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Di Maio Lucca 2013
Gli studi clinici
nell’era delle terapie
p
personalizzate
Highlights da Sidney
Massimo Di Maio
S.C. Sperimentazioni Cliniche
Istituto Nazionale Tumori
Fondazione G.Pascale – IRCCS
Napoli
[email protected]
Di Maio Lucca 2013
Gli studi clinici nell’era delle terapie personalizzate
Highlights da Sidney
• Qualche progresso… ma anche fallimenti!
• …siamo sicuri che il target sia sempre driver?
• …aspettando i risultati delle nuove metodologie
di studio
• Bisogna fare i conti con l’eterogeneità intratumorale!
Di Maio Lucca 2013
Mark Kris
PL03.07
Sidney 2013
Di Maio Lucca 2013
Mark Kris, PL03.07 , Sidney 2013
Di Maio Lucca 2013
Mark Kris, PL03.07 , Sidney 2013
Di Maio Lucca 2013
D. Gandara, The Future of RCTs in the Molecular Era? Sidney 2013
Di Maio Lucca 2013
D. Gandara, The Future of RCTs in the Molecular Era? Sidney 2013
Di Maio Lucca 2013
Alcuni risultati negativi
con la vecchia strategia “all comers”
Drug
Mechanism
of action
Selection
Author
(
(abstract)
)
Necitumumab
Anti-EGFR
Nonsquamous
Paz-Ares
(O03 02)
(O03.02)
Phase III:
Cis/Pem +/+/
Neci
Cixutumumab
Anti-IGF-1R
Nonsquamous
Scagliotti
(P1.11-018 )
Phase II
random:
Cis/Pem +/+/
Cix
Di Maio Lucca 2013
1° line treatment:
Cis/Pem +/+/ cixutumumab
(anti IGF-1R)
Scagliotti, P1.11-018 , Sidney 2013
Di Maio Lucca 2013
Gli studi clinici nell’era delle terapie personalizzate
Highlights da Sidney
• Qualche
Q l h progresso… ma anche
h ffallimenti!
lli
ti!
• …siamo sicuri che il target sia sempre
driver?
• …aspettando i risultati delle nuove metodologie
di studio
• Bisogna fare i conti con l’eterogeneità intratumorale!
Di Maio Lucca 2013
Matthew Meyerson. What can we learn from lung cancer sequencing?
Sidney 2013
Di Maio Lucca 2013
Matthew Meyerson. What can we learn from lung cancer sequencing?
Sidney 2013
Di Maio Lucca 2013
Lawrence et al, Nature 489, 519–525 (27 September 2012)
Matthew Meyerson. What can we learn from lung cancer sequencing?
Sidney 2013
Di Maio Lucca 2013
Lawrence et al, Nature 489, 519–525 (27 September 2012)
Matthew Meyerson. What can we learn from lung cancer sequencing?
Sidney 2013
Di Maio Lucca 2013
Matthew Meyerson. What can we learn from lung cancer sequencing?
Sidney 2013
Di Maio Lucca 2013
Gli studi clinici nell’era delle terapie personalizzate
Highlights da Sidney
• Qualche progresso… ma anche fallimenti!
• …siamo sicuri che il target sia sempre driver?
• …aspettando i risultati delle nuove
metodologie di studio
• Bisogna fare i conti con l’eterogeneità intratumorale!
Di Maio Lucca 2013
Statistics of Personalised Medicine
Clinical
Cli
i l Trial
T i l Designs
D i
f Biomarker
for
Bi
k Driven
Di
Th
Therapies
i
in Early Disease (Adjuvant)
Giorgio Scagliotti
Clinical Trial Designs for Biomarker Driven Therapies
in Advanced Disease
Roy Herbst
The Future of RCTs in the Molecular Era?
David Gandara
Di Maio Lucca 2013
G Scagliotti, Sidney 2013
Di Maio Lucca 2013
G Scagliotti, Sidney 2013
Di Maio Lucca 2013
G Scagliotti, Sidney 2013
Di Maio Lucca 2013
Statistics of Personalised Medicine
Clinical Trial Designs for Biomarker Driven Therapies
in Early Disease (Adjuvant)
Giorgio Scagliotti
Clinical Trial Designs for Biomarker Driven Therapies
in Advanced Disease
Roy Herbst
The Future of RCTs in the Molecular Era?
