GENOMIC BIOMARKERS TO PREDICT CANCER DRUG RESPONSE. Dan Rhodes PhD Compendia Bioscience October 26, 2011

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1 GENOMIC BIOMARKERS TO PREDICT CANCER DRUG RESPONSE Dan Rhodes PhD Compendia Bioscience October 26, 2011

2 Rationale» Cancer is a set of genetic diseases.» Rational development of cancer therapeutics requires an understanding of the genetic biomarkers associated with drug response.» New approaches are needed to efficiently identify predictive biomarkers for targeted cancer therapies and to place them into clinical context.

3 Large cell line panels as genomic biomarker discovery platforms» Cancer cell lines as model systems to investigate the link between genomic aberrations and drug sensitivity» McDermott et al PNAS

4 Systematic identification of predictive biomarkers and their clinical application Cell Line Response Biomarker Discovery Clinical Population Analysis

5 Cell Line Response Cell Line Response Biomarker Discovery Clinical Population Mapping Response to treatment characterized in a multi-cancer cell line panel 240 cell lines across diverse cancer types Multiple cell proliferation endpoints considered Cell lines ranked by IC 50, POC, GI 50 and designated sensitive or resistant

6 Biomarker Discovery Cell Line Response Biomarker Discovery Clinical Population Mapping Integrate sensitivity and resistance calls with genomic data Test associations between cell line response and biomarkers Biomarkers: Gene mutations, DNA copy aberrations, mrna over-expression, gene co-expression clusters/modules, gene signatures, composite pathway biomarkers Multi-variate analysis

7 Clinical Population Mapping Cell Line Response Biomarker Discovery Clinical Population Mapping Characterize biomarker profiles across 50,000+ clinical tumor samples annotated using the same biomarker designations Prioritize clinical populations and sub-populations for clinical development Optimize biomarker profile for clinical tumors

8 Parallel preclinical and clinical biomarker databases

9 CI-1040: Cell Line Response sensitive cell lines IC50 (µm) resistant cell lines 10.0

10 CI-1040: Summary of Biomarker Discovery RAS/RAF Pathway Mutation Resistance Signature Sensitivity Signature ERBB Signaling Pathway Overex BRAF Mutation KRAS Mutation KRAS Mutation

11 RAS/RAF pathway mutations were highly enriched in sensitive cell lines IC50 (µm) 0.1 BRAF and KRAS BRAF KRAS HRAS NRAS WT

12 RAS/RAF pathway mutations were distributed across cancer types IC50 (µm) 0.1 BRAF and KRAS BRAF KRAS HRAS NRAS WT General Cancer Type

13 Custom gene signatures for sensitivity and resistance to CI-1040 Analysis Differential expression analysis of sensitive and resistant cell lines Ranking Rank genes by p-value according to Student s two class t-test Custom Signatures Top 1% of genes differentially upregulated in sensitive and resistant cell lines 0.1 Sensitivity Signature Resistance Signature IC50 (µm)

14 CI-1040 sensitivity signature What drugs modulate signature? What pathways activate signature? What tumor populations show activated signature? What genes would serve as best biomarkers?

15 CI-1040 signature analysis

16 Mutations + Signature IC50 Ras/Raf PIK3CA Signature Sensitive Resistant

17 Clinical Tumor Population Analysis Biomarker Category Data Source # Patients Mutations COSMIC, TCGA ,000 AmpDels Oncomine 6,000 Gene Overexpression Oncomine 50,000» Clinical Population Frequency Toolset» Integrated Gene Browser» Uber133 (Quantile normalized Gene expression browser)

18 RAS/RAF pathway mutations in clinical tumors Mutation frequency

19 Signature scoring across clinical tumor populations Melanoma Colorectal cancer Breast Cancer Brain and CNS 14,992 Clinical tumor specimens 146 datasets

20 Mutations + Signature in clinical tumor populations Colorectal cancer Gastric cancer Melanoma Esophageal cancer Pancreatic cancer

21 Summary» Cell line profiling platform is capable of identifying novel & expected biomarkers» RAS/RAF mutations and custom gene signatures provided the best ability to segregate sensitive and resistant cell lines» MEK signature may identify RAS/RAF mutant tumors with activated pathway

22 Applications of a systematic predictive biomarker discovery platform» During lead development, how do candidates differentiate from each other or from precedented compounds?» Once clinical candidates are selected, what are the biomarkers of response and clinical populations with matching biomarker profiles?» Post-approval, what is an objective, scientific rationale for new indications discovery?» And how can the potential of in-licensed compounds be efficiently investigated?

23 Acknowledgments» Compendia Bioscience» Wendy Lockwood Banka» Sean Eddy» Mark Tomilo» Peter Wyngaard» Paul Williams» Dan Rhodes» Ricerca Biosciences» Yulia Ovechkina» Christine O Day» Usha Warrior