Download Treatment Beyond Progressive Disease:

Bridging Tumor Genomics to
Lung Cancer Therapeutics:
The keys to Precision Medicine
David R. Gandara, MD
University of California Davis
Cancer Center
Disclosures
• Research Grants: Clovis, Genentech, Lilly,
Merck, Novartis, Puma
• Consultant: Ariad, AstraZeneca, BoehringerIngelheim, Celgene, Clovis, Genentech, Lilly,
Merck, Novartis, Response Genetics, Synta
Case: Advanced NSCLC
• 43 year old woman never-smoker
presents with dry cough and
marked dyspnea on exertion
• Performance status (PS) = 1
• CT scan: diffuse bilateral
pulmonary nodules
• PET CT with mild FDG avidity of
some lesions (SUV ~5)
• No evidence of extra-thoracic
metastatic disease. Brain MRI
negative
• FNA: adenocarcinoma (CK7+,
CK20-, TTF1+)
• Molecular testing: EGFR exon 19
deletion
Case: Advanced NSCLC
• After initial PR with erlotinib sustained for 12
months, the patient is asymptomatic
• CT scan shows progressive disease, with
modest growth of multiple pulmonary lesions
Question: You decide to proceed with:
1. Continue erlotinib & add platinum-based
chemotherapy
2. Second-generation EGFR-TKI (afatinib)
3. Platinum doublet chemotherapy
Treatment Paradigms in Advanced NSCLC: Available “Tools”
Chemotherapy
“Targeted Therapy”
Histologic
Subtyping:
Chemotherapy
? Targeted
Nintedinib?
Necitumumab?
Ramucirumab?
Checkpoint Immunotherapy
Anti-PD-1
and PD-L1
Anti-CTLA-4
Targeted
TKIs:
-EGFR
-ALK
-ROS1
Can use of these therapeutic modalities be optimized by patient selection
based on defining a tumor “target” ? (predictive biomarker)
What are the issues to be addressed?
Modalities (Chemotherapy, targeted agents, checkpoint immunotherapy)
as “targeted therapy” = defined by a predictive biomarker
• How to select patients ? (All-comers vs biomarker-driven vs clinicalhistologic?)
• If biomarker-driven: a single Biomarker or Panel (gene signature)?
• Is the biomarker “static” (~mutation) or “dynamic” (gene exp or PD-L1)?
• Sequential use vs combinations? (Chemo-targeted agents – PD-L1)
• If combinations are employed, will the effects of the predictive biomarker
be “diluted out”?
Prognostic versus Predictive Biomarkers
Prognostic Marker
Information about
disease outcome
independent of treatment
Example : EGFR Mutation in NSCLC
Mutation +: better prognosis
Mutation - : worse prognosis
Predictive Marker
Information on disease
outcome related to a
specific treatment
Example : EGFR Mutation in NSCLC
Mutation + : ~70% probability of response
to EGFR TKI therapy
Mutation - : <5% probability of response
to EGFR TKI therapy
Some biomarkers are both prognostic & predictive
Only predictive biomarkers can be used to indicate
“which patients should be treated with which drug”
(a Targeted Therapy)
Predictive biomarkers can also identify patients who may be
harmed by “targeted therapy”
Need for Paradigm Shift in Targeted Therapy Clinical
Trial Design (Presumes Biomarker Potential)
“All Comer” Phase III Design adding Targeted Therapy to Chemotherapy
Standard
Therapy
“All
Comers”
Exp Therapy
(Targeted Agent
or
Standard + Targeted)
• When Marker not known or not validated (analytical)
• Marker (if known) can be retrospectively assessed
• Cautionary Tale: Most Phase III “All Comer” trials in NSCLC targeted therapy
fail
• May be random differences in Marker+ and Marker- proportions per arm
Gandara et al: NCI CAPR Workshop, April 2011
Classic RCT Design (Unselected): Phase III Trials of Chemotherapy +/Targeted Agent* in 1st-line Therapy of Advanced Stage NSCLC
Target
Agent
Survival Benefit
MMPs
Prinomastat, Others
No
EGFR TKI
Gefitinib or Erlotinib
No
Farnesyl Transferase (RAS)
Lonafarnib
No
PKCα
ISIS 3521
No
RXR
Bexarotene
No
VEGFR (TKI)
Sorafenib
No
VEGF (Mab)
Bevacizumab
Yes
EGFR (Mab)
Panitumumab
No
TLR9 Agonist
PF-351
No
EGFR (Mab)
Cetuximab
Yes**
IGR1-R
Figitumumab
No
VDA
ASA-404
No
*In combination with platinum-based chemotherapy versus chemotherapy
**EGFR IHC positive
from Gandara et al: Clin Lung Cancer, 2012
Treatment Paradigms in Advanced NSCLC: Available “Tools”
Chemotherapy
“Targeted Therapy”
Histologic
Subtyping:
Chemotherapy
? Targeted
Nintedinib?
