Translational Research in Non–Small Cell Lung
Cancer (NSCLC):
What Are the Available “Tools” & How Can You Use
Them?
David R. Gandara, MD
University of California Davis
Comprehensive Cancer Center
1
Available “Tools” for Translational Research in NSCLC: Interaction of
Pathology, “Omics,” and Immuno-Biology
From “All Patients Are the Same”
From Histology to
Prognostic and/or
Predictive Biomarkers
to Inter- and Intra-Patient
Heterogeneity in Tumour Biology
& Immuno-Biology
Translational Research
Personalised Therapy for
Individual Patients With NSCLC
Adapted from Gandara et al. Clin Lung Cancer. 2012.
2
Moving From Histologic Classification to Molecular
Classification of NSCLC Patients Into Prognostic or
Predictive Subgroups for Therapy
• Histologic subtyping groups tumours based on microscopic pattern recognition
by a pathologist
• At best, Histology = “crude molecular selection”
EGFR Mutation
Positive ALK FISH
3
Evolution of NSCLC Subtyping From Histologic to Molecular-Based
NSCLC
as one
disease
First
Targeted
Therapies
in NSCLC
ALK
EGFR
Li, Mack, Gandara et al. JCO. 2013 (adapted from Pao et al).
4
Magnitude of Genomic Derangement Is
Greatest in Lung Cancer
n=109 81
64
38
316
100
17
82
Mutations
Per Mb DNA
28
119
21
40
20
Carcinogen-induced Cancers
100 / Mb
10 / Mb
Hematologic &
Childhood Cancers
Ovarian, Breast,
Prostate Cancers
0.1 / Mb
Squamous
Adenoma
1 / Mb
??
Adapted from The Cancer Genome Atlas Project: Govindan & Kondath et al. Nature. 2013.
5
Lung Cancer Complexity on an Individual Patient Basis: Squamous-Cell
Lung Cancer Examples (“Circos”)
LUSC-66-2756
LUSC-34-2600
LUSC-56-1622
LUSC-60-2695
LUSC-43-3394
LUSC-60-2711
LUSC-34-2609
LUSC-60-2713
From Ramaswamy Govindan. TCGA (The Cancer Genome Atlas).
6
Integration of Biomarkers Into Clinical Practice: Past, Current &
Future
Empiric Approach (Past)
(Compound-Based Therapy):
Clinical-histologic factors to select drugs for
individual patients
1. Histomorphological
Diagnosis:
Cancerous
2. Molecular Diagnosis:
Archival FFPE
tumour specimens
Archival cancer
specimens
Macro- or
Micro-dissection
of Tumours
Extract tumour
nucleic acids:
DNA and RNA
Representative technologies:
Current Approach (Target-Based Therapy V1.0):
Single gene molecular testing for decision-making in
individual patients
Evolving Approach (Target-Based Therapy V2.0):
Multiplexed molecular tests with increased sensitivity &
output for decision-making in individual patients
Near-Future Approach (Patient-Based Therapy):
Genomic profiling by high throughput next generation
sequencing for decision-making in individual patients
From Li, Gandara et al. JCO. 2013.
