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Evaluating Patient-Derived Colorectal Cancer Xenografts as Preclinical Models by Comparison with Patient Clinical Data

15 avr. 2015Cancer Research

DOI : 10.1158/0008-5472.can-14-1590

Auteurs

Manoel Nunes, Patricia Vrignaud, Sophie Vacher, Sophie Richon, Astrid Lièvre, Wulfran Cacheux, Louis-Bastien Weiswald, Gerald Massonnet, Sophie Chateau-Joubert, André Nicolas, Colette Dib, Weidong Zhang, James Watters, Donald Bergstrom, Sergio Roman-Roman, Ivan Bièche, Virginie Dangles-Marie

Résumé

Abstract

Development of targeted therapeutics required translationally relevant preclinical models with well-characterized cancer genome alterations. Here, by studying 52 colorectal patient-derived tumor xenografts (PDX), we examined key molecular alterations of the IGF2–PI3K and ERBB–RAS pathways and response to cetuximab. PDX molecular data were compared with that published for patient colorectal tumors in The Cancer Genome Atlas. We demonstrated a significant pattern of mutual exclusivity of genomic abnormalities in the IGF2–PI3K and ERBB–RAS pathways. The genomic anomaly frequencies observed in microsatellite stable PDX reproduce those detected in nonhypermutated patient tumors. We found frequent IGF2 upregulation (16%), which was mutually exclusive with IRS2, PIK3CA, PTEN, and INPP4B alterations, supporting IGF2 as a potential drug target. In addition to maintaining the genomic and histologic diversity, correct preclinical models need to reproduce drug response observed in patients. Responses of PDXs to cetuximab recapitulate also clinical data in patients, with partial or complete response in 15% (8 of 52) of PDXs and response strictly restricted to KRAS wild-type models. The response rate reaches 53% (8 of 15) when KRAS, BRAF, and NRAS mutations are concomitantly excluded, proving a functional cross-validation of predictive biomarkers obtained retrospectively in patients. Collectively, these results show that, because of their clinical relevance, colorectal PDXs are appropriate tools to identify both new targets, like IGF2, and predictive biomarkers of response/resistance to targeted therapies. Cancer Res; 75(8); 1560–6. ©2015 AACR.