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Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients Subtitle: Treatment of life-threatening diseases mediated by the APE1/Ref-1 protein Mark R. Kelley, Ph.D. Associate Director of Basic Science Research, Indiana University Simon Comprehensive Cancer Center Betty and Earl Herr Professor in Pediatric Oncology Research and Professor, Departments of Pediatrics, Biochemistry & Molecular Biology, Pharmacology & Toxicology and Ophthalmology Adjunct Professor, Eugene and Marilyn Glick Eye Institute Director, Program in Pediatric Molecular Oncology & Experimental Therapeutics Glenn W. Irwin, Jr. M.D. Research Scholar Bantz-Petrino Translating Research into Practice Scholar Chair, Indiana University Conflict of Interest Committee Co-leader, Experimental and Development Therapeutics Program, IUSCCC PHARMACOLOGY PHARMACOLOGY The Journal of And Experimental Therapeutics A Publication of the American Society for Pharmacology and Experimental Therapeutics Volume 359 Number 2 November 2016 ISSN 1521-0103 6.18.20

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Page 1: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Out of the lab and into the clinic: Translating basic science discoveries into new treatments for

patients

Subtitle: Treatment of life-threatening diseases mediated by the APE1/Ref-1 protein

Mark R. Kelley, Ph.D.• Associate Director of Basic Science Research, Indiana University Simon Comprehensive

Cancer Center• Betty and Earl Herr Professor in Pediatric Oncology Research and• Professor, Departments of Pediatrics, Biochemistry & Molecular Biology,

Pharmacology & Toxicology and Ophthalmology• Adjunct Professor, Eugene and Marilyn Glick Eye Institute• Director, Program in Pediatric Molecular Oncology & Experimental Therapeutics• Glenn W. Irwin, Jr. M.D. Research Scholar• Bantz-Petrino Translating Research into Practice Scholar• Chair, Indiana University Conflict of Interest Committee• Co-leader, Experimental and Development Therapeutics Program, IUSCCC

PHARMACOLOGYPHARMACOLOGYThe Journal of

And Experimental Therapeutics

A Publication of the American Society forPharmacology and Experimental Therapeutics

Volume 359 Q Number 2 Q November 2016 Q ISSN 1521-0103

6.18.20

Page 2: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Today, I am going to talk about:

• A little science

• How big data/bioinformatics has led to new avenues of research

• Pathway from bench to clinical trial

• New directions based on data analysis, target and drug development

Page 3: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

The Target & DrugThe Target The Drug

Ref-1 function:oxidation-reduction

APE1/Ref-1

reduced

APX3330

Ref-1

oxidizedRef-1

TF

TF

oxidized

reduced

In a thiol/sulfide exchange on its cysteine residue, Ref-1/APE1 reduces a transcription factor to its active form. Ref-1/APE1 becomes oxidized in the process.

APE1 function:AP endonuclease

The reduced transcription factor (TF) can bind to DNA.

The TF triggers synthesis of RNA and subsequent proteins that affect growth, inflammation, metastasis, and angiogenesis.

After a glycosylase removes the damaged base, Ref-1/APE1 nicks the abasic site to prep it for

TF

Page 4: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

APE1/Ref-1 functions: DNA repair and Redox signaling regulation of TFs

C65C93 Redox Role

(reduced)

(oxidized) (reduced)

(oxidized)

STAT3NFkBHIF-1a

P53CREBAP-1

Redox control of Transcription factors

Target gene expression:GrowthInflammationAngiogenesis

Ref-1

C99

Glycosylase (Ogg1, Nth1)

DNA damage

C T T A GAG A T CT

5’-P AC T T A GAG A T CT

5’-P AC T T A GAG A T CT

5’-P A

C T T A GAG A T CTC T T A GAG A T CTC T T A GAG A T CT

DNA Ligase

C T T A GAG A A CT T

DNA Ligase

C T T A GAG A A CT TC T T A GAG A A CTC T T A GAG A A CT T

C T T A GAG A A T CTC T T GAG A A CTC T T GAG A A CT

C T T A GAG A T CT *C T T A GAG A T CT

C T T A GAG A A T CTC T T A GA

A A T C

APE1

DNA Repair

Summary Publication: F. Shah, D. Logsdon, R.A. Messmann, J.C. Fehrenbacher, M.L. Fishel, and M.R. Kelley. (2017) Exploiting the APE1-Ref-1 node in cancer signaling and other diseases: from bench to clinic. Nature Precision Oncology June 2017; 1:19.