Necitumumab?
Ramucirumab?
Checkpoint Immunotherapy
Anti-PD-1
and PD-L1
Anti-CTLA-4
Targeted
TKIs:
-EGFR
-ALK
-ROS1
Can use of these therapeutic modalities be optimized by patient selection
based on defining a tumor “target” ? (predictive biomarker)
What are the issues to be adressed?
Updated Treatment Algorithm for Advanced-Stage NSCLC (2014)
Proposed Treatment Algorithm
EGFR Mutation Positive
or ALK Positive
Erlotinib/Gefitinib
or Crizotinib
Molecular
Good PS
Non-squamous
Bevacizumab Eligible
Histologic
Clinical (PS)
Poor PS
Squamous
Single-Agent
Or
Combination
Chemotherapy
Bevacizumab Ineligible
Clinical
Platinum/Pemetrexed
(or Other*) ± Bevacizumab
Platinum/Pemetrexed
(or Other*)
Firstline
Platinum Doublet*
Progression
Chemotherapy by
Algorithm
Bevacizumab, Erlotinib ,
Pemetrexed
Or Observation
Based on Prior
Therapy
Updated from Gandara , Herbst et al.
Clin Lung Cancer. 2009
Erlotinib or Pemetrexed
Or Observation
Based on Prior
Therapy
Erlotinib
Or Observation
Based on Prior
Therapy
Based on Prior Therapy
Maintenance
End of First-line Chemotherapy
Secondline
*with docetaxel, paclitaxel, nab-paclitaxel, gemcitabine, vinorelbine
Advanced Stage NSCLC: Platinum-based
doublet chemotherapy (ECOG 1594)
Empirically selected chemotherapy produces
only modest benefits & does not distinguish one patient from the next
100
Median survival (mo)
% Survival
80
Cisplatin + paclitaxel
Cisplatin + gemcitabine
Cisplatin + docetaxel
Carboplatin + paclitaxel
60
7.8 P=NS
8.1 P=NS
7.4 P=NS
8.1 P=NS
40
20
0
0
5
10
15
20
25
Months
Schiller et al. N Engl J Med. 2002
30
Treatment Algorithm for Advanced-Stage NSCLC
Proposed Treatment Algorithm
Good PS
Non-squamous
Histologic
Bevacizumab Eligible
Bevacizumab Ineligible
Platinum/Pemetrexed
(or Other*) ±
Bevacizumab
Platinum/Pemetrexed
(or Other*)
Squamous
Platinum Doublet*
Potential Predictive
Biomarkers for Chemotherapy
• Platinim: ERCC1
• Gemcitabine: RRM1
• Pemetrexed: Thymidylate
Syntase
None fully validated
although noted in
NCCN guidelines
Options in Non-Squamous only
• Pemetrexed: based on histology alone
• Bevacizumab: based on histologic & clinical factors; no validated biomarker(s)
*with docetaxel, paclitaxel, nab-paclitaxel gemcitabine, vinorelbine
Adapted from Gandara DR, et al. Clin Lung Cancer. 2009;10(6):392-4.
