical analysis. However, the
study was based on a single cohort. Therefore, analysis of larger independent
patient material is needed for confirmation of the prognostic value.
Our study was performed using samples from the tumor bulk region, since the
tumor front contains carcinoma cell buds in almost 40% of cases and budding is a
strong prognostic factor (Lugli et al., 2017b). By definition, all cells in the buds are
in contact with mesenchymal areas of the tumor (Lugli et al., 2017b) and therefore
do not qualify for any AR population. However, it would be interesting to analyze
the front region for putative AR subpopulations.
We used digital image analysis for the assessment of areal proportions of
putative AR populations and for Ki-67 expression, and it showed good interrater
reproducibility in the latter. However, since the program required manual
annotation of different cell populations, there is clearly a need for development of
software capable of recognizing different tumor cell subpopulations.
86
Fig. 17. Schematic representation of the fates of anoikis-resistant cells in disease
formation or progression.
We reported (study I, II) that cells in micropapillary structures present distinct
biology with anoikis resistance property and features of quiescence. In cell-cycle
stage assessments of anoikis-resistant colon cancer cells transfected with mutant
KRAS or BRAF we found that the cells were arrested at G0/G1 phase (III),
indicative of quiescence. Based on these observations, the presence of quiescence
should be confirmed by separation of G0 cells from G1 cells. The significance of
putative quiescent populations in clinical tumor samples should be studied with
87
larger patient material to assess their prognostic value, the effect on treatment
responses, and finally, to optimize treatment regimens. Similarly, there is a need
for characterization of the oncological significance of other AR subpopulations as
well by using both retrospective analyses focusing on the relationship between
treatment response and occurrence of AR subpopulations and by using in vitro
models.
We showed (III) that transfection with mutant KRAS or BRAF induces anoikis
resistance feature in colon cancer cells in 3-D cultures and in anti-adhesion tests.
Although we did not find any association of KRAS or BRAF mutations with the
occurrence of putative AR subpopulations in CRC, histopathological assessment of
AR subpopulations in larger material and assessment of APC mutation in addition
to KRAS and BRAF might enable evaluation of any such association if also present
in actual carcinoma.
Finally, regardless of the validity and significance of the current anoikis
resistance paradigm in terms of the putative AR subpopulations, it is very likely
that these subpopulations in CRC tissue and in the 3-D model represent a
biologically different cell population as compared to cells in contact with the ECM.
The patterns of biological differences remain speculative at present, and likely
involve mechanisms analogous for any intra-tumoral heterogeneity, including
genetic and epigenetic as well as non-hereditary functional differences (Stanta &
Bonin, 2018). We are not aware of studies in CRC combining any feature of
heterogeneity of the microscopic structure of the tumor and mutational, epigenetic
or mRNA expression related heterogeneity. Furthermore, it is likely that there are
differences in the overall biology of tumors with and without these subpopulations.
More importantly, the presence of these subpopulations seems to have prognostic
value. Further characterization of structures will help to understand the underlying
mechanism of disease progression and their prognostic effects and may be
informative in designing optimal treatment.
88
89
7 Conclusions
CRC is a common cause of death in most western countries and resistance to
anoikis is considered one key feature enabling the formation of metastasis in CRC
and in other carcinomas. We aimed to identify putative AR carcinoma cell
subpopulations in CRC and to assess their prognostic role. Additionally, we
searched support for the concept by using a 3-D in vitro cell culture model and anti-
adhesion tests.
I We identified putative AR subpopulations in micropapillary, cribriform and
solid structures based on the absence of basement membrane proteins and
lower apoptosis indexes in all three subpopulations. High areal density sum of
these subpopulations was an independent prognostic factor indicating
shortened cancer-specific survival in CRC. (I, II).
II We studied the mechanisms behind survival of putative AR cells and found
decreased survivin expression by immunohistochemistry along with lower
proliferation and apoptosis rates in MIPs, a putative AR subpopulation in CRC.
KRAS and BRAF mutations induced acquisition of anoikis resistance in Caco-
2 colon cancer cells in vitro, while in colon carcinoma tissues, no clear
association was detected between these mutations and the occurrence of the
putative AR subpopulations (I, II, III).
III We generated a 3-D in vitro model by transfecting Caco-2 cells with KRAS or
BRAF mutations. Along with generation of anoikis resistance in adhesion free
culture, these oncogenes induced the formation of solid multicellular clusters
or cystic structures with focal piling of cells in 3-D cultures, both patterns
indicating survival of cells without ECM contact, and accordingly, anoikis
resistance. Histopathologically, these structures showed features reminiscent
of solid and micropapillary structures in CRC, respectively. These findings
suggest that solid growth and micropapillary-like structures are related with
anoikis resistance both in vitro and in actual CRC cases in vivo (III).
90
91
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Original publications
I Patankar M, Väyrynen S, Tuomisto A, Mäkinen M, Eskelinen S and Karttunen TJ. (2018). Micropapillary structures in colorectal cancer: An anoikis-resistant subpopulation. Anticancer Research 38, 2915-2921.
II Patankar M, Mattila T, Väyrynen JP, Klintrup K, Mäkelä J, Tuomisto A, Nieminen P, Mäkinen M J, Karttunen TJ. (2019). Histopathological assessment of anoikis resistance in colorectal carcinoma: Abundance of putative anoikis resistant subpopulations indicate poor prognosis. Manuscript.
III Patankar M, Eskelinen S, Tuomisto A, Mäkinen M, Karttunen TJ (2019). KRAS and BRAF mutations induce anoikis resistance in Caco-2 cells and characteristic 3D phenotypes in Caco-2 cells. Molecular Medicine Reports, 20: 4634-4644.
Reprinted with permission from published articles (I, III).
Original publications are not included in the electronic version of the dissertation
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adhura Patankar
OULU 2019
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Madhura Patankar
MODELING AND HISTOPATHOLOGICAL RECOGNITION OF ANOIKIS RESISTANCE IN COLORECTAL CARCINOMA
UNIVERSITY OF OULU GRADUATE SCHOOL;UNIVERSITY OF OULU,FACULTY OF MEDICINE
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