C65Repair Active site

Page 5: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

APE1 Repair & Nuclease Functions- BER:

- Endonuclease, exonuclease- 3ʹ phosphodiesterase- 3ʹ to 5ʹ exonuclease

- NIR: processes oxidative damage not repaired by BER- RNA metabolism

NF-KB, HIF1a, STAT3, AP-1, p53

1 318

H309D210C99C65

Lys6/7 ArgNuclear to cytoplasm

Lys98NIR

Asp210General nuclease

Agr177BER

coordination

Asp703ʹ-phosphodiesterase

Phe2663ʹ to 5ʹ exonuclease

FUNCTIONS

Regions

APPLICATIONSAnti-inflammation, anti-neovascularization for

cancers, CIPNocular diseases (AMD, DME, DR) and IBD

Inhibition of DNA repair for anti-cancer treatment (including

reversal of drug resistance)

289-318Mitochondrial

Targeting Sequence

Diagnosis based on secretory levels (Serum and Urine)

C93

35 127Redox Region

DNA repair and nuclease region

E96

Page 6: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

APE1/Ref-1 is a dual function protein

Function #1:

DNA Repair:repairs the DNA

single-strand breaks (SSB)

induced by ROS (i.e., oxidative

damage)

Function #2:

APE1 Redox: regulates

transcription factors (TFs) critical to cell

signaling and DNA duplication

APE1/Ref-1

Summary Publication: F. Shah, D. Logsdon, R.A. Messmann, J.C. Fehrenbacher, M.L. Fishel, and M.R. Kelley. (2017) Exploiting the APE1-Ref-1 node in cancer signaling and other diseases: from bench to clinic. Nature Precision Oncology June 2017; 1:19.

Page 7: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

APX3330 inhibits APE1/Ref-1 Redox Function Blocking TF Activity

C65C93

Redox active site

APX3330

XHIF-1aNFkBSTAT3

(reduced APE1)

X(oxidized TF)

TFTF

(oxidized APE1)(reduced TF)

(oxidized APE1)

TFTF

X (reduced TF binds to target DNA)

Target gene expression:GrowthInflammationAngiogenesisX

Summary Publication: F. Shah, D. Logsdon, R.A. Messmann, J.C. Fehrenbacher, M.L. Fishel, and M.R. Kelley. (2017) Exploiting the APE1-Ref-1 node in cancer signaling and other diseases: from bench to clinic. Nature Precision Oncology June 2017; 1:19.

Page 8: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Transcription Factors Redox-Reduced by APE1/Ref-1

AP-1 (c-Jun/c-Fos)

Jun: C269Fos: C154DNA binding region of basic leucine zipper domainsXanthoudakis and Curran (1992) EMBO J. 11(2):653-65

p53Ig fold

C275 & C277DNA-Binding DomainSeo, et al (2002) PNAS99(22):14548-53

Hif-1αHLH/leucineZipper

Probable redox-sensitive site: C824C-terminal transactivation domainLando, et al (2000) JBC 275(7):4618-27

p50 subunit: C62DNA binding region of Rel homology domainNishi, et al (2002) JBC277(46):44548-56

NFκBIg foldsof dimeric

STAT3Homodimer

Specific site unknown – multiple Cys residues in DNA binding domain and other domains important for transcriptional activation

Structure reference: Becker, et al (1998) Nature 394(6689):145-

51

Luo M, He H, Kelley MR, Georgiadis MM. (2010) Redox Regulation of DNA Repair: Implications for Human Health and Cancer Therapeutic Development. Antioxid Redox Signal, 12(11):1247-1269.

Page 9: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

The Importance of the APE1 Protein: Cancer CellsCancer cells “hijack” APE1 Redox Function to control transcription factors (TFs) and

increase tumor proliferation, survival, angiogenesis, inflammation, and migration

Redox control of TFs

HIF-1a, STAT3, NF-KB,

and othersTumor

aggressiveness

Page 10: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

The DrugAPX3330

The drug has a direct and selective interaction with APE1/Ref-1 as demonstrated by chemical footprinting, mass spectrometry, Thermal Shift Assay (TSA) and other

biochemical data.

Page 11: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

How does APX3330 work?APX3330 knocks out only the APE1/Ref-1 Redox function of

the APE1 protein. Keeping transcription factors in the “off” position

APX3330

APX3330 inhibits only the APE1 redox signaling activity.

C65

Jun Zhang; Meihua Luo; Daniela Marasco; Derek Logsdon; Kaice A. LaFavers; Qiujia Chen; April Reed; Mark R. Kelley; Michael L. Gross; Millie M. Georgiadis; Biochemistry 2013, 52, 2955-2966.

Luo M, Zhang J, He H, Su D, Chen Q, Gross ML, Kelley MR, Georgiadis MM. Characterization of the redox activity and disulfide bond formation in apurinic/apyrimidinic endonuclease. Biochemistry. 2012 Jan 17;51(2):695-705. Epub 2012 Jan 4.

Zhang J, Luo M, Marascot D, Logsdon D, LaFavers KA, Chen Q, Reed A, Kelley MR, Gross ML, Georgiadis MM. (2013) Inhibition of Apurinic/apyrimidinic endonuclease I’s redox activity revisited. Biochemistry. Apr 30;52(17):2955-66 PMCID: PMC3706204

Page 12: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

APE1/Ref-1 Nodal ModelCA9 inhibitors(e.g. SLC-0111)

APX3330 IL-6 targeted agents

IL#6%Stromal%Cells%

Upstream HIF1 Inhibitors (various

mechanisms)pH Stabilization

CA9

O2

HIF1α

CA9

Angiogenesis

VEGF

VEGF Signaling Inhibitors (e.g. Bevacizumab)

F. Shah, D. Logsdon, R.A. Messmann, J.C. Fehrenbacher, M.L. Fishel, and M.R. Kelley. (2017) Exploiting the APE1-Ref-1 node in cancer signaling and other diseases: from bench to clinic. Nature pj Precision Oncology June 2017; 1:19. PMCID: PMC5558897.