Plasma cfDNA by NGS
Single Biomarker Tests:
• Sanger DNA Sequencing
• RT-PCR
• FISH
• IHC
Multiplex, Hot Spot Mutation Tests:
• PCR-based SNaPshot
• PCR-based Mass Array SNP
• Sequenom
Initial High-Throughput Technologies:
• SNP/CNV DNA microarray
• RNA microarray
Next-Generation Sequencing (NGS):
• Whole Genome or Exome Capture Sequencing (DNA)
• Whole or Targeted Transcriptome Sequencing (RNA)
• Epigenetic profiling
7
Comprehensive Cancer Genomic Test: 200+ Genes
Foundation Medicine One
<14 days
8
Guardant360 Panel 2015: Plasma NGS
Complete* or Critical Exon Coverage in 68 Genes
Point Mutations
Amplifications
Fusions
Indels
AKT1
ALK
APC
AR
AR
ALK
EGFR exon 19 deletions
AFAR
ARID1A
ATM
BRAF
BRAF
RET
EGFR exon 20 insertions
BRCA1
BRCA2
CCDN1
CCND2
CCNE1
ROS1
CCNE1
CDH1
CDK4
CDK6
CDK4
NTRK1
CDKN2A
CDKN2B
CTNNB1
EGFR
CDK8
ERBB2
ESR1
EZH2
FBXW7
EGFR
FGFR1
FGFR2
FGFR3
GATA3
ERBB2
GNA11
GNAQ
GNAS
HNF1A
FGFR1
HRAS
IDH1
IDH2
JAK2
FGFR2
JAK3
KIT
KRAS
MAP2K1
KIT
MAP2K2
MET
MLH1
MPL
KRAS
MYC
NF1
NFE2L2
NOTCH1
MET
NPM1
NRAS
NTRK1
PDGFRA
MYC
PIK3CA
PTEN
PTPN11
RAF1
PDGFRA
RET
RHEB
RHOA
RIT1
PIK3CA
ROS1
SMAD4
SMO
SRC
RAF1
STK11
TERT**
TP53
VHL
*Complete exon coverage for genes in bold; **Includes TERT promoter region.
9
Available “Tools” for Translational Research in Advanced
NSCLC
“Targeted Therapy”
Chemotherapy
Histologic
Subtyping for
Chemotherapy
? Targeted
Nintedinib?
Necitumumab?
Ramucirumab?
Checkpoint Immunotherapy
Anti-PD-1
and PD-L1
Anti-CTLA-4
Targeted
TKIs:
-EGFR
-ALK
-ROS1
Translational Research Opportunities: How do we optimize use of
these “tools” (therapeutic modalities) in order to create
new treatment paradigms?
Targeted Therapies in Oncogene-Driven NSCLC:
De Novo & Acquired Resistance
• Targeted Therapies against Oncogene-Driven Cancers, EGFR mutation+ (erlotinib) or ALKfusion+ (crizotinib), improve response and PFS when compared with chemotherapy
• Even in these most sensitive cancers, approximately 25% to 40% do not respond to TKI
therapy (de novo resistance)
• Even in these most-sensitive cancers, acquired resistance is universal, with PFS averaging
≈10-14 months
Oncogene-driven
NSCLC
Gandara, Redman et al. Clin Lung Cancer. 2014.
11
Evolutionary Biology & Acquired Tumour Resistance
• Intra-tumour heterogeneity is present at
baseline (scenarios 1 & 2)
Scenario 1
Scenario 2
“Driver” Oncogene
“Driver” Oncogene
Evolution
over time
with therapy
Evolution
over time
with therapy
New
“Driver”
New
“Driver”
• Reducing sensitive clones by therapy
permits unopposed growth of less fit
resistant clones
or emergence of a new clone
(“Tumour Darwinism”)
• Separating “new drivers” from
“passengers” is complex
• This process is dynamic, not static
• Original sensitive clone is still present ].
at time of resistance
Original
Sensitive
Clone
Adapted from Gandara et al. Clin Lung Cancer. 2012.
12
Available “Tools” for Translational Research:
Re-Biopsy to Assess Tumour Evolution
Referring
Physician
Identify
Patient
Pathologist
Multidisciplinary
Team
(Tumour Board)
Identify
Target
Lesion
Med Oncologist
Thoracic Surgeon
Radiation Oncologist
Pulmonologist
Radiologist
Pathologist
Pulmonologist
Interventional Radiologist
Surgeon
Histology Evaluation
Determine
Therapy
Biopsy
Molecular Biomarker
Testing
When
Progression
 Re-Biopsy
Oncologist
T
r
e
a
t
Determine
New Therapy
Treat
When
Progression
 Re-Biopsy
Adapted from: Gandara. ASTRO/ASCO/IASLC Symposium on Molecular Testing, 2012.
