Disclosure slide. I provided consultations and attended advisory boards for. Astra-Zeneca, Boehringer Ingelheim, Daichii Saiko, Eli Lilly

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1 Clinical assessment and implication of biomarkers identification Cancer Biology International Master Program Montpellier - October 21, 2 Fabrice Barlesi, MD, PhD Multidisciplinary Oncology & Therapeutic Innovations CRO2 INSERM U911 Disclosure slide I provided consultations and attended advisory boards for Astra-Zeneca, Boehringer Ingelheim, Daichii Saiko, Eli Lilly Oncology, F. Hoffmann La Roche Ltd, Glaxo-Smithkline, Novartis, and Pfizer, for which I received appropriate honoraria. Bioguided Mutations treatments! de l EGFR Pao W, Nat Rev Cancers 21 Agenda Agenda EGFR mut discovery A decade in the EGFR mutations era Moving forward with new biomarkers? A nationwide access to the biomarkers assessment (example in France) Quantitative and qualitative evaluation of the current personalized medicine A decade in the EGFR mutations era Moving forward with new biomarkers? A nationwide access to the biomarkers assessment (example in France) Quantitative and qualitative evaluation of the current personalized medicine Baseline 4 months Adapted from Lynch 24 EGFR mut discovery EGFR mut screening (nsnsclc) program EGFR mutants profile (nsnsclc) INCa, tested samples 147 (1%) EGFR mutants (1%) rare EGFR mutants *complex mutation: rare EGFR mutation with a mutation in another EGFR exon (18, 19, 2, 21) G719X (n=29) Exon 2 28% insertions (n=41) 4% E79X (n=3) 3% Exon 18 other Complex susbstitutions (n=6) mutations 6% T79M (n=1) (n=) 1% % Exon 18 Exon 2 deletions/ins (n=3) other susbstitutions (n=7) 3% 7% Beau-Faller et al, ASCO 2 1

2 EGFR mutants in SCC also? Bioguided treatment: EGFR mut. Bioguided treatment: EGFR mut. 1,,8 Log-rank p <,1 HR erlotinib versus chimiothérapie =,342 ; IC 95:,2341-, m 1.4 m Probabilité de SSP,6,4,2 Erlotinib Chimiothérapie 5,1 1,4 Sos ML et al, Oncogene 2 Inoue et al, ESMO Mois Patients à risque (n) Erlotinib Chimiothérapie Cut-off au 11 avril 2 Rosell R et al, ESMO 2 Bioguided treatment: EGFR mut. EGFR-TKI Mutations vs EGFR-TKI de l EGFR EGFR-TKI Mutations vs EGFR-TKI de l EGFR EGFR RO % Etudes Pop. Médicament Mut + (N) TKI vs CT IPASS Asie Gefitinib ,2 vs 47,3 First-SIGNAL Asie Gefitinib 42 84,6 vs 37,5 WJTOG 345 Asie Gefitinib ,1 vs 32,2 NEJGSG2 Asie Gefitinib ,5 vs 29 OPTIMAL Asie Erlotinib vs 36 EURTAC Europe Erlotinib vs 11 LUX LUNG 3 Mixte Afatinib vs 22.6 LUX LUNG 6 Asie Afatinib vs 23 SSP (HR, IC95%),48 (,36 -,64),61 (,31 1,22),49 (,34,71),3 (,22,42),16 (,1,26),42 (,27-,64).58 ( ).28 (.2-.39) Patients Failed first-line CT PS -2 2 of 3 characteristics Adenocarcinoma Female Never-smoker or - EGFR activating mutation DCR, disease control rate Gefitinib 25 mg/day n=48 1:1 randomisation Erlotinib 15 mg/day n=48 Study in a Korean patient population Endpoints Primary ORR Secondary PFS OS QoL Overall DCRs Safety and tolerability Kim S et al, Lung Cancer 2 EGFR-TKI Mutations vs EGFR-TKI de l EGFR Outcomes: Mutations primary de l EGFR resistance Outcomes: primary resistance Gefitinib Erlotinib Afatinib #1%? #1%? Kim S et al, Lung Cancer 2 Mok et al, N J Engl Med 29; Rosell et al, Lancet Oncol 2 Sequist et al, J Clin Oncol 2; Wu et al, ASCO 2 2