JMDB Trial: Cisplatin-Pemextexed versus
Cisplatin-Gemcitabine
No difference in overall
PFS or Survival between
study arms
CisPem improves survival
over CisGem
in Non-SCCA
(HR 0.81, p=0.005)
CisGem improves survival
over CP
in SCCA (HR 1.23, p=0.05)
Scagliotti & Gandara. J Clin Oncol 2008;26:3543-3551
Thymidylate Synthase (TS) Expression in Lung Cancer
• Small Cell – Highest TS
• Squamous – Intermediate TS
• Adeno – Lowest TS
TS
Bhattacharjee A, et al. Proc Natl Acad Sci U S A. 2001;98(24):13790-5.
TS mRNA Results by Histology (N=1,671) :
Squamous (SCCA) versus Adenoca (AC)
TS
p<0.001
NSCLC-Total
42%
Adenoca
46%
SCCA
26%
NSCLC-Total
N=1,671
SCCA
N=316
AC
N=649
SCCA vs AC
p value
Median
2.71
4.1
2.5
<0.001*
Range
0.14-68.0
0.14-59.3
0.39-68.0
*Mann-Whitney
test
Biomarker
TS
(Reference
<2.33 for
pemetrexed)
% Below
Reference
Level
Maus MK, Gandara DR, et al. J Thorac Oncol. 2013
ECOG 4599: Carboplatin-Paclitaxel
+/- Bevacizumab
Overall Survival
Progression-Free Survival
100
Carboplatin / paclitaxel
Carboplatin / paclitaxel +
bevacizumab
80
P < .001; HR = 0.66
Median PFS: 6.2 months vs
4.5 months
6-Month PFS: 55% vs 33%
1-Year PFS: 15% vs 6%
60
40
20
0
Patients Surviving (%)
Patients With PFS (%)
100
Carboplatin / paclitaxel
Carboplatin / paclitaxel +
bevacizumab
80
P = .003; HR = 0.79
Median OS: 12.3 months vs
10.3 months
1-Year OS: 51% vs 44%
2-Year OS: 23% vs 15%
60
40
20
0
0
6
12
18
Months
24
30
36
Sandler A, et al. N Engl J Med. 2006;355(24):2542-50.
0
6
12
18
24
Months
30
36
Treatment Paradigms in Advanced NSCLC: Available “Tools”
Chemotherapy
“Targeted Therapy”
Histologic
Subtyping:
Chemotherapy
? Targeted
Nintedinib?
Necitumumab?
Ramucirumab?
Checkpoint Immunotherapy
Anti-PD-1
and PD-L1
Anti-CTLA-4
Targeted
TKIs:
-EGFR
-ALK
-ROS1
Can use of these therapeutic modalities be optimized by patient selection
based on defining a tumor “target” ? (predictive biomarker)
What are the issues to be addressed?
Evolution of NSCLC Subtyping from Histologic to Molecular-Based
NSCLC
as one
disease
ALK
EGFR
Li, Mack, Gandara et al: JCO 2013 (adapted from Pao et al)
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
Carcinogen-induced Cancers
100 / Mb
10 / Mb
20
Hematologic &
Childhood Cancers
Ovarian, Breast,
Prostate Cancers
0.1 / Mb
??
