期刊
CANCER BIOTHERAPY AND RADIOPHARMACEUTICALS
卷 37, 期 7, 页码 569-579出版社
MARY ANN LIEBERT, INC
DOI: 10.1089/cbr.2020.4249
关键词
bioinformatics analysis; differentially expressed genes; Gene Expression Omnibus database; ovarian cancer; PDZ-binding kinase
类别
资金
- National Key Research Program [2018YFC1002900]
This study utilized bioinformatics analysis to identify potential key genes associated with ovarian cancer, providing potential diagnostic and therapeutic targets. Through differential gene expression analysis and gene co-expression network analysis, PBK gene was identified to be potentially associated with the pathogenesis and prognosis of ovarian cancer.
Aim: As one of the three malignant genital tumors, mortality in women with ovarian cancer is consistently high worldwide. It is of great importance to find prognostic markers for diagnosis and treatment of ovarian cancer. In this study, the authors utilized the bioinformatics analysis to identify the potential key genes to reveal the potential mechanism for ovarian cancer. Methods: The authors used the gene expression profile (GSE14407) to perform differentially expressed gene (DEG) analysis and the weighted gene co-expression network analysis. They selected the key module and performed the gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for the genes in the hub module. Then they screened the key genes in the hub module, and further validated their expression level. Results: A total of 3124 DEGs were detected after differential gene expression analysis; of these, 433 were upregulated genes and 2691 were downregulated genes. The authors selected the brown module that is significantly associated with the BRCA gene expression. Then they selected 30 hub genes from the protein-protein interaction network. And the authors identify the PDZ binding kinase (PBK) as the prognosis-associated hub gene whose expression was significantly high in the ovarian cancer tissue. Conclusions: The bioinformatics analysis for the DEGs could be important to understand the pathogenesis for ovarian cancer. In this study, PBK is identified as a potential marker that might improve the understanding of the molecular mechanism and the diagnosis level for ovarian cancer.
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