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Cholangiocarcinoma?associated genes identified by integrative analysis of gene expression data.

ABSTRACT: Cholangiocarcinoma (CCA) is characterized by delayed diagnosis and poor survival rate. Research efforts have focused on novel diagnostic technologies for this type of cancer. Transcriptomic microarray technology is a useful research strategy for investigating the molecular properties of CCA. The objective of the present study was to identify candidate biomarkers with high potential for clinical application in CCA using a meta?analysis?based approach. Gene expression profiles of CCA were downloaded from the Gene Expression Omnibus database for integrated analysis. All differentially expressed genes (DEGs) were analyzed by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Protein?protein interaction (PPI) networks were further constructed, hub proteins were identified and functional modules were extracted. Following integrated analysis of the seven eligible datasets (428 cases and 46 controls), a set of 1,080 DEGs was identified, including 710 upregulated and 370 downregulated genes. Functional enrichment analysis demonstrated that 'chromosome organization' was a significantly enriched GO term in the biological process category. 'DNA replication', 'influenza A', and 'lysosome' were the top three significantly enriched KEGG pathways. Furthermore, PPI network analysis indicated that the significant hub proteins were histone deacetylase 1, cullin?associated NEDD8?dissociated protein 1, ubiquitin D, early growth response protein 1 and glycogen synthase kinase 3?. The majority of these proteins are involved in CCA. These results provided a set of targets that may help researchers to clarify further the underlying mechanisms of CCA tumorigenesis.

SUBMITTER: Zhong W

PROVIDER: S-EPMC5866017 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Cholangiocarcinoma‑associated genes identified by integrative analysis of gene expression data.

Zhong Wei W Dai Lianzhi L Liu Jing J Zhou Song S

Molecular medicine reports 20180212 4

Cholangiocarcinoma (CCA) is characterized by delayed diagnosis and poor survival rate. Research efforts have focused on novel diagnostic technologies for this type of cancer. Transcriptomic microarray technology is a useful research strategy for investigating the molecular properties of CCA. The objective of the present study was to identify candidate biomarkers with high potential for clinical application in CCA using a meta‑analysis‑based approach. Gene expression profiles of CCA were download ...[more]

PMID: 29436659

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Project description:The present study aimed to identify the key genes that are associated with the progression of intrahepatic cholangiocarcinoma through weighted gene co-expression network analysis (WGCNA). A total of three gene datasets were downloaded from the Gene Expression Omnibus database, including GSE107943, GSE119336 and GSE26566. Differentially expressed genes (DEGs) between intrahepatic cholangiocarcinoma tissues and adjacent liver tissues were identified using GSE107943, while tissue specific genes between bile duct and liver tissues were identified using GSE26566. Following the removal of tissue-specific genes, real DEGs were used to construct the WGCNA to investigate the association between gene modules and clinical traits. Following functional analysis, pathway enrichment analysis and the construction of a protein-protein interaction (PPI) network were performed, hub genes were selected and their diagnostic value was verified in GSE119336 using a receiver operating characteristic curve. Finally, the protein levels of the hub genes were also verified in intrahepatic cholangiocarcinoma tissues. A total of 1,643 real DEGs were identified and used to construct the WGCNA. Additionally, a total of seven co-expressed gene modules were identified following WGCNA, while genes in brown and yellow modules were identified to be associated with multiple clinical traits (the number of clinical traits >3) and used as key modules. A total of 63 core key module genes were subsequently identified, and it was indicated that these genes were most enriched in the nucleus (Gene Ontology term) and the cell cycle pathway (Kyoto Encyclopedia of Genes and Genomes term). Finally, a total of eight genes, including cyclin B1, cell division cycle 20, cell division cycle associated 8, cyclin dependent kinase 1, centrosomal protein 55, kinesin family member 2C, DNA topoisomerase IIα and TPX2 microtubule nucleation factor, exhibited the highest score in PPI analysis and had a high diagnostic value for intrahepatic cholangiocarcinoma. In addition, the protein levels of these genes were also revealed to be increased in most intrahepatic cholangiocarcinoma tissues. These eight genes may be used as novel biomarkers for the diagnosis of intrahepatic cholangiocarcinoma.

Dataset Information

Cholangiocarcinoma?associated genes identified by integrative analysis of gene expression data.

Publications

Cholangiocarcinoma‑associated genes identified by integrative analysis of gene expression data.

Similar Datasets

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