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Weighted gene coexpression network analysis reveals hub genes involved in cholangiocarcinoma progression and prognosis
Author(s) -
Tian Aiping,
Pu Ke,
Li Boxuan,
Li Min,
Liu Xiaoguang,
Gao Liping,
Mao Xiaorong
Publication year - 2019
Publication title -
hepatology research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.123
H-Index - 75
eISSN - 1872-034X
pISSN - 1386-6346
DOI - 10.1111/hepr.13386
Subject(s) - gene , biology , candidate gene , carcinogenesis , tumor progression , survival analysis , gene ontology , computational biology , bioinformatics , medicine , genetics , gene expression
Aim Cholangiocarcinoma (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. Method The 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. Results Genes 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. Conclusion These 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.