Enriqueta Felip Hospital Vall d’Hebron; Barcelona ¿Se deben administrar las terapias siempre personalizadas en cáncer de pulmón?: A FAVOR Enriqueta Felip Hospital Vall d’Hebron; Barcelona

DONDE ESTAMOS CON EL TRATAMIENTO CON “TARGETED THERAPIES”? Estos agentes tienen actividad en subgrupos de pacientes; pero ninguno tiene beneficio universal

Fase III positivos en 1 línea con “targeted therapies” en población no seleccionada ECOG carbo/pac/beva vs carbo/pac PFS 6,2 vs 4,5 meses; HR 0.66, p<0.001 MS 12,3 vs 10,3; HR 0.79, p<0.003 AVAIL cis/gem/beva 15 vs cis/gem/beva 7.5 vs cis/gem/placebo PFS 6,6 vs 6,8 vs 6,2 meses; HR 0.85/p=0.0456; HR 0.75/p=0.0003 MS 13,4 vs 13,6 vs 13,1 meses; HR 1.03/p=0.76; HR 0.93/p=0.42 FLEX cis/vin/cetuximab vs cis/vin (EGFR IH +) PFS 4,8 vs 4,8 meses; HR 0.943, p=NS MS 11,3 vs 10,1 meses; HR 0.871, p=0.044

Fase III positivos en 2-3 línea con “targeted therapies” en población no seleccionada BR.21 erlotinib vs placebo Mediana de supervivencia 6,7 vs 4,7 meses; HR 0.72; p=0.001 INTEREST gefitinib vs docetaxel Mediana de supervivencia 7,8 vs 8.0 meses; HR=1.02

Cronología interpretación mutaciones de EGFR 2004 mutaciones de EGFR; predictivas 2005 número copias del gen predictivo; mutaciones no 2007 mutaciones de EGFR pronosticas no predictivas 2008 mutaciones de EGFR predictivas de supervivencia libre de progresión

EGFR mutation positive EGFR mutation negative IPASS: PFS in EGFR mutation positive and negative pts EGFR mutation status is a predictive biomarker for the effect of gefitinib compared to CP EGFR mutation positive EGFR mutation negative Gefitinib (n=132) Carboplatin / paclitaxel (n=129) Gefitinib (n=91) Carboplatin / paclitaxel (n=85) 1.0 1.0 HR (95% CI) = 0.48 (0.36, 0.64) p<0.0001 No. events gefitinib, 97 (73.5%) No. events C / P, 111 (86.0%) HR (95% CI) = 2.85 (2.05, 3.98) p<0.0001 No. events gefitinib , 88 (96.7%) No. events C / P, 70 (82.4%) 0.8 0.8 0.6 0.6 Probability of progression-free survival Probability of progression-free survival 0.4 0.4 0.2 0.2 0.0 0.0 4 8 12 16 20 24 4 8 12 16 20 Months Months At risk : Gefitinib 132 108 71 31 11 3 91 21 4 2 1 C / P 129 103 37 7 2 1 85 58 14 1 Treatment by subgroup interaction test, p<0.0001 Mok et al, NEJM 09

IPASS: No two mutations are the same Exon 19 Deletion L858R Exon 19 Deletion Gefitinib C/P N 66 74 Events 46 (69.7%) 65 (87.8%) HR (95% CI) = 0.377 (0.255, 0.560) L858R Gefitinib C/P N 64 47 Events 48 (75.0%) 40 (85.1%) HR (95% CI) = 0.553 (0.352, 0.868) HR<1 is in favour of Gefitinib

IPASS. OS by mutation status Probability of overall survival 1.0 EGFR Mutation+ 1.0 EGFR Mutation- 0.8 0.8 0.6 0.6 0.4 Randomised treatment 0.4 Gefitinib Gefitinib 0.2 0.2 Carboplatin / paclitaxel Carboplatin / paclitaxel 0.0 0.0 4 8 12 16 20 24 28 4 8 12 16 20 24 28 Time from randomisation (months) Time from randomisation (months) No. of patients at risk Months 0 4 8 12 16 20 24 28 Gefitinib 132 126 114 73 41 17 0 0 Carboplatin / paclitaxel 129 123 105 67 38 15 1 0 No. of patients at risk Months 0 4 8 12 16 20 24 28 Gefitinib 91 69 44 25 13 5 0 0 Carboplatin / paclitaxel 85 76 55 24 8 4 0 0 M+ Gefitinib C/P N 132 129 Events 38 (28.8%) 43 (33.3%) HR (95% CI) = 0.776 (0.500, 1.202) M- Gefitinib C/P N 91 85 Events 52 (57.1%) 42 (49.4%) HR (95% CI) = 1.384 (0.915, 2.092) 8

