OPTIMIZACIÓN TRATAMIENTO ANTI-EGFR. Ruth Vera Oncología Médica

OPTIMIZACIÓN TRATAMIENTO ANTI-EGFR Ruth Vera Oncología Médica

OPTIMIZACIÓN TRATAMIENTO anti-egfr OPTIMIZAR quiere decir: Buscar los mejores resultados Planificar una actividad para obtener los mejores resultados Mejorar

EXPRESIÓN DE EGFR Head and neck Type of tumor Tumors with EGFR expression Head and neck 90 100% Colon 75 89% Pancreas Up to 95% Lung (NSCLC) Colorectal Breast Up to 91% Renal Up to 90% NSCLC Up to 80% Ovary Up to 77% Bladder Up to 72% Glioma Up to 63%

Importancia de la vía del EGFR en el Cáncer colorrectal Ligand AREG/EREG PTEN Proliferation/ maturation P PI3K AKT py py STAT Gene transcription P Cell cycle progression MYC JUN FOS MYC Chemotherapy/ radiotherapy resistance py Angiogenesis EGFR-TK GRB2 SOS Cyclin D1 Cyclin D1 Invasion and metastasis RAS RAF MEK MAPK Survival (anti-apoptosis) Meyerhardt JA & Mayer RJ. N Engl J Med 2005;352:476 487; Venook A. Oncologist 2005;10:250 261

OS estimate CRYSTAL study: OS KRAS exon 2 wt population 1 RAS wt population 2 1.0 Cetuximab + FOLFIRI (n=316) FOLFIRI (n=350) 1.0 Cetuximab + FOLFIRI (n=178) FOLFIRI (n=189) 0.8 0.6 0.4 20.0 23.5 HR 0.79 p=0.0093 0.8 0.6 0.4 20.2 28.4 HR 0.69 p=0.0024 0.2 0.2 0.0 0 6 12 18 24 30 36 Months 42 48 54 0.0 0 6 12 18 24 30 36 Months 42 48 54 Adapted from 1. Van Cutsem E, et al. J Clin Oncol 2011;29:2011 2019 and 2.Ciardiello F, et al. ASCO 2014 (Abstract No. 3506)

Proportion alive (%) Proportion alive (%) PRIME study: OS WT KRAS exon 2 1 WT RAS 2 100 90 80 HR = 0.83 (95% CI, 0.67 1.02) P = 0.072 100 90 80 HR = 0.78 (95% CI, 0.62 0.99) P = 0.043 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 4 8 12 16 20 24 28 32 36 Months 0 0 4 8 12 16 20 24 28 32 36 Months Panitumumab + FOLFOX4 (n = 325) Events n (%) Median (95% CI) months 165 (51) 23.9 (20.3 28.3) FOLFOX4 (n = 331) 190 (57) 19.7 (17.6 22.6) Panitumumab + FOLFOX4 (n = 259) Events n (%) Median (95% CI) months 128 (49) 26.0 (21.7 30.4) FOLFOX4 (n = 253) 148 (58) 20.2 (17.7 23.1) 1. Douillard JY, et al. J Clin Oncol 2010;28:4697-705; 2. Douillard JY, et al. N Engl J Med 2013; 369:1023-34. WT RAS, WT KRAS & NRAS exons 2/3/4 (includes 7 patients harbouring KRAS/NRAS codon 59 mutations)

Choice of targeted therapy: A growing body of evidence Phase III studies in 1st line mcrc: OS Study Biomarker n OS HR (95% CI) CRYSTAL 1,2 KRAS 666 0.80 (0.67 0.95) RAS 367 0.69 (0.54 0.88) PRIME 3,4 KRAS 656 0.83 (0.70 0.98) RAS 512 0.78 (0.62 0.99) Anti-EGFR + CT vs CT Benefit with anti-egfr Benefit without anti-egfr 0.1 1. Ciardiello F, et. al. ASCO 2014 (Abstract No. 3506) 2. Van Cutsem E, et. al. J Clin Oncol 2011; 29:2011 2019 3. Douillard J-Y, et al. N Engl J Med 2013;369:1023 1034 4. Douillard JY, et. al. Ann Oncol 2014;25:1346 1355 1.0 2.0

anti-egfr vs anti-vegf

OS estimate OS estimate FIRE-3 study: OS KRAS exon 2 wt population RAS wt population (84%) 1.0 Cetuximab + FOLFIRI (n=297) Bevacizumab + FOLFIRI (n=295) 1.0 Cetuximab + FOLFIRI (n=171) Bevacizumab + FOLFIRI (n=171) 0.75 0.50 0.25 25.0 months 28.7 months HR 0.77 p=0.017 0.7 5 0.5 0 0.2 5 25.6 months 33.1 months HR 0.70 p=0.011 0.0 0 12 24 36 48 60 72 Months 0.0 0 12 24 36 48 60 72 Months 1. Adapted from Heinemann V, et al. Lancet Oncol 2014;15:1065 1075

