8/6/2011. John Mendelsohn Gordon Mills. Stan Hamilton Gordon Mills

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1 Sheikh Zayed bin Sultan Al Nahyan Institute for Personalized Cancer Therapy John Mendelsohn Gordon Mills Robert J. Kleberg Jr. and Helen C. Kleberg Center For Molecular Markers Stan Hamilton Gordon Mills POTENTIAL CONFLICT OF INTEREST DISCLOSURES Financial Relationships SAB/Consultant: Asuragen, Aushon, Catena, Daiichi Pharmaceuticals, Foundation Medicine, Komen Foundation Stock/ Options/Financial: Aushon, Catena, PTV Ventures Sponsored Research: AstraZeneca, Celgene, CeMines, Exelixis, GSK, LPATH, Roche, SDI, Wyeth/Pfizer A SYSTEMS APPROACH TO DELIVERING ON THE PROMISE OF PERSONALIZED MOLECULAR MEDICINE I will discuss off label use and/or investigational use of drugs Targeted Therapy For Cancer Tumor Capitalizing on the vulnerabilities (Achilles Heel) of cancer Most Effective Targeted Agents Are Linked to Response Prediction Biomarkers Imatinib mesylate CML BCR-ABL translocation Oncogene addiction (1982) Imatinib mesylate Sunitinib Nilotinib Dasatinib Trastuzumab Pertuzumab Lapatinib Gefitinib, Erlotinib Cetuximab PKC412, SU11248, CMT53518 GIST Dermatofibrosarcoma protuberans Hypereosinophylic syndrome Melanoma c-kit mutation PDFGR mutation *Except VEGFR and proteosome inhibitors Oncogene addiction (1999) Breast amplification Oncogene addiction (1985) Lung cancer Bowel AML, ALL EGFR mutation Oncogene addiction (2004) FLT-3 mutation, tandem duplication Oncogene addiction (1996) PARP inhibitors Breast Ovarian BRCA1/2 mutation Synthetic lethality (2005) PLX4032 Melanoma BRAF (8 years) Oncogene addiction (2002) Crizotinib Lung EML-4 ALK (2 years) Oncogene addiction (2007) Tamoxifen, AIs Breast cancer ER expression Lineage (1800s) A TARGETED THERAPY TOOLKIT OFFERS THE OPPORTUNITY TO RAPIDLY LINK GENOMIC ABERRATIONS AND THERAPIES Hundreds of compounds in the developmental pipeline CAPITALIZE ON THE PERFECT STORM LET THE PATIENT TEACH US Ability to Characterize Tumor Drug Toolkit DRUGS IN DEVELOPMENT Cancer 878 Breast 125 Colorectal 82 Lung 120 Leukemia 119 Skin 86 Twenty billion dollar annual investment 1

2 UNEXPECTED HIGH RATE OF FAILURE OF TARGETED THERAPEUTICS Even for patients with the biomarker only subpopulations of patients benefit: Usually short term Three resistance mechanisms Intrinsic (Genetic) Selected (Genetic) Adaptive (Homeostatic loops, cross talk and bypass) Rationale combinatorial therapy Systems are robust to single perturbations. Tumors exhibit decreased robustness and may be more sensitive to multiple perturbations CHALLENGES TO PERSONALIZED TARGETED THERAPY PERSONALIZED MEDICINE Targeting the underlying genomic aberrations driving tumor progression (1980) Input Black Box Output INFORMATION OVERLOAD High throughput technology generates data but not knowledge Too many connections and information to integrate and visualize efficiently Much of the data is contextual and not generalizable Time dependent, spatial, homeostatic loops, pathwayness, cell cell interactions CANCER IS A SPECIAL CASE DUE TO MUTATIONS AND INSTABILITY LEADING TO NETWORK REWIRING DRUG Black Box 2

