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Discovery of co-occurring driver pathways in cancer
BACKGROUND: It has been widely realized that pathways rather than individual genes govern the course of carcinogenesis. Therefore, discovering driver pathways is becoming an important step to understand the molecular mechanisms underlying cancer and design efficient treatments for cancer patients. P...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4133618/ https://www.ncbi.nlm.nih.gov/pubmed/25106096 http://dx.doi.org/10.1186/1471-2105-15-271 |
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author | Zhang, Junhua Wu, Ling-Yun Zhang, Xiang-Sun Zhang, Shihua |
author_facet | Zhang, Junhua Wu, Ling-Yun Zhang, Xiang-Sun Zhang, Shihua |
author_sort | Zhang, Junhua |
collection | PubMed |
description | BACKGROUND: It has been widely realized that pathways rather than individual genes govern the course of carcinogenesis. Therefore, discovering driver pathways is becoming an important step to understand the molecular mechanisms underlying cancer and design efficient treatments for cancer patients. Previous studies have focused mainly on observation of the alterations in cancer genomes at the individual gene or single pathway level. However, a great deal of evidence has indicated that multiple pathways often function cooperatively in carcinogenesis and other key biological processes. RESULTS: In this study, an exact mathematical programming method was proposed to de novo identify co-occurring mutated driver pathways (CoMDP) in carcinogenesis without any prior information beyond mutation profiles. Two possible properties of mutations that occurred in cooperative pathways were exploited to achieve this: (1) each individual pathway has high coverage and high exclusivity; and (2) the mutations between the pair of pathways showed statistically significant co-occurrence. The efficiency of CoMDP was validated first by testing on simulated data and comparing it with a previous method. Then CoMDP was applied to several real biological data including glioblastoma, lung adenocarcinoma, and ovarian carcinoma datasets. The discovered co-occurring driver pathways were here found to be involved in several key biological processes, such as cell survival and protein synthesis. Moreover, CoMDP was modified to (1) identify an extra pathway co-occurring with a known pathway and (2) detect multiple significant co-occurring driver pathways for carcinogenesis. CONCLUSIONS: The present method can be used to identify gene sets with more biological relevance than the ones currently used for the discovery of single driver pathways. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2105-15-271) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4133618 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41336182014-08-16 Discovery of co-occurring driver pathways in cancer Zhang, Junhua Wu, Ling-Yun Zhang, Xiang-Sun Zhang, Shihua BMC Bioinformatics Methodology Article BACKGROUND: It has been widely realized that pathways rather than individual genes govern the course of carcinogenesis. Therefore, discovering driver pathways is becoming an important step to understand the molecular mechanisms underlying cancer and design efficient treatments for cancer patients. Previous studies have focused mainly on observation of the alterations in cancer genomes at the individual gene or single pathway level. However, a great deal of evidence has indicated that multiple pathways often function cooperatively in carcinogenesis and other key biological processes. RESULTS: In this study, an exact mathematical programming method was proposed to de novo identify co-occurring mutated driver pathways (CoMDP) in carcinogenesis without any prior information beyond mutation profiles. Two possible properties of mutations that occurred in cooperative pathways were exploited to achieve this: (1) each individual pathway has high coverage and high exclusivity; and (2) the mutations between the pair of pathways showed statistically significant co-occurrence. The efficiency of CoMDP was validated first by testing on simulated data and comparing it with a previous method. Then CoMDP was applied to several real biological data including glioblastoma, lung adenocarcinoma, and ovarian carcinoma datasets. The discovered co-occurring driver pathways were here found to be involved in several key biological processes, such as cell survival and protein synthesis. Moreover, CoMDP was modified to (1) identify an extra pathway co-occurring with a known pathway and (2) detect multiple significant co-occurring driver pathways for carcinogenesis. CONCLUSIONS: The present method can be used to identify gene sets with more biological relevance than the ones currently used for the discovery of single driver pathways. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2105-15-271) contains supplementary material, which is available to authorized users. BioMed Central 2014-08-09 /pmc/articles/PMC4133618/ /pubmed/25106096 http://dx.doi.org/10.1186/1471-2105-15-271 Text en © Zhang et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Article Zhang, Junhua Wu, Ling-Yun Zhang, Xiang-Sun Zhang, Shihua Discovery of co-occurring driver pathways in cancer |
title | Discovery of co-occurring driver pathways in cancer |
title_full | Discovery of co-occurring driver pathways in cancer |
title_fullStr | Discovery of co-occurring driver pathways in cancer |
title_full_unstemmed | Discovery of co-occurring driver pathways in cancer |
title_short | Discovery of co-occurring driver pathways in cancer |
title_sort | discovery of co-occurring driver pathways in cancer |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4133618/ https://www.ncbi.nlm.nih.gov/pubmed/25106096 http://dx.doi.org/10.1186/1471-2105-15-271 |
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