13
Emergence of ALK Resistance Mechanisms
After Crizotinib
•
•
•
•
Secondary resistance ALK mutations
ALK gene copy number increase
Transition to EGFR mutation
Transition to KRAS mutation
Consistent with mathematical models
of evolutionary biology
Doeble, Camidge et al. CCR. 2012.
14
Schema for Multidisciplinary Integration of Biomarker
Testing in Advanced-Stage NSCLC: Looking for “Actionable” Oncogenes
Referring
Physician
Identify
Patient
Pathologist
Multidisciplinary
Team
(Tumour Board)
Identify
Target
Lesion
Med Oncologist
Thoracic Surgeon
Radiation Oncologist
Pulmonologist
Radiologist
Pathologist
Pulmonologist
Interventional Radiologist
Surgeon
Histology Evaluation
Determine
Therapy
Biopsy
Molecular Biomarker
Testing
When
Progression
 Re-Biopsy
Plasma cfDNA
Oncologist
T
r
e
a
t
Determine
New Therapy
Treat
When
Progression
 Re-Biopsy
Plasma cfDNA
Adapted from: Gandara. ASTRO/ASCO/IASLC Symposium on Molecular Testing, 2012.
15
Association Between pEGFR mut+ at C3 and PFS/OS (Both Treatment
Arms Combined)
PFS
OS
C3 mut+
C3 mut+
C3 mut–
C3 mut–
PFS probability
0.8
0.6
0.4
0.2
0.8
0.6
0.4
0.2
7.2 12.0
0
0
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
42 42 35 28 14 7 6 4 1 1 1 1 0 0 0
80 80 77 65 59 47 40 34 32 28 23 19 13 10 7
18.2
31.9
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36
Time (months)
Patients, n
C3 mut+
C3 mut–
Median = 18.2 months
(95% CI: 14.2–27.4)
Median= 31.9 months
(95% CI: 23.5–undefined)
HR = 0.51
(95% CI: 0.31–0.84);
P=0.0066
1.0
OS probability
Median = 7.2 months
(95% CI: 6.0–7.8)
Median =1 2.0 months
(95% CI: 9.6–16.5)
HR = 0.32
(95% CI: 0.21–0.48);
P<0.0001
1.0
Time (months)
0
3
0
0
Patients, n
C3 mut+
C3 mut–
42 42 42 41 37 32 30 28 23 21 18 14 14 12 9 4 3 2 0
80 80 80 77 77 77 76 71 68 64 59 52 38 29 22 12 3 1 0
Mok et al. WCLC 2013.
16
Approaches to Acquired Resistance in Oncogene-driven Cancers
(EGFR MT & ALK Fusion)
Systemic-PD
Advanced
NSCLC With
Oncogene-driven
Cancer
Targeted
TKI
-EGFR Mutation
-ALK Fusion
Switch Therapy:
Chemotherapy or 2nd/3rd gen TKI
RECIST
Response
Subsequent
Systemic PD
Continue same TKI alone
(post-progressive disease)
Add Therapy to TKI
-Chemotherapy ?
-Another Targeted Agent?
Re-biopsy
Gandara et al. Clin Lung Cancer. 2014.
17
IMPRESS: Phase III Trial of Post-progression Gefitinib/Chemotherapy vs Chemotherapy
Alone in EGFR Mutation–Positive NSCLC After Prior Response (Acquired Resistance)
Gefitinib 250 mg +
cisplatin + pemetrexed
up to 6 cycles
(n=133)
• Stage IIIB/IV NSCLC
• EGFR mutation positive
• WHO PS 0–1
• Prior response* to 1st-line
gefitinib
PD
• PD <4 weeks prior to study
(n=265)
R
PD
Primary endpoint: PFS
1:1
Placebo +
cisplatin + pemetrexed
up to 6 cycles
(n=132)
PD
Secondary endpoints
• OS, ORR, DCR
• Safety and tolerability, health-related QoL
*CR/PR ≥4 months or SD >6 months.
Mok et al. ESMO-Ann Oncol. 2014;25(suppl 4): abstr LBA2_PR.