HIF-1

Other TF’s (e.g.

AP-1)

STAT3

JAK

JAK2 inhibitors (e.g. Ruxolitinib)

STAT3 Inhibitors (e.g. BBI, etc)

NFκB

IκBα Degradation Inhibitors (e.g. Bortezomib)

NFκB

STAT3

DNA

Page 13: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Example Cancer Data

• Pancreatic cancer• Bladder• MPNST

• (Malignant peripheral nerve sheath tumor)• Colon• Leukemia

• AML• T-cell ALL

• Chemotherapy-induced peripheral neuropathy• (CIPN)

• Apexian Phase I Clinical Trial

Page 14: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Inhibition of APE1/Ref-1 via knockdown decreases STAT3 activity

The phosphorylation (Y705) and nuclear translocation is not affected with APE1/Ref-1

knockdown.

APE1/Ref-1

T-STAT3p-STAT3

SC siAPE1/Ref-1

WCE

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

RLU/

MTS

fold

chan

ge

SCsiAPE1/Ref-1

Basal +IL-6

**

*

When APE1 protein levels are reduced, STAT3 activity

is decreased.

Ref-1 redox mutant does not stimulate STAT3

Luciferase assay with STAT3 reporter

pcDNA wtAPE1 C65A

Tran

sacti

vatio

n ac

tivity

(fold

)

0

1

2

3

4

#3#9

****

Page 15: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

STAT3 DNA binding is redox sensitive and can be and inhibited by APX3330

STAT

3 D

NA

bind

ing

(%)

***

** **

APX3330 (µM)

Tumor mass

STAT3APE1/ Ref-1 APE1/

Ref-1

APX3330

Basal

+ IL-6

- + APX3330

p-STAT3

T-STAT3

APX3330 uM

APX3330

Page 16: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Next generation APX compounds: some examples

A

D

B C

APX3330

APX2009

Sardar Pasha SPB, Sishtla K, Sulaiman RS, Park B, Shetty T, Shah F, Fishel ML, Wikel JH, Kelley MR, Corson TW. (2018) Ref-1/APE1 Inhibition with Novel Small Molecules Blocks Ocular Neovascularization. J Pharmacol Exp Ther. Oct;367(1):108-118. PMID:30076264

APX2014

Page 17: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Bladder Tumor Aggressiveness Correlates with APE1/Ref-1 Expression: APX compounds reduce tumor growth and angiogenesis

• SW7 (SW-780) low grade TCC• UC3 high grade TCC• T24 high grade papillary• RT4 low grade papillary • Sca (SCaBER) squamous variant• HUC, an immortalized benign urothelial cell

line.APX3330 blocks transcription factors that regulate Bcl-2, Mcl-1 and Survivin. These proteins are critical for bladder cancer tumor growth.

Benign

Low Grade

High Grade

Vehicle APX3330 APX2009

In vivo treatment of T24 tumor cells

Page 18: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Treatment with APE1/Ref-1 inhibitors potently blocks bladder cancer cell proliferationand activated caspase 3/7

Fishel et al. Mol Cancer Ther 2019;18:1947-1960

APX3330APX2009APX2014

Page 19: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Inhibition of APE1/Ref-1 in monolayer and in 3D culture using PDX-derived cells RP-B-01 and RP-B-02 blocks tumor growth

Fishel et al. Mol Cancer Ther 2019;18:1947-1960

APX3330APX2009APX2014

Page 20: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Studies in this paper used APX3330 to block cancer progression

Inhibition of STAT3 through APE1/Ref-1 inhibition by APX3330 blocked leukemia cancer progression

Kapur

Page 21: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Why do single-cell sequencing?Allows us to compare the transcriptional changes between these two cells which have both been treated with siAPE1, but clearly have different levels of APE1

10nM SCR

• To observe heterogeneity and subpopulations

• Look at lineages and subsets• Compare cells with undetectable

APE1 to a cells with reduced levels of APE1

10nM siAPE1

Page 22: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Single cell RNA-seq analysis in Normoxia and Hypoxia – APE1/Ref-1 KD

si Hypoxia

si Normoxia

Scr Normoxia

Scr Hypoxia

ScRNA-seq Differential Gene Expression Analysis

NormoxiaSCR siAPE1

HypoxiaSCR siAPE1

Page 23: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

The “usual suspects” are changed as expected.Pathway affected by Ref-1

knockdownp-value

STAT3 Pathway 1.2e-6HIF1 Signaling 8e-4 NFkB Signaling 3e-3

1855 DEGs identified between Ref-1 knock-down and control cells in normal O2, 2114DEGs in hypoxia

>100 different canonical pathways found to be overrepresented amongst differentially expressed genes

Page 24: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Genes Selected for scRNA-seq Validation

Rationale for selection• p-value• Fold change• Regulation by

Transcription Factors that are regulated by APE1

STAT3TAPBP

NOTCH3RAB3D

Shah, Goosens, Atallah, Grimard, Kelley and Fishel (2017) APE1/Ref-1 knockdown in pancreatic ductal adenocarcinoma: Characterizing gene expression changes and identifying novel pathways using single-cell RNA sequencing. Molecular Oncology, In Press.

