Data Science Insitute
Center for Computational Molecular Biology

Algorithm Identifies Networks of Genetic Changes Across Cancers

Cancers often involve far more than a genetic mutation acting alone. Multiple mutations, many of which are rare, may occur in different networks of multiple genes. HotNet2 is a powerful algorithm that analyzes genes at the network level and can help cancer researchers search for genetic associations and likely sources of disease across almost unimaginable genetic complexities.

Using a computer algorithm that can sift through mounds of genetic data, researchers from Brown University have identified several networks of genes that, when hit by a mutation, could play a role in the development of multiple types of cancer.

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.

Read the full article