Adapted from The Cancer Genome Atlas Project: Govindan & Kondath et al Nature 2013
Squamous
Adenoca
1 / Mb
Integration of Biomarkers into Clinical Practice: Past, Current & Future
1. Histomorphological
Diagnosis:
2. Molecular Diagnosis:
Archival FFPE tumor
specimens
Cancerous
Archival cancer
specimens
Empiric Approach (Past)
(Compound-Based Therapy):
Clinical-histologic factors to select
drugs for individual patients
Macro- or
Micro-dissection
of Tumors
Extract tumor
nucleic acids:
DNA and RNA
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
Representative technologies:
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
Evolution of NSCLC Subtyping from Histologic to Molecular-Based
NSCLC
as one
disease
ALK
EGFR
Li, Mack, Gandara et al: JCO 2013 (adapted from Pao et al)
Reported Prognostic-Predictive Biomarkers of
EGFR Pathway Activation
• EGFR mutation status by
gene sequencing
GGCGGGCCAAACTGCTGGGTGCG
• EGFR gene copy number by
fluorescence in situ hybridization
(FISH)
• EGFR protein expression by
immunohistochemistry (IHC)
• Serum Proteomics by MALDI MS
Survival distribution function
BR.21 (Erlotinib vs Placebo) in 2nd-3rd line therapy of advanced NSCLC:
Overall Survival
• BR.21 results not explained by EGFR Mutation alone
• BR.21 survival primarily the results of increased
Stable Disease & increased DCR
• Target population for cytostatic DCR effect is EGFR WT
but high EGFR gene expression
• This DCR effect is likely also true for Cetuximab
in NSCLC (FLEX and S0819 trials)
1.00
0.75
0.50
6.7 mo
HR=0.73 (95% CI, 0.61-0.86)*
P<0.001†
4.7 mo
0.25
Erlotinib
Placebo
0
0
6
12
18
Months
Shepherd et al: NEJM, 2005
24
30
IPASS (Gefitinib versus Chemotherapy): Impact of EGFR mutation
Progression-free survival in EGFR mutation positive & negative cancers
Gefitinib (n=132)
Carboplatin / paclitaxel (n=129)
1.0
HR (95% CI) = 0.48 (0.36, 0.64)
p<0.0001
0.8
0.6
0.4
0.2
0.0
0
4
8
12
Months
•
•
EGFR mutation negative
16
20
24
Probability of progression-free survival
Probability of progression-free survival
EGFR mutation positive
Gefitinib (n=91)
Carboplatin / paclitaxel (n=85)
1.0
0.8
HR (95% CI) = 2.85 (2.05, 3.98)
p<0.0001
0.6
0.4
0.2
0.0
0
4
8
12
16
20
Months
Treatment by
subgroup
interaction
test, p<0.0001
Clinical characteristics
are
insufficient
for selection
of 1st line
EGFR TKI Therapy
Front line EGFR TKI should be restricted to EGFR MT+ patients
Mok: NEJM, 2009
24
First-line Treatment With EGFR TKIs vs
Chemotherapy in EGFR-Mutated NSCLC
Improved Progression-free Survival; (PFS)
Study
No differences in Overall Survival (OS)
Treatment
N
Maemondo[1]
Gefitinib vs carboplatin/
paclitaxel
Mitsudomi[2,3]
OPTIMAL[4,5]
EURTAC[6]
LUX-Lung 3[7]
Median PFS
(mos)
Median OS
230
10.8 vs 5.4
(P < .001)
30.5 vs 23.6
(P = .31)
Gefitinib vs
cisplatin/docetaxel
177
9.2 vs 6.3
(P < .0001)
36 vs 39
(HR: 1.19)
Erlotinib vs
Carboplatin/gemcitabine
165
13.1 vs 4.6
(P < .0001)
HR: 1.065
(P = .65)
Erlotinib vs
platinum-based chemotherapy
174
9.7 vs 5.2
(P < .0001)
19.3 vs 19.5
(P = .87)
Afatanib vs
CDDP/pemetrexed
345
11.1 vs 6.9
(P < .0004)
Not reported
1. Maemondo M, et al. N Engl J Med. 2010;362:2380-2388. 2. Mitsudomi T, et al. Lancet Oncol. 2010;11:121-128. 3. Mitsudomi T, et a.
ASCO 2012. Abstract 7521. 4. Zhou C, et al. Lancet Oncol. 2011;12:735-742. 5. Zhang C, et al. ASCO 2012. Abstract 7520. 6. Rosell R, et al.
Lancet Oncol. 2012;13:239-246. 7. Yang J C-H, et al. ASCO 2012. Abstract LBA 7500.
