Mining Cancer Cell Lines Databases: NCI-60, COSMIC, CCLE and Beyond

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1 Mining Cancer Cell Lines Databases: NCI-60, COSMIC, CCLE and Beyond Aik Choon Tan, Ph.D. Associate Professor of Bioinformatics Division of Medical Oncology Department of Medicine 11/1/2016

2 Outline Cancer Cell Lines to study human cancer biology preclinical model for drug discovery and development Cancer Cell Lines Resources NCI-60 Catalog of Somatic Mutations in Cancer (COSMIC) Cancer Cell Lines Encyclopedia (CCLE) Genentech Cancer Cell Line Screening Initiative (gcsi) Beyond Cancer Cell Lines Patient-derived tumor xenografts (PDX) XactMice Humanized Mice

3 HeLa First cancer cell lines Derived from cervical cancer patient (Henrietta Lacks) in 1951 at Johns Hopkins The cell line was found to be remarkably durable and prolific Contamination of many other cell lines used in research

4 HeLa HeLa cells were also the first human cells to be successfully cloned in 1955 by Theodore Puck and Philip I Marcus at the University of Colorado, Denver. PNAS (7)

5 Cancer Cell Lines as Preclinical Models for Studying Human Cancers Model Systems Model Tumor Cancer Patients Identify targets of genetic alterations Mechanistic studies Perturbagen data Genetic/Molecular Information Tumor dependency Response to treatments Resistance mechanisms

6 Cancer Cell Lines Resources for Drug Development

7 NCI-60

8 GI50 (50% growth inhibition) LC50 (50% lethal concentration) TGI (total growth inhibition) NCI-60

9 NCI-60

10 NCI-60 DTP website

11 NCI-60 DTP website

12 NCI-60 DTP website

13 NCI-60 DTP website

14 NCI-60 Mean GI50 Graph

15 NCI-60 Dose-Response Curves

16 Download Data

17 Molecular Target Data

18 Coming Soon: NCI ALMANAC (Slides from Susan Holbeck, NCI)

19 Coming Soon: NCI ALMANAC (Slides from Susan Holbeck, NCI)

20 Catalogue of Somatic Mutations in Cancer (COSMIC)

21 Querying Gene Mutation in COSMIC

22 Querying Gene Mutation in COSMIC

23 Querying Gene Mutation in COSMIC

24 Querying Gene Mutation in COSMIC

25 Querying Gene Mutation in COSMIC

26 Querying Gene Mutation in COSMIC

27 Querying Cancer Cell Line in COSMIC

28 Genomics of Drug Sensitivity in Cancer (GDSC COSMIC)

29 639 cell lines treated with 130 drugs

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33 Analytical Framework for Biomarkers Discovery in GDSC Cell Lines Data Mut Data CNV Data Epi Data Exp Data Drug Sensitivity Data Feature Selection Analytical Models ANOVA Elastic Net Logic Models Putative Biomarkers

34 Querying Drug in GDSC

35 Volcano Plot

36 Querying Drug in GDSC

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38 Correlating Mutation with Drug

39 Correlating Mutation in Specific Tumor Type

40 High Confidence Drivers

41 Stringent Filters using HCD -3X 3X 143,000 drug-gene interactions 2,286 significance associations (p < 0.05, FDR < 20%) FDR 1% FDR 20%

42 GDSC 2.0

43 GDSC Download

44 978 cell lines treated with 24 drugs

45 Cancer Cell Lines Encyclopedia (CCLE) (Broad and Novartis)

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50 Analysis Tools in CCLE

51 Reproducibility between CCLE & GDSC?

52 Reproducibility between CCLE & GDSC?

53 Genentech Cancer Cell Line Screening Initiative (gcsi)

54 Genentech Cancer Cell Line Screening Initiative (gcsi)

55 Cancer Therapeutics Response Portal

56 Project Achilles - CCLE

57 A Word of Caution

58 Moving Forward

59 Patient-Derived Tumor Xenografts (PDTX)

60 Patient-Derived Tumor Xenografts (PDTX)

61 Patient-Derived Tumor Xenografts (PDTX)

62 Patient-Derived Tumor Xenografts (PDTX)

63 Patient-Derived Xenografts Encyclopedia (PDXE) (~1000 PDX models) Model Systems Model Tumor Cancer Patients Identify targets of genetic alterations Mechanistic studies Perturbagen data Genetic/Molecular Information Tumor dependency Response to treatments Resistance mechanisms

64 NIBR PDXE

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67 Immunotherapy in Cancer Treatment

68 Immunotherapy in Cancer Treatment

69 XactMice

70 XactMice

71 XactMice

72 Humanized Mice

73 Lessons Learned

74 Take Home Message Cancer cell lines capture the genomic features of human cancers Comprehensive characterization of the cancer cell lines served as rich resources for studying human cancer biology Pharmacogenomics profiling in cancer cell may identify putative biomarkers of drug response for future validation