from trials evaluating drugs to trials evaluating treatment algorithms – focus on the shiva trial

From trials evaluating drugs to trialsevaluating treatment algorithms –

Focus on the SHIVA trial

Christophe Le Tourneau, MD, PhD

Institut Curie

Head of the Phase I Program

Department of Medical Oncology

INSERM U900

EACR – Munich – July 7, 2014

Introduction

Chemotherapy

Targeted agent

Chemotherapy

Targeted agent

Chemotherapy

Targeted agent

Chemotherapy

Targeted agent

Chemotherapy

Targeted agent

Chemotherapy

Targeted agent

Chemotherapy

Targeted agent

Chemotherapy

Targeted agent

Introduction

Targets

EGFR

HER-2

mTOR

c-Kit

SMO

VEGF(R)

HDAC

NF-κB

CTLA4

RAF

ALK

RET

Drugs

Erlotinib/GefitinibCetuximab/PanitumumabCetuximab

Trastuzumab/TDM-1Lapatinib/PertuzumabTrastuzumab

Temsirolimus/EverolimusEverolimus

Imatinib

Vismodegib

BevacizumabSunitinibSorafenib

Vorinostat

Bortezomib

Ipilumumab

Vemurafenib

Crizotinib

Vandetanib/Cabozantinib

Tumor types

NSCLCCRCHNSCC

BreastBreastGastric adenocarcinoma

KidneyEndocrine tumors

GIST

Basal cell carcinoma

Breast, kidney, CRC, NSCLCKidney, endocrine tumorsKidney, HCC

Cutaneous lymphoma

Myeloma

Melanoma

Melanoma

NSCLC

Medullary thyroid cancer

Biomarkers

EGFR mutationKRAS mutation

-

HER2 amplificationHER2 amplificationHER2 amplification

--

c-Kit overexpression

-

---

-

-

-

V600E BRAF mutation

ALK translocation

-

Introduction

Ciriello et al. Nature Genet 2013;45:1127-33

IntroductionLUNG ADENOCARCINOMA – HER2 V659E MUTATION – LAPATINIB

Serra et al. Cancer Discov 2013;3:1238-44

IntroductionMELANOMA – KIT MUTATION – IMATINIB

Hodi et al. JCO 2013;31:3182-90

Introduction

Molecularprofile

Molecularalteration

Targeted agentTargeted agentTargeted agentTargeted agent Targeted agent Targeted agent Targeted agent

Introduction

Tsimberidou et al. CCR 2012;18:6373-83

Patients receiving matched targeted therapy Patients receiving no matched targeted therapy

Introduction

Failure-free survival

Patients receiving matched targeted

Overall survival

Patients receiving matched

targeted therapy

therapy

Patients receiving no matched targeted therapy

Tsimberidou et al. CCR 2012;18:6373-83

Outline

• Stratified trials:

- Molecular stratification

- Histologic stratification

• Algorithm-testing trials:

- Non-randomized trials

- Randomized trials

Le Tourneau et al. Chin Clin Oncol 2014;3:13

Outline






- Randomized trials

• FOCUS4 trial

Molecular stratification

Kaplan et al. JCO 2013;31:4592-8

Stratified trials Algorithm-testing trials

Molecularly-stratified

Histology-stratified

Non-randomized

Randomized

Tumor types

MolecularAlterations

Treatments

Test

Summary

Personalized medicine trials



Non-randomized

Randomized

Tumor types


1


Treatments

Test

Summary




Non-randomized

Randomized

Tumor types

Molecular


1

NAlterations

Treatments

Test

Summary




Non-randomized

Randomized

Tumor types



1

N

NTreatments

Test

Summary


Outline






- Randomized trials

Histologic stratification

• 1 drug

• Multiple tumor types harbouring specificmolecular alterations

• V-BASKET: vemurafenib (V600E BRAF mutation)

• CREATE: crizotinib (ALK/MET alterations)


Non-randomized

Randomized

Tumor types



1

N


N

1 or N

N 1Treatments

Test

Summary



Non-randomized

Randomized

Tumor types



1

N


N

1 or N

Treatments N 1

Test Test drugs efficacy

Summary


Outline






- Randomized trials

• Pilot study by Von Hoff et al.

