Cancer-mutation network and the number and specificity of driver mutations
A partir de données génomiques portant sur 7 665 tumeurs (30 types de cancer) et 198 gènes associés au cancer, cette étude met en oeuvre des méthodes mathématiques développées pour l'analyse de réseau et évalue le nombre moyen de gènes mutés par module statistique issu de cette analyse
Cancer genomics yields a wealth of information on cancer-associated mutations in various cancer types, but current understanding of the number and tissue specificity of the driver mutations remains limited. We applied mathematical methods for network analysis to identify distinct modules linking tumors to driver mutations. About 27% of the tumors belong to such modules, whereas the rest form a diffuse component of the gene–tumor network. The cancers from the diffuse component show an onset later in life than those in the modules and have fewer associated known drivers, implying the existence of multiple unidentified and/or interchangeable drivers in the former. Cancer genomics has produced extensive information on cancer-associated genes, but the number and specificity of cancer-driver mutations remains a matter of debate. We constructed a bipartite network in which 7,665 tumors from 30 cancer types are connected via shared mutations in 198 previously identified cancer genes. We show that about 27% of the tumors can be assigned to statistically supported modules, most of which encompass one or two cancer types. The rest of the tumors belong to a diffuse network component suggesting lower gene specificity of driver mutations. Linear regression of the mutational loads in cancer genes was used to estimate the number of drivers required for the onset of different cancers. The mean number of drivers in known cancer genes is approximately two, with a range of one to five. Cancers that are associated with modules had more drivers than those from the diffuse network component, suggesting that unidentified and/or interchangeable drivers exist in the latter.