IPASS. Improvement in QOL of EGFR mutation +ive patient receiving gefitinib

North East Japan Gefitinib Study Group Gefitinib vs Carbo/Pac in EGFR mutated patients Response Gefitinib (N=98) CBDCA+Paclitaxel (N=100) CR 4 PR 69 29 SD 13 50 PD 8 15 NE 6 CR+PR 73 (74.5%) 29 (29%) Kobayashi K, ASCO 2009 10

North East Japan Gefitinib Study Group Progression-free survival Kobayashi K, ASCO 2009 10.4 vs 5.5 months, HR=0.357 (95%CI: 0.25-0.51), logrank test: p<0.001 11

Screening for EGFR mutations in lung cancer (Rosell et al, NEJM 09) Analizan mutaciones EGFR en 2105 pacientes de 129 centros (2005-08) 350 mutaciones (16,6%) > frecuente en mujeres (69,7%) y no fumadores (66,6%) Deleciones exon 19, 62% / mutaciones L858R, 38% 217 pacientes recibieron erlotinib PFS 14 meses; MS 27 meses

Erlotinib for patients with positive EGFR mutation Progression-free survival Median: 14 meses Overall survival Median: 27 meses Rosell et al, NEJM 2009 13

Spanish Lung Cancer Group Groupe Français de Pneumo-Cancérologie EURTAC N=146 RANDOMIZATION ARM A CROSSOVER Erlotinib 150 mg/d/vo N=73 Population Cis 75/Gem 1250 Cis 75/ Doc 75 Carbo5/Gem 1000 Carbo6/Doc 75 ARM B N=73 3-month improvement in PFS α=0.05 (two-tailed comparison) β=0.2 (80% power) Spanish Lung Cancer Group Groupe Français de Pneumo-Cancérologie Italy

SATURN. PFS according to EGFR mutation status EGFR wild-type HR=0.10 (0.04–0.25) HR=0.78 (0.63–0.96) Log-rank p<0.0001 Log-rank p=0.0185 1.0 0.8 0.6 0.4 0.2 1.0 0.8 0.6 0.4 0.2 Erlotinib (n=22) Placebo (n=27) Erlotinib (n=199) Placebo (n=189) PFS probability 0 8 16 24 32 40 48 56 64 72 80 88 96 0 8 16 24 32 40 48 56 64 72 80 88 96 Time (weeks) Time (weeks) Interaction p<0.001 Capuzzo et al; ASCO 09

SATURN. OS according to EGFR mutation status EGFR wild-type HR=0.83 (0.34–2.02) HR=0.77 (0.61–0.97) 1.0 0.8 0.6 0.4 0.2 Log-rank p=0.6810 1.0 0.8 0.6 0.4 0.2 Log-rank p=0.0243 Erlotinib (n=199) Median 11.3 Placebo (n=189) Median 10.2 OS probability Erlotinib (n=22) Median NR Placebo (n=27)* Median 23.8 0 3 6 9 12 15 18 21 24 27 30 33 36 0 3 6 9 12 15 18 21 24 27 30 33 36 Time (months) Time (months) *Note that 67% of patients with EGFR mutation+ disease in the placebo arm received a second-line EGFR TKI Capuzzo et al; IASLC 09

EGFR TKIs works well on EGFR mutation positive patients: Be it first or second line

Two mutually exclusive pathways to lung ADC (pooled data from East Asian and western countries) Tobacco Smokers KRAS mutations (14%) ADC Genetic factors ? ? Carcinogen Never Smokers EGFR mutations (31%) HER2 mutations (4%) BRAF mutations (1%) Gazdar, IASLC Workshop 2006 18

Mutaciones de KRAS en ADC de pulmón y beneficio a EGFR TKIs Mutaciones de KRAS; 20-30% de ADC, sobretodo en fumadores Resultados NO concluyentes, pero: En KRAS mutado; respuesta a EGFR TKIs < 1% Meta-análisis de estudios publicados (Linardou et al; Lancet Oncol 08); mutación de KRAS se asocia a ausencia de respuesta a TKIs Evidencia insuficiente para confirmar que mutaciones de KRAS no son una contraindicación a cetuximab en pacientes con ADC (FLEX: KRAS analizado en 395 muestras / 75 mutaciones)

Características clínicas de pacientes con NSCLC con EML4-ALK + (Shaw AT, JCO 09) EMLK4-ALK; proteína tyrosine kinasa de fusión “Screening” EMLK4-ALK / EGFR si > 2 características: mujer, etnia asiática, no fumador, ADC 141 analizados, 13% EMLK4-ALK + / 22% mutaciones EGFR EMLK4-ALK +: Excluyente con mutaciones de EGFR / KRAS Pacientes más jóvenes y frecuentemente hombres Frecuentemente no fumadores Asociado a resistencia a EGFR TKIs EMLK4-ALK +, subgrupo molecular de NSCLC diferente

