Systematic identification of mutations and copy number alterations associated with cancer patient prognosis
Menée à partir de l'analyse des profils génomiques de 17 879 tumeurs et à partir de données cliniques, cette étude met en évidence l'intérêt de rechercher des anomalies du nombre de copies de gènes "conducteurs", plutôt que des mutations, pour améliorer la stratification des patients, établir un pronostic et définir une stratégie thérapeutique
Successful treatment decisions in cancer depend on the accurate assessment of patient risk. To improve our understanding of the molecular alterations that underlie deadly malignancies, we analyzed the genomic profiles of 17,879 tumors from patients with known outcomes. We find that mutations in almost all cancer driver genes contain remarkably little information on patient prognosis. However, CNAs in these same driver genes harbor significant prognostic power. Focal CNAs are associated with worse outcomes than broad alterations, and CNAs in many driver genes remain prognostic when controlling for stage, grade, TP53 status, and total aneuploidy. By performing a meta-analysis across independent patient cohorts, we identify robust prognostic biomarkers in specific cancer types, and we demonstrate that a subset of these alterations also confer specific therapeutic vulnerabilities. In total, our analysis establishes a comprehensive resource for cancer biomarker identification and underscores the importance of gene copy number profiling in assessing clinical risk.
eLife , article en libre accès, 2018