What is Precision Medicine?

Transcription

1 Precision Medicine and the Treatment of Cancer Carlos L. Arteaga, MD Center for Cancer Targeted Therapies VICC Breast Cancer Program Vanderbilt-Ingram Cancer Center (VICC) Departments of Medicine and Cancer Biology Vanderbilt University School of Medicine What is Precision Medicine? An approach for disease treatment and prevention that takes into account individual variability in genes, environmentand lifestyle for each person For cancer treatment, precision medicine involves the identification of actionable gene alterations (biomarkers) in tumor DNA that can be used to select therapies that will be most effective Best actionable biomarkers are those alterations that a) drive cancer progression, and b) are uniquely expressed or only altered in cancer cells (i.e., mutations, gene deletions) compared to normal cells

2 Outline Examples of driver oncogenes representing actionable therapeutic targets in cancer Approaches to identify targetable somatic alterations in cancer Adaptive and acquired resistance to molecularly targeted therapies Genotype-specific or basket (tumor site agnostic) clinical trials Patients with breast cancers harboring HER2 (ERBB2) gene amplification have a poor outcome 100 Percentage survival p< HER2-negative HER2-positive Slamon et al. Science 235:177-82, 1987 Pauletti et al. JCO 18: , 2000 Witton et al. J Pathol. 200:290, Years

3 HER2 (ERBB2) is an oncogene Control HER2 HER2 Soft Agar Trastuzumab (Humanized IgG 1 ): Mechanisms of action Cytostatic Receptor downregulation Reduces signaling: MAPK, Akt Decreases cyclin D1 levels Induces p27 kip1 and p27 kip1 - Cdk2 interaction Reduced S phase Increased G1 Inhibits angiogenesis Cytotoxic ADCC DNA repair: synergy with chemotherapies Apoptosis HER2 epitopes recognized by hypervariable murine antibody fragment Human IgG-1

4 Clinical development of trastuzumab: Challenges and opportunities of precision medicine HER2 HER2 HER2 Breast Cancer Precision drugs are targeted to specific cancer genes Yap et al. Nat Rev Cancer 10: , 2011 Trastuzumab improves time to progression in patients with HER2 overexpressing metastatic breast cancer Probability Trast Chemotx (n = 235) Median TTP = 7.4 mon Chemotx alone (n = 234) Median TTP = 4.6 mon Effect limited to HER2 tumors Slamon DJ, et al. N Engl J Med. 2001;344(11): P < Months When trastuzumab was first approved based on the results above, few thought it would have such a profound effect on the course of HER2 breast cancer

5 Adjuvant trastuzumab improves disease-free survival in patients with HER2 early breast cancer H = Trastuzumab (Herceptin) Updated N9831/B-31 Joint Analysis Overall Survival* % 95.9% 94.6% 92.7% 92.6% 89.4% AC TH AC T Alive (%) (36%) of the 710 events needed for final analysis have occurred unadjusted HR=0.65 (95%CI: ) P= Small survival difference, but likely to increase over time. 20 1,886 1, Number 1,863 1, at risk Follow-up (yrs) Perez et al, *Intent ASCO to treat 2007

6 Trastuzumab and pertuzumab disrupt different types of HER2/HER3 heterodimers CLEOPATRA Junttila TT et al. Cancer Cell 15:429, 2009 Processing and mechanism of action of trastuzumab-dm1 Linker: MCC (non-reducible, not cleavable) Derivative of Maytansine Trastuzumab HER2 T-DM1 Emtansine release Inhibition of microtubule polymerization Lysosome P P P Internalization Nucleus

7 In 2016, 90% of women diagnosed with early (operable) HER2 breast cancer will likely be cured Initial Randomized Trial Demonstrating Benefit of Trastuzumab 2002 Three Large Adjuvant Trials Lapatinib Reported Approved Phase II Randomized Trial of T DM Phase III of Pertuzumab 2012 Pertuzumab Preop Approval 1998 First Preoperative Trials Reported Initial Trials 2010 Of T DM1, Pertuzumab, Neratinib Preoperative Trials of Dual Blockade 2011 Phase III of T DM1 vs Cape/Lap 2013 Oncogene dependence or synthetic lethality: DNA alterations predict response to therapy (~2004) Gene mutation, amplification, deletion Disease Active Drug BCR-ABL CML imatinib, dasatinib Mutant Kit, PDGFR GIST imatinib Mutant EGFR NSCLC gefitinib, erlotinib HER2 (ERBB2) Breast cancer trastuzumab, lapatinib, T-DM1, pertuzumab PDGFR CMML imatinib BRCA1/2 Breast/Ovarian PARP inhibitors