18
IMPRESS: Phase III Trial of Post-progression Gefitinib/Chemotherapy vs Chemotherapy
Alone in EGFR Mutation–Positive NSCLC After Prior Response (Acquired Resistance)
PFS (primary endpoint; ITT)
OS (ITT; 33% of events)
Gefitinib
(n=133)
Placebo
(n=132)
5.4
5.4
Median PFS, months
Response:
Number of events, n (%)
34%
0.9
0.9
0.8
0.8
0.7
0.7
0.6
0.5
0.4
0.3
0.2
14.8
17.2
50 (37.6)
37 (28.0)
HRa (95% CI) = 1.62 (1.05, 2.52); p=0.029
1.0
Probability of PFS
Probability of PFS
32%
Placebo
(n=132)
Median OS, months
HRa (95% CI) = 0.86 (0.65, 1.13); p=0.273
1.0
Gefitinib
(n=133)
0.6
0.5
0.4
0.3
0.2
Gefitinib (n=133)
0.1
0
0
2
4
Gefitinib (n=133)
0.1
Placebo (n=132)
Placebo (n=132)
0
6
8
10
12
14
0
2
4
Time of randomisation (months)
Patients at risk:
Gefitinib
133
Placebo
132
110
100
88
85
40
39
25
17
12
5
6
8
10
12
14
16
18 20
22
24
26
2
4
0
2
0
0
Time of randomisation (months)
6
4
0
0
Patients at risk:
Gefitinib
133
Placebo
132
125
129
111
119
88
94
64
76
43
55
27
39
19
27
12
16
8
10
4
7
Mok et al. ESMO-Ann Oncol. 2014;25(suppl 4): Abstract LBA2_PR.
19
Mechanisms of EGFR TKI Resistance (Selected)
• Secondary EGFR mutation
(ie, T790m)
2nd Gen EGFR TKIs
ie, Afatinib
Afatinib/Cetuximab
rd
3 Gen- AZ9291, CO1686
• Bypass signaling via ERBB3
Anti-ERBB3 drugs
ie, MM151 MoAB
• MET over-expression
MET Inhibitors
ie, MET-Mab (MoAB)
ARQ197 (TKI)
• PIK3CA Mutation/AKT
ie, BKM120 (PIK3CA)
ie, MK2206 (AKT)
& Others
HSP inhibitors
ie, Ganetespib
AUY922
Adapted from Engelman et al.
20
Best Response in EGFR-Mutated T790M+ Cancers
CO-1686
(Sequist: Targ Tx 2015)
AZD9291
(Jänne: Targ Tx 2015)
21
22
ETCTN Project Team Proposals: AZD9291 in EGFR-mutated NSCLC
Post-progression After Erlotinib
23
Clinical Trial Designs to Address Circumvention of Acquired
Resistance in Oncogene-Driven NSCLC
Prolongation
of Remission
(delay time to PD)
Oncogene-driven
NSCLC
Targeted TKI Monotherapy
(Standard of Care)
Biopsy
AdvancedStage
NSCLC
Identification
of
Driver
Oncogene
EGFR Mutation
Targeted TKI Monotherapy
(2nd-Generation Agent)
Multi-drug Targeted Therapy
Gandara et al. Clin Lung Cancer. 2014.
24
Phase II/III Trial of Afatinib With or Without Cetuximab in
1st-Line Therapy of EGFR-mutated NSCLC (S1403)
Stage IIIB-IV NSCLC
with EGFR mutation
1st Line
EGFR TKI naive
R
A
N
D
O
M
I
S
A
T
I
O
N
Afatinib*
Afatinib +
Cetuximab*
*at PD: Biopsy for genomic study
& PDX development (selected patients)
PD: progressive disease
PDX: patient-derived xenograft
PIs: Goldberg, Lilenbaum, Politi.
25
Modulator Effects of EGFR MoAB Cetuximab:
Afatinib (BIBW) + Cetuximab in EGFR T790M+ GEMMs
Pretreatment
Cetuximab
H
Cetux/BIBW
H
H
Pretreatment
BIBW
H
Cetux/BIBW
H
H
C
Control
N
T1
T2
T1 T2
B
T1
T2
B+C
T1
T2
pEGFR
tEGFR
Regales et al. J Clin Invest. 2009.
