Addressing Tumor Molecular Heterogeneity using A Novel Clinical Trial - - PowerPoint PPT Presentation

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Addressing Tumor Molecular Heterogeneity using A Novel Clinical Trial - - PowerPoint PPT Presentation

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Addressing Tumor Molecular Heterogeneity using A Novel Clinical Trial Design - PANGEA Daniel Catenacci, MD Assistant Professor of Medicine Associate Director GI Oncology Program May 12, 2017 Addressing Molecular Heterogeneity Gastroesophageal

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Daniel Catenacci, MD Assistant Professor of Medicine Associate Director GI Oncology Program

May 12, 2017 Addressing Tumor Molecular Heterogeneity using A Novel Clinical Trial Design - PANGEA

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Gastroesophageal Cancer

Addressing Molecular Heterogeneity

“Molecular Drivers” “Oncogene Addiction” Inter-patient Heterogeneity Intra-patient Heterogeneity

Next-Generation Companion Diagnostics & Next-Generation Trials

‘Classic’ Companion Diagnostics ‘Classic’ Biomarker-Driven Trials Next-Gen Companion Diagnostics Next-Gen Clinical Trial Designs

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Gastroesophageal Cancer

Addressing Molecular Heterogeneity

“Molecular Drivers” “Oncogene Addiction” Inter-patient Heterogeneity Intra-patient Heterogeneity

Next-Generation Companion Diagnostics & Next-Generation Trials

‘Classic’ Companion Diagnostics ‘Classic’ Biomarker-Driven Trials Next-Gen Companion Diagnostics Next-Gen Clinical Trial Designs

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EGJ AC Gastric (non-Cardia) AC

Esophagus Diaphragm Esophagogastric Junction (EGJ) Fundus Lesser curvature Duodenum Cardia Body Pyloric Antrum Greater curvature

The Gastroesophageal Nomenclature

Angular notch (incisura angularis) Pylorus

Esophageal (SCC)

Type I, II, III Seiwert

TYPE I TYPE II TYPE III

Esophageal vs. Gastric Adenocarcinoma 7th edition 2010 AJCC/UICC Staging

Gastric or Stomach Cancer

Sehdev A, Catenacci D. Discov Med 2013

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Gastric Cancer

  • 26,370 new cases/year
  • 10,730 deaths/year

Esophageal Cancer

(70% EGJ Adenocarcinoma)

  • 16,940 new cases/year
  • EGJ 400% increase in the last decades
  • 15,690 deaths/year

Gastroesophageal Adenocarcinoma

Epidemiology US 2010

  • Worldwide Gastroesophageal Cancer 2012:

– >1,000,000 deaths/year – 3rd cancer incidence – 2nd cancer death

Ferlay et al. Int J Can. 2014; www.cancer.org Kris et al. J Clin Oncol. Dec, 2010; www.cancer.org.

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First Line Management of Advanced Gastroesophageal Cancer

  • 1. Murad, et al. Cancer 1993
  • 2. Vanhoefer, et al. JCO 2000
  • 3. Aj ani, et al. AS

CO 2009

  • 4. Van Cut sem, et al. JCO 2006
  • 5. Dank, et al. Ann Oncol 2008
  • 6. Cunningham, et al. NEJM 2008
  • 7. Kang, et al. Ann Oncol 2009
  • 8. Guimbaud, et al. JCO 2014
  • 9. S

hah, et al. JAMA ONC 2016 BSC = best support ive care; MTX = met hot rexat e; S = S

  • 1; A = doxorubicin

F = 5-FU; C/P = cisplat in; I = irinot ecan; E = epirubicin; O = oxaliplat in; D = docet axel

mOS Months BSC 1 6 2 4 12 8 10 FAMTX 2 SP 3 EOX 6 XP 7 FP 4 IF 5 EOF 6 DCF 4 ECF 6 ECX 6 FOLFIRI 8 FOLFOXFOLFIRIFOLTAX FOLFOX 9

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mOS Months BSC 1 6 2 4 12 8 10 FAMTX 2 SP 3 EOX 6 XP 7 FP 4 IF 5 EOF 6 DCF 4 ECF 6 ECX 6 FOLFIRI 8

  • 1. Murad, et al. Cancer 1993 2. Vanhoefer, et al. JCO 2000 3. Ajani, et al. ASCO 2009 4. Van Cutsem, et al. JCO 2006
  • 5. Dank, et al. Ann Oncol 2008 6. Cunningham, et al. NEJM 2008 7. Kang, et al. Ann Oncol 2009 8. Guimbaud, et al. JCO 2014
  • 9. Shah et al. JCO Abstr 4012 ASCO 2015. 10. Bang et al. Lancet 2010.

