Interpreting pathways to discover cancer driver genes with Moonlight

Antonio Colaprico (), Catharina Olsen, Matthew H. Bailey, Gabriel J. Odom, Thilde Terkelsen, Tiago C. Silva, André V. Olsen, Laura Cantini, Andrei Zinovyev, Emmanuel Barillot, Houtan Noushmehr, Gloria Bertoli, Isabella Castiglioni, Claudia Cava, Gianluca Bontempi, Xi Steven Chen () and Elena Papaleo ()
Additional contact information
Antonio Colaprico: Interuniversity Institute of Bioinformatics in Brussels (IB)2
Catharina Olsen: Interuniversity Institute of Bioinformatics in Brussels (IB)2
Matthew H. Bailey: Washington University in St. Louis
Gabriel J. Odom: University of Miami, Miller School of Medicine
Thilde Terkelsen: Computational Biology Laboratory, and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center
Tiago C. Silva: University of Miami, Miller School of Medicine
André V. Olsen: Computational Biology Laboratory, and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center
Laura Cantini: Institut Curie
Andrei Zinovyev: Institut Curie
Emmanuel Barillot: Institut Curie
Houtan Noushmehr: University of Sao Paulo
Gloria Bertoli: Institute of Molecular Bioimaging and Physiology of the National Research Council (IBFM-CNR)
Isabella Castiglioni: Institute of Molecular Bioimaging and Physiology of the National Research Council (IBFM-CNR)
Claudia Cava: Institute of Molecular Bioimaging and Physiology of the National Research Council (IBFM-CNR)
Gianluca Bontempi: Interuniversity Institute of Bioinformatics in Brussels (IB)2
Xi Steven Chen: University of Miami, Miller School of Medicine
Elena Papaleo: Computational Biology Laboratory, and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center

Nature Communications, 2020, vol. 11, issue 1, 1-17

Abstract: 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.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.nature.com/articles/s41467-019-13803-0 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-019-13803-0

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-019-13803-0

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().