Estudio fase I PF-02341066 (Kwak et al ASCO 09) PF-02341066 inhibidor oral de c-MET y receptor tyrosine kinasa ALK Cohorte enriquecida en fase I; 29 pacientes con NSCLC con translocación EML4-ALK en tumor (76% no fumadores / 90% ADC): Respuesta parcial 59% pacientes Control de la enfermedad 83% pacientes

Algoritmo sugerido en pacientes con ADC pulmonar antes de tto con “targeted therapy” oral (Horn & Pao JCO 09)

Courtesy of Dr Mark Kris All Lung Cancer Tumor Specimens (operated or referred) LC-MAP: The Lung Cancer Mutation Analysis Project LC-MAP: The Lung & Colorectal Mutation Analysis Project Diagnostic Pathology (morphology) Non-Adenocarcinoma Adenocarcinoma Clinical testing EGFR/KRAS/BRAF Sequenom Assays Clinical billing and reporting Research testing (under IRB 06-107) Other Sequenom Assays: (above +) PIK3CA, HER2, MEK1, AKT1, etc… IHC assays: PDGFRα, IGF1R FISH for MET, ALK + + Data to research database If result used for management, reconfirm rare mutations by “clinical sequencing” LC-MAP panel: total of 40 mutations in 7 genes; 4 multiplexed PCRs Courtesy of Dr Mark Kris

Genetic profiling in ADC at MSKCC Courtesy of Dr Mark Kris Routine use of molecular characteristics to select therapies for patients with ADC EGFR Mutation Use erlotinib KRAS Mutation Do not use of erlotinib Do not use cisplatin-based adjuvant therapy HER2 Mutation or Amplification Use trastuzumab Molecular characteristics used to select patients for protocols at MSK EGFR BIBW 2992 Erlotinib (Adjuvant) KRAS Salirasib - Deforolimus EML4-ALK MET Amplification PF-02341066 BRAF AZ6244

Looking for a target on every tumor Science 9 October 2009

Advanced NSCLC; pharmacogenomic approaches: prospective ERCC1-study (GILT) ORR 39% 53% 51% (P=0.02) 47% MS 9.8 10.4 9.5 N 141 129 96 1:2 R A D O Control CDDP/Doce RT-PCR: ERCC1 low ERCC1 high Gem/Doce ERCC1 mRNA predicts response but not survival Cobo et al, JCO 2007

First-line cis/pem vs cis/gem in NSCLC Randomized phase III, non-inferiority design, 1725 pts, histology pre-defined subgroup analysis ADC and LCC (1000 patients, 58% of study population) Scagliotti et al, JCO 2008

Pemetrexed maintenance: survival by histology Ciuleanu et al; Lancet 09 Non-squamous (n=481) Squamous (n=182) HR=0.70 (95% CI: 0.56-0.88) P =0.002 HR=1.07 (95% CI: 0.49–0.73) P =0.678 Survival Probability Pemetrexed 15.5 mos Pemetrexed 9.9 mos Placebo 10.3 mos Placebo 10.8 mos Time (months) Time (months)

Histology: surrogate of molecular markers

NATCH trial DFS in preop CT arm vs surgery arm At risk: Surgery 130 98 77 53 34 23 Preop CT 140 105 81 57 37 26 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1 2 3 4 5 6 Time (years) Probability Surgery Preop CT (N=210) (N=199) Events 132 117 Median DFS (mo) 25.1 31.5 3-year DFS 41.9% 48.4% 5-year DFS 34.1% 38.3% HR = 0.92; 95% CI (0.81 to 1.04); P = 0.176

NATCH trial. DFS in pts responding to preop CT 85 68 54 38 26 17 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1 2 3 4 5 6 At risk: Time (years) Probability PR/CR to Preop CT 16 15 14 9 19 pCR to Preop CT 106 PR/CR to Preop CT pCR to Preop CT (N= 106) (N=19) 3-year DFS 59% 79% 5-year DFS 51% 59%

Survival to neo gem/cis in NSCLC according to BRCA1 mRNA expression Survival (months) 60 50 40 30 20 10 1,0 .9 .8 .7 .6 .5 .4 .3 .2 .1 Probability q1 q2+q3 q4 HAZARD RATIO Taron et al. Hum Mol Genet 2004

El tratamiento personalizado es una realidad en cáncer de pulmón ¿Se deben administrar las terapias siempre personalizadas en cáncer de pulmón?: SI Mutaciones de EGFR predictivas de beneficio a EGFR TKIs Mutaciones de KRAS y EMLK4-ALK + definen subgrupos de pacientes con diferentes evoluciones a inhibidores TKIs Histología: surrogado de marcadores moleculares Aplicación clínica marcadores genéticos en estadios iniciales; cuando se plantee QT neoadyuvante El tratamiento personalizado es una realidad en cáncer de pulmón