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Associating transcriptional modules with colon cancer survival through weighted gene co-expression network analysis

BACKGROUND: Colon cancer (CC) is a heterogeneous disease influenced by complex gene networks. As such, the relationship between networks and CC should be elucidated to obtain further insights into tumour biology. RESULTS: Weighted gene co-expression network analysis, a powerful technique used to ext...

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Autores principales: Liu, Rong, Zhang, Wei, Liu, Zhao-Qian, Zhou, Hong-Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5424422/
https://www.ncbi.nlm.nih.gov/pubmed/28486948
http://dx.doi.org/10.1186/s12864-017-3761-z
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author Liu, Rong
Zhang, Wei
Liu, Zhao-Qian
Zhou, Hong-Hao
author_facet Liu, Rong
Zhang, Wei
Liu, Zhao-Qian
Zhou, Hong-Hao
author_sort Liu, Rong
collection PubMed
description BACKGROUND: Colon cancer (CC) is a heterogeneous disease influenced by complex gene networks. As such, the relationship between networks and CC should be elucidated to obtain further insights into tumour biology. RESULTS: Weighted gene co-expression network analysis, a powerful technique used to extract co-expressed gene networks from mRNA expressions, was conducted to identify 11 co-regulated modules in a discovery dataset with 461 patients. A transcriptional module enriched in cell cycle processes was correlated with the recurrence-free survival of the CC patients in the discovery (HR = 0.59; 95% CI = 0.42–0.81) and validation (HR = 0.51; 95% CI = 0.25–1.05) datasets. The prognostic potential of the hub gene Centromere Protein-A (CENPA) was also identified and the upregulation of this gene was associated with good survival. Another cell cycle phase-related gene module was correlated with the survival of the patients with a KRAS mutation CC subtype. The downregulation of several genes, including those found in this co-expression module, such as cyclin-dependent kinase 1 (CDK1), was associated with poor survival. CONCLUSION: Network-based approaches may facilitate the discovery of biomarkers for the prognosis of a subset of patients with stage II or III CC, these approaches may also help direct personalised therapies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3761-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-54244222017-05-11 Associating transcriptional modules with colon cancer survival through weighted gene co-expression network analysis Liu, Rong Zhang, Wei Liu, Zhao-Qian Zhou, Hong-Hao BMC Genomics Research Article BACKGROUND: Colon cancer (CC) is a heterogeneous disease influenced by complex gene networks. As such, the relationship between networks and CC should be elucidated to obtain further insights into tumour biology. RESULTS: Weighted gene co-expression network analysis, a powerful technique used to extract co-expressed gene networks from mRNA expressions, was conducted to identify 11 co-regulated modules in a discovery dataset with 461 patients. A transcriptional module enriched in cell cycle processes was correlated with the recurrence-free survival of the CC patients in the discovery (HR = 0.59; 95% CI = 0.42–0.81) and validation (HR = 0.51; 95% CI = 0.25–1.05) datasets. The prognostic potential of the hub gene Centromere Protein-A (CENPA) was also identified and the upregulation of this gene was associated with good survival. Another cell cycle phase-related gene module was correlated with the survival of the patients with a KRAS mutation CC subtype. The downregulation of several genes, including those found in this co-expression module, such as cyclin-dependent kinase 1 (CDK1), was associated with poor survival. CONCLUSION: Network-based approaches may facilitate the discovery of biomarkers for the prognosis of a subset of patients with stage II or III CC, these approaches may also help direct personalised therapies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3761-z) contains supplementary material, which is available to authorized users. BioMed Central 2017-05-09 /pmc/articles/PMC5424422/ /pubmed/28486948 http://dx.doi.org/10.1186/s12864-017-3761-z Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 Research Article
Liu, Rong
Zhang, Wei
Liu, Zhao-Qian
Zhou, Hong-Hao
Associating transcriptional modules with colon cancer survival through weighted gene co-expression network analysis
title Associating transcriptional modules with colon cancer survival through weighted gene co-expression network analysis
title_full Associating transcriptional modules with colon cancer survival through weighted gene co-expression network analysis
title_fullStr Associating transcriptional modules with colon cancer survival through weighted gene co-expression network analysis
title_full_unstemmed Associating transcriptional modules with colon cancer survival through weighted gene co-expression network analysis
title_short Associating transcriptional modules with colon cancer survival through weighted gene co-expression network analysis
title_sort associating transcriptional modules with colon cancer survival through weighted gene co-expression network analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5424422/
https://www.ncbi.nlm.nih.gov/pubmed/28486948
http://dx.doi.org/10.1186/s12864-017-3761-z
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