Actin
26
Afatinib + Cetuximab in EGFR-mutated NSCLC Refractory to EGFR
TKI
Response rate: ≈30%
Clinical benefit (DCR): 75%
Janjigian, Pao et al. Cancer Discovery. 2014;4:1036-1045.
27
Phase II/III Trial of Afatinib With or Without Cetuximab in 1st-Line Therapy of
EGFR-mutated NSCLC (S1403)
Stage IIIB-IV NSCLC
with EGFR mutation
1st Line
EGFR TKI naive
R
A
N
D
O
M
I
S
A
T
I
O
N
Afatinib*
Afatinib +
Cetuximab*
*at PD: Biopsy for genomic study
& PDX development (selected patients)
PD: progressive disease
PDX: patient-derived xenograft
PIs: Goldberg, Lilenbaum, Politi.
28
Strategies for Integrating Biomarkers Into Clinical Trial Designs
for NSCLC When Viewed as a Multitude of Genomic Subsets
Evolution of NSCLC  Histologic Subsets  Genomic Subsets
Unmet needs addressed by master
protocols:
• How to develop drugs for
uncommon-rare genotypes?
• How to apply broad-based
screening (NGS)?
• How to achieve acceptable turnaround times for molecular testing
for therapy initiation (<2 weeks)?
• How to expedite the new drugbiomarker FDA approval process
(companion diagnostic)?
Li, Mack, Kung, Gandara. JCO. 2013.
29
“Strategies for Integrating Biomarkers Into Clinical
Development of New Therapies for Lung Cancer”
A Joint NCI Thoracic Malignancies Steering Committee-FDA Workshop
Bethesda MD – February 2-3, 2012
• Trial Design Challenges in the Era of Biomarker-driven
Trials
– Innovative Statistical Designs
– Challenges for Community Oncology Practice Participation
– The Patient Perspective
• Drug & Biomarker Co-Development in Lung Cancer
– Need for Early Co-Development
– Need for Improved Pre-Clinical Models With Clinical
Relevance
• Development of Future Lung Cancer Trials
– TMSC Master Protocol Task Force in NSCLC
– Biomarker-driven trial designs in both early stage adjuvant
therapy & advanced-stage NSCLC
– Account for inter-patient tumour heterogeneity & genomic
complexity of NSCLC
30
Master Protocol Subtypes
Umbrella
Trials
Basket
Trials
Single Type of Cancer:
Test multiple drug-biomarker
combinations
Multiple Cancer Types:
Test multiple drugs against
single or multiple biomarkers
• BATTLE
• Imatinib Basket
• I-SPY2
• BRAF+
• SWOG Lung MAP (S1400):
adv SCCA
• NCI MATCH
• ALCHEMIST: early stage
NSCLC
• ALK Master Protocol: ALK+
NSCLC
31
ALCHEMIST Trial Schema
Non-Match: Phase III trial
of nivolumab vs placebo
X 1 year after any adj tx
(EGFR & ALK testing performed by RGI)
32
ALK Master Protocol: Proposed Trial Design
Control Arm
(Criz.)
Control Arm
(Criz.) Crizotinib
ALK positive
NSCLC Treatment
Naïve patients
Central
Confirmation ALK
NGS
Drug A
Drug B
Drug C
Drug A To B
Drug A To C
Drug A To Criz.
Cross
Over
PD
NGS
PD
NGS
New Biopsy
Drug B to A
Drug B To C
Drug B to Criz.
Archived tissue
From S Malik: NCI.
Drug Criz. To A
Drug Criz. To B
Drug Criz. To C
New Biopsy
Drug C
33
Rationale for “MASTER PROTOCOL” in SCCA
• SCCA represents an unmet need
Therapeutic targets
SCCA-TCGA 2012
• Candidate molecular targets are
available from results of TCGA &
other studies, identified by a
biomarker
• Drugs (investigational) are now
available for many of these targets
• Trials can be designed to allow
testing & registration of multiple
new drug-biomarker combinations
at the same time (“MASTER
PROTOCOL” concept)
• Result of this concept is Lung-MAP
(S1400), activated in June 2014
34
S1400 Lung-MAP Protocol: A Unique Private-Public Partnership
Within the NCTN
Alliance
SWOG
NCI-C
S1400
Master
Protocol
ECOGAcrin
NRG
35
S1400: MASTER LUNG-1: Squamous Lung Cancer —
2nd-Line Therapy
CT
Biomarker
Profiling (NGS/CLIA)
Biomarker
Non-Match
Multiple Phase II-III Sub-studies with Rolling Opening & Closure
Biomarker A
TT A
CT
Primary Endpoint
PFS/OS
Biomarker Β
TT B
CT
Primary Endpoint
PFS/OS
Biomarker C
TT C+CT
CT
Primary Endpoint
PFS/OS
NonMatch
Drug
Biomarker D
TT D+E
E
Primary Endpoint
PFS/OS
TT = Targeted therapy; CT = chemotherapy (docetaxel or gemcitabine); E = erlotinib.
Project Chair: V. Papadimitrakopoulou
Steering Committee Chair: R. Herbst
SWOG Lung Chair: D. Gandara
36
LUNG-MAP (S1400): Squamous Lung Cancer —
2nd-Line Therapy
Common Broad Platform
CLIA Biomarker Profiling◊
CDK4/6
M: CCND1, CCND2,
CCND3, cdk4 ampl
PI3K
M:PIK3CA mut
GDC-0032
CT
Endpoint
PFS/OS
PD-0332991
CT
Endpoint
PFS/OS
FGFR
M: FGFR ampl,
mut, fusion
AZD4547
CT
Non-match
CT
Endpoint
PFS/OS
Anti-PD-L1:
MEDI4736
HGF
M:c-Met Expr
AMG102+E
E
Endpoint
PFS/OS
CT = chemotherapy (docetaxel or gemcitabine); E = erlotinib.
◊ Archival FFPE tumour, fresh CNB if needed.
Project Chair: V. Papadimitrakopoulou
Steering Committee Chair: R. Herbst
SWOG Lung Chair: D. Gandara
37
LUNG-MAP (S1400): Squamous Lung Cancer—
2nd-Line Therapy
Assign Treatment
Arm by Marker
Patient
Registration
Consent
Investigational
Targeted Therapy
Randomisation
Tumour
Collection
Genomic Screening
(FM one)
<2 weeks
New Tumour
Biopsy
(if needed)
Treatment
Interim Endpoint: PFS
NGS/IHC
(Foundation
Medicine)
Primary Endpoint: OS
Standard-of-Care
Therapy
• Organisers: NCI-TMSC, FDA, FNIH, FOCR
• Participants: Entire North American Lung Intergroup
(SWOG, Alliance, ECOG-Acrin, NRG, NCI-Canada)
• Screening: up to 1,000 patients/year
• With 4-6 arms open simultaneously, anticipate a hit rate ≈65% in
matching a patient with a drug/biomarker arm
38
Squamous Lung Master Protocol Clinical Trial Assay Based on Foundation
Medicine NGS Platform
Foundation Medicine NGS test platform (CLIA/CAP)
1) DNA extraction
Classification rules
2) Library construction:
3) Analysis pipeline
selected cancer genes
Illumina HiSeq 2500
4) Master protocol CTA
• Based on FM T5 NGS
platform
• Implemented as “mask” of
T5 content and classification
rules on called alterations
• Rules determine biomarker
positive/negative status
Classification rules (preliminary)
Non-NGS biomarkers:
Supplementary
assays
Non-match arm
MET IHC (+)
All assays (-)
MET pathway
inhibitor
Anti-PD-L1 Ab
PIK3CA mutation
CCND1 amplification or
CDKN2A/B deletion, and
RB1 wild-type
FGFR1/2/3/4
amplification,
mutation or fusion
PI3K inhibitor
CDK4/6 inhibitor
FGFR inhibitor
39
Biomarker Trial Design Based on
Comprehensive Genomic Profiling
60%
50%
Screen success rate: up to ≈80% of patients, depending on
biomarkers selected
PIK3R1/2,
TSC1/2, AKT1/2
5%
CCND3 amp
CCNE1 amp
CDK6 amp
STK11 loss
46%
4%
CCND2 amp
40%
% of
lung
squamous 30%
patients
with alteration
FBXW7 loss
CCND1 amp
PTEN loss
26%
26%
PIK3CA
amp
CDKN2A/B loss
20%
10%
25%
5%
PIK3CA
mutation
47%
4%
FGFR3 amp
FGFR1 amp/
mutation
0%
PI3K/AKT/mTOR
lead candidate biomarkers
Cell Cycle
FGFR
additional potential biomarkers
18%
40
What Are the Statistical Assumptions?
