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

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

Oct 30, 2022 206 likes •448 views

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

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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

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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

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Gastric Cancer Epidemiology

Gastric Cancer Global Incidence in Men and Women Gastric Cancer Global Death Rates in Men and Women

GLOBOCAN 2012 http://gco.iarc.fr/today GLOBOCAN 2012 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, 3rd most common cause globally
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The Problem with Targets in Gastroesophageal Cancers

Burrell et al., Nature 2013

Gastric Cancer is NOT a monogenic single disease

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Heterogeneity Models – A Conceptual Framework

Hunter KW et al., Nat Rev Cancer 2018

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Sub-clonal Drivers in Advanced Disease

Landau et al., Cell 2013;152:714-726

  • 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

  • ther tumors
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From Botany to Gastric Cancer – Sub-clonal Complexity

Palm Tree Degree of heterogeneity and sub-clonal drivers = risk of treatment failure? Pine Tree Baobab Tree

Adapted from Gerlinger et al., NEJM 2012

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Why? Because Negative Phase III Gastric Trials Keep Happening

Credit: Kohei Shitara, ASCO 2018

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Genomic Profiling and Temporal Changes in HER2 – Prototype Example

Janjigian YY et al., Cancer Discovery 2017

  • 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

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Examining Targets in Gastric Cancer – MSI and MET

Primary Progressor, ICI refractory Multi-region Biopsy

Kim ST et al., Nature Med 2018

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
  • Heterogeneity in hypermutant GBM recurrences driven by

acquired MSH6 pathogenic mutations (Johnson et al., Science 2014)

Kwak E et al., Cancer Discovery 2015

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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

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Examining Heterogeneity in Gastric Cancer – Other Targets

PloS ONE 2015;10:e0143207

  • 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

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Assessing Response and Tumor Landscape with ctDNA

Kim ST et al., Nature Med 2018 Pectasides et al., Cancer Discovery 2018

WES ctDNA

Pooled NSCLC, melanoma, MSI-H CRC (n=15) ctDNA at baseline and week 8 Treatment with nivolumab or pembrolizumab monotherapy

Cabel L et al., Ann Oncol 2017

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ctDNA Monitoring to Define Responder/non-responder Features

Kim ST, et al., Ann Oncol 2017 Chao J, Klempner SJ, Ann Oncol 2017 No ERBB2 amp in ctDNA, more baseline heterogeneity? Concordant ctDNA and tissue, less heterogeneity?

  • 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
  • Paired primary and metastatic samples from 10pts
  • 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-

detectable Her2 amp, ORR = 100%

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Profiling to Define Baseline Tumor Composition

Case Ⅱ Case Ⅲ Case Ⅰ Case Ⅴ Case Ⅳ Case Ⅵ

  • 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

  • Goal to examine pre-existing heterogeneity and

understand impact on outcomes

Under Revision, Scientific Reports, Klempner et al. ESMO 2018

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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. 1. Biomarker Enrichment – Her2 IHC 3+, ctDNA+ and PD-L1+ -- encouraging activity with margetuximab + pembrolizumab in GC (Catenacci D et al., ESMO 2018)

Credit: Al-Batran, ASCO 2016

OS in GEA, >70% CLDN18.2 in TC

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Utilizing Molecular Classification to Inform Therapy

Ge S, et al., Nature Comm 2018

Proteomic Subgroups within Diffuse Gastric Cancer Do dMMR GC/GEJ Need Perioperative Therapy?

Smyth E, et al., JAMA Oncology 2017

Any role for chemo at all? Baseline heterogeneity assessment important, combo vs mono HELP Please

TCGA Gastric, Nature 2014, ACRG, Nat Med 2015, Adapted from Ajani et al., Nat Rev 2016

  • Periop IO only?
  • No need for

+CTLA4?

  • Diff

surveillance?

Treatment implications

  • Chemo ever?
  • RTK alterations

likely passenger

  • ctDNA post-IO
  • Early surgery?
  • More pre-op
  • Any role for RT

ever

  • CLDN18.2

testing?

  • RTK-directed yes
  • RTK combinations?
  • Heterogeneity critical
  • ctDNA serially

ACRG Samsung Singapore TCGA

SMC/TCGA/Singapore

ALL Cohorts

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The Future – Broad Implementation of Iterative Profiling Capable of Assessing Tumor Adaptive Changes

Biologically Uninformed – Still Standard/Common

Diagnosis Stage IV, Her2-, MSS, PD-L1-No Further testing

Chemo #1 (1L)

Chemo stopped working, how to decide?

Chemo #2 (2L)

Chemo stopped working, how to decide?

Biologically Informed – Here and hopefully more to come

Diagnosis Stage IV, Extended Molecular Testing, ctDNA, immune profiling?

Chemo/Targeted/Immuno #1 (1L)

Treatment stopped working. Look at DNA again (blood, tissue) to help guide therapy

Chemo/Target/Immuno #2 (2L)

Treatment stopped working. Look at DNA again (blood, tissue) to help guide therapy Chemo/Target/Immuno #3 (3L) Treatment stopped working. Look at DNA again (blood, tissue) to help guide therapy

Overall Survival Overall Survival

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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
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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)

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A Word on PD-L1 From Randomized Data

Any role for chemo at all? Baseline heterogeneity assessment important, combo vs mono

Keynote-061 2L, PD-L1 CPS >10

Shitara et al., Lancet, 6/4/2018

Keynote-061 2L, PD-L1 CPS >1 mOS 9.1 vs 8.3 12m OS est 40% mOS 10.4 vs 8.0 12m OS est >40% ATTRACTION-2, >= 2L, Irrespective PD-L1 ATTRACTION-2, >= 2L, PD-L1 >= 1% ATTRACTION-2, >= 2L, PD-L1< 1% mOS 5.3 vs 4.1 12m OS 26.2% mOS 5.2 vs 3.8 mOS 6.0 vs 4.2

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