Computing microRNA-gene interaction networks in pan-cancer using miRDriver.
Ontology highlight
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 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
SUBMITTER: Bose B
PROVIDER: S-EPMC8904490 | biostudies-literature | 2022 Mar
REPOSITORIES: biostudies-literature
ACCESS DATA