Page 25: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Validation via qPCR demonstrates all 12 genes change expression as in scRNA-seq

Shah, Goosens, Atallah, Grimard, Kelley and Fishel (2017) APE1/Ref-1 knockdown in pancreatic ductal adenocarcinoma: Characterizing gene expression changes and identifying novel pathways using single-cell RNA sequencing. Mol Oncol. 2017 Dec;11(12):1711-1732.

Vinculin

Ape1

SCR

siAPE

1

Page 26: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

qPCR of genes in 4 PDAC cell lines shows variable expression

ITGA1TNFAIP2

COMMD7RAB3D

PRDX5ISYNA1

NOTCH3

BCRPPPIFSIPA1

Pa03C (Metastatic)

Pa02C (Metastatic)

Panc10.05 (Primary)

Panc198 (Primary)

Shah, Goosens, Atallah, Grimard, Kelley and Fishel (2017) APE1/Ref-1 knockdown in pancreatic ductal adenocarcinoma: Characterizing gene expression changes and identifying novel pathways using single-cell RNA sequencing. Mol Oncol. 2017 Dec;11(12):1711-1732.

TAPBP

CIRBP*

*

Page 27: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Confirmation that the redox function of APE1 is responsible for the decrease in expression

sc RNAseq ITGA1 PRDX5 SIPA1 RAB3D

Fold change from SCR

0.01 0.26 0.01 0.10

p value 0.0011.02x10-15 2.78x10-6 8.14x10-7

Page 28: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

0" 10" 20" 30" 40" 50" 60" 70" 80"

NADH"Repair"(100%)"Putrescine"Degreda@on"III"(35%)"

Glycolysis"I"(36%)"Regula@on"of"Ac@nGbased"Mo@lity"by"Rho"(21%)"

Apoptosis"Signaling"(22%)"CDK5"Signaling"(21%)"

Androgen"Signaling"(20%)"Virus"Entry"via"Endocy@c"Pathway"(22%)"

Sumoyla@on"Pathway"(25%)"Aryl"Hydrocarbon"Receptor"Signaling"(19%)"

Oxida@ve"Phosphoryla@on"(25%)"Aldosterone"Signaling"in"Epithelial"Cells"(20%)"

ILK"Signaling"(18%)"Mitochondrial"Dysfunc@on"(22%)"

Hun@ngton's"Disease"Signaling"(17%)"Regula@on"of"eIF4"and"p70S6K"Signaling"(27%)"

Protein"Ubiqui@na@on"Pathway"(17%)"mTOR"Signaling"(28%)"

Protein"Kinase"A"Signaling"(16%)"EIF2"Signaling"(32%)"

No.$of$DEGs$in$Pathway$

20$Most$Overrepresented$Canonical$Pathways$

Top 10 Over-represented Pathways comparing siAPE1 vs. SC(normal O2)

0" 10" 20" 30" 40" 50" 60" 70" 80"

NADH"Repair"(100%)"Putrescine"Degreda@on"III"(35%)"

Glycolysis"I"(36%)"Regula@on"of"Ac@nGbased"Mo@lity"by"Rho"(21%)"

Apoptosis"Signaling"(22%)"CDK5"Signaling"(21%)"

Androgen"Signaling"(20%)"Virus"Entry"via"Endocy@c"Pathway"(22%)"

Sumoyla@on"Pathway"(25%)"Aryl"Hydrocarbon"Receptor"Signaling"(19%)"

Oxida@ve"Phosphoryla@on"(25%)"Aldosterone"Signaling"in"Epithelial"Cells"(20%)"

ILK"Signaling"(18%)"Mitochondrial"Dysfunc@on"(22%)"

Hun@ngton's"Disease"Signaling"(17%)"Regula@on"of"eIF4"and"p70S6K"Signaling"(27%)"

Protein"Ubiqui@na@on"Pathway"(17%)"mTOR"Signaling"(28%)"

Protein"Kinase"A"Signaling"(16%)"EIF2"Signaling"(32%)"

No.$of$DEGs$in$Pathway$

20$Most$Overrepresented$Canonical$Pathways$EIF2 Signaling (32%)

Protein Kinase A (16%)mTOR (28%)

Ubiquitination (17%)Regulation of eIF4 and p70S6K (27%)

Huntington’s Disease (17%)Mitochondrial dysfunction (22%)

ILK signaling (18%)Aldosterone signaling (20%)

Oxidative phosphorylation (25%)

No. of DEGs in Pathway

Page 29: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Mitochondrial dysfunctionnormal O2

Page 30: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Mitochondrial dysfunction1% O2

Page 31: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Metabolic genes implicated in APE1 signaling following hypoxia using single cell RNA-seq

Data unpublished, removed

Page 32: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Functional effects of APE1 redox inhibition on tumor cell growth and metabolism

Data unpublished, removed

Page 33: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

CPI-613 : metabolic inhibitor in Phase 2 clinical trials.

