Transcript Voir la présentation (médecine personnalisée)

ITMO Cancer
From Precision to
Personalised Medicine
Brussels 24/09/2013
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Genomics in Oncology:
from biology to care
 Generating information about cancer
development and metastasis
 Identifying new genes susceptible to induce
« addiction », thus « targetable »
 Helping to develop new therapies
 Helping to accelerate new drug approval: new
early phase trials, shortening time to MA
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How are we currently using
genomics in patient management?
Single Gene Alteration
 Already incorporated in
patient management
 Impacts the following
decisions :
• Selection of agents:
− Positive effect
− Negative effect
• Prediction of toxicity
• Treatment changes in
case of resistance
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Multiple gene alterations
Under investigation at
many institutions
Should it be incorporated in
routine care (when?) or
remain a research tool?
Is it practical?
What is the cost/benefit?
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Structures and Infrastructures:
Molecular genetic centers
 High quality molecular
testing, all patients,
anywhere in France
 Partnerships between
University hospitals
and cancer centers

Regional organization
 PPPs with Roche,
Amgen, Pfizer, GSK, AZ
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From genetic centers to biology
driven therapy
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F Nowak,
Soria and
F Calvo,
Nat Rev MERIEUX
Clin Oncol. INERIS
2012
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An increasing number of actionable
molecular alterations
Druggable Target
Class
Drug
KRAS mut
MEKi
Pi3Ki
GSK1120212
PF-04691502
BRAF V600E
RAFi
Pi3Ki
GSK2118436
PF-04691502
HER2 mut/ampl
HER2i
PF-00299804
BIBW2992
NRAS
Pi3Ki
MEKi
PF-04691502
GSK1120212
PTEN
Pi3Ki
BKM120
PI3KCA1 or
PDPK1
Pi3Ki
Pi3Ki
PF-04691502
BKM120
FGFR mut/ampl
FGFRi
AZD4547
LKB1 or STK11
LKB1i
CC-223
ALK
Meti
PF 02341066
MET mut/ampl
METi
ARQ197
Crizotinib
 Implementation of Next Generation Sequencing (NGS) for clinical use
 Development of pharmacogenetics for reducing toxicities and improving
efficacy
 Implementation ongoing for the investigation of a panel of genes
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 Next
: analysis
whole
exome
genome
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Single genes
Gene panels
Exomes
Whole genomes
 Gene expression profiles
 Copy Number Variation
2000
2010
2015
New technologies… have resulted in > 100,000-fold decreases in
sequencing costs:
• $1,000/genome will soon be achieved
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ICGC Map
64 projects launched
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ICGC: Liver Cancer genome
programme
Guichard et al. Nature Genetics, 2012
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Proof of concept for molecularly guided
therapy: prospective trial for the future
 Need to demonstrate that sequencing tumours (Exome-Whole
GS) is of interest for treatment decision
 A national cooperative randomized study in early metastatic
patient in some tumour types
 Comparing therapeutic decision based on NGS to current
diagnostic procedures including defined genetic tests
 To be performed in the CLIP2 (INCa- Fondation ARCUnicancer)
 With the help of Pharmas to provide drugs already in phase 2
trials
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Conclusions and perspectives
The French molecular screening initiative :
 has been operational for 5 years for access to targeted therapies
 Opens the path to switch to complete genomics and personalized
therapy
 is an opportunity to improve patient accrual into clinical trials
Current research on genomics of cancer
 is the basis to understand the steps of cancer development,
identify new targets and develop new therapies through the
synergy between fundamental, translational and clinical sciences
 Allows to foster on innovation through bioinformatics, biomarkers
and drug development
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Rapid access to innovation
Offer each patient in France an equal access to molecular
tests as soon as a new targeted therapy is available
Mid 2008 : EMA approvals for panitumumab and
cetuximab for patients with wild type KRAS
tumours
June 2009 : gefitinib approvals by EMA for
patients with activating mutations of EGFR in
their tumors
 Allocation of €2.5M to the 28 centres at the end of
2008
 Allocation of €1.7M to the 28 centres at the
end of 2009
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Surveys of mutation databases indicate
that most mutations are found in many
tumour types
80.0%
70.0%
Lung carcinoma (all subtypes)
60.0%
Prostate adenocarcinoma
50.0%
Breast carcinoma (all subtypes)
Colon adenocarcinoma
40.0%
Pancreatic ductal adenocarcinoma
Ovarian carcinoma (all subtypes)
30.0%
Hepatocellular carcinoma
20.0%
Gastric adenocarcinoma
Renal cell carcinoma
10.0%
Malignant melanoma
0.0%
Sanger Institute: http://www.sanger.ac.uk/cosmic, COSMIC v54
Release (Forbes et al., 2011).
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Targeted therapies with sufficient
preclinical and clinical data (level 1)
Activation of AKT/mTor
pathway (20%)
PIK3CA mutations (1%)
TSC1 and TSC2 mutations (7%)
PTEN HD (2%)
Activation without
known mutation (10%)
Activation of
ras/raf/MAP kinase
pathway (9 %)
Targeted
therapy
mTor inhibitor
(everolimus, sirolimus)
BRAF V600 inhibitor
(vemurafenib)
BRAF mutation (1%)
FGFR inhibitor
FGF19 amplification (1%)
Cytokine and growth
factor receptors (7%)
EGFR overexpression (1%)
(pazopanib)
Antibody anti-EGFR
(cetuximab)
HER2neu overexpression (1%)
Antibody anti-HER2
(trastuzumab)
SUFU mutation (1 %)
Private mutations (2%)
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MGMT HD (1%)
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Courtesy of Nault and Zucman, unpublished
Inhibitor of sonic
hedgehog (vismodegib)
Oral alkylating agent
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Putative targeted therapies: on-going
pre-clinical analyses (level 2)
NFE2L2 mutation (5%)
KEAP1 mutation (3%)
Activation without known
mutation (12%)
Activation of
NFE2L2/KEAP1 pathway
(20 %)
Activation of ras/raf/MAP
kinase pathway (9 %)
Targeted
therapy
HSP90 inhibitor
(17-AAG and 17DMAG)
MEK 1/2
inhibitor
RPS6KA3 mutation (8%)
(selumitinib)
Cytokine and growth
factor receptors (7 %)
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JAK1/JAK2
inhibitor
IL6ST mutation (2%)
(ruxolitinib)
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Courtesy of Nault and Zucman, unpublished
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SAFIR02
Biopsy
Metastatic Site:
NGS target gene
sequencing
Arm A: targeted therapy
According to the
molecular alteration
R
Metastatic Her2-neg
breast cancer
pretreated with 1 line
chemotherapy
Metastatic EGFR /
ALK wt lung cancer
not pretreated with
chemotherapy
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Druggable
molecular
alteration
Chemotherapy:
6-8 cycles
PR,
SD
No alteration
Or non
druggable
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Arm B: best available
therapy
Based on available
mono-test
PI: Fabrice André
Sponsor: UNICANCERFunding partners INCaARC
N: 1000 for screening, 400
for therapeutic phase
Not included
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2012
data
36,4%
3,9%
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Liver Cancer genome programme
Guichard et al. Nature Genetics, 2012
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