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Identifying Cancer Specific Driver Modules Using a Network-Based Method
Detecting driver modules is a key challenge for understanding the mechanisms of carcinogenesis at the pathway level. Identifying cancer specific driver modules is helpful for interpreting the different principles of different cancer types. However, most methods are proposed to identify driver module...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6100049/ https://www.ncbi.nlm.nih.gov/pubmed/29738475 http://dx.doi.org/10.3390/molecules23051114 |
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author | Li, Feng Gao, Lin Wang, Peizhuo Hu, Yuxuan |
author_facet | Li, Feng Gao, Lin Wang, Peizhuo Hu, Yuxuan |
author_sort | Li, Feng |
collection | PubMed |
description | Detecting driver modules is a key challenge for understanding the mechanisms of carcinogenesis at the pathway level. Identifying cancer specific driver modules is helpful for interpreting the different principles of different cancer types. However, most methods are proposed to identify driver modules in one cancer, but few methods are introduced to detect cancer specific driver modules. We propose a network-based method to detect cancer specific driver modules (CSDM) in a certain cancer type to other cancer types. We construct the specific network of a cancer by combining specific coverage and mutual exclusivity in all cancer types, to catch the specificity of the cancer at the pathway level. To illustrate the performance of the method, we apply CSDM on 12 TCGA cancer types. When we compare CSDM with SpeMDP and HotNet2 with regard to specific coverage and the enrichment of GO terms and KEGG pathways, CSDM is more accurate. We find that the specific driver modules of two different cancers have little overlap, which indicates that the driver modules detected by CSDM are specific. Finally, we also analyze three specific driver modules of BRCA, BLCA, and LAML intersecting with well-known pathways. The source code of CSDM is freely accessible at https://github.com/fengli28/CSDM.git. |
format | Online Article Text |
id | pubmed-6100049 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61000492018-11-13 Identifying Cancer Specific Driver Modules Using a Network-Based Method Li, Feng Gao, Lin Wang, Peizhuo Hu, Yuxuan Molecules Article Detecting driver modules is a key challenge for understanding the mechanisms of carcinogenesis at the pathway level. Identifying cancer specific driver modules is helpful for interpreting the different principles of different cancer types. However, most methods are proposed to identify driver modules in one cancer, but few methods are introduced to detect cancer specific driver modules. We propose a network-based method to detect cancer specific driver modules (CSDM) in a certain cancer type to other cancer types. We construct the specific network of a cancer by combining specific coverage and mutual exclusivity in all cancer types, to catch the specificity of the cancer at the pathway level. To illustrate the performance of the method, we apply CSDM on 12 TCGA cancer types. When we compare CSDM with SpeMDP and HotNet2 with regard to specific coverage and the enrichment of GO terms and KEGG pathways, CSDM is more accurate. We find that the specific driver modules of two different cancers have little overlap, which indicates that the driver modules detected by CSDM are specific. Finally, we also analyze three specific driver modules of BRCA, BLCA, and LAML intersecting with well-known pathways. The source code of CSDM is freely accessible at https://github.com/fengli28/CSDM.git. MDPI 2018-05-08 /pmc/articles/PMC6100049/ /pubmed/29738475 http://dx.doi.org/10.3390/molecules23051114 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Feng Gao, Lin Wang, Peizhuo Hu, Yuxuan Identifying Cancer Specific Driver Modules Using a Network-Based Method |
title | Identifying Cancer Specific Driver Modules Using a Network-Based Method |
title_full | Identifying Cancer Specific Driver Modules Using a Network-Based Method |
title_fullStr | Identifying Cancer Specific Driver Modules Using a Network-Based Method |
title_full_unstemmed | Identifying Cancer Specific Driver Modules Using a Network-Based Method |
title_short | Identifying Cancer Specific Driver Modules Using a Network-Based Method |
title_sort | identifying cancer specific driver modules using a network-based method |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6100049/ https://www.ncbi.nlm.nih.gov/pubmed/29738475 http://dx.doi.org/10.3390/molecules23051114 |
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