X/FP+/-T10 X/FP+/-T10

HER2 IHC3+ or IHC2+/FISH+ HER2 (+)

X/FP+/-T10 HER2 IHC3+/FISH+ +T +T

14 16 18 FOLFOX 9

+T

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Molecular Phenotyping- Solid Tumors

“Molecular Drivers” “Oncogene Addiction” Inter-patient Heterogeneity Intra-patient Heterogeneity

Next-Generation Companion Diagnostics & Next-Generation Trials

‘Classic’ Companion Diagnostics ‘Classic’ Biomarker-Driven Trials Next-Gen Companion Diagnostics Next-Gen Clinical Trial Designs

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Addressing Molecular Heterogeneity

“Molecular Drivers” “Oncogene Addiction” Inter-patient Heterogeneity Intra-patient Heterogeneity

Next-Generation Companion Diagnostics & Next-Generation Trials

‘Classic’ Companion Diagnostics ‘Classic’ Biomarker-Driven Trials Next-Gen Companion Diagnostics Next-Gen Clinical Trial Designs

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11

How Gene Alterations Can Cause Cancer

ALTERED PROTEINS

CDKN2a PTEN RAS RAF mTOR MAPK AKT

ALTERED PATHWAYS

RAS RAF MAPK

CANCER ALTERED GENES

Code for Resulting in

DNA  Transcription  RNA  Translation  protein

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Addressing Molecular Heterogeneity

“Molecular Drivers” “Oncogene Addiction” Inter-patient Heterogeneity Intra-patient Heterogeneity

Next-Generation Companion Diagnostics & Next-Generation Trials

‘Classic’ Companion Diagnostics ‘Classic’ Biomarker-Driven Trials Next-Gen Companion Diagnostics Next-Gen Clinical Trial Designs

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Inter-Patient Tumor Heterogeneity

Catenacci D. Next-generation clinical trials: Novel strategies to address the challenge of tumor molecular heterogeneity. Molecular Oncology 2014

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Mutation Profile: Targeted Multiplex Inter-patient Heterogeneity

1. TP53 mt, ARID1A mt 2. TP53 mt, APC mt 3. MET amp+, TP53 mt, NOTCH1 mt 4. FGFR2 amp+, TP53 mt, E-cadherin mt 5. KRAS amp+, TP53 mt, CDKN2A/B mt 6. PI3KCA mt, PTCH1 mt, MLH1 mt, MSH1 mt 7. HER2 amp+, SRC amp+, TOP1 amp+ 8. HER2 amp+, KRAS amp+, AKT amp+, CCNE1 amp+, CCND1 amp+, MCL1 amp+ 9. TP53 mt, PIK3CA mt, CTNNB1 mt, SMAD4 mt

  • 10. IGF1R amp+
  • 11. CEBPA mt
  • 12. MET amp+
  • 13. HER2 amp+, PIK3CAmt, PTEN mt, CDK6 amp, TP53 mt
  • 14. MDM2 amp+
  • 15. CDH1 mt
  • 16. Src amp+, AURKA amp+, CCND1 amp+, CDK4 amp+, RICTOR amp+, CDKN2A/B

loss, ATM mt

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Mutation Profile: Targeted Multiplex Inter-patient Heterogeneity

1. TP53 mt, ARID1A mt 2. TP53 mt, APC mt 3. MET amp+, TP53 mt, NOTCH1 mt 4. FGFR2 amp+, TP53 mt, E-cadherin mt 5. KRAS amp+, TP53 mt, CDKN2A/B mt 6. PI3KCA mt, PTCH1 mt, MLH1 mt, MSH1 mt 7. HER2 amp+, SRC amp+, TOP1 amp+ 8. HER2 amp+, KRAS amp+, AKT amp+, CCNE1 amp+, CCND1 amp+, MCL1 amp+ 9. TP53 mt, PIK3CA mt, CTNNB1 mt, SMAD4 mt

