Integrated Bioinformatics Analysis for the Screening of Hub Genes andTherapeutic Drugs in Hepatocellular Carcinoma

作者：Qiuming Su, Wang Li, Xibing Zhang, Ruichao Wu, Kepu Zheng, Tao Zhou, Yun Dong, Yutao He, Duo Wang, Jianghua Ran · 发表于：Current Pharmaceutical Biotechnology · 年份：2022 · DOI：10.2174/1389201023666220628113452 · 被引用次数：20 · 研究领域：Bioinformatics and Genomic Networks、Ferroptosis and cancer prognosis、Kruppel-like factors research

BACKGROUND: Liver cancer is a major medical problem because of its high morbidity and mortality. Hepatocellular carcinoma (HCC) is the most common type of liver cancer. Currently, the mechanism of HCC is unclear, and the prognosis is poor with limited treatment. OBJECTIVE: The purpose of this study is to identify hub genes and potential therapeutic drugs for HCC. METHODS: We used the GEO2R algorithm to analyze the differential expression of each gene in 4 gene expression profiles (GSE101685, GSE62232, GSE46408, and GSE45627) between HCC and normal hepatic tissues. Next, we screened out the differentially expressed genes (DEGs) by corresponding calculation data according to adjusted P-value < 0.05 and | log fold change (FC) | > 1.0. Subsequently, we used the DAVID software to analyze the DEGs by GO and KEGG enrichment analysis. Then, we carried out the protein-protein interaction (PPI) network analysis of DEGs using the STRING tool, and the PPI network was constructed by Cytoscape software. MCODE plugin was used for module analysis, and the hub genes were screened out by the Cyto- Hubba plugin. Meanwhile, we used The Kaplan-Meier plotter, GEPIA2 and HPA databases to exert survival analysis and verify the expression alternation of hub genes. Furthermore, we used ENCORI, TargetScan, miRDB and miRWalk database to predict the upstream regulated miRNA of hub genes and construct a miRNA-hub genes network by Cytoscape software. Finally, we selected potential therapeutic drugs for HCC...