520 Broad Street, Newark, New Jersey 07102 Tel: (973) 438-2000; Fax: (973) 438-2001

CPI-613: A First-in-Class Therapeutic Agent Targeting Cancer Cell Metabolism

WHAT IS CPI-613

§ CPI-613 is a first-in-class investigational small-molecule (lipoate analog), developed by Rafael, based on the Altered Energy Metabolism Directed (AEMD) platform

§ CPI-613 targets the altered energy metabolism that is unique to many cancer cells

§ In nonclinical studies, CPI-613 exhibited excellent sensitivity and specificity to cancer cells

§ CPI-613 was investigated in multiple hematological malignancies and solid tumors, and exhibited very good signal of efficacy

§ FDA has approved initiation of pivotal trials of CPI-613 for Acute Myeloid Leukemia and Pancreatic Cancer, and Rafael is planning to initiate these trials by second half of 2017

§ CPI-613 was granted ‘Orphan Designation’ by U.S. FDA for Acute Myeloid Leukemia (AML), Myelodysplastic Syndrome (MDS) and Pancreatic Cancer

CPI-613: MECHANISM OF ACTION

§ Both Pyruvate dehydrogenase (PDH) and alpha-ketoglutarate dehydrogenase (KGDH) of TCA cycle use lipoate as a catalytic co-factor

§ Lipoate transiently forms several chemically distinct

intermediates during catalysis and these intermediates allow monitoring of carbon flux in mitochondria specific necrosis

§ To fulfill the altered metabolic requirement, many tumor

cells over-express a different set of lipoate-sensitive regulators than normal cells

§ CPI-613 is a lipoate analog designed to mimic the

catalytic intermediates to which the regulatory components that are over-expressed in tumor cells respond to

§ Thus, tumor cell PDH and KGDH regulators respond

robustly to CPI-613, allowing tumor-specific regulatory inactivation of these two indispensable enzymes

CPI-613: CLINICAL TRIALS

§ Currently being evaluated in 15 Phase I to Phase II trials as a single agent, as well as in combination with standard drug therapy for hematological malignancies and solid tumors

§ To date, over 290 subjects have received one or more doses of CPI-613 and the drug exhibited signals of efficacy with excellent response rate and extended duration of response in several tumor types

§ In pancreatic cancer, CPI-613 in combination with modified FOLFIRINOX exhibited 61% Objective Response Rate and 78% Clinical Benefit Rate

§ In acute myeloid leukemia patients with poor cytogenetic risk, CPI-613 in combination with high dose cytarabine and mitoxantrone exhibited 38% Complete Response Rate

§ In both these trials, the efficacy of CPI-613 combinations

were substantially higher than standard therapy

§ In peripheral T-cell lymphoma, CPI-613 in combination with Bendamustine exhibited signal of efficacy

APX compounds

Page 34: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

CPI-613 metabolic inhibitor alone and in combination with APE1 redox inhibition

Data unpublished, removed

Page 35: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Patient derived panc tumor + patient derived cancer associated fibroblasts (CAFs)

(Pa03C & 1301-63 hTERT-GFP)

Dr. Melissa Fishel

Page 36: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Co-culture PDAC tumor cells + CAFs respond to combination therapy of APX inhibition and metabolic

inhibitor, CPI-613

Data unpublished, removed

Page 37: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Trajectory of APE1/Ref-1 studies into the Clinic…Market crash; recession begins

April 2008: ApeX formed based on APE1/Ref-1

assets.Sept 2009 Received Phase 1 STTR

July 2013 Received Phase 1 SBIR

1989 1993 1995

Kelley develops specific antibody for APE1

First antibody soldBy Novus Biological

Kelley joins Dept of Pediatrics

and IUSM

Publishes APE1 expression level

data for normal & malignant tissue

2000 2005 2008 2010 2012 2013

Shows specific inhibition of TF

activation of APE1 by 3330

Work initiated to discover &

develop novel, potent

APE1 inhibitor

Efficacy of APE1 inhibitor vs panc and other cancers

First in vivo eye study with APX3330 and APE1 as target published

First grant studying APE1 in sensory neurons funded:Vasko

Biochemical mechanism of APE1 inhibitors described

NCI grant on APE1 in pancreatic

cancerFunded with

Melissa Fishel

ApeX

Kelley Lab & Collaborators

2009: Funded by Indiana VC Group

2010: Private Investors

Oct 2012 Private Investors &BioCrossroads

Series A

Page 38: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Trajectory of APE1/Ref-1 studies into the Clinic…continued…….2015 - Additional funding through various individual

IND DME/DR indication accepted

by FDA2017: Anti-CIPN indication accepted by FDA for inclusion

into current IND

Apexian Pharmaceuticals

Kelley Lab & Collaborators

2015: ApeX renamed Apexian Pharmaceuticals

2015: Rich Messmann joins

as CMO

IND accepted by FDA

Phase I trial opens

Phase I trial completed

Licensing agreement with Ocuphire for

eye indication

Various new indications identified

using APX3330

Patents granted for numerous uses

of APX3330 and new COM

NCI Provocative Question grant on CIPN funded withJill Fehrenbacher, Millie Georgiadis

APE1 pancreatic

cancer grant renewed withMelissa Fishel

Collaboration with Reuben

Kapur in leukemia models-

published in Cell Stem Cell

Additional patents submitted and

granted for various non-cancer and

cancer indications

Collaboration with Tim Corson on eye studies continues – 2nd gen cpds; JPET publication.