3 EGFR mutants: Mutations not de all l EGFR the same EGFR mutants: Mutations not de all l EGFR the same EGFR mutants: Mutations not de all l EGFR the same Probability of progression-free survival Deletion exon 19 L858R Gefitinib (n=66) Carboplatin/paclitaxel (n=74) 1. HR (95% CI) =.377 (.255,.56) No. events gefitinib, 46 (69.7%).8 No. events C/P, 65 (87.8%) Months Patients at risk : Gefitinib C/P Probability of progression-free survival Gefitinib (n=64) Carboplatin/paclitaxel (n=47) 1. HR (95% CI) =.553 (.352,.868) No. events gefitinib, 48 (75.%).8 No. events C/P, 4 (85.1%) Months Exon 2 T79M H773L + V774M D77 N771insSVD V769 D77delinsGI S768 D77dupSVD P772 S768 D77dupSVD D77 N771insSVD N771dupN H773_V774dupH A767 V769dupASV M766 V769insWPA A767 V769dupASV S768 D77dupSVD A767S768insSVR S768 D77dupSVD T79M H773L + V774M A767 V769dupASV N771 delinskpp A763 Y764insFQEA T79M H773_V774dupH Exon 18 G719S E79H T71del G719C Y693I L692V G719S G719S E79A + G719S G719C G719C Rosell et al, Lancet Oncol 2 Mok et al, IASLC 29 Beau-Faller et al, ASCO 2 EGFR mutants: Mutations not de all l EGFR the same Special populations: Mutations de l EGFR brain mets Outcomes: secondary Mutations de l EGFR resistance Author n Drug ORR (%) PFS (m) OS (m) 1, Hotta 14 GEF Porta 17 ERL PFS,8,6,4 Log-rank p <,1 HR erlotinib versus chemotherapy=,342 ; IC 95 :,2341-,4944 Erlotinib Chemotherapy Kim 23 GEF/ERL ,2 Li 14 GEF ,1 1,4 Wu 48 ERL Months Erlotinib Chemotherapy Hata A et al, J Thorac Oncol 2 Rosell R et al, ESMO 2 Progression by RECIST Progression by RECIST Histological/biological change Ms. S. Marie Mr. P. Pierre Molecular characteristics of tumours with acquired resistance to EGFR TKI Unknown mechanism (3%) T79M (49%) Baseline M8 Adenocarcinoma Stage IV EGFR mut (ex21) M9 M18 Adenocarcinoma Stage IV EGFR mut (del19) PIK3CA (5%) * SCLC transformation (14%) MET amp (5%) *1 pt with PIK3CA and SCLC transformation Sequist L et al, Sci Trans Med 211 3

4 Patients at risk G1: Low/Intermediate BIM and T79M present G2:Low/Intermediate BIM and T79M absent G3: High BIM and T79M present G4:High BIM and T79M absent 19/11/2 Histological/biological change Histological/biological change Histological/biological change Molecular characteristics of tumours with acquired resistance to EGFR TKI Molecular characteristics of tumours with acquired resistance to EGFR TKI G3 G4 G G1 4 1 Oxnard G et al, Clin Cancer Res 211 Yu H et al, Clin Cancer Res 2 Rosell R et al, ESMO 2 Histological/biological change Flare up Non bioguided strategies Mr. P. Serge 61 patients éligibles Temps jusqu à progression sous gef ou erlo Author Treatment for Sample size RR resistance (%EGFR mutation) Efficacy 14 patients (23 %) avec flare 47 patients avec période de washout sans problème Flare Sans flare Médiane : 9 versus 15 mois (p =,2) Riely et al CCR 27 Soria et al Ann Onco 29 Sequist et al JCO 21 Gefitinib + (62) TTP 3 m everolimus Everolimus 43 () 2% TTP 2.7 m Neratinib 91 (1) 3% PFS 3.6 m 3 décès 3 patients inclus dans un essai clinique 8 patients avec réinstauration rapide d ITK Mois Janjigian et al CCR 211 Sequist et al JCO 21 Erlotinib + 19 (84) PFS 3 m cetuximab IPI (1) 4% NR Adenocarcinoma pt3nm Adenocarcinoma Metastatic relapse Take time for discussion on the optimal strategy Johnson et al JTO 211 Miller et al ASCO 28 Dasatinib (1) PFS 3 m XL % NR EGFR mut (del 19) Kras mut (GV) D après Chaft JE et al., WCLC 211 abstr. O19.5 actualisé Oxnarg G et al Clin Cancer Res 211 Rebiopsy Standard therapy: cisplatin-based Rx Combination of EGFR inhibitors + Cx Efficacy of chemotherapy: ORR: 47 % DCR: 87 % Advance stage NSCLC with EGFR Mutation Gefitinib PD By RECIST Gefitinib + Pemetrexed/Platinum Lymph node biopsy CT scan biopsy Primary endpoint: PFS Pemetrexed/Platinum Courtesy of Dr Dutau and Dr Gaubert, Aix Marseille University Mok et al, J Clin Oncol 211 IMPRESS, Co-PI: JC Soria & T Mok 4