Non-randomized trials

von Hoff et al. JCO 2010;28:4877-83

Non-randomized trials

von Hoff et al. JCO 2010;28:4877-83

• 18/66 patients (27%): ratio>1.3

Outline






- Randomized trials

• Question:

SHIVA

>?

SHIVA

• Promotion: Institut Curie (Paris & Saint-Cloud)

• Other participating centers:

- Centre Léon Bérard (Lyon)

- Centre René Gauducheau (Nantes)

- Institut Claudius Régaud (Toulouse)

- Institut Paoli-Calmettes (Marseille)

- Centre Georges-François Leclerc (Dijon)

- Centre Alexis Vautrin (Nancy)

SHIVA

• Primary objective:- To compare the efficacy of targeted therapy based on

tumor molecular profiling versus conventional therapy inpatients with refractory cancer

• Primary end point:- Progression-free survival

Le Tourneau et al. Target Oncol 2012;7:253-65

SHIVA

• Secondary objectives:- To evaluate overall response rate

- To compare overall survival

- To evaluate tumor growth kinetics*

- To evaluate safety

- To evaluate the ability of circulating tumor DNA to earlypredict treatment efficacy/resistance

- To evaluate the medico-economic impact of theexperimental strategy

*Le Tourneau et al. BJC 2012;106:854-7

SHIVA

• Inclusion criteria:- >18 years old

- patients with any type of cancer that is refractory tostandard of care

- biopsiable & measurable disease

- ECOG PS 0 or 1

- adequate blood counts and organ functions

Informedconsentsigned

Tumor biopsy

Molecularprofile

Patients with refractorycancer (all tumor types)

Molecular profile

• Mutations:

- Ampliseq Cancer Panel

- Ion Torrent / PGM (Life Technologies®)

• Gene copy number alterations:

- Cytoscan HD (Affymetrix®)

• Protein expression:

- IHC (ER, PR, AR)

Molecular profile

• Variants of interest:

- validated hotspots mutations* frequency: >4% for SNVs and >5% for indels

* coverage: >30X for SNVs and >100X for indels

- non targeted variants* outside an hotspot

* frequency >10%

* no synonymous mutations

* no polymorphisms

Molecular profile

• Amplifications:

- Gene copy number* diploid tumor: >6

* tetraploid tumor: >7

- Amplicon size* <1 Mb

* <10 Mb if protein expression is validated in IHC

Servant et al. Frontiers in Genetics 2014;5:e152


Tumor biopsy

NGS+Cytoscan HD

+IHC

Bioinformatics



Molecularbiologyboard


Tumor biopsy

NGS+Cytoscan HD

+IHC

Bioinformatics

PathologistsBiologists

Plateforms managers

BioinformaticiansPhysicians

Molecular profile

Le Tourneau et al. BJC [Epub ahead of print April 24, 2014]


Tumor biopsy

NGS+Cytoscan HD

+IHC

Bioinformatics


Specifictherapyavailable

Non eligiblepatient

NO

Eligiblepatient

YES


RConventional therapy atphysicians' discretion

Bioinformatics


Tumor biopsy

NGS+Cytoscan HD

+IHC

therapyavailable


YESNO

Non eligiblepatient

Eligiblepatient



ImatinibEverolimusSorafenibErlotinibDasatinibLapatinib

TrastuzumabVemurafenibTamoxifenLetrozoleAbiraterone

Targeted therapy based on molecularprofiling

Cross-over

Specific

Treatment algorithm

Targets

KIT, ABL1/2, RET

PI3KCA, AKT1AKT2/3, mTOR, RICTOR, RAPTORPTEN

STK11

INPP4B

BRAF

PDGFRA/B, FLT3

EGFR

HER-2

SRCEPHA2, LCK, YES1

ER, PR

AR

Molecular alterations

Mutation/Amplification

Mutation/AmplificationAmplificationHomozygous deletionHeterozygous deletion + mutation or IHCHomozygous deletionHeterozygous deletion + mutationHomozygous deletion





Mutation/AmplificationAmplification

Protein expression >10% IHC

Protein expression >10% IHC

Targeted therapies

Imatinib

Everolimus

Vemurafenib

Sorafenib

Erlotinib

Lapatinib + Trastuzumab

Dasatinib

Tamoxifen or Letrozole

Abiraterone

Le Tourneau et al. BJC [Epub ahead of print April 24, 2014]

