A computational approach for the discovery of significant cancer genes by weighted mutation and asymmetric spreading strength in networks

Identifying significantly mutated genes in cancer is essential for understanding the mechanisms of tumor initiation and progression. This task is a key challenge since large-scale genomic studies have reported an endless number of genes mutated at a shallow frequency. Towards uncovering infrequently...

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Autores principales: Cutigi, Jorge Francisco, Evangelista, Adriane Feijo, Reis, Rui Manuel, Simao, Adenilso
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8651746/
https://www.ncbi.nlm.nih.gov/pubmed/34876593
http://dx.doi.org/10.1038/s41598-021-02671-8
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author Cutigi, Jorge Francisco
Evangelista, Adriane Feijo
Reis, Rui Manuel
Simao, Adenilso
author_facet Cutigi, Jorge Francisco
Evangelista, Adriane Feijo
Reis, Rui Manuel
Simao, Adenilso
author_sort Cutigi, Jorge Francisco
collection PubMed
description Identifying significantly mutated genes in cancer is essential for understanding the mechanisms of tumor initiation and progression. This task is a key challenge since large-scale genomic studies have reported an endless number of genes mutated at a shallow frequency. Towards uncovering infrequently mutated genes, gene interaction networks combined with mutation data have been explored. This work proposes Discovering Significant Cancer Genes (DiSCaGe), a computational method for discovering significant genes for cancer. DiSCaGe computes a mutation score for the genes based on the type of mutations they have. The influence received for their neighbors in the network is also considered and obtained through an asymmetric spreading strength applied to a consensus gene network. DiSCaGe produces a ranking of prioritized possible cancer genes. An experimental evaluation with six types of cancer revealed the potential of DiSCaGe for discovering known and possible novel significant cancer genes.
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spelling pubmed-86517462021-12-08 A computational approach for the discovery of significant cancer genes by weighted mutation and asymmetric spreading strength in networks Cutigi, Jorge Francisco Evangelista, Adriane Feijo Reis, Rui Manuel Simao, Adenilso Sci Rep Article Identifying significantly mutated genes in cancer is essential for understanding the mechanisms of tumor initiation and progression. This task is a key challenge since large-scale genomic studies have reported an endless number of genes mutated at a shallow frequency. Towards uncovering infrequently mutated genes, gene interaction networks combined with mutation data have been explored. This work proposes Discovering Significant Cancer Genes (DiSCaGe), a computational method for discovering significant genes for cancer. DiSCaGe computes a mutation score for the genes based on the type of mutations they have. The influence received for their neighbors in the network is also considered and obtained through an asymmetric spreading strength applied to a consensus gene network. DiSCaGe produces a ranking of prioritized possible cancer genes. An experimental evaluation with six types of cancer revealed the potential of DiSCaGe for discovering known and possible novel significant cancer genes. Nature Publishing Group UK 2021-12-07 /pmc/articles/PMC8651746/ /pubmed/34876593 http://dx.doi.org/10.1038/s41598-021-02671-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Cutigi, Jorge Francisco
Evangelista, Adriane Feijo
Reis, Rui Manuel
Simao, Adenilso
A computational approach for the discovery of significant cancer genes by weighted mutation and asymmetric spreading strength in networks
title A computational approach for the discovery of significant cancer genes by weighted mutation and asymmetric spreading strength in networks
title_full A computational approach for the discovery of significant cancer genes by weighted mutation and asymmetric spreading strength in networks
title_fullStr A computational approach for the discovery of significant cancer genes by weighted mutation and asymmetric spreading strength in networks
title_full_unstemmed A computational approach for the discovery of significant cancer genes by weighted mutation and asymmetric spreading strength in networks
title_short A computational approach for the discovery of significant cancer genes by weighted mutation and asymmetric spreading strength in networks
title_sort computational approach for the discovery of significant cancer genes by weighted mutation and asymmetric spreading strength in networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8651746/
https://www.ncbi.nlm.nih.gov/pubmed/34876593
http://dx.doi.org/10.1038/s41598-021-02671-8
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