1 Precision Medicine in Advanced Non- Small Cell Lung Cancer A therapy that works…so lets get the...
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Transcript of 1 Precision Medicine in Advanced Non- Small Cell Lung Cancer A therapy that works…so lets get the...
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Precision Medicine in Advanced Non-Small Cell Lung Cancer
A therapy that works…so lets get the most out of it that we can
Gary Middleton, University of Birmingham
Original Article Activating Mutations in the Epidermal Growth
Factor Receptor Underlying Responsiveness of Non–Small-Cell Lung Cancer to Gefitinib
Thomas J. Lynch, M.D., Daphne W. Bell, Ph.D., Raffaella Sordella, Ph.D., Sarada Gurubhagavatula, M.D., Ross A. Okimoto, B.S., Brian W. Brannigan, B.A., Patricia L.
Harris, M.S., Sara M. Haserlat, B.A., Jeffrey G. Supko, Ph.D., Frank G. Haluska, M.D., Ph.D., David N. Louis, M.D., David C. Christiani, M.D., Jeff Settleman, Ph.D., and
Daniel A. Haber, M.D., Ph.D.
N Engl J MedVolume 350(21):2129-2139
May 20, 2004
BRAF mutant NSCLC and CRC are both agressive diseases.
Antonio Marchetti et al. JCO 2011;29:3574-3579Gavin P G et al. Clin Cancer Res 2012;18:6531-6541
However, dual BRAF/MEK blockade works in NSCLC but doesn’t in CRC
Corcoran R. ASCO, 2014Johnson B. ASCO, 2014
Tumor Responses to Crizotinib in ROS1-Rearranged Non–Small-Cell Lung Cancer.
Shaw AT et al. N Engl J Med 2014;371:1963-1971
Progression-free Survival.
Shaw AT et al. N Engl J Med 2014;371:1963-1971
Response to ALK Inhibition
Kwak EL et al. N Engl J Med 2010;363:1693-1703
But there is a problem….
7524 cases completed successfully for ALK testing between Nov 2011 and May 2015 (included
144 positive cases in total: 2%
Centre 1: 1/74 1.35% Centre 2: 3/308 1%
Centre 3: 2/170 1.2% Centre 4 4/253 1.6%
Centre 5: 3/356 0.85% Centre 6: 7/434 1%
Centre 7: 7/401 1.75% Centre 8: 7/200 3.5%
Centre 9: 6/361 1.7% Centre 10: 6/275: 2.2%
Centre 11: 10/464: 2.1%
Phillipe Taniere, UHB.
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National Lung Matrix Trial
A Multi-drug, genetic marker directed, non-comparative multi-arm Phase II trial in NSCLC
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Trial Design• A multi-arm non-randomised design, with treatment allocation
according to molecular phenotype• No ‘standard’ control arm• Each biomarker/drug arm will contain 30 + patients• Endpoints are principally objective response rate and duration of
response: progression free survival for some drugs• The study will be a national study open at all ECMCs• The study will be carried out under a single clinical trial protocol
and regulatory submission
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The biology of stratification
MATRIX Targets
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AZD5363 AZD4547 AZD2014 Palbociclib Crizotinib AZD9291 Selumetinib + docetaxel
MEDI
4736
SUPPLEMENT NO. A B C D E NA
SCC PIK3CA mutant (11%)
SCC PIK3CA amplified (40%)
SCC PTEN loss, not mutated (40%)
SCC PTEN mutant (6%)
Ad - PI3kinase/AKT deregulated (4.5%)
NSCLC harbouring AKT1 mutation
FGFR (A1) - NSCLC harbouring FGFR mutations (4.0% SCC and <1% Adeno)
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AZD5363 AZD4547 AZD2014 Palbociclib Crizotinib AZD9291 Selumetinib+ Docetaxel
MEDI
4736
SUPPLEMENT NO. A B C D E NATSC (B1) – NSCLC harbouring TSC1/2 mutations (2.7% SCC and 0.5% adeno)
LKB1 (B2 and B3) – NSCLC harbouring LKB1 mutations (Tier 1 - 4.6% Ad and 1.6% SCC: Tier 2 2.4% and <1%)
SCC with proficient Rb and p16 loss (C1)
(CDKN2A HD 29%)
CDK4 amplified NSCLC (C2) (7% Ad and <1% SCC)
CCND1 amplified NSCLC (C3) (12% SCC, 5% Ad)
Adeno harbouring KRAS mutations (C4) (25.8%)