  • 10. IGF1R amp+
  • 11. EGFR amp+, CEBPA mt
  • 12. MET amp+
  • 13. HER2 amp+, PIK3CAmt, PTEN mt, CDK6 amp, TP53 mt
  • 14. MDM2 amp+
  • 15. CDH1 mt
  • 16. Src amp+, AURKA amp+, CCND1 amp+, CDK4 amp+, RICTOR amp+, CDKN2A/B

loss, ATM mt

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Addressing Molecular Heterogeneity

“Molecular Drivers” “Oncogene Addiction” Inter-patient Heterogeneity Intra-patient Heterogeneity

Next-Generation Companion Diagnostics & Next-Generation Trials

‘Classic’ Companion Diagnostics ‘Classic’ Biomarker-Driven Trials Next-Gen Companion Diagnostics Next-Gen Clinical Trial Designs

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Baseline Spatial Heterogeneity Revealed by Multi-site NGS Sequencing

Pectasides…Catenacci. Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma. 2017 in review

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Temporal Heterogeneity: Tumors Evolve Over Time to Develop Treatment Resistance

Misale et al. Cancer Discovery (2014)

Response Progression

Sensitive Clone Resistant Clones

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Addressing Molecular Heterogeneity

“Molecular Drivers” “Oncogene Addiction” Inter-patient Heterogeneity Intra-patient Heterogeneity

Next-Generation Companion Diagnostics & Next-Generation Trials

‘Classic’ Companion Diagnostics ‘Classic’ Biomarker-Driven Trials Next-Gen Companion Diagnostics Next-Gen Clinical Trial Designs

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Stricker, Catenacci, Seiwert. Semin Oncol 2011

Tumor Heterogeneity: Inter-patient!!

How to characterize economically?

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Addressing Molecular Heterogeneity

“Molecular Drivers” “Oncogene Addiction” Inter-patient Heterogeneity Intra-patient Heterogeneity

Next-Generation Companion Diagnostics & Next-Generation Trials

‘Classic’ Companion Diagnostics ‘Classic’ Biomarker-Driven Trials Next-Gen Companion Diagnostics Next-Gen Clinical Trial Designs

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Classic Biomarker-Driven Clinical Trial Designs

“Retrospective - prospective” “Biomarker-stratified” “Biomarker population enriched”

Catenacci D. Next-generation clinical trials: Novel strategies to address the challenge of tumor molecular heterogeneity. Molecular Oncology 2014

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Catenacci D. Next-generation clinical trials: Novel strategies to address the challenge of tumor molecular heterogeneity. Molecular Oncology 2014

Prognostic Predictive

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“Biomarker-stratified”

Catenacci D. Next-generation clinical trials: Novel strategies to address the challenge of tumor molecular heterogeneity. Molecular Oncology 2014

Prognostic Predictive

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“Biomarker population enriched”

Catenacci D. Next-generation clinical trials: Novel strategies to address the challenge of tumor molecular heterogeneity. Molecular Oncology 2014

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“Biomarker population enriched”

  • eg. ‘TOGA’ trial HER2 amp+

Catenacci D. Next-generation clinical trials: Novel strategies to address the challenge of tumor molecular heterogeneity. Molecular Oncology 2014

Screened 4000 patients To get 584 (~20% positive rate) (and this had ~130 HER2- pts)

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“Biomarker population enriched”

  • eg. ‘Phase I expansions’  PIK3CA mt

Catenacci D. Next-generation clinical trials: Novel strategies to address the challenge of tumor molecular heterogeneity. Molecular Oncology 2014

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Addressing Molecular Heterogeneity

“Molecular Drivers” “Oncogene Addiction” Inter-patient Heterogeneity Intra-patient Heterogeneity

Next-Generation Companion Diagnostics & Next-Generation Trials

‘Classic’ Companion Diagnostics ‘Classic’ Biomarker-Driven Trials Next-Gen Companion Diagnostics Next-Gen Clinical Trial Designs

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Stricker, Catenacci, Seiwert. Semin Oncol 2011

How do we molecularly profile? Now…NGS (DNA/RNA), MS

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Next-Generation Diagnostics: NGS for Inter-Patient Tumor Heterogeneity

Khoury, Catenacci. Next-Generation Companion Diagnostics: Promises, Challenges, and Solutions. Arch Pathol Lab Med 2015.

