Abstract

BackgroundHepatocellular carcinoma (HCC) is the fourth main cause of cancer-related death globally. Based on the evidence, type 2 diabetes mellitus (T2DM) is associated with the onset of HCC. The current work was conducted to discover molecular mechanisms and hub genes of both diseases concurrently by carrying out integrated bioinformatics analysis. Material and methodsIn this study, the microarray datasets of HCC and T2DM diseases were retrieved from the Gene Expression Omnibus (GEO) database. In order to identify differentially expressed genes (DEGs), datasets of both diseases were analyzed by employing the GEO2R online tool separately. Shared DEGs between both diseases were used for subsequent analyses. The Enrichr database was applied to evaluate the functional enrichment analysis of DEGs. The STRING database was used to establish protein-protein interaction (PPI) networks visualized using Cytoscape. The hub genes were defined using the cytoHubba plugin of Cytoscape based upon the degree method. The diagnostic accuracy of hub genes was evaluated using the area under the curve (AUC) values obtained from receiver operating characteristic (ROC) curve analysis. Eventually, the interactions of the transcription factors (TFs) and microRNAs (miRNAs) with the hub genes were constructed by utilizing the Networkanalyst database. ResultsA total of 98 common DEGs were found between HCC and T2DM datasets. PPI network acquired from the STRING database was imported to the cytoHubba plugin of Cytoscape, and 10 hub genes were screened based on the degree method using the above plugin (which included BUB1, CDCA8, DLGAP5, ASPM, POLQ, CENPE, WDHD1, HELLS, TRIP13, and DEPDC1). According to the ROC curve, all hub genes have a high diagnostic value, with high specificity and sensitivity. Among miRNAs, miR-192-5p was most correlated with the hub genes, and regarding the TFs, E2F4 was identified as a transcription factor responsible for regulating most of the hub genes. ConclusionsThis research provides a novel vision about the progression and pathogenesis of HCC in T2DM sufferers through bioinformatics tools. However, to verify key genes and biological pathways obtained from this study, additional experiments are required.

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