Lung-MAP Sub-studies
Phase 2
Phase 3
Approximate
Time of
Sample
Analysis
Size
Approximate
Time of
Analysis
Prevalence
Estimate
Approximate
Sample Size
56.0%
170
GNE+
5.6%
78
FMI+
8.0%
152
19
400
72
S1400C
11.7%
124
11
312
45
S1400D
9.0%
112
11
302
53
S1400E
16.0%
144
9
326
37
Sub-study ID
S1400A
8
380
21
S1400B
288
41
Is Lung-MAP Self-sustaining?
Activation of Lung-MAP Within 1st Month (July 2014)
42
LUNG-MAP (S1400): Squamous Lung Cancer —
2nd-Line Therapy
Common Broad Platform
CLIA Biomarker Profiling◊
PI3K
M:PIK3CA mut
GDC-0032
CT
Endpoint
PFS/OS
CDK4/6
M: CCND1, CCND2,
CCND3, cdk4 ampl
PD-0332991
CT
Endpoint
PFS/OS
CT
Non-match
FGFR
M: FGFR ampl,
mut, fusion
AZD4547
CT
Endpoint
PFS/OS
Anti-PD-L1:
MEDI4736
HGF
M:c-Met Expr
AMG102+E
E
Endpoint
PFS/OS
CT = chemotherapy (docetaxel or gemcitabine); E = erlotinib.
◊ Archival FFPE tumour, fresh CNB if needed.
Project Chair: V. Papadimitrakopoulou
Steering Committee Chair: R. Herbst
SWOG Lung Chair: D. Gandara
43
44
Is Lung-MAP “Self-sustaining”?
Lung MAP is designed to be adaptable with changes in the therapeutic
landscape
• Example: recent approval of nivolumab in 2nd-line therapy of squamous lung
cancer
– Lung MAP modified to be 2nd-line and beyond (ie, some substudies are now 2nd3rd line, others 2nd-line)
– One planned immunotherapy combination substudy is 2nd- line with nivolumab
control arm
– Another planned substudy is 3rd-line after nivolumab PD
45
Is Lung-MAP “Self-sustaining”?
• New Targets-New Opportunities
– PARP
– mTORC1/mTORC2
(RICTOR)
– PI3K/PTEN
– Wee-1 kinase
– ATR
– VEGFR2
– TRK
– Drug combinations
(Immunotherapies)
Hammerman et al. Nature. 2012.
46
SUPPORTING COOPERATIVE GROUPS:
ALLIANCE
Everett Vokes, M.D.
University of Chicago Medical Center
NCIC-CTG
Glenwood Goss, M.D.
University of Ottawa
ECOG/ACRIN
Suresh Ramalingam, M.D.
Emory University
NRG
Jeff Bradley, M.D.
Washington University School of
SUPPORTING COOPERATIVE GROUPS:
ALLIANCE
Everett Vokes, M.D.
University of Chicago Medical Center
NCIC-CTG
Glenwood Goss, M.D.
University of Ottawa
ECOG/ACRIN
Suresh Ramalingam, M.D.
Emory University
NRG
Jeff Bradley, M.D.
Washington University School of Medicine
47