Proportion event-free (%) Proportion event-free (%) PEAK study: PFS WT KRAS exon 2 WT RAS 100 100 90 80 HR* = 0.84 (95% CI, 0.64 1.11) P = 0.22 90 80 HR* = 0.66 (95% CI, 0.46 0.95) P = 0.03 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 4 8 12 16 20 24 28 32 36 40 Months 0 0 4 8 12 16 20 24 28 32 36 40 Months Events n (%) Median (95% CI) months Events n (%) Median (95% CI) months Panitumumab + mfolfox6 (n = 142) 100 (70) 10.9 (9.7 12.8) Panitumumab + mfolfox6 (n = 88) 57 (65) 13.0 (10.9 15.1) Bevacizumab + mfolfox6 (n = 143) 108 (76) 10.1 (9.0 12.0) Bevacizumab + mfolfox6 (n = 82) 66 (80) 10.1 (9.0 12.7) Schwartzberg L, et al. J Clin Oncol 31, 2013 (suppl; abstr 3631 and poster). *Stratified Cox proportional hazards model; No formal hypothesis testing was planned; WT RAS, WT KRAS & NRAS exons 2/3/4

Proportion alive (%) Proportion alive (%) PEAK study: OS WT KRAS exon 2 WT RAS 100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 10 0 HR* = 0.62 (95% CI, 0.44 0.89) P = 0.009 0 4 8 12 16 20 24 28 32 36 40 Months 44 20 10 0 HR* = 0.63 (95% CI, 0.39 1.02) P = 0.058 0 4 8 12 16 20 24 28 32 36 Months 40 44 Panitumumab + mfolfox6 (n = 142) Bevacizumab + mfolfox6 (n = 143) Events n (%) Median (95% CI) months 52 (37) 34.2 (26.6 NR) 78 (55) 24.3 (21.0 29.2) Schwartzberg L, et al. J Clin Oncol 31, 2013 (suppl; abstr 3631 and poster). Panitumumab + mfolfox6 (n = 88) Bevacizumab + mfolfox6 (n = 82) Events n (%) Median (95% CI) months 30 (34) 41.3 (28.8 41.3) 40 (49) 28.9 (23.9 31.3) *Stratified Cox proportional hazards model; No formal hypothesis testing was planned; WT RAS, WT KRAS & NRAS exons 2/3/4; NR, not reached

Phase III 80405 Trial: PFS Lenz H et al. ESMO, 2014.

Phase III 80405 Trial: OS Lenz H et al. ESMO, 2014.

Summary of results Khattak et al. Clin Colorectal Cancer 2015

ORR with RAS Khattak et al. Clin Colorectal Cancer 2015

PFS with RAS Khattak et al. Clin Colorectal Cancer 2015

OS with RAS Khattak et al. Clin Colorectal Cancer 2015

DETERMINACIÓN RAS: DÓNDE Y CUÁNDO? Se puede OPTIMIZAR mas el Circulating free DNA as biomarker and source for mutation detection in metastatic colorectal cancer. tratamiento Spindler KL con anti-egfr? RAS mutations vary between lesions in synchronous primary colorectal cancer: testing only one lesion is not sufficient to guide anti- EGFR treatment decisions. Oncoscience. 2015 Feb 9;2(2):125-30 Mutational analysis of circulating tumor cells from colorectal cancer patients and correlation with primary tumor tissue. PLoS One. 2015 Apr 22;10(4):e0123902

Además de la selección por RAS Como podemos OPTIMIZAR mas el tratamiento con anti-egfr?

Mut PI3K Pérdida expresión PTEN Amplif MET Amplif HER2 Sobreex HER3 Mut adquiridas Sobreex Ligandos EGFR

Anti-EGFR +

CONCLUSIONES RAS story como el mejor ejemplo de OPTIMIZACIÓN COMO y CUANDO? Otros Biomarcadores Combinación con otros fármacos en pacientes con mutaciones Manejo de Toxicidad cutánea