Collaboration with Kulmira Nurgali (Australia) on IBDindications and models.

2014 2015 2016 2017 2018 2019 2020 2021 2022

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Big Data Training for Cancer Research

http://apexianpharma.com/MilestonesQ3, 2016 IND acceptedQ3, 2017 Anti-CIPN indication added to current INDQ1, 2018: Initiate phase I safety study (19 patient study)Q1, 2019: Phase I trial completed, 19 patients Q2, 2019: Presentation of data at ASCOQ4, 2019; Presentation of additional data at AACR Mol Ther MeetingQ1, 2020; License APX3330 and pipeline to Ocuphire for eye indications.Q3/4 2020 Phase II trial in DME/DR will initiate

https://www.ocuphire.com/

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Big Data Training for Cancer Research

A phase I study targeting the APE1/Ref-1 DNA repair-redox signaling protein with the

APX3330 inhibitor

Mark R. Kelley1,4, 5, Safi Shahda5, Nehal J. Lakhani2, Bert O’Neil5, Lincy Chu3, Amanda K. Anderson3, Jun Wan5, Amber L Mosley5, Hao Liu5, Richard A. Messmann4

1Wells Center for Pediatric Research5Indiana University Simon Cancer Center 2START-Midwest, Grand Rapids, MI3Epic Sciences, Inc., San Diego, CA4Apexian Pharmaceuticals, Indianapolis, IN

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Big Data Training for Cancer Research

Completed Successful Phase 1 Oncology StudyAPX3330:

• Was well tolerated at dose levels from 240-600 mg/d • Is safe for chronic oral dosing at 600 mg/d• Patients on drug for extended period of time:

• Six subjects had disease stabilization for > 4 cycles, and of these, four subjects with the following diagnosis, RECIST response and days on study included: (CRC, PR, 357d), (Endometrial, SD, 421d), (Melanoma, SD, 337d), (Prostate, SD, 252d).

• The most frequent treatment-related adverse events (all grades) included G1 nausea (16%) and fatigue (16%). A G3 rash occurred in two subjects at the 720 mg level defining 600 mg/d as the RP2D for further development

• Provides clinical benefit to patients with a variety of tumor types - 30% Response Rate• Patient biopsy evaluation indicates APX3330-mediated effect upon cancer cells, including decrease in

transcription factor activity regulated by the APE1/Ref-1 protein• Circulating tumor cell analysis indicates APX3330-mediated decrease in tumor cells• All results consistently show that APX3330 mediates activity of APE1/Ref-1 target as expected.

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Approximately 30% Response Rate

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Big Data Training for Cancer Research

Overall protein expression of genes downstream of APE1 are decreased in SD patient vs. PD patients

Paired biopsy analysis of pre-treatment and while on-treatment: Melanoma patient with disease stabilization > 1

year (green arrow) with lower APE1-regulated protein expression than patients with mPCa and mCRC.

FCs in the scale of log2.

Heatmap of differentially-expressed proteins (DEPs) obtained by comparing pre-treatment and on-treatment tumor biopsies from 3 patients receiving APX3330.

Patient diagnoses:

PancColonMelanoma

DEPs with <1.5-fold change (FC) are shown as grey bars.

White bars represent proteins not detected.

Panc Colon Melanoma

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Big Data Training for Cancer Research

Confirmed target engagement: Proteins altered downstream of APE1 regulated transcription factors

Proteins altered downstream of APE1/Ref-1 regulated

transcription factors HIF1a, NFkB and STAT3 by APX3330

in melanoma patient

HIF1 NFkB STAT3

Heatmap of APE1 protein levels which were reduced

following APX3330 treatment in the melanoma patient with

SD > 1 year.

Panc Colon Melanoma

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Big Data Training for Cancer Research

Pharmacokinetic Analyses: Results were as predicted for APX3330 plasma concentrations

PK analysis performed by Robert Stratford, Clin Pharm

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Big Data Training for Cancer Research

Clinical Trial Acknowledgements:• Richard A. Messmann – CMO, Apexian Pharmaceuticals• Safi Shahda - IU Cancer Center (now at Eli Lilly)• Nehal J. Lakhani - START Midwest• Bert O’Neil - IU Cancer Center (now at Eli Lilly)• Lincy Chu - Epic Sciences• Amanda K. Anderson – Epic Sciences• Jun Wan – Medical Genetics, Bioinformatics, IUSM• Amber L Mosley – Biochemistry and Molecular Biology, Director Proteomics Core• Hao Liu – Biostatistics, IUSM• Randy Wireman – Research Analyst, IUSM• Robert Stratford – IUSM

Academic Studies Supported by:The National Institutes of Health, National Cancer Institute grants: CA167291-06, CA167291-06S1, CA205166, and CA231267Betty and Earl Herr Chair in Pediatric Oncology Research, Tom Wood Foundation, Tom Wood Cares, Jeff Gordon Children’s Research Foundation and the Riley Children’s Foundation.

