Passenger Mutations in More Than 2,500 Cancer Genomes: Overall Molecular Functional Impact and Consequences

Menée à partir de données génomiques du projet "ICGC/TCGA Pan-Cancer Analysis of Whole Genomes" portant sur 2 500 tumeurs, cette étude analyse les caractéristiques des mutations passagères ainsi que leurs effets sur la tumorigenèse et la progression tumorale

Résumé en anglais

The dichotomous model of ?drivers? and ?passengers? in cancer posits that only a few mutations in a tumor strongly affect its progression, with the remaining ones being inconsequential. Here, we leveraged the comprehensive variant dataset from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) project to demonstrate that?in addition to the dichotomy of high- and low-impact variants?there is a third group of medium-impact putative passengers. Moreover, we also found that molecular impact correlates with subclonal architecture (i.e., early versus late mutations), and different signatures encode for mutations with divergent impact. Furthermore, we adapted an additive-effects model from complex-trait studies to show that the aggregated effect of putative passengers, including undetected weak drivers, provides significant additional power (?12% additive variance) for predicting cancerous phenotypes, beyond PCAWG-identified driver mutations. Finally, this framework allowed us to estimate the frequency of potential weak-driver mutations in PCAWG samples lacking any well-characterized driver alterations.