8 40% Somatic Gene Alterations in 128 Cancer Relevant Genes in 962 Breast Cancers in TCGA 35% 30% 25% 20% Which of these are therapeutically actionable? 15% 10% 5% 0% PIK3CA MYC AKT3 MCL1 FGFR1 DDR2 PTEN GNAS RARA MAP2K4 NF1 IGF1R CDKN2A RUNX1 ATM ETV6 NTRK3 CDKN1B CCND2 ESR1 KRAS FBXW7 ROS1 BCL2 ERBB4 KMT2A WT1 JAK3 FLT3 SMAD4 ATR RAF1 BRAF ASXL1 NUTM1 MSH2 ETV1 AKT1 MSH6 KDR TMPRSS2 NFKBIA PDGFRA RET ALK CDK6 TET2 CRKL EWSR1 HRAS STK11 EPHA3 EZH2 NKX2 1 BAP1 MEN1 GNA11 BRD2 MAP2K1 SMARCB1 NRAS PDGFRB MAPK1 CTNNB1

9 How to define an actionable therapeutic target in cancer? Genotype to phenotype Gene alteration results in gain of function and is causal to tumorigenesis and/or cancer progression Tumor cells with the alteration are inhibited when this gene mutation is targeted Phenotype to genotype Identification of the genetic basis for extraordinary responses to molecularly targeted therapies Would this genotype then guide patient selection for clinical trials with targeted therapies? Nature 448:561-6, 2007

10 Best responses with crizotinib in 82 patients with lung adenocarcinoma with an EML4 ALK translocation Maximum Change in Tumor Size (%) PD SD Confirmed PR Confirmed CR FDA Approval: August 26, 2011 For patients with locally advanced or metastatic ALK NSCLC Kwak et al., NEJM 2010 How to define an actionable therapeutic target in cancer? Genotype to phenotype Gene alteration results in gain of function and is causal to tumorigenesis and/or cancer progression Tumor cells with the alteration are inhibited when this gene mutation is targeted Phenotype to genotype Identification of the genetic basis of extraordinary responses to molecularly targeted therapies Would this genotype then guide patient selection for clinical trials with targeted therapies?

11 Extraordinary response of patient with breast cancer to HER2 (ERBB2) tyrosine kinase inhibitor neratinib ERBB2 mutant (L755_E757delinsS) ER/HER2 breast carcinoma Baseline 8 weeks 16 weeks Confirmed PR: 70% reduction by RECIST following neratinib monotherapy ERBB2 mutation hotspots across cancer types S310F Bladder: 1 Breast: 3 Cervical: 1 Colorectal: 2 Lung adeno: 2 Ovarian: 2 Stomach: 1 CCLE: 1 (bladder) L755S/M/P/W Breast: 4 Colorectal: 2 Endometrial: 1 Kidney (pap): 1 Melanoma: 1 Stomach: 1 CCLE: 3 (colorectal, stomach, brain) R678Q Breast: 1 Colorectal: 1 Endometrial: 1 Stomach: 2 CCLE: 1 (colorectal) ins Lung adeno: 6 CCLE: 1 (lung) V777L/A Breast: 1 Colorectal: 2 GBM: 2 V842I Breast: 1 Colorectal: 4 Endometrial: 2 CCLE: 4 (Lung, ovarian, endometrial) Rec L domain Furin like Rec L domain Kinase domain

12 ERBB2 (HER2) amplifications and mutations across cancer types March 27, 2014 SUMMIT study design (A4) EGFR mutant ERBB2 mutant tumors ERBB3 mutant ERBB4 mutant Primary brain tumors EGFR mutant/amplified Lung cancers with EGFR exon 18 mutations Breast cancer Biliary tract Bladder/urinary tract Colorectal Endometrial Gastro esophageal Lung Ovarian Solid tumors (NOS) Solid tumors (NOS) Solid tumors (NOS) Open label, multinational, multihistology phase 2 signal seeking study of neratinib as monotherapy or in combination in patients with tumors harboring EGFR, ERBB2, ERBB3 or ERBB4 mutations (NCT ) Neratinib 240 mg po daily (28 day cycle) Monotherapy or combination therapy in ERBB2 mutant cohort* PD or Toxicity Primary endpoint: Objective response rate (ORR) at 8 weeks Secondary endpoints: ORR (confirmed); Clinical Benefit Rate (CBR); PET CT; Progression Free Survival (PFS); Safety; Patient Reported Outcomes; Biomarkers Simon 2 stage design: If 1 response in first evaluable 7 patients expand cohort to Stage 2 (N=18); if 4 responses in Stage 2, then further expand cohort or consider breakout strategy Sample size: N 18 / cohort; N 30 for NOS cohorts CONFIDENTIAL *HR MBC fulvestrant or endocrine regimen CRC and NSCLC trastuzumab Bladder cancer paclitaxel

