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

Colaprico, A., Olsen, C., Bailey, M., Odom, G., Terkelsen, T., Silva, T., et al. (2020). Interpreting pathways to discover cancer driver genes with Moonlight. NATURE COMMUNICATIONS, 11(1) [10.1038/s41467-019-13803-0].

Interpreting pathways to discover cancer driver genes with Moonlight

Castiglioni I.;
2020

Abstract

Cancer driver gene alterations influence cancer development, occurring in oncogenes, tumor suppressors, and dual role genes. Discovering dual role cancer genes is difficult because of their elusive context-dependent behavior. We define oncogenic mediators as genes controlling biological processes. With them, we classify cancer driver genes, unveiling their roles in cancer mechanisms. To this end, we present Moonlight, a tool that incorporates multiple -omics data to identify critical cancer driver genes. With Moonlight, we analyze 8000+ tumor samples from 18 cancer types, discovering 3310 oncogenic mediators, 151 having dual roles. By incorporating additional data (amplification, mutation, DNA methylation, chromatin accessibility), we reveal 1000+ cancer driver genes, corroborating known molecular mechanisms. Additionally, we confirm critical cancer driver genes by analysing cell-line datasets. We discover inactivation of tumor suppressors in intron regions and that tissue type and subtype indicate dual role status. These findings help explain tumor heterogeneity and could guide therapeutic decisions.
Articolo in rivista - Articolo scientifico
Computational Biology; DNA Methylation; Genes, Tumor Suppressor; Humans; Mutation; Neoplasms; Oncogenes; Software
English
2020
11
1
69
open
Colaprico, A., Olsen, C., Bailey, M., Odom, G., Terkelsen, T., Silva, T., et al. (2020). Interpreting pathways to discover cancer driver genes with Moonlight. NATURE COMMUNICATIONS, 11(1) [10.1038/s41467-019-13803-0].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/522103
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