首页> 外文期刊>Oncology reports >Uncovering the potential differentially expressed miRNAs as diagnostic biomarkers for hepatocellular carcinoma based on machine learning in The Cancer Genome Atlas database
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Uncovering the potential differentially expressed miRNAs as diagnostic biomarkers for hepatocellular carcinoma based on machine learning in The Cancer Genome Atlas database

机译:将潜在的差异表达的miRNA作为癌症基因组数据库中的机器学习基于机器学习的肝细胞癌诊断生物标志物

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摘要

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.
机译:本研究旨在鉴定新型诊断差异表达的MicroRNA(miRNA / miR),以了解肝细胞癌下面的分子机制。下载miRNA和mRNA的表达数据以进行差异表达分析。通过随机林算法鉴定最佳诊断差异表达的miOMarkers。建立了分类模型,以区分肝细胞癌和正常个体的患者。然后构建了最佳诊断差异表达的miRNA和差异表达的MRNA之间的调节网络。 GSE63046数据集和体外实验用于验证鉴定的最佳诊断差异表达miRNA的表达。另外,进行最佳诊断差异表达miRNA的诊断和预后分析。总共14种差异表达的miRNA(全部上调)和2,982个差异表达的MRNA(1,989个上调和下调993个)。 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。由这五个miRNA靶向的MRNA包括分泌的混发相关蛋白1(SFRP1),内皮素受体型B(EDNRB),核受体亚家族4组构件3(NR4A3),四个半肢体2(FHL2),NK3 Homeobox 1(NKX3-1),白细胞介素6信号换能器(IL6ST)和FORKHEAD框O1(FOXO1)。 “胆汁酸生物合成和胆固醇”是这些靶MRNA最富集的信号传导途径。五种miRNA的表达验证与目前的生物信息学分析一致。值得注意的是,HSA-MIR-10B-5P和HSA-MIR-10B-3P对肝细胞癌患者具有显着的预后值。总之,五种差异表达的miRNA可以被认为是肝细胞癌患者的诊断生物标志物。此外,这五种MRNA的靶标的差异表达水平,包括SFRP1,EDNRB,NR4A3,FHL2,NKX3-1,IL6ST和FOXO1可参与肝细胞癌肿瘤发生。

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