ALK Fusion in NSCLC
ALK Rearrangement in NSCLC
• Present in ~4% of NSCLC cases
• Enriched in younger never or light smokers
with adenocarcinoma (~20%)
• Rarely overlaps with EGFR or KRAS mutations
(de novo)
• Clinical Testing
• IHC
• RT-PCR
• Break apart FISH Assay
• ALK-specific inhibitor Crizotinib: ~60% RR
Soda et al: Nature 2007
Crizotinib in ALK+ NSCLC
PFS~10 mos
from Camidge et al: Nat Rev Clin Oncol, 2012
Acquired Resistance to Targeted Therapies in Oncogene-Driven
NSCLC: Clinical Practice & Clinical Trials
• Targeted Therapies against Oncogene-Driven Cancers [EGFR mutation+
(Erlotinib) or ALK fusion+ (Crizotinib)] improve response and PFS when
compared with chemotherapy
• Even in these most sensitive cancers, acquired resistance is ~universal,
with PFS averaging ~10-14 months
• The “subtype” of progressive disease (PD) in individual patients varies
greatly (Systemic-PD, Oligo-PD and CNS-PD)
Oncogene-driven
NSCLC
Gandara, Redman et al: Clin Lung Cancer 2014
Acquired Resistance to Targeted TKIs: PD Subtype
influences Clinical Practice & Clinical Trial Design
Systemic-PD
Oligo-PD
CNS-PD
(Sanctuary)
Gandara, Redman et al: Clin Lung Cancer 2014
Evolutionary Biology & Acquired Tumor Resistance
• Intra-tumor heterogeneity is present
at baseline (scenarios 1 & 2)
• Reducing sensitive clones by therapy
permits unopposed growth of less fit
resistant clones
or emergence of a new clone
(“Tumor 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
Scenario 1
Scenario 2
“Driver”
Oncogene
“Driver”
Oncogene
Evolution
over time
with
therapy
Evolution
over time
with
therapy
New
“Driver”
New
“Driver”
Schema for Multidisciplinary Integration of Biomarker
Testing in Advanced Stage NSCLC: Looking for
“Actionable”
Oncogenes
Referring
Physician
Identify
Patient
Pathologist
Multidisciplinary
Team
(Tumor 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
Adapted from: Gandara: ASTRO/ASCO/IASLC Symposium on Molecular Testing, 2012
Treat
When
Progression
 Re-Biopsy
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
Approaches to Acquired Resistance in Oncogene-driven
Cancers (EGFR MT & ALK Fusion)
Systemic-PD
Advanced
NSCLC with
Oncogene-driven
Cancer
-EGFR Mutation
-ALK Fusion
Targeted
TKI
Switch Therapy
(Chemotherapy or 2nd gen TKI)
RECIST
Response
Subsequent
Systemic PD
Re-biopsy
Gandara et al: Clin Lung Cancer 2014
Continue same TKI alone
(to “slow progression”)
Add Therapy to TKI
-Chemotherapy ?
-Another Targeted Agent?
IMPRESS: Phase III trial of Post-progression Gefitinib/Chemotherapy vs
Chemotherapy alone in EGFR mutation-positive NSCLC after prior response
(Acquired Resistance)
• Stage IIIB/IV NSCLC
Gefitinib 250 mg +
cisplatin + pemetrexed
up to 6 cycles
(n=133)
PD
Placebo +
cisplatin + pemetrexed
up to 6 cycles
(n=132)
PD
• EGFR mutation positive
• WHO PS 0–1
• Prior response* to 1st-line
gefitinib
• PD <4 weeks prior to study
(n=265)
PD
R
1:1
Primary endpoint
Secondary endpoints
• PFS
• OS, ORR, DCR
• Safety and tolerability, health-related QoL
*CR/PR ≥4 months or SD >6 months
Mok et al. Ann Oncol 2014; 25 (suppl 4): abstr LBA2_PR
IMPRESS: PFS (primary endpoint; ITT)
Probability of PFS
1.0
0.9
Gefitinib
(n=133)
Placebo
(n=132)
0.8
Median PFS, months
5.4
5.4
0.7
0.6
