Cancer Driver Gene Detection using Deep Convolutional Neural Networks on H3K4me3 Enrichment Profiles

Abstract: In spite of our current knowledge regarding the biology underlying cancer genesis, reliable methods for the discovery of cancer driver (CD) genes are still in great need. The rather recent incorporation of epigenetic markers to the cancer paradigm has nevertheless opened the door for the development of new computational approaches to the problem. This work is aimed to study the enrichment of certain genome regions with the histone post-translational modification (PTM) H3K4me3. This epigenetic marker can be used to distinguish cancer driver genes from neutral genes (NGs). To this end, a convolutional neural network (CNN) comparing H3K4me3 enrichment profiles for matching healthy and cancer samples is proposed and evaluated. The obtained results for OriGENE, the presented model, show promise in pan-cancer but also tissue-specific cancer driver gene detection.