Abstract

Background: The poor prognosis of Hepatocellular Carcinoma (HCC) is mainly due to late diagnosis, rapid progression and high recurrence rate. Reliable biomarkers for the diagnosis and prognosis of HCC are urgently needed. Methods: We selected four public datasets from the GEO database to identify Differentially Expressed Genes (DEGs) and Differentially Expressed miRNAs (DE miRNAs). GO functional annotation, KEGG pathway enrichment analysis, and a Protein-Protein Interaction (PPI) network were constructed to explore the functions and importance of DEGs. To determine the target genes of 33 DE miRNAs screened from GSE10694, the miRNet WebServer was utilized. The key genes were screened out by mRNA-microRNA interaction analysis. Then, those highly expressed genes were verified in parallel databases (ONCOMINE, GEPIA and HPA databases). Further prognostic analysis by Kaplan Meier and diagnostic analysis based on TCGA were conducted. Furthermore, we investigated the association between key genes and immune infiltration in HCC tissues using the TIMER database. Results: We identified seven key genes, including CCNA2, DLGAP5, MAD2L1, MELK, NCAPG, PRC1, and RRM2 based on public databases. The overexpression of these key genes has been demonstrated in HCC tissues and is associated with advanced disease and poor prognosis of patients with HCC. Furthermore, we found these key genes affect various of infiltrating immune cells and be positively correlated with the expression of gene markers of immune escape in HCC. Conclusion: These seven key genes might be used as biomarkers for the diagnosis, prognosis, and prediction response to immunotherapy for patients with HCC, as well as the therapeutic targets of HCC

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