Disclosure: • Subcontract funding from Apexian Pharmaceuticals.• Chief Scientific Founder and CSO of Apexian Pharmaceuticals.

Page 47: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

One target, one drug family: multiple indicationsPipeline of APX small molecules

The Target

XPrototype:APX3330

Completed phase I trial

TFs

NFkBHIF1aSTAT3

CancerPhase I Clinical Trial Completed

Ophthalmology(DME, DR, AMD)

Planned Phase 2 trial in DME/DR – IND approved

Inflammatory Bowel Disease (IBD)

Colitis, Crohn’s

Anti-CIPN

Page 48: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

APX3330 Unique Dual Action MOARationale for Potential Efficacy in Diabetic Retinopathy and DME

v APX3330 is a small molecule oral tablet drug candidate and a first-in-class inhibitor of the Ref-1 protein

v Ref-1 is a novel target in ocular diseasev Dual MOA uniquely decreases both abnormal

angiogenesis and inflammation by blocking pathways downstream of Ref-1v Blocks HIF-1a to reduce VEGF signalingv Blocks NF-kB to modulate VEGF, TNF-α and other

inflammatory cytokines

Avastin and similar compounds

steroids

Page 49: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

One target, one drug family: multiple indicationsPipeline of APX small molecules

XPrototype:APX3330

Completed phase I trial

The Target

TFs

NFkBHIF1aSTAT3

CancerPhase I Clinical Trial Completed

Ophthalmology(DME, DR, AMD)

Planned Phase 2 trial in DME/DR – IND approved

Anti-CIPN

Inflammatory Bowel Disease (IBD)

Colitis, Crohn’s

Page 50: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

APE1/Ref-1 signaling and effect of APX3330 in IBD Winnie Mouse Model

Sahakian L, Filippone R, Stavely R, Robinson A, Yan X, Abalo R, Eri R, Bornstein J, Kelley MR, Nurgali K. (2020) Inhibition of APE1/Ref-1 redox signallingalleviates intestinal dysfunction and enteric nervous system damage in a mouse model of chronic colitis, Inflammatory Bowel Disease, in press

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APX3330 corrects severity of inflammation in Winnie IBD mouse modelThe Winnie mouse, carrying a missense mutation in Muc2, is a model for chronic intestinal inflammation

demonstrating symptoms closely resembling inflammatory bowel disease (IBD).

Control Winnie-Sham Winnie-APX3330 A

B

Severity of intestinal inflammation indicated by presence of rectal prolapse with blood vessel proliferation and oedema.

Images taken at day 14 of treatment in control, Winnie-Sham and Winnie-APX3330 treated mice.

Control Winnie-Sham Winnie-APX3330

Histological Scoring

***15

10

10

5

0

Scor

es /

Arb

Uni

ts

Winnie-APX3330Control Winnie-Sham

C

**** ^^^^

Winnie-Sham

Winnie-APX3330Control

Sahakian L, Filippone R, Stavely R, Robinson A, Yan X, Abalo R, Eri R, Bornstein J, Kelley MR, Nurgali K. (2020) Inhibition of APE1/Ref-1 redox signalling alleviates intestinal dysfunction and enteric nervous system damage in a mouse model of chronic colitis, Inflammatory Bowel Disease, in press

Page 52: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

APX3330 corrects colonic contractile activity in IBD mice

5mm

Control Winnie-Sham Winnie-APX3330

Total Lengthsof Colonic Contractions

****** ^̂ ^̂

Leng

th(%

)

Colo

n w

idth

(mm

)

100s

ORAL ANAL

Control Winnie-Sham

Winnie-APX3330

80

60

40

20

0

Sahakian L, Filippone R, Stavely R, Robinson A, Yan X, Abalo R, Eri R, Bornstein J, Kelley MR, Nurgali K. (2020) Inhibition of APE1/Ref-1 redox signalling alleviates intestinal dysfunction and enteric nervous system damage in a mouse model of chronic colitis, Inflammatory Bowel Disease, in press

Page 53: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Control Winnie-Sham Winnie-APX3330

APX3330 reduces oxidative stress levels back to control levels in the Myenteric Plexus