David Gandara
Di Maio Lucca 2013
Roy Herbst, Sidney 2013
Di Maio Lucca 2013
Roy Herbst, Sidney 2013
Di Maio Lucca 2013
Roy Herbst, Sidney 2013
Di Maio Lucca 2013
Roy Herbst, Sidney 2013
Di Maio Lucca 2013
Roy Herbst, Sidney 2013
Di Maio Lucca 2013
Roy Herbst, Sidney 2013
Di Maio Lucca 2013
Clinical Trial Design
for Drug Development
Adaptive Designs: For
J Jack Lee
J.
Adaptive Designs: Against
Marc Buyse
Pro/Con session, Sidney 2013
Di Maio Lucca 2013
Adaptive randomization: pro
Jack Lee, ASCO 2012
Di Maio Lucca 2013
Adaptive randomization: contra
• Adaptive randomization, which consists of allocating
more patients to the treatment that appears to have
more efficacy ("play-the-winner"), is justified neither
statistically
t ti ti ll nor ethically.
thi ll
• This strategy may produce slight reductions in the
number
b off patients
ti t exposed
d to
t the
th inferior
i f i treatment,
t t
t but
b t
it may increase the total sample size of the trial as
compared to using a fixed allocation ratio
ratio.
• More importantly, this adaptive strategy conveys the
misleading impression that one treatment is known to be
better than the other, a situation in which equipoise is
not maintained and randomization no longer ethical
ethical.
Marc Buyse, Sidney 2013
Di Maio Lucca 2013
Rationale for Master Protocol Design
•
Multi-arm Master Protocol
•
Homogeneous patient populations & consistent eligibility
from arm to arm
•
Each arm independent of the others
•
Infrastructure facilitates opening new arms faster
•
Phase II-III
II III design allows rapid drug/biomarker testing for
detection of “large effects”
•
Screening large numbers of patients for multiple targets by a
broad-based NGS platform reduces the screen failure rate
•
Provides a sufficient “hit
hit rate
rate” to engage patients & physicians
•
Bring safe & effective drugs to patients faster
•
Designed to faciliate FDA approval of new drugs
Roy Herbst, Sidney 2013
Di Maio Lucca 2013
Master Protocol: Potential targets and drugs
Target
Drug
Biomarker
Prevalence
IGFR
LDK378
IGFR expression
60%
PI3K
BKM120
(PI3Ka) MLN1117
(AKT)GSK2110183
PI3K expr/ amplif, p/
p ,
PIK3CA mut
PTEN loss
AKT , PIK3CA fus.
25%.
16%
15%
FGFR
LY2874455
JNJ42756493
FGF Trap
Trap‐
GSK3052230
FRGFR expr
FGFR1, 2 amplif, FGFR 1, 2 mut
FGFR 1, 2 mut
15%.
10%
p53
MK‐1775 (+gem)
TP53 mut
81%
MET
AMG337
LY2801653
JNJ38877605
F ti ib
Foretinib
(GSK1363089)
MET expression
50%
HGF
AMG102
HGF expression
PD‐1
MEDI4736 (PD‐L1)
PDL‐1 expression
Roy Herbst, Sidney 2013
50%
Di Maio Lucca 2013
Target
Drug
Biomarker
HDM2
Anti‐HDM2
HDM2 amplif
RANKL
Denosumab
RANK/RANKL expr
Notch
LY2835219
Notch1 mut
8%
EGFR
CO1686
L858R, Del(19),
T790M
1‐3%
RAS
MEKi+panPI3K
RAS
CKN2A
LY2835219 (CDK4/6)
CDKN2A mut, deletion
deletion, methylation
CCND1 amplif
HER3
HER3mAb
HER3 expression
HER3 expression
mTOR1/TORC2
MLN0128
STK11,TSC1, TSC2 mut
Raf
MLN2480
TBD
Roy Herbst, Sidney 2013
Prevalence
15%,
30%
21%
13%
2%, 3%, 3%
Di Maio Lucca 2013
S1400: MASTER LUNGLUNG-1: Squamous Lung Cancer
Cancer-- 2nd Line Therapy
CT*
Biomarker
Profiling (NGS/CLIA)
Biomarker
Non‐‐Match
Non
Non‐
Non‐
Match
Drug
Multiple Phase II‐ III Arms with “rolling Opening & Closure
Biomarker A
Biomarker A
Biomarker TT A
TT A
CT*
Endpoint
(Interim PFS)
OS
Biomarker Β
Biomarker Β
Biomarker TT B
TT B
CT*
Endpoint
(Interim PFS)
OS
Biomarker C
Biomarker C
