The aim of this study was to identify novel prognostic mRNA and microRNA (miRNA) biomarkers for hepatocellular carcinoma (HCC) using methods in systems biology. Differentially expressed mRNAs, miRNAs, and long non-coding RNAs (lncRNAs) were compared between HCC tumor tissues and normal liver tissues in The Cancer Genome Atlas (TCGA) database. Subsequently, a prognosis-associated mRNA co-expression network, an mRNA–miRNA regulatory network, and an mRNA–miRNA–lncRNA regulatory network were constructed to identify prognostic biomarkers for HCC through Cox survival analysis. Seven prognosis-associated mRNA co-expression modules were obtained by analyzing these differentially expressed mRNAs. An expression module including 120 mRNAs was significantly correlated with HCC patient survival. Combined with patient survival data, several mRNAs and miRNAs, including CHST4, SLC22A8, STC2, hsa-miR-326, and hsa-miR-21 were identified from the network to predict HCC patient prognosis. Clinical significance was investigated using tissue microarray analysis of samples from 258 patients with HCC. Functional annotation of hsa-miR-326 and hsa-miR-21-5p indicated specific associations with several cancer-related pathways. The present study provides a bioinformatics method for biomarker screening, leading to the identification of an integrated mRNA–miRNA–lncRNA regulatory network and their co-expression patterns in relation to predicting HCC patient survival.

本研究的目的是使用系统生物学方法确定肝细胞癌(HCC)的新型预后 mRNA 和 microRNA (miRNA) 生物标志物。在癌症基因组图谱 (TCGA) 数据库中比较了 HCC 肿瘤组织和正常肝组织之间差异表达的 mRNA、miRNA 和长链非编码 RNA (lncRNA)。随后，一个与预后相关的 mRNA 共表达网络、一个 mRNA-miRNA 调控网络和一个mRNA-miRNA-lncRNA 调控网络构建以通过 Cox 生存分析识别 HCC 的预后生物标志物。通过分析这些差异表达的mRNA，获得了七个与预后相关的mRNA共表达模块。包含 120 个 mRNA 的表达模块与 HCC 患者存活率显着相关。结合患者生存数据，几种 mRNA 和 miRNA，包括CHST4、SLC22A8、STC2从网络中鉴定出 hsa-miR-326 和 hsa-miR-21 来预测 HCC 患者的预后。使用来自 258 名 HCC 患者的样本的组织微阵列分析来研究临床意义。hsa-miR-326 和 hsa-miR-21-5p 的功能注释表明与几种癌症相关途径的特定关联。本研究提供了一种用于生物标志物筛选的生物信息学方法，从而识别出整合的 mRNA-miRNA-lncRNA 调控网络及其与预测 HCC 患者生存相关的共表达模式。