Interpreting pathways to discover cancer driver genes with Moonlight

• DOI: 10.7490/f1000research.1118074.1
• Publication Date: 2020-07-21
• Authors: Antonio Colaprico; Catharina Olsen; Matthew H. Bailey; Gabriel Odom; Thilde Terkelsen; Tiago C. Silva; André Vidas Olsen; Laura Cantini; Andreï Zinovyev; Emmanuel Barillot; Houtan Noushmehr; Gloria Bertoli; Isabella Castiglioni; Claudia Cava; Gianluca Bontempi; Xi Steven Chen; Elena Papaleo
• Keywords: Moonlight

Cancer driver gene alterations influence cancer development, occurring in oncogenes, tumor suppressors, and dual role genes. Discovering genes is difficult because of their elusive context-dependent behavior. We define oncogenic mediators as controlling biological processes. With them, we classify genes, unveiling roles mechanisms. To this end, present Moonlight, a tool that incorporates multiple -omics data to identify critical analyze 8000+ tumor samples from 18 types, discovering 3310 mediators, 151 having roles. By incorporating additional (amplification, mutation, DNA methylation, chromatin accessibility), reveal 1000+ cancer corroborating known molecular Additionally, confirm by analysing cell-line datasets. discover inactivation suppressors intron regions tissue type subtype indicate status. These findings help explain heterogeneity could guide therapeutic decisions. Identification especially those can act tumour or oncogenes depending on context, remains challenge. Here, the authors introduce integrates multi-omic address challenge numerous dual-role