AMITOSOX

0

50

100

150

200 **** ^^^^

Fluo

resc

ence

/ Ar

bU

nits

Winnie-Sham

Winnie-APX3330

Control

MitosoxB

20

15

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5

0

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Tran

sloc

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HM

GB1

C

ellC

ount

Winnie-Sham

Winnie-APX3330

Control

HMGB1 Translocation within the Myenteric Plexus

** ^^

C

Sahakian L, Filippone R, Stavely R, Robinson A, Yan X, Abalo R, Eri R, Bornstein J, Kelley MR, Nurgali K. (2020) Inhibition of APE1/Ref-1 redox signalling alleviates intestinal dysfunction and enteric nervous system damage in a mouse model of chronic colitis, Inflammatory Bowel Disease, in press

Page 54: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

APX3330 protects myenteric neurons from DNA damage in IBD colon model

GFAPControl Winnie-Sham Winnie-APX3330

0

80

60

40

20

100

** ^

Nor

mal

ised

GFA

P

Den

sity

(%)

Winnie-Sham

Winnie-APX3330

Control

GFAP

Control Winnie-Sham Winnie-APX3330

Control Winnie-Sham Winnie-APX3330

DN

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Control Winnie-Sham Winnie-APX3330

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mal

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age

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DNA Damage Neuronal Count

DNA Damage

DN

AD

amag

e

Den

sity

(%)

Winnie-Sham

Winnie-APX3330

Control0

5

10

15

20

25**** ^^^^

0

20

40

60

80

*** ^^^

Com

bine

d

Similar APX neuronal protection observed in CIPN models:

Neural Regen Res. 2017 Jan;12(1):72-74. J Pharmacol Exp Ther. 2016 Nov;359(2):300-309. MutatRes. 2015 Sep;779:96-104. PLoS One. 2014 Sep 4;9(9):e106485.

Sahakian L, Filippone R, Stavely R, Robinson A, Yan X, Abalo R, Eri R, Bornstein J, Kelley MR, Nurgali K. (2020) Inhibition of APE1/Ref-1 redox signalling alleviates intestinal dysfunction and enteric nervous system damage in a mouse model of chronic colitis, Inflammatory Bowel Disease, in press

Page 55: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

One target, one drug family: multiple indicationsPipeline of APX small molecules

XPrototype:APX3330

Completed phase I trial

The Target

TFs

NFkBHIF1aSTAT3

CancerPhase I Clinical Trial Completed

Ophthalmology(DME, DR, AMD)

Planned Phase 2 trial in DME/DR – IND approved

Anti-CIPN

Inflammatory Bowel Disease (IBD)

Colitis, Crohn’s

Page 56: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

APE1 Repair & Nuclease Functions- BER:

- Endonuclease, exonuclease- 3ʹ phosphodiesterase- 3ʹ to 5ʹ exonuclease

- NIR: processes oxidative damage not repaired by BER- RNA metabolism

NF-KB, HIF1a, STAT3, AP-1, p53

1 318

H309D210C99C65

Lys6/7 ArgNuclear to cytoplasm

Lys98NIR

Asp210General nuclease

Agr177BER

coordination

Asp703ʹ-phosphodiesterase

Phe2663ʹ to 5ʹ exonuclease

FUNCTIONS

Regions

APPLICATIONSAnti-inflammation, anti-neovascularization for

cancers, CIPNocular diseases (AMD, DME, DR) and IBD

Inhibition of DNA repair for anti-cancer treatment (including

reversal of drug resistance)

289-318Mitochondrial

Targeting Sequence

Diagnosis based on secretory levels (Serum and Urine)

C93

35 127Redox Region

DNA repair and nuclease region

E96

Page 57: Big Data Training for Cancer Research...Big Data Training for Cancer Research Out of the lab and into the clinic: Translating basic science discoveries into new treatments for patients

Big Data Training for Cancer Research

Acknowledgements: • Collaborators

• Dr. Melissa Fishel• Olivia Babb• Dr. Silpa Gampala

• Dr. Millie Georgiadis (biochemistry)• Dr. Tim Corson (eye)• Dr. Jill Fehrenbacher (CIPN)• Dr. Kulmira Nurgali (Australia - IBD)• Dr. Travis Jerde (prostate/bladder)• Dr. Reuben Kapur (AML)• Dr. Karen Pollok (in vivo therapeutics)• Dr. Chi Zhang and Jun Wan (C3B

bioinformatics)• Dr. Andrew Tee (Cardiff- TSC/MPNST)• Dr. Amber Mosley (proteomics)• Dr. Gianluca Tell (Italy – APE1 studies)

ü Randy Wireman – Research Analystü Rachel Caston – Postdoctorateü Lee Armstrong – MS graduate studentü Fenil Shah, PhD P -- ex-Postdoctorateü Derek Logsdon – ex-Graduate Student

Supported by:

The National Institutes of Health, National Cancer Institute RO1CA205166, RO1CA231267, RO1CA167291, RO1CA167291-S1, RO1HL140961, DOD W81XWH1910217

Betty and Earl Herr Chair in Pediatric Oncology Research, Tom Wood Foundation, Tom Wood Cares, Jeff Gordon Children’s Research Foundation and the Riley Children’s Foundation.

Disclosure: • Subcontract funding from Apexian Pharmaceuticals.• Chief Scientific Founder and CSO of Apexian Pharmaceuticals.