Genomic Profiling and Biomarker-Guided Therapy in Esophagogastric - PowerPoint PPT Presentation

Genomic Profiling and Biomarker-Guided Therapy in Esophagogastric Cancers Samuel J. Klempner, MD Director of Precision Medicine and GI Oncology The Angeles Clinic and Research Institute Cedars-Sinai Medical Center Los Angeles, CA, USA

Disclosures • Research Funding: Merck (institutional), Leap Therapeutics (institutional), Astellas (institutional) • Consultant/Advisory: Lilly Oncology, Astellas, Foundation Medicine Inc., Hope for Stomach Cancer (unpaid) • Stock/Equity: TP Therapeutics • Other: New England Patriots fan 2002, 2004, 2005, 2015, 2017, 2019

Gastric Cancer Epidemiology Gastric Cancer Global Incidence in Men and Women Gastric Cancer Global Death Rates in Men and Women GLOBOCAN 2012 GLOBOCAN 2012 http://gco.iarc.fr/today http://gco.iarc.fr/today • Roughly 951,000 new cases per year, accounts for 6.8% of all new cancer diagnoses Over 720,000 deaths per year, 8.8% of cancer-related deaths, 3 rd most common cause globally •

The Problem with Targets in Gastroesophageal Cancers Gastric Cancer is NOT a monogenic single disease Burrell et al., Nature 2013

Heterogeneity Models – A Conceptual Framework Hunter KW et al., Nat Rev Cancer 2018

Sub-clonal Drivers in Advanced Disease • Heterogeneity impacts outcomes • Gastric cancers are not unidimensional • This is not a new phenomenon and exists in all GC • No standardized method to compare degrees of heterogeneity across GC or other tumors Landau et al., Cell 2013;152:714-726

From Botany to Gastric Cancer – Sub-clonal Complexity Pine Tree Baobab Tree Palm Tree Degree of heterogeneity and sub-clonal drivers = risk of treatment failure? Adapted from Gerlinger et al., NEJM 2012

Why? Because Negative Phase III Gastric Trials Keep Happening Credit: Kohei Shitara, ASCO 2018

Genomic Profiling and Temporal Changes in HER2 – Prototype Example • Her2 IHC demonstrates intra- and inter-tumoral variation • Outgrowth of Her2 negative clones may drive resistance under therapeutic pressure • Timing of sample acquisition may identify those who may benefit from Her2-directed therapy beyond first line • There is no current heterogeneity scoring system to standardize Makiyama et al., phase II T-ACT trial, ASCO 2018 Janjigian YY et al., Cancer Discovery 2017

Examining Targets in Gastric Cancer – MSI and MET Protein Level – MMR Proteins/RTKs • Multiple paths to same end (co-amp in same cell vs. outgrowth resistance population with alternate bypass RTK amp) • Intratumoral MSI heterogeneity can drive IO failure Multi-region Biopsy • Heterogeneity in hypermutant GBM recurrences driven by Kim ST et al., Nature Med 2018 acquired MSH6 pathogenic mutations (Johnson et al., Science 2014) Primary Progressor, ICI refractory Kwak E et al., Cancer Discovery 2015

Genomic Profiling and Insights into Negative Trials -- SHINE Genomics Level – FGFR2 • AZD5457 is a selective FGFR1-3 TKI highly effective in pre-clinical FGFR2-amplified GC studies • FGFR2 amplification exists in 5-10% GC • Phase II open-label study vs. paclitaxel in advanced GC s/p 1L of therapy (SHINE trial) • Stratification by polysolmy, low amp (FISH >2 to <5), high (FISH ratio >5) • Primary endpoint = PFS • No improvement in any subgroup. Why? Van Cutsem E et al., Annals Oncology 2017

Examining Heterogeneity in Gastric Cancer – Other Targets • Intratumoral heterogeneity exists for all examined putative biomarkers in gastric cancer • Serial testing is required and perhaps those that retain high level of a given biomarker would benefit from continued therapy PloS ONE 2015;10:e0143207

Assessing Response and Tumor Landscape with ctDNA WES Pooled NSCLC, melanoma, MSI-H CRC (n=15) ctDNA at baseline and week 8 Treatment with nivolumab or Kim ST et al., Nature Med 2018 pembrolizumab monotherapy ctDNA Cabel L et al., Ann Oncol 2017 Pectasides et al., Cancer Discovery 2018

ctDNA Monitoring to Define Responder/non-responder Features • Phase II single arm trial of CapOX + lapatinib in 1L Her2+ (IHC 3+ or IHC2+ with SISH amp) gastric cancer • n = 32, 29 evaluable, primary endpoint = CR rate Concordant ctDNA and tissue, less • Paired primary and metastatic samples from 10pts heterogeneity? • 6/10 concordant tissue inter-tumor assessment, only 1 PD among concordant • Intra-tumor heterogeneity (IHC h-score) from primary in 29pts. 5/7 CR patients had homogenous Her2 IHC • Among 8 evaluable pts with ctDNA, 6/8 had ctDNA- No ERBB2 amp detectable Her2 amp, ORR = 100% in ctDNA, more baseline heterogeneity? Kim ST, et al., Ann Oncol 2017 Chao J, Klempner SJ, Ann Oncol 2017