5 Agenda Step by step strategy Drug availability strategy A decade in the EGFR mutations era Moving forward with new biomarkers? HER2mut A nationwide access to the biomarkers assessment (example in France) Quantitative and qualitative evaluation of the current personalized medicine PI3K mut KRASmut BRAFmut Pao W, Nat Rev Cancer 21 By chance : ALK rearrangement By chance : ALK rearrangement Driver mutation Séparation du signal: ALK réarrangé Image: Patrice Roll, Assistance Publique Hôpitaux de Marseille; Ou et al, J Thorac Oncol 21 Probability of survival without progression (%) Crizotinib Pemetrexed Docetaxel (n=172 a ) (n=99 a ) (n=72 a ) 1 Events, n (%) 1 (58) 72 (73) 54 (75) Median, mo HR b (95% CI).59 (.43 to.8).3 (.21 to.43) 8 P.4 < Time (months) Shaw A et al, NEJM 2 How can we (ideally) define it? Induces the disease in an animal model Is assessable reproducibly in patients Induces a permanent oncogenic addiction Translates in an oncogenic shock when efficacely targeted Adapted from Sharma et al, Nat Rev Cancer 27 Driver mutation Driver mutations outside lung cancer Driver mutations outside lung cancer LMC (bcr-abl): Imatinib GIST (c-kit): Imatinib Resistances Protein Drug Disease Mutation Mélanome (BRaf V6E): Vemurafenib BCR-ABL Imatinib/Dasati nib LMC T315I KIT Imatinib GIST T67I Sharma SV et al, Clin Cancer Res 26; Sharma SV, Nat Rev Cancer 27 Shah et al, 22; O Hare et al, 25; Cools et al, 23; Tamborini et al, 24 5

6 Driver mutations in lung cancer Probability of additional drivers? Probability of additional drivers? Proven driver mutations (2): Mutations activatrices EGFR: #1% Translocations EML4-ALK: 3% Vogelstein, Science 2 Ding et al, Nature 28 Probability of additional drivers? Techniques Targets 3726 point mutations 9 indels x1 chez les fumeurs IHC 1 Ab / biomarker SANGER Few exons / gene Govindan et al, Cell 2 Li et al, J Clin Oncol 2 Targets Targets Targets Oxnard et al, J Clin Oncol 2 Hanahan & Weinberg, Cell 211 Li et al, J Clin Oncol 2 6

7 High Throughput Molecular Screening Recherche sans à priori CGH array (comparative genomic hybridation) Comparaison Nbre copies ADN Code couleur High Throughput Molecular Screening High Throughput Molecular Screening NGS (next generation sequencing) Characteristics Sanger NGS Read lenght 4-9 bp 5-22, bp Accuracy % Reads per run - Up to 1.4 billion Time per run 2 min 3h 2h 1 days Price (machine) $ 2 95, 4, 7, Cost (1 million bases) $ Courtesy JC Soria Quail M et al, BMC genomics 2; Liu L et al, J of Biomed and Biotechnology 2 High Throughput Molecular Screening High Throughput Molecular Screening New Ressources needed NGS: Mathematicians Biologically trained Human ressources Logistics Multidisciplinary Tumor board Trained and continously updated Human ressources Large clinical trials access Govindan et al, Cell 2 Molecular changes Molecular change Molecular change Vignot et al, J Clin Oncol 2 Greaves & Maley, Nature 2 Gerlinger et al, New Engl J Med 2 7