NGS can also provide:

  • MSI status
  • Mutations/Mb
  • >19mt/Mb

Implications for immunotherapy

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Khoury, Catenacci. Next-Generation Companion Diagnostics: Promises, Challenges, and Solutions. Arch Pathol Lab Med 2015.

Next-Generation Diagnostics: “Liquid Biopsy” ctDNA NGS for Intra-Patient Tumor Heterogeneity

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Next-Generation Diagnostics: Mass Spec for Inter-Patient Tumor Heterogeneity

Khoury, Catenacci. Next-Generation Companion Diagnostics: Promises, Challenges, and Solutions. Arch Pathol Lab Med 2015.

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Addressing Molecular Heterogeneity

“Molecular Drivers” “Oncogene Addiction” Inter-patient Heterogeneity Intra-patient Heterogeneity

Next-Generation Companion Diagnostics & Next-Generation Trials

‘Classic’ Companion Diagnostics ‘Classic’ Biomarker-Driven Trials Next-Gen Companion Diagnostics Next-Gen Clinical Trial Designs

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Next-Generation Clinical Trial Designs

“Exploratory Platform” “Expansion Platform Type IA – ‘Global’/Compartmentalized”

  • Histology Dependent

“Expansion Platform Type IB – ‘Global’/Compartmentalized”

  • Histology Agnostic

“Expansion Platform Type IIA – ‘Grass-roots’/Holistic”

  • Histology Dependent
  • Without Biologic Beyond Progression
  • With Biologic Beyond Progression

“Expansion Platform Type IIB ‘Grass-roots’

  • Histology Agnostic

Catenacci D. Next-generation clinical trials: Novel strategies to address the challenge of tumor molecular heterogeneity. Molecular Oncology 2014

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Catenacci D. Molecular Oncology 2014

“Exploratory Platform”

  • Eg. ‘I-SPY’, ‘BATTLE’

Umbrella: Biomarker Stratified (if control included)

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Catenacci D. Next-generation clinical trials: Novel strategies to address the challenge of tumor molecular heterogeneity. Molecular Oncology 2014

“Expansion Platform Type IA – Global/Compartmentalized”

  • eg. ‘FOCUS - Colon’

 Umbrella: Population Enriched

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How? With different tumor types?

Catenacci D. Next-generation clinical trials: Novel strategies to address the challenge of tumor molecular heterogeneity. Molecular Oncology 2014

“Expansion Platform Type IB – Global/Compartmentalized” Histology Agnostic eg (‘NCI-MATCH’, ‘Signature’)

 Umbrella: Population Enriched

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Catenacci D. Molecular Oncology 2014

IIA

“Expansion Platform Type IIA – Grass-Roots/Holistic”

  • eg. ‘PANGEA - GEC’
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IIA-

Expansion Platform Type IIA –

with biologic beyond progression (BBP)

  • eg. ‘PANGEA - BBP’

Catenacci D. Next Generation Clinical Trials: Strategies to Address Tumor Molecular Heterogeneity. Molecular Oncology 2014 Catenacci D. Expansion Platform Design Type II: Testing a Treatment Strategy. Lancet Oncol 2015.

INTER-PATIENT HETEROGENIETY

INTRA-PATIENT HETEROGENIETY

Regulatory Challenge

  • because multiple :
  • Biomarkers
  • Assays
  • Drugs
  • Lines
  • NEW/Different

Intrapatient

  • space 10 v Met
  • over time
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IIB-

“Expansion Platform Type IIB – Grass-Roots/Holistic”

  • eg. ‘SHIVA’

Agnostic

Le Tourneau et al. Molecularly targeted therapy based on tumour molecular profiling versus conventional therapy for advanced cancer (SHIVA). Lancet Oncol 2015. Catenacci D. Expansion Platform Design Type II: Testing a Treatment Strategy. Lancet Oncol 2015.

