Algorithm identifies networks of genetic changes across cancers
The algorithm, called Hotnet2, was used to analyze genetic data from 12 different types of cancer assembled as part of the pan-cancer project of The Cancer Genome Atlas (TCGA). The research looked at somatic mutations — those that occur in cells during one’s lifetime — and not genetic variants inherited from parents. The study identified 16 subnetworks of genes — several of which have not previously received much attention for their potential role in cancer — that are mutated with surprising frequency in the 3,281 samples in the dataset. The researchers hope the new findings, published in Nature Genetics, will provide scientists with new leads in the search for somatic mutations that drive cancer…