基于生物信息学分析鉴定与乙型肝炎病毒相关的肝细胞癌早期诊断、肿瘤分期和不良预后相关的 5 个枢纽基因。

Identification of 5 Hub Genes Related to the Early Diagnosis, Tumour Stage, and Poor Outcomes of Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis.

机构信息

Department of Infectious Diseases, Guang'anmen Hospital, China Academy of Traditional Chinese Medicine, Beijing 100053, China.

Department of Oncology, The Second Affiliated Hospital of Harbin Medical University, Harbin 150081, China.

出版信息

Comput Math Methods Med. 2021 Sep 23;2021:9991255. doi: 10.1155/2021/9991255. eCollection 2021.

DOI:10.1155/2021/9991255

PMID:34603487

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8483908/

Abstract

BACKGROUND

The majority of primary liver cancers in adults worldwide are hepatocellular carcinomas (HCCs, or hepatomas). Thus, a deep understanding of the underlying mechanisms for the pathogenesis and carcinogenesis of HCC at the molecular level could facilitate the development of novel early diagnostic and therapeutic treatments to improve the approaches and prognosis for HCC patients. Our study elucidates the underlying molecular mechanisms of HBV-HCC development and progression and identifies important genes related to the early diagnosis, tumour stage, and poor outcomes of HCC.

METHODS

GSE55092 and GSE121248 gene expression profiling data were downloaded from the Gene Expression Omnibus (GEO) database. There were 119 HCC samples and 128 nontumour tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). Volcano plots and Venn diagrams were drawn by using the ggplot2 package in R. A heat map was generated by using Heatmapper. By using the clusterProfiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, KM survival curves and ROC curves were generated to validate hub gene expression.

RESULTS

By GO enrichment analysis, 694 DEGs were enriched in the following GO terms: organic acid catabolic process, carboxylic acid catabolic process, carboxylic acid biosynthetic process, collagen-containing extracellular matrix, blood microparticle, condensed chromosome kinetochore, arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. In the KEGG pathway enrichment analysis, DEGs were enriched in arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. By PPI network construction and analysis of hub genes, we selected the top 10 genes, including CDK1, CCNB2, CDC20, BUB1, BUB1B, CCNB1, NDC80, CENPF, MAD2L1, and NUF2. By using TCGA and THPA databases, we found five genes, CDK1, CDC20, CCNB1, CENPF, and MAD2L1, that were related to the early diagnosis, tumour stage, and poor outcomes of HBV-HCC.

CONCLUSIONS

Five abnormally expressed hub genes of HBV-HCC are informative for early diagnosis, tumour stage determination, and poor outcome prediction.

摘要

背景

全球大多数成人原发性肝癌为肝细胞癌（HCC，也称为肝癌）。因此，深入了解 HCC 发病机制和癌变的分子水平的潜在机制可以促进新型早期诊断和治疗方法的发展，以改善 HCC 患者的治疗方法和预后。我们的研究阐明了 HBV-HCC 发展和进展的潜在分子机制，并确定了与 HCC 的早期诊断、肿瘤分期和不良预后相关的重要基因。

方法

从基因表达综合（GEO）数据库中下载 GSE55092 和 GSE121248 基因表达谱数据。有 119 个 HCC 样本和 128 个非肿瘤组织样本。使用 GEO2R 筛选差异表达基因（DEGs）。通过 R 中的 ggplot2 包绘制火山图和 Venn 图。使用 Heatmapper 生成热图。通过使用 STRING 数据库构建 PPI 网络，使用 clusterProfiler R 包进行 DEGs 的 KEGG 和 GO 富集分析。通过 KM 生存曲线和 ROC 曲线验证关键基因的表达。

结果

通过 GO 富集分析，694 个 DEGs 富集在以下 GO 术语中：有机酸分解代谢过程、羧酸分解代谢过程、羧酸生物合成过程、富含胶原蛋白的细胞外基质、血液微粒体、浓缩染色体动粒、花生四烯酸环氧化酶活性、花生四烯酸单加氧酶活性和单加氧酶活性。在 KEGG 途径富集分析中，DEGs 富集在花生四烯酸环氧化酶活性、花生四烯酸单加氧酶活性和单加氧酶活性中。通过 PPI 网络构建和关键基因分析，我们选择了前 10 个基因，包括 CDK1、CCNB2、CDC20、BUB1、BUB1B、CCNB1、NDC80、CENPF、MAD2L1 和 NUF2。通过使用 TCGA 和 THPA 数据库，我们发现了五个与 HBV-HCC 的早期诊断、肿瘤分期和不良预后相关的基因，包括 CDK1、CDC20、CCNB1、CENPF 和 MAD2L1。