3 UNEXPECTED HIGH RATE OF FAILURE OF TARGETED THERAPEUTICS SIGNALING PATHWAYS ARE UNDER HOMEOSTATIC CONTROL Dynamical Network Robust Predict homeostatic loops Unexpected components Biology Medicine Genetics Mathematics Physics Computer Science Sensitivity Analysis Predict effects of degree of inhibition of specific nodes Combinatorial Targets Predict mechanisms to bypass homeostatic loops ROBUST PREDICTIVE MATHEMATICAL MODELS EMERGENT PROPERTIES (not intuitively obvious) Prahlad Ram, Debra Smith, Mandri Obeyesekere, Yiling Lu EXTRACELLULAR Initial Evidence MATRIX that Extracellular PROTECTS CELLS Matrix FROM EFFECTS Protects OF from TARGETED Drug-Induced THERAPEUTICS Killing 3D culture system Joan Brugge Explore role of microenvironment EXTRACELLULAR Initial Evidence MATRIX that Extracellular PROTECTS CELLS Matrix FROM EFFECTS Protects OF from TARGETED Drug-Induced THERAPEUTICS Killing 3D culture system Joan Brugge Explore role of microenvironment Allow cells to form spheroids Tubulin PI3K/mTOR Add drug PI3K/mTOR PI3K/mTOR PI3K MEK Determine effects on cell viability Harvest cells for analysis G. Gao EXTRACELLULAR MATRIX PROTECTS CELLS FROM Example of a protective microenvironment EFFECTS OF TARGETED THERAPEUTICS IN VIVO SUM225 + cells - Intraductal injection Lapatinib EXTRACELLULAR Initial Evidence MATRIX that Extracellular PROTECTS CELLS Matrix FROM EFFECTS Protects OF from TARGETED Drug-Induced THERAPEUTICS Killing ALTERNATIVE HYPOTHESES A. Extracellular matrix induces an intrinsic signaling program that renders cells resistant to therapy? Jason Zoeller, Joan Brugge A. Targeted therapeutics interrupt normal cellular signaling networks induced by extracellular matrix resulting in an adaptive response that generates drug resistance TEST USE FUNCTIONAL PROTEOMICS TO DETERMINE EFFECT OF MATRIX AND TARGETED THERAPEUTIC 3

4 Functional Proteomics REVERSE PHASE PROTEIN ARRAYS Quantitative high throughput multiplexed inexpensive ELISA Protein printed on slide: each slide developed with a single antibody Femtogram sensitivity ng of starting protein 1000 samples per slide with 1000 controls 300 validated antibodies Dot blot: Less sensitive to degradation Require high quality validated antibodies and robotics HUMAN PROTEOMICS ATLAS TCGA (Breast, ovary, GBM, Endo, RCC) 2000 breast cancers 750 ovarian cancers 1500 leukemias 250 endometrial Cell Line Encyclopedia 1000 cell lines 38,000 in total 50 publications Nature Genetics Molecular Cell Cancer Cell Cancer Discovery CCSG Core Web Site Functional proteomics Duplicate Spotting Reliability Raoul Tibes 5nanogram of starting lysate femotgram of target R 2 =.996 ERK pmapk Stat3 pstat3 705 Akt pakt473 Breast Cancer Proteomics Atlas TCGA (Log) samples 210 Antibodies Median Centered Unsupervised Hierarchical Cluster PR ER/pER Gata3 AR INPP4B IGFR1 Claudin 7 Cyclin E/B MSH6 MLH2 A catenin B catenin E cadherin Bim PR ER/pER Gata3 AR INPP4B IGFR1 Nancy Shih EGFR/pEGFR 1068 /p 1248 Collagen Caveolin CD31 p53 CHK1/2 Rab25 Signaling Cluster pyap, pfoxo3a, pp38, PMAPK, pyb1, psrc, pmek, p, pjun BASAL UNKNOWN 1 STROMAL 1? UNKNOWN 2 STROMAL 2? LUMINAL B? LUMINAL LUMINAL A? TOWARDS A PROTEOMIC CLASSIFICATION OF BREAST CANCER(n=712) 140 markers 5 ER/Luminal Basal Stromal Signaling off 3 2 Bryan Hennessy Ana Gonzalez Roshan Agarwal Zhenlin Ju Stromal Signaling on TOWARDS A PROTEOMIC CLASSIFICATION OF BREAST CANCER(n=712) 140 markers P< log rank p< Bryan Hennessy Ana Gonzalez Roshan Agarwal Zhenlin Ju Inhibition of PI3K and mtor with Induces Activation of Survival Pathways Increased signal with BEZ Decreased signal with BEZ Laura Selfors Joan Brugge Yiling Lu Months ER/Luminal Basal Stromal Signaling off Stromal Signaling on OV2008-rep1 OV2008-rep2 OV2008-rep3 OV2008-exp1 SKOV3-rep1 SKOV3-rep2 SKOV3-rep3 p4ebp p4ebp pfoxo3a p4ebp Ratio of BEZ treated to un treated 4