Treatment algorithm

• Multiple molecular alterations:- DNA alterations are considered of a higher impact than

hormone receptors expression

- If AR and ER/PR are both overexpressed, the hormonereceptor with the highest expression level is taken intoaccount

- If >2 DNA alterations are identified, clinically validatedalterations prevail (i.e. HER-2 amplification)

- Erlotinib is not given in case of KRAS mutation

SHIVA

• Randomization:

- 1:1

- stratification on the Royal MarsdenPrognostic score for oncology phase Icancer patients

- stratification on the signalling pathway(PI3K/AKT/mTOR, Hormone receptors, MAPK pathway)

Arkenau et al. JCO 2009;27:2692-6

SHIVA

• Sample size:- 6 months PFS = 15% in phase I cancer patients treated

with cytotoxic agents

- Hypothesis: 6 months PFS = 30% in the experimentalarm (HR = 0.625)

142 events with a type 1 error of 5% and a power of80% in the bilateral setting

200 patients should be randomized

up to 1,000 patients might have to be included

Hortsmann et al. NEJM 2005;352:895-904

Accrual

Included

Planned

740

Randomization

Randomized

Planned

170

MPACT (NCI)

Kummar et al. NCI-EORTC-ASCO 2013




Non-randomized

Randomized

1 or NTumor types


1

N

N

1 or N

Treatments N 1


Summary





Non-randomized

Randomized

Tumor types


1

N

N

1 or N

1 or N

N

Treatments N 1


Summary





Non-randomized

Randomized

Tumor types


1

N

N

1 or N

1 or N

N

Treatments N 1 N


Summary





Non-randomized

Randomized

Tumor types


1

N

N

1 or N

1 or N

N

Treatments N 1 N

Test Test drugs efficacy Test algorithm efficiency

Summary


Conclusions

• High-throughput technologies haveentered the clinic

• Emergence of personalized medicineclinical trials

• Multiples challenges

• It remains to be demonstrated that the useof high throughput technologies improvespatients outcome

Acknowledgments• Direction

Thierry Philip

Claude Huriet

Pierre Teillac

Daniel Louvard

• ICGEXOlivier Delattre

Thomas Rio Frio

Quentin Leroy

Virginie Bernard

• UGECPatricia Tresca

Sebastien Armanet

Fabrice Mulot

• BiostatisticsXavier Paoletti

Corine Plancher

Cécile Mauborgne

• PathologyAnne Salomon

Odette Mariani

Frédérique Hammel

Xavier Sastre

Didier Meseure

• Translational researchMaud Kamal

David Gentien

Sergio Roman-Roman

• RadiologyVincent Servois

Daniel Szwarc

• BioinformaticsPhilippe Huppé

Nicolas Servant

Julien Romejon

Emmanuel Barillot

Philippe La Rosa

Alexandre Hamburger

Pierre Gestraud

Fanny Coffin

Séverine Lair

Bruno Zeitouni

Alban Lermine

Camille Barette

• ComunicationCéline Giustranti

Catherine Goupillon-Senghor

Cécile Charre

• GeneticsIvan Bièche

Gaëlle Pierron

Etienne Rouleau

Céline Callens

Marc-Henri Stern

• SurgeryThomas Jouffroy

José Rodriguez

Angélique Girod

Pascale Mariani

Virginie Fourchotte

Fabien Reyal

• FoundationHélène Bongrain- Meng

Ifrah El-Alia

Véronique Masson

Agnès Hubert

• Clinical researchMalika Medjbahri

• SamplingSolène Padiglione

• PharmacyLaurence Escalup

• OncologyAlain Livartowski

Suzy Scholl

Laurent Mignot

Philippe Beuzeboc

Paul Cottu

Jean-Yves Pierga

Véronique Diéras

Valérie Laurence

Sophie Piperno-Neumann

Catherine Daniel

Wulfran Cacheux

Bruno Buecher

Emmanuel Mitry

Astrid Lièvre

Coraline Dubot

Etienne Brain

Barbara Dieumegard

Frédérique Cvitkovic

from trials evaluating drugs to trials evaluating treatment algorithms – focus on the shiva trial

Science

stratified histology

introduction tsimberidou

introduction ciriello

introduction targets

nsclc kidney

endocrine tumors kidney

ckit overexpression

cancer discov