Biomarker TT C
TT C+CT
CT*
Endpoint
(Interim PFS)
OS
Biomarker D
Biomarker D
Biomarker TT D
TT D+E
E*
Endpoint
(Interim PFS)
OS
TT=Targeted therapy, CT=chemotherapy (docetaxel
TT=Targeted therapy, CT=chemotherapy (
docetaxel or gemcitabine), E=erlotinib
or gemcitabine), E=erlotinib
p
p
(
)
PI: V. Papadimitrakopoulou (SWOG)
Steering Committee Chair: R. Herbst (YALE, SWOG)
Roy Herbst, Sidney 2013
Di Maio Lucca 2013
S1400: MASTER LUNGLUNG-1: Squamous Lung Cancer
Cancer-- 2nd Line Therapy
CT*
Biomarker
Profiling (NGS/CLIA)
Biomarker
Non‐‐Match
Non
PD‐‐L1i
PD
Multiple Phase II‐ III Arms with “rolling Opening & Closure
PiK3CA Mut
PiK3CA Mut
PiK3CA CCND1 ampl or
CCND1
CCND1 ampl
CDKN2 loss + RB WT
CT*
CDK 4/6i CT*
Endpoint
(Interim PFS)
OS
Endpoint
(Interim PFS)
OS
PI3Ki
FGFR ampl, FGFR
FGFR ampl
ampl,, ,
ampl
Mut, Fusion
Mut
, Fusion
FGFRi+CT
CT*
Endpoint
(Interim PFS)
OS
MET Expr
MET Expr
MET HGFi+E
E*
Endpoint
(Interim PFS)
OS
TT=Targeted therapy, CT=chemotherapy (docetaxel
TT=Targeted therapy, CT=chemotherapy (
docetaxel or gemcitabine), E=erlotinib
or gemcitabine), E=erlotinib
Roy Herbst, Sidney 2013
Di Maio Lucca 2013
Gli studi clinici nell’era delle terapie personalizzate
Highlights da Sidney
• Qualche progresso… ma anche fallimenti!
• …siamo sicuri che il target sia sempre driver?
• …aspettando i risultati delle nuove metodologie
di studio
• Bisogna fare i conti con l’eterogeneità intratumorale!
Di Maio Lucca 2013
Unmet Needs in Future NSCLC Clinical Trials
when viewed as a Multitude of Genomic Subsets
• H
How tto develop
d
l d
drugs ffor uncommon-rare
genotypes?
• How to apply broad-based genomic screening
(
(NGS)?
)
• How to initiate therapy with an acceptable turnaround
d time
i
ffor molecular
l
l testing?
i ? ((<2
2 weeks)
k )
• H
How d
do you accountt ffor b
both
th iintert
and
d iintra-tumor
t t
heterogeneity?
D. Gandara, The Future of RCTs in the Molecular Era? Sidney 2013
Di Maio Lucca 2013
Charlie Swanton, Sidney 2013
Di Maio Lucca 2013
Implications for Therapy and Outcome
p
py
Intertumour Heterogeneity
Intratumour Heterogeneity
Intercellular Heterogeneity
Review principles of intratumour
p
p
heterogeneity learned from Renal Cancer
g
y
Apply methods to study cancer evolution in Non‐Small Cell Lung Cancer
Charlie Swanton, Sidney 2013
Burrell, Mcgranahan, Bartek and Swanton Nature 2013
Di Maio Lucca 2013
Charlie Swanton, Sidney 2013
Di Maio Lucca 2013
Di Maio Lucca 2013
Charlie Swanton, Sidney 2013
Yap, Gerlinger, Pusztai, Futreal and Swanton Sci Trans Med 2012
Di Maio Lucca 2013
Target Tumour Phylogenetic Trunks and Resolve Branches
Branched Genetic Events Present in
Some Cancer Cells not others
Dynamic during disease course
Monitor subclonal events to define
drug resistance mechanisms
Trunk Genetic Events Present in
Every
y Cancer Cell
DEFINE TRUNK DRIVERS
Charlie Swanton, Sidney 2013
Di Maio Lucca 2013
Roy Herbst, Sidney 2013
Di Maio Lucca 2013
Gli studi clinici nell’era delle terapie personalizzate
Highlights da Sidney
• Qualche progresso… ma anche fallimenti!
• …siamo sicuri che il target sia sempre driver?
• …aspettando i risultati delle nuove metodologie
di studio
• Bisogna fare i conti con l’eterogeneità intratumorale!
Di Maio Lucca 2013
Grazie per l’attenzione!
Massimo Di Maio
S.C. Sperimentazioni Cliniche
Istituto Nazionale Tumori
Fondazione G.Pascale – IRCCS
Napoli
[email protected]