8 Targets Molecular profile of lung cancer Targets 1 LCC OTHER/UNK 27,9 6,6 SCC PI3K SCC FGFR1 4,4 1,2,8 SCC MET,4 6,6 SCC DDR2 SCC BRAF SCC OTHER/UNK ADC KRAS,7,7 1,4 1,4 1,4 3,4 1,4 21 ADC EGFR ADC ALK ADC FGFR4 ADC BRAF ADC HER2 ADC MEK ADC PI3K ADC OTHER/UNK Oxnard et al, J Clin Oncol 2 Adapted from Janne P et al, JCO 2; Perez-Moreno P et al, Clin Cancer Res 2 Agenda A decade in the EGFR mutations era Moving forward with new biomarkers? A nationwide access to the biomarkers assessment (example in France) Quantitative and qualitative evaluation of the current personalized medicine Why? Biology > clinical characteristics Biomarker-driven Strategies? First-step: biomarker testing Availability Quality control Global Access D Angelo S et al, JCO 211 The French Bio-platforms Network The begining (26) The begining (26) Starting (26) Platforms for molecular cancer diagnosis Leaded by: DGOS (Health Ministery) INCa (French NCI) Biomarkers assesment for Prediction (targeted therapies) Diagnosis Prognostic Residual disease Daily practice Link with research activities Translational research Clinical trials National Cancer Institute (USA) Drugs Companies 8

9 Clinical research / Competitors Finances (27/28) Evolution: Plan Cancer 29-2 Financial support from the French NCI Equipment: 4.7 M Recruitment (non MD): 4. M Support from drugs companies * To be reimbursed by the national health All types of clinical trials LEEM study, 21 insurance in the future (CCAM/NABM) * Guarante an equal access to treatments and innovations Results 29 Evolution (21) Results: 21 Quality control Generalization (EGFR only) Disponible sur Generalization Evaluation: 21 Prescription origin for EGFR mutations testing University Hospitals / Anticancer centers General hospitals Private hospitals / clinicians from the private From one system platform to another one Evaluation: 21 Anticipate for new biomarkers/therapies Large opportunities (theoritically) Mutation Rate (%) EGFR act. 9.6 EML4/ALK* 4.6 KRAS 25.4 BRAF 1.8 Pi3KCA 2.1 HER2 Ex

10 Large opportunities (theoritically) Evolution (211) Finances (211) 2 trials 3 trials 1 trial 1 trial 2 trials Quality Control (registre essais cliniques / accès au 28/3/2 Disponible sur Disponible sur How it currently works? How it currently works? How it currently works? 28 platforms (26) 7 biomarkers for Non-sq NSCLC (starting 21) Cancer Molecular Target Lung EGFR mutations (activating and resistant) Non-sq EML4-ALK transloc. NSCLC KRAS mutations HER2 ex2 mutations BRAF mutations PI3K mutations * i.e. Regional molecular genetics centers Barlesi F et al, ASCO 2 #8 Courtesy: Laboratoire d Anatomie Pathologique, Aix Marseille Université Assistance Publique Hôpitaux de Marseille Courtesy: Laboratoire de Transfert, Aix Marseille Université Assistance Publique Hôpitaux de Marseille Results: 211 Results: 211 Results: 2 1.2% 26.8% 1.8%.9% 2.4% 3.9% 1

11 Additional national programs: Acsé Additional national programs: PredictAMM Agenda ACSé program (Crizotinib): ALK Amplification ALK Mutations MET Amplification MET Mutations ROS1 Translocations Stage IV NSCLC EGFR ex19-21 mut EGFR ex2 mut (T79M) KRAs mut EML4-ALK ERCC1 / Msh2 BTubIII TS CMet 18 centres Ongoing, A decade in the EGFR mutations era Moving forward with new biomarkers? A nationwide access to the biomarkers assessment (example in France) Quantitative and qualitative evaluation of the current personalized medicine The Biomarkers France project Methods Results: timeline Routine biomarker screening on platforms Biomarkers results sent both to: The prescribing physician (ie daily practice) Analyses (n) Reality of bioguided treatments? Efficacy? The Biomarkers France database (IFCT) Database access granted to the physician in order to complete patients data 9 items for demographics items for therapeutics Pilot study Nov. Feb Apr. 2, 2 Database implementation Current analysis Apr. 1, 2 FU / Monitoring Results: flow-chart Analyses (Jan 2) Database n 9,911 samples Analyzed * Other type of cancer (n=); Unknown patient (n=77) 1, 9,464 patients Excluded 89* Results: flow-chart Median follow-up: 4.4 months (-15.8 m) Data availability (ie data already completed by the clinicians at the time of this analysis) Ethnicity Smoking history ECOG PS Previous cancer (patient) Previous cancer (family) Stage 1st line treatment Results: demographic (n=9464*) % Sex Male/Female 64/36 Age (yrs, median [Range]) 64.5 [ ] Ethnicity Asian/Other 1.2/98.8 Smoking History Current/Former smoker 38.1/44.2 Never smoker 17.7 ECOG PS / or more 27.3 Previous history of cancer Patient 2.2 Family 14.5 Stage I/II 14.6 IIIB/IV/Relapse 71.8/7.6 * Accordingly to the data availability as described in the previous slide 11

