ArticleHepatology research : the official journal of the Japan Society of Hepatology2019
Weighted gene coexpression network analysis reveals hub genes involved in cholangiocarcinoma progression and prognosis.
Article in Hepatology research : the official journal of the Japan Society of Hepatology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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20 citing papers in PubMed, 26 citations in OpenAlex.
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- A comprehensive transcriptomic landscape of cholangiocarcinoma based on bioinformatics analysis from large cohort of patients.Scientific reports · 2021Article
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- Identification of hub methylated-CpG sites and associated genes in oral squamous cell carcinoma.Cancer medicine · 2020Article
- Identification of potential key genes in gastric cancer using bioinformatics analysis.Biomedical reports · 2020Article
- Weighted Gene Co-expression Network Analysis of Key Biomarkers Associated With Bronchopulmonary Dysplasia.Frontiers in genetics · 2020Article
- Identifying Biomarkers to Predict the Progression and Prognosis of Breast Cancer by Weighted Gene Co-expression Network Analysis.Frontiers in genetics · 2020Article
- Feature selection with the Fisher score followed by the Maximal Clique Centrality algorithm can accurately identify the hub genes of hepatocellular carcinoma.Scientific reports · 2019Article
- Weighted gene coexpression network analysis reveals hub genes involved in cholangiocarcinoma progression and prognosis.Hepatology research : the official journal of the Japan Society of Hepatology · 2019Article
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7 authors at 2 institutions in 1 country.
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Abstract
aimCholangiocarcinoma (CCA) is a highly malignant tumor found in the bile duct epithelial cells, and the second most common primary tumor of the liver. However, the pivotal roles of molecular biomarkers in oncogenesis of CCA are unclear. Therefore, we aim to explore the underlying mechanisms of progression and screen for novel prognostic biomarkers and treatment targets.
methodThe data of mRNA sequencing and clinical information of CCA patients in The Cancer Genome Atlas was analyzed by weighted gene coexpression network analysis (WGCNA). Modules and clinical traits were constructed according to Pearson's correlation analysis, and Gene Ontology and pathway enrichment analysis were applied. Hub genes of these modules were screened by intramodule analysis; Cytoscape with Search Tool for the Retrieval of Interacting Genes was utilized to visualize protein-protein interaction of these modules; hub genes of these modules were validated afterwards. Furthermore, the significance of these genes was confirmed by survival analysis.
resultsGenes MRPS18A, CST1, and SCP2 were identified as candidate genes in the module, which was associated with clinical traits including pathological stage, histological grade, and liver function and which also affected overall survival of CCA patients. Nineteen hub genes were analyzed together and were associated with progression and prognosis of CCA. Survival analyses found that several of the multiple genes could serve as biomarkers to stratify CCA patients into low- and high-risk groups.
conclusionThese candidate genes could be involved in progression of CCA, which could serve as novel prognostic markers and treatment targets. Moreover, most of them were first reported in CCA and deserve further research.
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