Number of events, n
(%)
98 (73.7)
107 (81.1)
HRa (95% CI) = 0.86 (0.65, 1.13); p=0.273
0.5
Response rate:
34%
0.4
0.3
32%
0.2
Gefitinib (n=133)
Placebo (n=132)
0.1
0.0
0
Patients at risk:
Gefitinib 133
Placebo 132
aPrimary
Mok et al, ESMO, 2014
2
110
100
4
6
8
10
Time of randomisation (months)
88
85
40
39
cox analysis with covariates
A HR <1 implies a lower risk of progression with
gefitinib
25
17
12
5
12
14
6
4
0
0
Mechanisms of EGFR TKI Resistance (Selected)
•Secondary EGFR
mutation (i.e. T790m)
2nd Gen EGFR TKIs
i.e. Afatinib
Afatinib/Cetuximab
3rd Gen- AZ9291, CO1686
•Bypass signaling via ERBB3
Anti-ERBB3 drugs
i.e. MM151 MoAB
•MET over-expression
MET Inhibitors
i.e. MET-Mab (MoAB)
ARQ197 (TKI)
•PIK3CA Mutation/AKT
i.e. BKM120 (PIK3CA)
i.e. MK2206 (AKT)
& Others
adapted from Engelman et al
HSP inhibitors
i.e. Ganetespib
AUY922
3rd generation EGFR TKIs:
Preliminary Efficacy Comparison in EGFRmutated NSCLC resistant to Erlotinib/Gefitinib
CO-1686
AZD9291 (80mg)
Response in
T790M +
Response in
T790M -
PFS
(months)
58%
NA
>12
(estimate)
70%
(N=43)
17%
N=23)
~9.6
(preliminary)
Sequist: ASCO 2014
Yang: ESMO 2014
37
Afatinib + Cetuximab in EGFR-mutated
NSCLC refractory to EGFR TKI
Response rate: 30%
Clinical benefit (DCR): 75%
Janjigian et al. Cancer Discovery 2014;4:1036-1045
S1403: Phase II/III trial: Afatinib +/- Cetuximab in EGFR mutation+
NSCLC (North American Intergroup)
Stage IIIB-IV
Adenocarcinoma
with EGFR mutation+
1st Line
EGFR TKI naive
R
A
N
D
O
M
I
Z
A
T
I
O
N
Afatinib*
*at PD: Biopsy for genomic study
& PDX development (optional)
PIs: Goldberg, Lilenbaum, Politi
Afatinib + Cetuximab*
Evolution of NSCLC Subtyping from Histologic to Molecular-Based
NSCLC
as one
disease
ALK
EGFR
Li, Mack, Gandara et al: JCO 2013 (adapted from Pao et al)
Rationale for “MASTER PROTOCOL” in SCCA
• SCCA represents an unmet need
• 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 drugbiomarker combinations at the same
time (“MASTER PROTOCOL” concept)
• Result of this concept is Lung-MAP
(S1400), activated in June 2014
Therapeutic targets
SCCA-TCGA 2012
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
Biomarker D
TT D+E
E*
Primary Endpoint
PFS/OS
TT=Targeted therapy, CT=chemotherapy (docetaxel or gemcitabine), E=erlotinib
NonMatch
Drug
S1400
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
TT=Targeted therapy, CT=chemotherapy (docetaxel or gemcitabine), E=erlotinib
◊ Archival FFPE tumor, fresh CNB if needed
LUNG-MAP (S1400): Squamous Lung Cancer- 2nd Line Therapy
Assign treatment
Arm by marker
Patient
Registration
Consent
Investigational
Targeted Therapy
Randomization
Tumor
Collection
Genomic Screening
<2 weeks
NGS/IHC
(Foundation
Medicine)
Treatment
Interim Endpoint: PFS Primary Endpoint: OS
Standard of Care
Therapy
• Organizers: NCI-TMSC, FDA, FNIH, FOCR
• Participants: Entire North American Lung Intergroup
(SWOG, Alliance, ECOG-Acrin, NRG, NCI-Canada)
• Screening: ~1,000 patients/year
• With 4-6 arms open simultaneously, anticipate a “hit rate
~65% in matching a patient with a drug/biomarker arm
Treatment Paradigms in Advanced NSCLC: Available “Tools”
Chemotherapy
“Targeted Therapy”
Histologic
Subtyping:
Chemotherapy
? Targeted
Nintedinib?
Necitumumab?
Ramucirumab?
