Department of General Surgery, Beijing You'an Hospital, Capital Medical University, Beijing 100069, China.
Department of Hepatobiliary Surgery, Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
J Environ Pathol Toxicol Oncol. 2022;41(1):27-43. doi: 10.1615/JEnvironPatholToxicolOncol.2021039641.
Early detection of hepatocellular carcinoma (HCC) is significantly effective in clinical management. This study aimed to identify potential HCC biomarkers.
Analysis of expression profiles in HCC clinical samples downloaded from the cancer genome atlas (TCGA) and the gene expression omnibus (GEO) datasets was performed to identify differentially expressed genes (DEGs) using R packages. The epigenetic differentially expressed genes (epiDEGs) were obtained after intersections of genes between DEGs and epigenetic factors (EFs). The biological functions of epiDEGs were annotated by gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis. Protein-protein interaction and expression correlation were performed to investigate the interactions among epiDEGs by the STRING online tool and R packages. The epiDEGs associated with overall survival (OS) were identified as patient prognosis using the Cox regression analysis. The levels of gene expression were validated by RT-qPCR and Western blot between HCC cell lines, (HepG2, and Huh-7) and normal cell lines (THLE-2).
Thirty-five epiDEGs were obtained, including 25 upregulated genes and 10 downregulated genes. Functional enrichment and PPI analysis indicated the development of HCC is a complicated process involving various genes and proteins. Survival analysis showed nine epiDEGs associated with the OS of patients and these might be the independent prognostic biomarkers for HCC. The expressions of most epiDEGs were significantly higher in HCC patients with stage II and III compared with stage I. Furthermore, the expression of these epiDEGs between HCC cell lines with normal cell lines was shown to be consistent with the TCGA and GEO datasets except PBK.
Eight hub epiDEGs, including EZH2, CDK1, CENPA, RAD54L, HELLS, HJURP, AURKA, and AURKB, were associated with the overall survival of HCC patients and could be potential biomarkers to predict prognosis.
早期发现肝细胞癌（HCC）在临床管理中具有显著的效果。本研究旨在鉴定潜在的 HCC 生物标志物。
使用 R 软件包分析从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）下载的 HCC 临床样本的表达谱，以鉴定差异表达基因（DEGs）。将 DEGs 与表观遗传因子（EFs）进行交集后获得表观遗传差异表达基因（epiDEGs）。通过基因本体论（GO）和京都基因与基因组百科全书（KEGG）富集分析注释 epiDEGs 的生物学功能。通过 STRING 在线工具和 R 软件包进行蛋白质-蛋白质相互作用和表达相关性分析，以研究 epiDEGs 之间的相互作用。通过 Cox 回归分析，将与总生存期（OS）相关的 epiDEGs 鉴定为患者的预后。通过 RT-qPCR 和 Western blot 在 HCC 细胞系（HepG2 和 Huh-7）和正常细胞系（THLE-2）之间验证基因表达水平。
获得了 35 个 epiDEGs，包括 25 个上调基因和 10 个下调基因。功能富集和 PPI 分析表明，HCC 的发生是一个涉及多种基因和蛋白质的复杂过程。生存分析显示，有 9 个 epiDEGs 与患者的 OS 相关，这些可能是 HCC 的独立预后生物标志物。与 HCC 患者的 I 期相比，II 期和 III 期患者的大多数 epiDEGs 表达明显更高。此外，与 TCGA 和 GEO 数据集相比，除了 PBK 之外，这些 epiDEGs 在 HCC 细胞系与正常细胞系之间的表达也一致。
八个 hub epiDEGs，包括 EZH2、CDK1、CENPA、RAD54L、HELLS、HJURP、AURKA 和 AURKB，与 HCC 患者的总生存期相关，可能是预测预后的潜在生物标志物。