SHIVA: 10 treatment groups No placebo – MD choice N=741  496 (67%) profiled  195 (26%) fit  Randomized  99 vs 96  NEGATIVE for PFS!

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Catenacci D. Molecular Oncology 2014

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One size fits all N of 1 Individualized therapy PANGEA 

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Inter-patient Heterogeneity

  • prioritized algorithm

Intra-patient Heterogeneity

  • through space 10 vs Metastases
  • over time (resistance)
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van Hagen P et al. N Engl J Med 2012;366:2074-2084.

Hazard Ratios for Death.

Forrest Plot

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Subgroup All Patients (ITT)

Expansion Platform Type II

A B C D E F G H Z Y X W V U T S Treatment Personalized Tx New Tx “Z” Better Standard Tx Better Biomarker groups Personalized Tx Better Z Z Z Z Z Z Z Z Z

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Subgroup All Patients (ITT)

PANGEA

HER2++ MET++ FGFR2++ EGFR++ KRAS++ MET+ EGFR+ VEGFR2+ HER2-Ab MET-Ab FGFR2-Ab EGFR-Ab VEGFR2-Ab MET-Ab EGFR-Ab VEGFR2-Ab Personalized Tx Better Standard Tx Better Treatment Personalized Tx MSI-H/EBV+ PD1-Ab

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Diagnosis: metastatic cancer

Biomarker Evaluation in all samples to allow for treatment assignment

FOLFOX

HER2 amplified MET amplified/Hi Anticipated Incidence

20%

7% 5/20% 15/10% FOLFOX

  • Trastuzumab

FOLFOX

  • METab

FOLFOX

  • EGFRab

Arm B1 Arm B2 Arm B4 Arm B5

ARM B: Therapy based

  • n molecular

profile FOLFOX

  • VEGFR2ab

The PANGEA -IMBBP Trial

Personalized ANtibodies for Gastro-Esophageal Adenocarcinoma: A Pilot 1st Metastatic Trial of Biologics Beyond Progression

FGFR2 amplified

8% FOLFOX

  • FGFR2ab

Arm B3

PD1 FOLFIRI + T PD1 FOLFIRI + M PD1 FOLFIRI + EGFRab PD1 FOLFIRI + V FOLFIRI + F PFS1 PD2 PD2 PD2 PD2 PFS2 PD1 PD2 FOLTAX + T FOLTAX + M FOLTAX + EGFRab FOLTAX + V FOLTAX + F PFS3 FOLFIRI PFS1 PFS2 PFS3 FOLTAX

KRAS/BRAF/ PIK3CA/AKT/PTENdel mt/amplified

Nl HER2,FGFR2,RON,MET

EGFR amplified/Hi

KRAS wild type Nl HER2,FGFR2,RON,MET

Historical Control (Arm A)

60% 30% 6m 4m 2m

primary mOS Endpoint (N~68)

15%

Arm B6

FOLFOX

  • PD1ab

PD1 FOLFIRI + PD1 PD2 FOLTAX + PD1

MSI-H, High TMB, EBV+

Dose finding – phase Ib lead in

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Inter-patient Heterogeneity

  • prioritized algorithm

Baseline Intra-patient Heterogeneity 9/28 = 32% 9 2 3 2 1 6 4 1

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Enrollment

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ORR – ITT (excluding MET++/FGFR2++)

Biomarker group N=15 HER2++ 8 13/15 87% ORR EGFR++ 2 MSI-H 1 16/16 100% DCR VEGFR2++ 3 EGFR+ 1 VEGFR2+ 1 (not eval-->peritoneal dz not measurable) 15

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ORR1 and DCR1

ITT plan 68 patients (all treated with biologic therapy) Interim analysis at 30% of enrolled patients ORR All pts evaluable for ORR ORR = 16/20

