Department of Hepatobiliary Surgery, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, P.R. China.
Department of Infection, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, P.R. China.
Oncol Rep. 2020 Jun;43(6):1771-1784. doi: 10.3892/or.2020.7551. Epub 2020 Mar 19.
The present study aimed to identify novel diagnostic differentially expressed microRNAs (miRNAs/miRs) in order to understand the molecular mechanisms underlying hepatocellular carcinoma. The expression data of miRNA and mRNA were downloaded for differential expression analysis. Optimal diagnostic differentially expressed miRNA biomarkers were identified via a random forest algorithm. Classification models were established to distinguish patients with hepatocellular carcinoma and normal individuals. A regulatory network between optimal diagnostic differentially expressed miRNA and differentially expressed mRNAs was then constructed. The GSE63046 dataset and in vitro experiments were used to validate the expression of the optimal diagnostic differentially expressed miRNAs identified. In addition, diagnostic and prognostic analyses of optimal diagnostic differentially expressed miRNAs were performed. In total, 14 differentially expressed miRNAs (all upregulated) and 2,982 differentially expressed mRNAs (1,989 upregulated and 993 downregulated) were identified. hsa‑miR‑10b‑5p, hsa‑miR‑10b‑3p, hsa‑miR‑224‑5p, hsa‑miR‑183‑5p and hsa‑miR‑182‑5p were considered as the optimal diagnostic biomarkers for hepatocellular carcinoma. The mRNAs targeted by these five miRNAs included secreted frizzled related protein 1 (SFRP1), endothelin receptor type B (EDNRB), nuclear receptor subfamily 4 group A member 3 (NR4A3), four and a half LIM domains 2 (FHL2), NK3 homeobox 1 (NKX3‑1), interleukin 6 signal transducer (IL6ST) and forkhead box O1 (FOXO1). 'Bile acid biosynthesis and cholesterol' was the most enriched signaling pathways of these target mRNAs. The expression validation of the five miRNAs was consistent with the present bioinformatics analysis. Notably, hsa‑miR‑10b‑5p and hsa‑miR‑10b‑3p had a significant prognosis value for patients with hepatocellular carcinoma. In conclusion, the five differentially expressed miRNAs may be considered as diagnostic biomarkers for patients with hepatocellular carcinoma. In addition, the differential expression levels of the targets of these five mRNAs, including SFRP1, EDNRB, NR4A3, FHL2, NKX3‑1, IL6ST and FOXO1, may be involved in hepatocellular carcinoma tumorigenesis.
本研究旨在鉴定新型诊断差异表达 microRNAs(miRNAs/miRs),以了解肝细胞癌的分子机制。下载 miRNA 和 mRNA 的表达数据进行差异表达分析。通过随机森林算法识别最佳诊断差异表达 miRNA 生物标志物。建立分类模型以区分肝细胞癌患者和正常个体。然后构建最佳诊断差异表达 miRNA 与差异表达 mRNA 之间的调控网络。使用 GSE63046 数据集和体外实验验证所鉴定的最佳诊断差异表达 miRNA 的表达。此外,还对最佳诊断差异表达 miRNA 进行了诊断和预后分析。总共鉴定出 14 个差异表达 miRNA(均上调)和 2982 个差异表达 mRNA(1989 个上调和 993 个下调)。hsa-miR-10b-5p、hsa-miR-10b-3p、hsa-miR-224-5p、hsa-miR-183-5p 和 hsa-miR-182-5p 被认为是肝细胞癌的最佳诊断生物标志物。这 5 个 miRNA 靶向的 mRNAs 包括分泌卷曲相关蛋白 1(SFRP1)、内皮素受体 B(EDNRB)、核受体亚家族 4 组 A 成员 3(NR4A3)、四个半 LIM 结构域 2(FHL2)、NK3 同源盒 1(NKX3-1)、白细胞介素 6 信号转导物(IL6ST)和叉头框 O1(FOXO1)。这些靶 mRNAs 最富集的信号通路是“胆汁酸生物合成和胆固醇”。5 个 miRNA 的表达验证与本生物信息学分析一致。值得注意的是,hsa-miR-10b-5p 和 hsa-miR-10b-3p 对肝细胞癌患者的预后具有显著的预后价值。综上所述,这 5 个差异表达 miRNA 可作为肝细胞癌患者的诊断生物标志物。此外,这 5 个 miRNA 的靶标,包括 SFRP1、EDNRB、NR4A3、FHL2、NKX3-1、IL6ST 和 FOXO1 的差异表达水平可能参与了肝细胞癌的肿瘤发生。