13 SUMMIT: distribution of ERBB2 mutations Receptor_L Furin Like Receptor_L GF_IV TM Tyrosine Kinase Domain # # & D251fs*1 R1153X D277G G292R N319D V659E R678Q V679L R814H L841V R970Q L869R E930D T862A ERBB2 GRB7 Fusion V842I P780_Y781InsGSP & G778A or G778_S779insCPG V777L & L755S / L755P L755_E757delinsS D769H / D769Y / D769N V773M G776V, G776VinsC or G776AinsVGC A775_G776insYVMA 12 bp exon 20 insertion S310F or S310Y ERBB2 mutation type Incidence (n=93) Single nucleotide variants 70% (65/93) Insertions/deletions 28% (26/93) Rearrangements 1% (1/93) Frameshift 1% (1/93) Tumor Legend Bladder NSCLC Cervical CRC Ovarian Kidney Ampullary Unknown Primary Endometrial MBC Liposarcoma Vagina SCC LCNEC Gallbladder Duodenal Gastroesophageal Cholangiocarcinoma Neuroendocrine small bowel Extramammary Paget s #,, &Coexisting mutations in same patient CONFIDENTIAL Data cut off 22 October 2015 Best change in tumor burden 100 RECIST PET response criteria 100 RECIST: change in tumor size (%) Cut off for RECIST PR: 30% * Limit for RECIST SD: 20% 76 * Change in PET SUV value (%) Mutation status *One patient had a response evaluation by both RECIST and PET response criteria and is therefore represented twice on this chart Hyman et al, 2015 SABCS Abstract PD5 05

14 Sample case: CR following neratinib fulvestrant therapy ERBB2 mutant (S310F) ER/HER2 lobular breast cancer Complete response by RECIST and PET response criteria after 8 weeks Patient had progressed on prior fulvestrant therapy Hyman et al, 2015 San Antonio Breast Cancer Symposium Somatic Gene Alterations in 128 Cancer Relevant Genes In 962 Breast Cancers in TCGA 40% 35% PI3 kinase/akt/mtor inhibitors 30% 25% 20% FGFR Inhibitors 15% CDK4/6 Inhibitors AKT Inhibitors 10% 5% MEK/ERK inhibitors 0% PIK3CA MYC AKT3 MCL1 FGFR1 DDR2 PTEN GNAS RARA MAP2K4 NF1 IGF1R CDKN2A RUNX1 ATM ETV6 NTRK3 CDKN1B CCND2 ESR1 KRAS FBXW7 ROS1 BCL2 ERBB4 KMT2A WT1 JAK3 FLT3 SMAD4 ATR RAF1 BRAF ASXL1 NUTM1 MSH2 ETV1 AKT1 MSH6 KDR TMPRSS2 NFKBIA PDGFRA RET ALK CDK6 TET2 CRKL EWSR1 HRAS STK11 EPHA3 EZH2 NKX2 1 BAP1 MEN1 GNA11 BRD2 MAP2K1 SMARCB1 NRAS PDGFRB MAPK1 CTNNB1

15 But, there is on problem Drug resistance almost invariably occurs after response to a single-agent targeted therapy HER2 RAS PI3K PTEN LKB1 AKT AMPK TSC1/2 TSC2 mutation exceptional response everolimus TORC1 S6K

16 HER2 RAS PI3K PTEN LKB1 AKT AMPK TSC1/2 TSC2 mutation exceptional response acquired resistance everolimus TORC1 2 nd mutation in TOR S6K A 38 year old man with BRAF-mutant melanoma and miliary subcutaneous metastases Prior to treatment Post-vemurafenib (15 wks) Relapse at 23 wks Wagle et al. JCO 29: , 2011

17 A 38 year old man with BRAF-mutant melanoma and miliary subcutaneous metastases Prior to treatment Post-vemurafenib (15 wks) Relapse at 23 wks We have to rebiopsy recurrent drugresistant cancers like this one Wagle et al. JCO 29: , 2011

