Ma Yuyu, Yan Dong, Tian Fengming, Song Wen, Sha Ruocheng, Shang Xiaoqian, Lv Jie, Maimaiti Naifeisha, Kong Panpan, Ma Xiumin
State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Clinical Laboratory Center, Tumor Hospital Affiliated to Xinjiang Medical University Urumqi 830011, Xinjiang, P. R. China.
The First Ward of Hepatobiliary and Pancreatic Surgery, Tumor Hospital Affiliated to Xinjiang Medical University Urumqi 830011, Xinjiang, P. R. China.
Am J Transl Res. 2023 Aug 15;15(8):5007-5034. eCollection 2023.
The morbidity of hepatocellular carcinoma (HCC) is increasing annually. The aim of this study is to investigate the molecular mechanisms of upregulated genes in HCC using bioinformatic methods, so as to identify new potential biological markers.
The Gene Expression Omnibus database (GEO database) was mined for HCC datasets, which were screened for hub genes and subjected to (Gene Ontology) GO and (Kyoto Encyclopedia of Genes and Genomes) KEGG enrichment analysis. The hub genes were analyzed in terms of Receiver Operating Characteristic (ROC) and methylation levels. Validation of hub genes was completed through basic pathological alterations based on the protein and gene expression level of hub genes. The correlation of genes with immune infiltration in HCC was analyzed based on the database Timer 2.0, and the prognosis as well as survival of hub genes in HCC was analyzed using R studio software. Finally, we performed a gene combination drug analysis on the potential therapeutic targets in HCC.
Expression-up-regulated genes were screened via differential analysis, which were mainly enriched in cell cycles and DNA replication pathways. Five hub genes, BRCA1 associated RING domain 1 (BARD1), Mismatch Repair Protein (MSH2), Recombinant H2A Histone Family, Member X (H2AFX), Recombinant H2A Histone Family, Member z (H2AFZ) and Chromosome 18 Open Reading Frame 54 (C18orf54) were identified using a Protein-Protein Interaction Networks (PPI). After a comprehensive analysis of ROC curves and methylation gene mutation sites, C18orf54 was localized followed by basic experiments, so as to verify the C18orf54 upregulated in HCC. Based on the online database Timer 2.0, the immune infiltration of C18orf54 gene in HCC was analyzed, which was found to be negatively correlated with CD4 T cells and macrophages in HCC, meanwhile a further refinement of the immune checkpoint correlation analysis revealed that C18orf54 was mainly correlated with Hepatitis A virus cellular receptor 2 (HAVCR2), T cell immunoreceptor with Ig and ITIM domains (TIGIT) and Cytotoxic T lymphocyte associate protein-4 (CTLA4). The prognosis and survival of patients with HCC expressing C18orf54 were also analyzed, and it was found that such patients had a higher incidence of adjacent liver tissue inflammation, a higher child-Pugh grade score and a higher rate of residual tumor recurrence. Similarly, the prognosis was worse in the subset of patients with C18orf54. Finally, we performed a combined genetic analysis, which suggested that cyclosporine, quercetin, testosterone and calcitriol might be effective in reducing C18orf54 mRNA expression.
C18orf54 is involved in the immune infiltration and promotes the poor prognosis of HCC, which could be a candidate biomarker for HCC.
肝细胞癌(HCC)的发病率逐年上升。本研究旨在利用生物信息学方法探究HCC中上调基因的分子机制,以识别新的潜在生物标志物。
在基因表达综合数据库(GEO数据库)中挖掘HCC数据集,筛选出枢纽基因并进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)富集分析。从接受者操作特征(ROC)和甲基化水平方面分析枢纽基因。基于枢纽基因的蛋白质和基因表达水平,通过基本病理改变完成枢纽基因的验证。基于Timer 2.0数据库分析基因与HCC免疫浸润的相关性,并使用R studio软件分析HCC中枢纽基因的预后和生存情况。最后,我们对HCC中的潜在治疗靶点进行了基因联合药物分析。
通过差异分析筛选出表达上调的基因,这些基因主要富集在细胞周期和DNA复制途径中。使用蛋白质-蛋白质相互作用网络(PPI)鉴定出五个枢纽基因,即BRCA1相关环结构域1(BARD1)、错配修复蛋白(MSH2)、重组H2A组蛋白家族成员X(H2AFX)、重组H2A组蛋白家族成员z(H2AFZ)和18号染色体开放阅读框54(C18orf54)。在对ROC曲线和甲基化基因突变位点进行综合分析后,定位了C18orf54,随后进行基础实验,以验证其在HCC中上调。基于在线数据库Timer 2.0,分析了C18orf54基因在HCC中的免疫浸润情况,发现其与HCC中的CD4 T细胞和巨噬细胞呈负相关,同时对免疫检查点相关性分析的进一步细化显示,C18orf54主要与甲型肝炎病毒细胞受体2(HAVCR2)、具有Ig和ITIM结构域的T细胞免疫受体(TIGIT)以及细胞毒性T淋巴细胞相关蛋白4(CTLA4)相关。还分析了表达C18orf54的HCC患者的预后和生存情况,发现这类患者肝组织邻近炎症的发生率更高、Child-Pugh分级评分更高且残余肿瘤复发率更高。同样,C18orf54患者亚组的预后更差。最后,我们进行了联合基因分析,结果表明环孢素、槲皮素、睾酮和骨化三醇可能有效降低C18orf54 mRNA表达。
C18orf54参与免疫浸润并促进HCC的不良预后,可能是HCC的候选生物标志物。