Checkpoint Immunotherapy
Anti-PD-1
and PD-L1
Anti-CTLA-4
Targeted
TKIs:
-EGFR
-ALK
-ROS1
Can use of these therapeutic modalities be optimized by patient selection
based on defining a tumor “target” ? (predictive biomarker)
What are the issues to be addressed?
Targeted Immunotherapy: Anti-PD-1/PD-L1 agents
X
X
•
Blocking PD-1 on T cells
•
Blocking PD-L1 on the tumor
Strategies for Optimizing Development of New Therapies:
Single Agents vs Combinations vs Sequential (Advanced Stage)
Single Agent
New
Drug
Combo
New
Drug
Chemo
Combo
New
Drug
Targeted
Therapy
Sequential
New
Drug
Sequential
Targeted
Therapy
Targeted
Therapy
or Chemo
New Drug
maintenance
adapted from Gandara et al: IASLC LALCA 2014
Strategies for Optimizing Development of New Therapies:
Single Agents vs Combinations vs Sequential (Advanced Stage)
Single Agent
PD-L1
Platinum
Chemo
Combo
PD-L1
Combo
PD-L1
Sequential
PD-L1
Targeted
Therapy
Sequential
Targeted
Therapy
or Chemo
PD-L1
Erlotinib
maintenance
adapted from Gandara et al: IASLC LALCA 2014
Checkpoint Immunotherapy vs Chemotherapy:
Trial Designs
Measurement of PD-L1 in
Cancer/NSCLC by IHC
Spigel et al: #8008 ASCO 2013.
Intra-tumoral PD-L1 expression and response to
PD-1/PD-L1 blockade
n=
42
44
34
94
30
53
113
129
65
55
411
Unselected
21%
32%
29%
22%
23%
23%
40%
19%
26%
18%
40%
PD-L1 +
36%
67%
44%
39%
27%
46%
49%
37%
43%
46%
49%
PD-L1 -
0%
19%
17%
13%
20%
15%
13%
11%
11%
11%
13%
Response Rates
from Callahan: ASCO 2014
Lack of Correlation of Response/Survival with
Nivolumab therapy & PD-L1 Expression with Anti-PD-L1
Antibodya
1% Staining
Positive
aFigure
Neg. Control Ab
5% Staining
Positive
Neg. Control Ab
from Antonia SJ, et al. WCLC 2013. Poster P2.11-035. PD-L1 staining is shown in archival tumor tissue
 PD-L1 expression measured in archival pretreatment tumor (including >1 year old)
 Responses in PD-L1+ & PD-L1– tumors were similar; ORRs 15% (5/33) vs 14% (5/35)
 PD-L1 expression not associated with better OS;
median OS was 7.8 mo vs 10.5 mo in PD-L1+ and PD-L1– tumors
PD-L1 expression was measured using the automated BMS/Dako IHC assay based on the anti-PD-L1 monoclonal antibody (clone 28-8). Positive staining with this
assay is defined as tumor cell membrane staining at any intensity, analyzed with cut-off values of 1% and 5% in a minimum number of 100 evaluable cells
Rizvi et al: IASLC LALCA, August 2014
Phase III Trials of PD-1 therapy compared to Docetaxel in
2nd/3rd-Line Advanced/Metastatic NSCLC
“All comers” Strategy:
(PD-L1+ & PD-L1-)
Nivolumab Phase III Trials
Stage IIIB/IV Squam (017) NSCLC
non-squamous(057) NSCLC
Docetaxel
75 mg/m2 IV
Q3W
Nivolumab
3 mg/kg IV
Q2W
Treat until progression or
unacceptable toxicity or
withdrawal of consent
Overall Survival (OS)
CheckMate 017: Squamous
CheckMate 057: Non-Squamous
Marker positive Strategy:
PD-L1+
Pembrolizumab Phase III Trial
Stage IIIB/IV NSCLC
Docetaxel
75 mg/m2 IV
Q3W
Pembro
2 mg/kg IV
Q3W
Pembro
10 mg/kg IV
Q3W
Treat until progression or
unacceptable toxicity or
withdrawal of consent
Overall Survival (OS)
PD-1/PD-L1 + Chemotherapy vs Chemotherapy:
Trial Designs
“All Comer”
Design
Advanced NSCLC
(tumor collected)
“Marker Positive”
Design
Advanced NSCLC
PD-L1 positive
R
A
N
D
O
M
I
Z
E
R
A
N
D
O
M
I
Z
E
PD-1 + Chemotherapy
Chemotherapy
PD-1 + Chemotherapy
Chemotherapy
Rationale for combining PD-L1 therapy & Chemotherapy
Strong endogenous
anti-tumor immune
response
Weak endogenous
anti-tumor immune
response
PD-L1 up-regulation
in tumor
Anti-PD-1
monotherapy
RESPONSE
No PD-L1 up-regulation
in tumor
1. Inducer of anti-tumor immunity (Chemotherapy, vaccine, TKI)
Endogenous
anti-tumor immune
response
PD-L1 up-regulation
in tumor
2. Anti-PD-1
adapted from Pardoll et al: ASCO 2014
2.
