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肝癌基因表达图谱的综合模块分析

Integrative module analysis of HCC gene expression landscapes.

作者信息

Li Hongshi, Wei Ning, Ma Yi, Wang Xiaozhou, Zhang Zhiqiang, Zheng Shuang, Yu Xi, Liu Shuang, He Lijie

机构信息

Department of Medical Oncology, People's Hospital of Liaoning Province, Shenyang, Liaoning 110016, P.R. China.

出版信息

Exp Ther Med. 2020 Mar;19(3):1779-1788. doi: 10.3892/etm.2020.8437. Epub 2020 Jan 8.

Abstract

Despite hepatocellular carcinoma (HCC) being a common cancer globally, its initiation and progression are not well understood. The present study was designed to investigate the hub genes and biological processes of HCC, which change substantially during its progression. Three gene expression profiles of 480 patients with HCC were obtained from the Gene Expression Omnibus database. Subsequent to performing functional annotations and constructing protein-protein interaction (PPI) networks, 657 differentially expressed genes were identified, which were subsequently used to screen candidate hub genes. PPI networks were modularized using the weighted gene correlation network analysis algorithm, the topological overlapping matrix and the hierarchical cluster tree, which were utilized via STRING. Clinical data obtained from The Cancer Genome Atlas were then analyzed to validate the experiments performed using six hub genes. Additionally, a transcription factor and microRNA-mRNA network were constructed to determine the potential regulatory mechanisms of six hub genes. The results revealed that the oxidation-reduction process and cell cycle associated processes were markedly involved in HCC progression. Six highly expressed genes, including cyclin B2, cell division cycle 20, mitotic arrest deficient 2 like 1, minichromosome maintenance complex component 2, centromere protein F and BUB mitotic checkpoint serine/threonine kinase B, were confirmed as hub genes and validated via experiments associated with cell division. These hub genes are necessary for confirmatory experiments and may be used in clinical gene therapy as biomarkers or drug targets.

摘要

尽管肝细胞癌(HCC)是全球常见的癌症,但其起始和进展情况仍未得到充分了解。本研究旨在调查HCC的核心基因和生物学过程,这些在其进展过程中会发生显著变化。从基因表达综合数据库中获取了480例HCC患者的三个基因表达谱。在进行功能注释并构建蛋白质-蛋白质相互作用(PPI)网络后,鉴定出657个差异表达基因,随后用于筛选候选核心基因。使用加权基因共表达网络分析算法、拓扑重叠矩阵和层次聚类树对PPI网络进行模块化,这些通过STRING来实现。然后分析从癌症基因组图谱获得的临床数据,以验证使用六个核心基因进行的实验。此外,构建了转录因子和微小RNA-信使核糖核酸网络,以确定六个核心基因的潜在调控机制。结果显示,氧化还原过程和细胞周期相关过程明显参与了HCC的进展。六个高表达基因,包括细胞周期蛋白B2、细胞分裂周期20、有丝分裂阻滞缺陷2样1、微小染色体维持复合体组分2、着丝粒蛋白F和BUB有丝分裂检查点丝氨酸/苏氨酸激酶B,被确认为核心基因,并通过与细胞分裂相关的实验进行了验证。这些核心基因对于验证性实验是必要的,并且可作为生物标志物或药物靶点用于临床基因治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4e9/7027144/daff48930035/etm-19-03-1779-g00.jpg

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