12 Results: samples (n=9911) % Samples collection Bronchoscopy 27.5 Trans-thoracic biopsy 28 Surgery 24.1 Other 2.4 Delay between sample collection and analysis (days, 8 median) Samples analyzed/patient or more.2 Delay between start of analysis and results 11 (days, median) Histology Adenocarcinoma/Large Cell C. 76.1/3.2 Squamous Cell C. 5.3 Other NSCLC subtypes 15.4 EGFR mut screening failures Lack of DNA amplification Absence of tumor cells % of tumor cells below the limit INCa, 2 Results: biomarkers assessment (n=9911) EGFR act mut 9.5% EGFR res mut.8% HER2 mut.9% KRAS mut UKN/Other 27% 53.8% BRAF mut ALK 1.7% Results expressed in % rearrangement PI3K mut on available analyses 3.7% 2.6% Results: biomarkers assessment (n=9911) Results: biomarkers by smoking status (n=9911*) Results: rate of bioguided 1 st line treatment (n=9464*)? Double mutation (n=79) UKN Mutant/Translocated EGFR ALK KRAS BRAF PI3K HER2 EGFR - ALK 3 - KRAS BRAF PI3K HER2 1 - Smokers Never smokers * Including 2664 with full clinical data available at the time of this analysis. EGFR activ EGFR resist KRAS BRAF ALK PI3K HER2 UNK NO (Other): 31.6% NO (delay): 11.5% YES: 56.9% * Including 2671 with full clinical data available at the time of this analysis. Results: type of 1 st line treatment (n=9464*) Results: type of 1 st line treatment by biomarker (EGFR mut, n=16*) Results: type of 1st line treatment by biomarker (ALK, n=141*) Cx (TXT/TXL) Cx (VNR) Bioguided Rx % Bioguided Rx % Cx (PEM) EGFR TKI Trial BSC only Yes 7 No (delay) 1 No (other) Cx (TXT/TXL) Cx (VNR) Cx (PEM) EGFR TKI Trial BSC only Other Yes 52.4 No (delay) 26.5 No (other) Cx (TXT/TXL) Cx (VNR) Cx (PEM) EGFR TKI Trial BSC only Other Other * Including 2671 with full clinical data available at the time of this analysis. * Including 217 with full clinical data available at the time of this analysis. * Including 46 with full clinical data available at the time of this analysis.

13 Apr- May- Jun- Jul- Aug- Sep- Oct- Nov- Dec- Jan- Feb- Mar- Apr- May- Jun- Jul- Aug- Sep- 19/11/2 Results: type of 1st line treatment by biomarker (Other) KRAS (n=675) BRAF (n=29) PI3K (n=31) HER2 (n=) Chemo 6, EGFR-TKI,7 8 Trial 2,2 4 Other,5 2 3 BSC 23, Bioguided strategies: emerging biomarkers KRAS (n=675) BRAF (n=29) PI3K (n=31) HER2 (n=) Chemo 6, EGFR-TKI,7 8 Trial 2,2 4 Other,5 2 3 BSC 23, Barlesi F et al, ASCO 2; Janne PA et al, Lancet Oncol 2; Planchard D et al, ASCO 2; Mazières et al, J Clin Oncol Results: survival (global pop.*) Median OS : 11.4 months (95%CI: 1.5-NR) * Including 225 pts with full clinical data available at the time of this analysis Months Perspectives Entire cohort #19, biomarker analyses Data to be progressively completed A form of medicine that uses information about a person s genes, proteins and environment to prevent, diagnose and treat disease Everything is personalized Nothing is personalized NCI dictionary of cancer terms Bio-guided phases I: Efficacy Bio-guided phases I: Market access Bio-guided phases I: Market access PhI 5 PhIII PhI PhIII 1 8 To reach an FDA/EMEA label: 5 phases I 7 phases II 11% 14 Vinorelbine Pemetrexed Gefitinib Erlotinib 14 Vinorelbine Pemetrexed Gefitinib Erlotinib 6 Années 4 phases III Trastuzumab Crizotinib Vemurafenib Dabrafenib 1 8 PhI PhIII Trastuzumab Crizotinib Vemurafenib Dabrafenib PhI PhIII 4 2 Vinorelbine Pemetrexed Gefitinib Erlotinib Trastuzumab Crizotinib Vemurafenib Dabrafenib Receptor targeted therapy: 31% Bio-marker guided therapy: 62% Falconi A et al, ASCO 2 CIC-CPCET CIC-CPCET CIC-CPCET