80% Historic ORR = 30-45%

Of those treated with ORR = 13/15

87%

biologic therapy: Of those NOT treated ORR = 3/5 60% with biologic therapy (ie MET/FGFR2+): Historic ORR by HER2 + vs - ORR by HER2 HER2+ pts per PANGEA ORR HER2+ 8/8

100%

HER2+ = 47% (TOGA), vs 35% chemo alone) HER2- pts per PANGEA ORR HER2- 8/12 66.70% HER2- = 30-40% (METGASTRIC, FOLFOX-placebo 40% in HEr2- pts) Of those treated with ORR HER2- 5/7

71%

biologic therapy: Of those NOT treated ORR HER2- 3/5 60% with biologic therapy: (ie MET/FGFR2+) DCR Of those treated with DCR 16/16

DCR = 100% Historic DCR = 60-70%

biologic therapy: Of those NOT treated DCR 5/5 100% with biologic therapy: (ie MET/FGFR2+)

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Primary Endpoint OS

  • In a phase IIa pilot study

– 80% power, one-sided alpha 0.1, HR 0.67 (mOS 18 months)

  • Assuming historical mOS is 12 months (it isn’t)

– H0: 50% of patients alive at 12 months – H1: 63% of patients alive at 12 months – Sample size needed: 68 patients (43 alive at 12 months)

  • 10/13 (77%) alive 12 months.
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Stratify:

i) Stage ii) PS iii) Biomarker iv) GEJ v distal stomach vi) Site of metastases

Diagnosis: metastatic cancer

Biomarker Evaluation in all samples prior to randomization

Standard care: Control Arm

FOLFOX + placebo

R 2:1

HER2 amplified MET amplified/Hi Anticipated Incidence

15% 20% 20% 25% FOLFOX

  • METab

FOLFOX

  • EGFRab

Arm B1 Arm B2 Arm B4 Arm B5

ARM B: Therapy based

  • n molecular

profile

Arm A1: HER2 amplified FOLFOX-Traztuzumab

FOLFOX

  • VEGFR2ab

The PANGEA -2MBBP Trial

Personalized ANtibodies for Gastro-Esophageal Adenocarcinoma: Phase II Metastatic Biologic Beyond Progression Trial (R 2:1)

FGFR2 amplified

5% FOLFOX

  • FGFR2ab

Arm B3

ARM A: Standard Chemotherapy + Placebo PD FOLFIRI + T PD FOLFIRI + M PD FOLFIRI + E PD FOLFIRI + V FOLFIRI + F PFS1 PD PD PD PD PFS2 PD PD FOLTAX + T FOLTAX + M FOLTAX + E FOLTAX + V FOLTAX + F PFS3 FOLFIRI + placebo PFS1 PFS2 PFS3 FOLTAX + placebo

KRAS/BRAF/ PIK3CA/AKT/PTENdel mt/amplified

Nl HER2,FGFR2,RON,MET

EGFR/HER3 amplified/Hi

KRAS wild type Nl HER2,FGFR2,RON,MET

  • Primary Endpoint: OS (HR 0.67)

i) Arm A v B (N=192, 128-B:64-A ) ii)Arm Ax v Bx Secondary Endpoints: PFS1,2,3, PFS1+2+3, 2nd/3rd line rates RR, toxicity, Arm A1 v A2, B1 v B2 etc Tissue correlates

FOLFOX

  • Trastuzumab

Arm A2: MET amplified/Hi Arm A4: KRAS/PI3K wild type Arm A5: KRAS/BRAF/PIK3CA mt/amp Arm A3: FGFR2 amplified

15%

Arm B6

FOLFOX

  • PD-1ab

PD FOLFIRI + PD1 PD FOLTAX + PD1

MSI-H, High TMB, EBV+

Arm A6: MSI-H, High TMB, EBV+

primary mOS Endpoint (N~192)

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Gastroesophageal Cancer

Addressing Molecular Heterogeneity

“Molecular Drivers” “Oncogene Addiction” Inter-patient Heterogeneity Intra-patient Heterogeneity

Next-Generation Companion Diagnostics & Next-Generation Trials

‘Classic’ Companion Diagnostics ‘Classic’ Biomarker-Driven Trials Next-Gen Companion Diagnostics Next-Gen Clinical Trial Designs

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Thank you!