18 cobrim Study Design Melanoma, unresectable locally advanced or metastatic (n = 495) BRAF V600 mutation (cobas 4800) No prior systemic therapy for advanced disease ECOG PS 0/1 1:1 Vemurafenib 960 mg BID 28 days (Days 1-28) Cobimetinib 60 mg QD 21 days (Days 1-21) Stratification Geographic region Extent of disease (M1c vs other) Disease progression, unacceptable toxicity, or withdrawal of consent Primary end point PFS, investigator assessed 1 Secondary end points OS, objective response rate, duration of response, PFS, IRC assessed, safety, pharmacokinetics, quality of life: QLQ-C30 and EQ-5D Vemurafenib 960 mg BID 28 days (Days 1-28) Placebo Primary analysis for PFS: Performed in 2014 with the data cutoff as May 9, Protocol-specified first OS interim analysis was also performed 1 Updated analysis for PFS: Presented here with the data cutoff as January 16, BID, two times daily; ECOG, Eastern Cooperative Oncology Group; EQ, EuroQol; HR, hazard ratio; IRC, independent review committee; OS, overall survival; PS, performance status; QD, once daily; QLQ, quality of life questionnaire. 1. Larkin J et al. N Engl J Med. 2014;371: cobrim Updated Investigator-Assessed PFS Kaplan-Meier Plot for PFS Intent-to-Treat Population 100 Survival Distribution Function (%) Cobimetinib vemurafenib (n=247) Placebo vemurafenib (n=248) Censored ITT Population Cobi Vem n = 247 Pbo Vem n = 248 PFS events, n (%) 143 (57.9) 180 (72.6) Median PFS, months (95% CI) HR a (95% CI) b ( ) 0.58 b ( ) 7.20 b (CI: ) Data cutoff of January 16, 2015 was 1 year from enrollment of last patient No. of patients at risk Vemurafenib cobimetinib Vemurafenib placebo 1 Months 5 Months 9 Months 13 Months 17 Months 21 Months 25 Months Time a Stratified HR. b The median PFS was 6.2 months in Pbo Vem, and 9.9 months in Cobi Vem (HR, 0.51; 95% CI, ) at the May 9, 2014 data cutoff. Larkin J et al. N Engl J Med. 2014;371:

19 Resistance to Targeted Therapies Proven mechanisms Secondary alterations in the drug target or in the pathway where the molecular drug target is Alternative mechanisms that bypass the targeted pathway Indifference to the target (i.e., outgrowth of cancer clones that do not express or rely on the drug target) Drug resistance almost invariably occurs after response to a single-agent targeted therapy (combinations are needed!) Re-biopsy and molecular profiling of recurrent drug-resistant cancers is required to identify mechanisms of drug escape Resistance mechanisms can be multiple and may not be shared by all metastatic sites Genotype Driven Clinical Trials and Cancer Care

20 341 cancer associated genes NCI-Molecular Analysis for Therapy Choice (NCI-MATCH or EAY131) A phase II precision medicine cancer trial Co-developed by the ECOG-ACRIN Cancer Research Group and the National Cancer Institute Version Date: 11/11/2015

21 NCI-MATCH Hypotheses Primary: Tumors that share common somatic genetic alterations in oncogenes or tumor suppressors will be variably responsive to therapies targeting the pathways disregulated by those alterations regardless of tumor type Secondary: Concomitant somatic genetic alterations will predict responsiveness or resistance. 11/11/ amois in NCI-MATCH and Estimated Prevalence AKT (1 10%) mtor (5%) PIK3CA (17 18%) TSC1 or TSC2 (2.6 and 3.5%) BRAF (2.79) BRAF V600E or V600K (1 12%) GNA11 (1.6%) GNAQ (2%) NF1 (7.7%) DDR2 (2%) ALK (<2%) ckit (2%) EGFR (1 4%) EGFR T790M (1 2%) FGFR (5%) HER2 amplification (5%) HER2 mutation (2 5%) MET (4%) NF2 (2%) PTEN loss (11%) PTEN mutation or deletion (11%) ROS1 (<2%) SMO or PTCH1 (<2%) 0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% 18.0% 20.0% 11/11/

22 NCI-MATCH Schema 11/11/ Summary Precision (genomic) medicine has revolutionized the conventional clinical trials and drug approval processes Serial genomic profiling of tumors should help us understand tumor evolution upon pressure by targeted therapies Not all cancers are driven by genomic alterations (i.e., epigenetic mechanisms) Identification of cancer drivers vs. passengers in tumors with multiple somatic gene alterations remains a big hurdle Identification of target-specific drugs and combinations given at the right schedule is key for this process to work

23 Genotype Driven Clinical Trials and Cancer Care Sample case: PR following neratinib fulvestrant therapy ERBB2 mutant (P780_Y781insGSP) ER/HER2 ductal carcinoma Baseline 8 Weeks 45% partial response by RECIST v1.1 at 8 weeks Hyman et al, 2015 San Antonio Breast Cancer Symposium