Network-Based Analysis to Identify Drivers of Metastatic Prostate Cancer Using GoNetic.

ABSTRACT: Most known driver genes of metastatic prostate cancer are frequently mutated. To dig into the long tail of rarely mutated drivers, we performed network-based driver identification on the Hartwig Medical Foundation metastatic prostate cancer data set (HMF cohort). Hereto, we developed GoNetic, a method based on probabilistic pathfinding, to identify recurrently mutated subnetworks. In contrast to most state-of-the-art network-based methods, GoNetic can leverage sample-specific mutational information and the weights of the underlying prior network. When applied to the HMF cohort, GoNetic successfully recovered known primary and metastatic drivers of prostate cancer that are frequently mutated in the HMF cohort (TP53, RB1, and CTNNB1). In addition, the identified subnetworks contain frequentl

SUBMITTER: de Schaetzen van Brienen L 

PROVIDER: S-EPMC8582433 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature