4.3 Article

Gene expression profile predictive of response to chemotherapy in metastatic colorectal cancer

Journal

ONCOTARGET
Volume 6, Issue 8, Pages 6151-6159

Publisher

IMPACT JOURNALS LLC
DOI: 10.18632/oncotarget.3152

Keywords

Colorectal cancer; chemotherapy; gene expression; predictive; microarray

Funding

  1. Fundacion Mutua Madrilena (FMM) [P0497/2006]
  2. Fondo de Investigacion Sanitaria/Instituto de Salud Carlos III Spanish Cancer Networks RTICC [R12/0036/0008, R12/0036/0028]
  3. Fondo de Investigacion Sanitaria [PI10/02164, PI13/02295, CD1100153, CD0900148]
  4. Servicio Andaluz de Salud [PI-0259/2007]
  5. RTICC [R12/0036/0028]
  6. Rio Hortega grant from the Instituto de Salud Carlos III (ISCiii) [09/00207]
  7. Ministerio de Sanidad, Spain
  8. Consejeria de Salud of the Junta de Andalucia [PI-0135-2010, CTS-6844, PI-0142]
  9. Fundacion Cientifica de la Asociacion Espanola Contra el Cancer
  10. ISCiii [PI081156, PI1102688, RTICC R12/0036/0008]
  11. Consejeria de Innovacion, Ciencia y Empresa - Junta de Andalucia [P08-CVI-04090]
  12. 75th Anniversary Roche Spain Fellowship
  13. Spanish Ministry of Science and Innovation [SAF2009-08605]
  14. FIS [PI12/00137]
  15. Consejeria de Ciencia e Innovacion
  16. Consejeria de Salud of the Junta de Andalucia
  17. Fundacion Oncologica FERO - Fundacion Josep Botet

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Fluoropyrimidine-based chemotherapy (CT) has been the mainstay of care of metastatic colorectal cancer (mCRC) for years. Response rates are only observed, however, in about half of treated patients, and there are no reliable tools to prospectively identify patients more likely to benefit from therapy. The purpose of our study was to identify a gene expression profile predictive of CT response in mCRC. Whole genome expression analyses (Affymetrix GeneChip r HG-U133 Plus 2.0) were performed in fresh frozen tumor samples of 37 mCRC patients (training cohort). Differential gene expression profiles among the two study conditions (responders versus non-responders) were assessed using supervised class prediction algorithms. A set of 161 differentially expressed genes in responders (23 patients; 62%) versus non-responders (14 patients; 38%) was selected for further assessment and validation by RT-qPCR (TaqMan (R) Low Density Arrays (TLDA) 7900 HT Micro Fluidic Cards) in an independent multi-institutional cohort (53 mCRC patients). Seven of these genes were confirmed as significant predictors of response. Patients with a favorable predictive signature had significantly greater response rate (58% vs 13%, p = 0.024), progression-free survival (61% vs 13% at 1 year, HR = 0.32, p = 0.009) and overall survival (32 vs 16 months, HR = 0.21, p = 0.003) than patients with an unfavorable gene signature. This is the first study to validate a gene-expression profile predictive of response to CT in mCRC patients. Larger and prospective confirmatory studies are required, however, in order to successfully provide oncologists with adequate tools to optimize treatment selection in routine clinical practice.

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