14 Bio-guided phases I New drug Known or potential biomarker: bioguided phase I No biomarker Signal + Signal - Standard PhI Phase III STOP? New potential biomarker Hollebecque A et al, ASCO 2 Courtesy JC Soria (presented during the 2 nd phase I seminar, Marseille, 2) CIC-CPCET Personalization needs organization Sampling (shorting the delays) Analyses (innovate continuously) Interpretation and decision (biomath) Access to new drugs (trials) The more convenient solution Centralization (sampling, analyses, treatment decision) Regionalization (follow-up, trials)? Network (French, European, International) Sequist L et al, Ann Oncol 211 Bio-guided phase III trial PS Stage IV patient Superiority is not demonstrated regarding OS Bioguided Rx (AZ pipeline: AZD214, 1L Standard CDDPbased Cx 2L Standard 2 nd line Cx 3L Standard 3 rd line Cx Standard Experiment. bioguided Bioguided Rx Rx EGFRm (rebiopsy) ALK Cost-effectiveness to be demonstrated (7.5M ) Excessive patient s expectations Personalized medicine is currently just a part of a global treatment strategy Stage IV NSCLC No EGFRm No ALK Fresh 2 cycles max CGH NGS SAPHIR2L trial design (PI JC 4 cycles R No molecular alteration or Progression AZD4547, AZD5363, AZD8931, selumetinib, vandetanib) Standard Cx PMX (nsq) ERL (SQ) Until PRG 14

15 Don t extrapolate too much! Don t extrapolate too much! Surgery Inclusion Biomarker Analysis CG + PL C AUC 4 Randomisation Treatmentt D 1 D 61 SUCCES 8% (N=)* % 1% 2% 3% 4% 5% 6% 7% 8% 9% 1% Succes Failures Biomarker status not available on time 5% (n=8) End of study before treatment 3% (n=5) Time between surgery and treatment >61 days 11% (n=17) Soria JC et al, ASCO 2 Don t extrapolate too much! CG + PL Control Arm CDDP pemetrexed EGFR Erlotinib mutated Experimental Arm ERCC1+ Observation Customized EGFR wt Stratification criteria : Center ERCC1- CDDP-Pemetrexed EGFR status ERCC1 status Sex Stage (IIA vs IIB vs IIIB) Stage II and IIIA (non-n2) NSCLC patients with non-scc histology (6 th TNM edition) Soria JC et al, ASCO 2 CG + PL C AUC 4 N = 74 CG + PL C AUC 4 Platinum-sensitive recurrent Control OC a Arm Measurable CDDP disease pemetrexed ECOG /1 No prior chemo for EGFR Erlotinib N = 7 recurrent OC mutated No prior BV Experimental Arm (n=484) ERCC1+ Observation Customized EGFR N = 16 wt N = 76 ERCC1- CDDP-Pemetrexed N = 53 Soria JC et al, ASCO 2 Don t extrapolate too much! Conclusions Implication of biomarkers assessment CG + PL C AUC 4 Biomarker distribution CG + PL C AUC 4 PS-1 Stage IV NSCLC Expected Observed EGFR mut ns-nsclc EGFR WT s-nsclc ARM B (Experimental) customized EGFR mutated ERCC1+ 1% 44% 9% 25% EGFR-TKI (Gefitinib, Erlotinib, Afatinib) Bev eligible Bev non eligible EGFR WT or UND CDDP/Pem (or CDDP/ X) + Bevacizumab followed by bevacizumab maintenance CDDP/Pem or CDDP/ X CDDP/ X 56% 75% Crizotinib ERCC1- or UND EML4- ALK transloc ANTICIPATE! Bioguided trials Soria JC et al, ASCO 2 X= Gemcitabine or Docetaxel or Vinorelbine (Carboplatin/Paclitaxel may also be an alternative to CDDP-based combo) Implication of biomarkers assessment Implication of biomarkers assessment Implication of biomarkers assessment Personalized medicine is a common wish of patients and doctors, but it s Not so easy (logistics) Expensive Not always possible / effective Personalized medicine: Several targets few routinely used (how many lost?) Several drugs few labeled (how many lost?) Ciccolini et al, Nat Rev Clin Oncol

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