Computing microRNA-gene interaction networks in pan-cancer using miRDriver

Computing microRNA-gene interaction networks in pan-cancer using miRDriver

Blog Article

Abstract DNA copy number aberrated regions in cancer are known to harbor cancer driver genes and the short non-coding RNA molecules, i.e., microRNAs.

In this study, we integrated the multi-omics datasets such as copy number aberration, DNA methylation, gene and microRNA expression to identify the revlon colorstay lip liner plum signature microRNA-gene associations from frequently aberrated DNA regions across pan-cancer utilizing a LASSO-based regression approach.We studied 7294 patient samples associated with eighteen different cancer types from The Cancer Genome Atlas (TCGA) database and identified several cancer-specific and common microRNA-gene interactions enriched in experimentally validated microRNA-target interactions.We highlighted several oncogenic and tumor suppressor microRNAs that were cancer-specific and common in several cancer types.

Our method substantially outperformed the five state-of-art methods in selecting significantly known microRNA-gene interactions in multiple cancer bempresas.com types.Several microRNAs and genes were found to be associated with tumor survival and progression.Selected target genes were found to be significantly enriched in cancer-related pathways, cancer hallmark and Gene Ontology (GO) terms.

Furthermore, subtype-specific potential gene signatures were discovered in multiple cancer types.