Profiling to Define Baseline Tumor Composition • Few if any studies have looked at baseline heterogeneity in Gastric Cancer • Collaboration with Samsung Medical Center, Seoul, Korea • Pre-planned multi-region biopsies from newly diagnosed advanced gastric adenocarcinomas Case Ⅰ Case Ⅱ Case Ⅲ • Goal to examine pre-existing heterogeneity and understand impact on outcomes Under Revision, Scientific Reports, Klempner et al. ESMO 2018 Case Ⅳ Case Ⅴ Case Ⅵ

Other Emerging Biomarkers in GEA – CLDN18.2, Subsets, Etc. 1. CLDN18.2 (Tight junction protein): Overexpressed in 30-40% GEA, FAST trial +, ongoing phase II ILUSTRO and phase III SPOTLIGHT trials. OS in GEA, >70% CLDN18.2 in TC Credit: Al-Batran, ASCO 2016 1. Biomarker Enrichment – Her2 IHC 3+, ctDNA+ and PD-L1+ -- encouraging activity with margetuximab + pembrolizumab in GC (Catenacci D et al., ESMO 2018)

Utilizing Molecular Classification to Inform Therapy Do dMMR GC/GEJ Need Perioperative Therapy? Baseline heterogeneity assessment important, ACRG Samsung Singapore combo vs mono Any role for Smyth E, et al., JAMA Oncology 2017 chemo at all? TCGA ALL Cohorts SMC/TCGA/Singapore Proteomic Subgroups within Diffuse Gastric Cancer • Chemo ever? • More pre-op • RTK-directed yes • Periop IO only? • RTK alterations • Any role for RT • RTK combinations? • No need for Treatment HELP likely passenger ever • Heterogeneity critical +CTLA4? implications • ctDNA post-IO • CLDN18.2 • ctDNA serially • Diff Please • Early surgery? testing? surveillance? TCGA Gastric, Nature 2014, ACRG, Nat Med 2015, Adapted from Ajani et al., Nat Rev 2016 Ge S, et al., Nature Comm 2018

The Future – Broad Implementation of Iterative Profiling Capable of Assessing Tumor Adaptive Changes Biologically Uninformed – Still Standard/Common Chemo #1 (1L ) Chemo #2 (2L) Chemo stopped Diagnosis Stage IV, Chemo stopped working, how to Her2-, MSS, PD-L1-No working, how to decide? Further testing decide? Overall Survival Biologically Informed – Here and hopefully more to come Chemo/Targeted/Immuno #1 (1L) Chemo/Target/Immuno #3 (3L) Chemo/Target/Immuno #2 (2L) Treatment Treatment Diagnosis Stage stopped working. Treatment stopped working. IV, Look at DNA Look at DNA stopped working. Extended again (blood, Look at DNA again (blood, Molecular Testing, again (blood, tissue) to help tissue) to help ctDNA, immune guide therapy guide therapy tissue) to help profiling? guide therapy Overall Survival

SUMMARY • Her2, PD-L1, and MSI testing should be considered standard of care for all advanced patients – recent or archival tissue, more recent preferred when possible • Inter and intra-tumoral heterogeneity exist in the majority of gastric cancers – ctDNA and tissue at diagnosis • Subclonal drivers impact duration of therapeutic effect and impact resistance – single biomarkers testing inadequate, genomic context matters • EBV testing for all or targeted populations/biomarker results – consider earlier IO for EBV+ • Increased heterogeneity fosters polyclonal resistance – serial samples, novel combinations will be needed • Increasing heterogeneity may be exploitable – ICI combinations, IO + target (Pembrolizumab + trastuzumab for example) • Need to move these technologies earlier – ctDNA in detection, post-op, in peritoneal washing

THANK YOU Samuel J. Klempner, MD The Angeles Clinic and Research Institute Cedars-Sinai Medical Center Los Angeles, CA, USA sklempner@theangelesclinic.org Tel: +1 1-310-948-5990 (cell)

A Word on PD-L1 From Randomized Data ATTRACTION-2, >= 2L, Irrespective PD-L1 Keynote-061 2L, PD-L1 CPS >10 Baseline heterogeneity assessment important, mOS 10.4 vs 8.0 combo vs mono 12m OS est >40% mOS 5.3 vs 4.1 12m OS 26.2% Shitara et al., Lancet, 6/4/2018 Any role for Keynote-061 2L, PD-L1 CPS >1 ATTRACTION-2, >= 2L, PD-L1 >= 1% ATTRACTION-2, >= 2L, PD-L1< 1% chemo at all? mOS 9.1 vs 8.3 mOS 6.0 vs 4.2 mOS 5.2 vs 3.8 12m OS est 40%