免疫浸润相关的7个关键基因揭示肝癌预后意义

T. M., D. L
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摘要

背景:肝细胞癌(HCC)的预后不良主要是由于诊断晚、进展快和复发率高。迫切需要用于HCC诊断和预后的可靠生物标志物。方法:我们从GEO数据库中选择了四个公共数据集来鉴定差异表达基因(DEGs)和差异表达miRNAs(DE-miRNAs)。构建GO功能注释、KEGG通路富集分析和蛋白质-蛋白质相互作用(PPI)网络,以探索DEG的功能和重要性。为了确定从GSE10694中筛选的33个DE miRNA的靶基因,利用miRNet Web服务器。通过信使核糖核酸-微核糖核酸相互作用分析筛选出关键基因。然后,在并行数据库(ONCOMPINE、GEPIA和HPA数据库)中验证这些高表达基因。Kaplan-Meier进行了进一步的预后分析,并基于TCGA进行了诊断分析。此外,我们使用TIMER数据库研究了关键基因与HCC组织免疫浸润之间的关系。结果:基于公共数据库,我们鉴定了7个关键基因,包括CCNA2、DLGAP5、MAD2L1、MELK、NCAPG、PRC1和RRM2。这些关键基因的过度表达已在HCC组织中得到证实,并与HCC患者的晚期疾病和不良预后有关。此外,我们发现这些关键基因影响各种浸润性免疫细胞,并与HCC免疫逃逸基因标志物的表达呈正相关。结论:这7个关键基因可作为HCC患者诊断、预后和免疫治疗反应预测的生物标志物,也可作为肝癌的治疗靶点
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Seven Key Genes Correlated with Immune Infiltration Reveal Prognostic Significance of Hepatocellular Carcinoma
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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