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鉴定肝细胞癌中的关键枢纽基因和circRNA调控的ceRNA网络

Identifying Essential Hub Genes and circRNA-Regulated ceRNA Networks in Hepatocellular Carcinoma.

作者信息

Yu Xiaoqian, Xu Hao, Xing Yutao, Sun Dehui, Li Dangdang, Shi Jinming, Sui Guangchao, Li Guangyue

机构信息

College of Life Science, Northeast Forestry University, Harbin 150040, China.

Institute of Biology, Westlake Institute for Advanced Study, Hangzhou 310030, China.

出版信息

Int J Mol Sci. 2025 Feb 7;26(4):1408. doi: 10.3390/ijms26041408.

Abstract

Competitive endogenous RNAs (ceRNAs) absorb microRNAs and subsequently promote corresponding mRNA and long noncoding RNA (lncRNA) expression, which may alter cancer cell malignancy. Thus, dissecting ceRNA networks may reveal novel targets in cancer therapies. In this study, we analyzed differentially expressed genes (DEGs) of mRNAs and lncRNAs, and differentially expressed microRNAs (DE-miRNAs) and circular RNAs (DE-circRNAs) extracted from high-throughput sequencing datasets of hepatocellular carcinoma patients. Based on these data, we identified 26 gene modules using weighted gene co-expression network analysis (WGCNA), of which 5 were associated with tumor differentiation. In these modules, 269 genes were identified by GO and KEGG enrichment and patient's survival correlation analyses. Next, 40 DE-miRNAs, each of which potentially bound a pair of DE-circRNA and hub gene, were discovered. Together with 201 circRNAs and 24 hub genes potentially bound by these miRNAs, 1151 ceRNA networks were constructed. Among them, 75 ceRNA networks consisting of 24 circRNAs, 28 miRNAs and 17 hub genes showed a positive circRNA-hub gene correlation. For validation, we carried out experiments for 4 randomly selected circRNAs regulating 19 potential ceRNA networks and verified 5 of them. This study represents a powerful strategy to identify essential gene networks and provides insights into designing effective therapeutic strategies.

摘要

竞争性内源性RNA(ceRNA)可吸附微小RNA,进而促进相应信使核糖核酸(mRNA)和长链非编码RNA(lncRNA)的表达,这可能会改变癌细胞的恶性程度。因此,剖析ceRNA网络可能会揭示癌症治疗中的新靶点。在本研究中,我们分析了从肝细胞癌患者高通量测序数据集中提取的mRNA和lncRNA的差异表达基因(DEG),以及差异表达的微小RNA(DE-miRNA)和环状RNA(DE-circRNA)。基于这些数据,我们使用加权基因共表达网络分析(WGCNA)鉴定了26个基因模块,其中5个与肿瘤分化相关。在这些模块中,通过基因本体论(GO)和京都基因与基因组百科全书(KEGG)富集以及患者生存相关性分析鉴定出269个基因。接下来,发现了40个DE-miRNA,每个DE-miRNA可能结合一对DE-circRNA和枢纽基因。连同这些miRNA可能结合的201个circRNA和24个枢纽基因,构建了1151个ceRNA网络。其中,由24个circRNA、28个miRNA和17个枢纽基因组成的75个ceRNA网络显示出circRNA与枢纽基因的正相关。为进行验证,我们对调控19个潜在ceRNA网络的4个随机选择的circRNA进行了实验,并验证了其中5个。本研究代表了一种识别关键基因网络的有效策略,并为设计有效的治疗策略提供了见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c666/11855757/e9fa93f9126d/ijms-26-01408-g001.jpg

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