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Identification of key genes and pathways associated with cholangiocarcinoma development based on weighted gene correlation network analysis
BACKGROUND: As the most frequently occurred tumor in biliary tract, cholangiocarcinoma (CCA) is mainly characterized by its late diagnosis and poor outcome. It is therefore urgent to identify specific genes and pathways associated with its progression and prognosis. MATERIALS AND METHODS: The differ...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6825751/ https://www.ncbi.nlm.nih.gov/pubmed/31687280 http://dx.doi.org/10.7717/peerj.7968 |
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author | Liu, Jingwei Liu, Weixin Li, Hao Deng, Qiuping Yang, Meiqi Li, Xuemei Liang, Zeng |
author_facet | Liu, Jingwei Liu, Weixin Li, Hao Deng, Qiuping Yang, Meiqi Li, Xuemei Liang, Zeng |
author_sort | Liu, Jingwei |
collection | PubMed |
description | BACKGROUND: As the most frequently occurred tumor in biliary tract, cholangiocarcinoma (CCA) is mainly characterized by its late diagnosis and poor outcome. It is therefore urgent to identify specific genes and pathways associated with its progression and prognosis. MATERIALS AND METHODS: The differentially expressed genes in The Cancer Genome Atlas were analyzed to build the co-expression network by Weighted gene co-expression network analysis (WGCNA). Gene ontology (GO) as well as Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted for the selected genes. Module–clinical trait relationships were analyzed to explore the association with clinicopathological parameters. Log-rank tests and cox regression were used to identify the prognosis-related genes. RESULTS: The most related modules with CCA development were tan module containing 181 genes and salmon module with 148 genes. GO analysis suggested enrichment terms of digestion, hormone transport and secretion, epithelial cell proliferation, signal release, fibroblast activation, response to acid chemical, wnt, Nicotinamide adenine dinucleotide phosphate metabolism. KEGG analysis demonstrated 15 significantly altered pathways including glutathione metabolism, wnt, central carbon metabolism, mTOR, pancreatic secretion, protein digestion, axon guidance, retinol metabolism, insulin secretion, salivary secretion, fat digestion. Key genes of SOX2, KIT, PRSS56, WNT9A, SLC4A4, PRRG4, PANX2, PIR, RASSF8, MFSD4A, INS, RNF39, IL1R2, CST1, and PPP3CA might be potential prognostic markers for CCA, of which RNF39 and PRSS56 also showed significant correlation with clinical stage. DISCUSSION: Differentially expressed genes and key modules contributing to CCA development were identified by WGCNA. Our results offer novel insights into the characteristics in the etiology, prognosis, and treatment of CCA. |
format | Online Article Text |
id | pubmed-6825751 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68257512019-11-04 Identification of key genes and pathways associated with cholangiocarcinoma development based on weighted gene correlation network analysis Liu, Jingwei Liu, Weixin Li, Hao Deng, Qiuping Yang, Meiqi Li, Xuemei Liang, Zeng PeerJ Bioinformatics BACKGROUND: As the most frequently occurred tumor in biliary tract, cholangiocarcinoma (CCA) is mainly characterized by its late diagnosis and poor outcome. It is therefore urgent to identify specific genes and pathways associated with its progression and prognosis. MATERIALS AND METHODS: The differentially expressed genes in The Cancer Genome Atlas were analyzed to build the co-expression network by Weighted gene co-expression network analysis (WGCNA). Gene ontology (GO) as well as Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted for the selected genes. Module–clinical trait relationships were analyzed to explore the association with clinicopathological parameters. Log-rank tests and cox regression were used to identify the prognosis-related genes. RESULTS: The most related modules with CCA development were tan module containing 181 genes and salmon module with 148 genes. GO analysis suggested enrichment terms of digestion, hormone transport and secretion, epithelial cell proliferation, signal release, fibroblast activation, response to acid chemical, wnt, Nicotinamide adenine dinucleotide phosphate metabolism. KEGG analysis demonstrated 15 significantly altered pathways including glutathione metabolism, wnt, central carbon metabolism, mTOR, pancreatic secretion, protein digestion, axon guidance, retinol metabolism, insulin secretion, salivary secretion, fat digestion. Key genes of SOX2, KIT, PRSS56, WNT9A, SLC4A4, PRRG4, PANX2, PIR, RASSF8, MFSD4A, INS, RNF39, IL1R2, CST1, and PPP3CA might be potential prognostic markers for CCA, of which RNF39 and PRSS56 also showed significant correlation with clinical stage. DISCUSSION: Differentially expressed genes and key modules contributing to CCA development were identified by WGCNA. Our results offer novel insights into the characteristics in the etiology, prognosis, and treatment of CCA. PeerJ Inc. 2019-10-31 /pmc/articles/PMC6825751/ /pubmed/31687280 http://dx.doi.org/10.7717/peerj.7968 Text en © 2019 Liu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Liu, Jingwei Liu, Weixin Li, Hao Deng, Qiuping Yang, Meiqi Li, Xuemei Liang, Zeng Identification of key genes and pathways associated with cholangiocarcinoma development based on weighted gene correlation network analysis |
title | Identification of key genes and pathways associated with cholangiocarcinoma development based on weighted gene correlation network analysis |
title_full | Identification of key genes and pathways associated with cholangiocarcinoma development based on weighted gene correlation network analysis |
title_fullStr | Identification of key genes and pathways associated with cholangiocarcinoma development based on weighted gene correlation network analysis |
title_full_unstemmed | Identification of key genes and pathways associated with cholangiocarcinoma development based on weighted gene correlation network analysis |
title_short | Identification of key genes and pathways associated with cholangiocarcinoma development based on weighted gene correlation network analysis |
title_sort | identification of key genes and pathways associated with cholangiocarcinoma development based on weighted gene correlation network analysis |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6825751/ https://www.ncbi.nlm.nih.gov/pubmed/31687280 http://dx.doi.org/10.7717/peerj.7968 |
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