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AZD5363 AZD4547 AZD2014 Palbociclib Crizotinib AZD9291 selumetinib+ Docetaxel
MEDI
4736
SUPPLEMENT NO. A B C D E NAMET (D1) – Met amplified NSCLC (4% SCC and Ad - Rx effect))
ROS (D2) –NSCLC harbouring ROS fusions (Ad 1.7% and SCC <1%)
EGFR mutation and T790M+
NF1 (E1) –SCC harbouring NF1 mutations (5.8%)
NF1 (E2) – Ad harbouring NF1 mutations (4.6%)
N-RAS (E3) – NSCLC harbouring N-RAS mutations (Ad 0.7%)
Biomarker negative cohorts (F)
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NLMT – rationale for single arm design
Crizotinib, EML4-ALK and ROS fusion as exemplars – the bona fide targeted therapy
Option for biomarker-specificity testing in biomarker negative patients
Allows discrete bio-marker testing
Based on strong pre-clinical data (and/or clinical data) and the appropriate implementation of those findings
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AZD5363 AZD4547 AZD2014 Palbociclib Crizotinib
AZD9291 Selumetinib + docetaxel
MEDI
4736
SUPPLEMENT NO. A B C D E NA
SCC PIK3CA mutant
SCC PIK3CA amplified
SCC PTEN loss, not mutated
SCC PTEN mutant
Ad - PI3kinase/AKT deregulated
NSCLC harbouring AKT1 mutation
FGFR (A1) - NSCLC harbouring FGFR mutations (4.0% SCC and <1% Adeno)
NLMT – discrete biomarker/drug cohorts
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Implementing the implications of the pre-clinical dataFGFR – amplifications and mutation types
Liao R G et al. Cancer Res 2013;73:5195-5205
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Implementing the implications of the pre-clinical data5363 and Palbo molecular exclusion rules
These will change with different drugs
PIK3CA, PTEN and AKT (5363) – no KRAS mutation
Davies BR et al. Mol Cancer Ther 2012;11:873-887
KRAS mutation (Palbo) – no activation of PI3K/Akt/MTOR signaling – genetically simple models and the re-induction of senescence with cdk4 knockdown
Puyol M et al. Cancer Cell, 2010; 18: 63 – 73Kennedy AL et al Mol Cell. Apr 8, 2011; 42(1): 36–49
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Randomised precision medicine trials in lung cancer SAFIR 02 and LUNG-MAP
Assessing the benefits of the novel therapy rather than potential prognostic effects of the biomarker
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SAFIR 02 - objectives
PRIMARY OBJECTIVE :
To evaluate whether treatment with targeted agents guided by high throughput molecular analyses (CGH array, next generation sequencing) improves progression-free survival as compared to standard maintenance therapy in patients with metastatic NSCLC.
SECONDARY OBJECTIVES :
To explore the efficacy (response rate, progression-free survival, overall survival) of the individual targeted agents
To correlate molecular mechanisms in patients with the efficacy endpoints (response rate,progression-free and overall survival)
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SAFIR 02, MATRIX and LUNG-MAP – Gene blocks in common
Akt 1-3, PIK3CA, PTEN, STK11, TSC1/2 (PIK3R1, mTOR)
FGFR 1-4
NRAS, KRAS, NF1 (HRAS, MAP2K1, MAP2K4, MAP3K1)
CDKN2A loss, CDK4 amplification, CCND1 amplification
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Concluding remarks – the importance of sustainability and a unique opportunity to collaborate
“Therefore, there is maybe a place for, at least, a European project, supported by the EU, setting up a global platform with adequate resources (informatics, mathematics, statisticians, etc) able to fully combined and interpreted the data, taking into account differences in design and drugs, but aiming to propose a unique interpretation of generated knowledge as soon as it becomes available?”
Fabrice Barlesi