RESPONSE
Efficacy Endpoints in NSCLC Patients
Treated With Nivolumab + PT-Doublet Chemotherapy
Nivo 10 mg/kg
Nivo 5 mg/kg
Gem/Cis
(n = 12)
Pem/Cis
(n = 15)
Pac/Carb
(n = 15)
Pac/Carba
(n = 14)
33%
47%
47%
43%
Median PFS, weeks (range)
24.7
(0.1+, 61.4)
29.7
(4.0+, 91.9+)
21.0
(3.1, 97.9+)
31.0
(0.1+, 82.4+)
1-year OS rate, % (95% CI)
51 (21, 74)
83 (56, 96)
65 (32, 80)
85 (51, 96)
Median OS, weeks (range)
50.5
(19.7, 99.3+)
83.4
(33.0, 105.1+)
64.9
(13.9, 105.0+)
Not Reached
(33.7+, 87.1+)
ORR, % (95% CI)
These data are not so different from
Platinum-based Chemotherapy alone
Or PD-1 directed therapy alone
Antonia et al: IASLC LALCA 2014 & CMSTO 2014
PD-1/PD-L1 + Targeted TKI vs TKI: Potential Trial Designs
“Hybrid”
Design
Advanced NSCLC
Oncogene positive
(tumor collected
for PD-L1)
“Marker Positive”
Design
Advanced NSCLC
Oncogene positive
PD-L1 positive
R
A
N
D
O
M
I
Z
E
R
A
N
D
O
M
I
Z
E
PD-1 + Targeted TKI
TKI alone
PD-1 + Targeted TKI
TKI alone
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
Carcinogen-induced Cancers
100 / Mb
10 / Mb
20
Hematologic &
Childhood Cancers
Ovarian, Breast,
Prostate Cancers
0.1 / Mb
??
Adapted from The Cancer Genome Atlas Project: Govindan & Kondath et al Nature 2013
Squamous
Adenoca
1 / Mb
Relationship of Mutational Load to Checkpoint Immunotherapy Efficacy
Champiat et al: OncoImmunology 2014
Efficacy Endpoints in EGFR-mutated NSCLC Patients
Treated With Nivolumab Plus ERL (N=21)
Prior treatment
with ERL (n = 20)
No prior treatment
with ERL (n = 1)
19% (5.4, 41.9)
ORR, %
0
0
Partial response
3 (15%)
1 (100%)
Stable disease
9 (45%)
0
Progressive disease
8 (38%)
0
Complete response
Median PFS, weeks (range)
29.4 (4.6, 81.7+)
1-year OS rate, % (95% CI)
73% (46, 88)
Median OS, weeks (range)
Not Reached (10.7+, 86.9+)
These data are not so different from
anti-PD-L1 therapy alone
from Antonia et al: IASLC LALCA 2014
Will these PD-1/PD-L1 agents end up being
“Untargeted Use of Targeted Therapy”
“None of the recent trials was based
on selecting patients whose tumors
were producing the targets”
David R. Gandara, MD
from The Economist, June 2007
Bevacizumab:
“Untargetd use of targeted therapy”
Only time will tell