5 Inhibition of PI3K and mtor with Induces Activation of Survival Pathways Increased signal with BEZ Decreased signal with BEZ Inhibition of PI3K and mtor with Induces Activation of Survival Pathways Increased signal with BEZ Decreased signal with BEZ IGF-1R p p pstat3 BCL-2 pegfr OV2008-rep1 OV2008-rep2 OV2008-rep3 OV2008-rep1 OV2008-rep2 OV2008-rep3 OV2008-exp1 OV2008-exp1 SKOV3-rep1 SKOV3-rep2 SKOV3-rep3 SKOV3-rep1 SKOV3-rep2 SKOV3-rep3 p4ebp p4ebp pfoxo3a p4ebp Ratio of BEZ treated to un treated Laura Selfors Yiling Lu Ratio of BEZ treated to un treated 4EBP1 4EBP1 4EBP1 4EBP1 5

6 8/6/2011 CART PREDICTS RATIONAL COMBINATIONS GENERALIZABLE ACROSS CELL LINES p53 p16 SMAD4 PIK3CA KRAS P16 SMAD4 and inhibition demonstrate synthetic lethality PIK3CA, PIK3CA p53 complete semi-disintegrated disintegrated GENETIC EPISTASIS: protects from EGFR inhibitor and not inhibitor Synthetic Lethality: Presence of PI3K PTEN Linear: Genetic epistasis Inhibition of each component would have marked effects on cell survival the effects Enforced Bcl2 expression would reverse of upstream inhibitors Convergence: Multiple pathways converge on Inhibition of each component would have little or no effect Taru Muranen 4EBP1 EXTRACELLULAR MATRIX PROTECTS CELLS FROM EFFECTS OF TARGETED THERAPEUTICS IN VIVO SUM225 + cells - Intraductal injection Summary PI3K-mTOR inhibition Increased pampk Fibronectin Annexin EGFR PTEN P27 p Vehicle (Log 2) P38 BCLx BCLxl pstat3 IGF1R PI3K-mTOR + lapatinib Joan Brugge Increased Jason Zoeller Decreased CyclinD1 pegfr pyb1 pacc prb p PRAS40 p4ebp p BCL-2 IGF-R1 prsk pegfr etc. BCL-2 inhibitor IGF-R1 shrna prsk shrna pegfr inhibitor Combinatorial Adaptive Resistance Therapy CART Caspase

7 COLLABORATORS MILLS LAB PI3K/Networks/Protein Arrays Yiling Lu Wei Guo Fabiana Morales Shuangxing Yu Qinghua Yu Dong Zhang Doris Siwak Bioinformatics Roel Verhaak Han Liang Wenbin Liu Zhenlin Ju Fan Zhang BRUGGE LAB Laura Selfors Jason Zoeller John Albeck Grace Gao Breast cancer team Funda Meric Bryan Hennessy Ana Gonzalez-Angulo Ana Lluch Sam Aparicio Chuck Perou Harvard Department of Cell Biology 7