Zahid Kashif Rafiq, Su Mingyang, Khan Abdur Rehman Raza, Han Shiming, Deming Gou, Raza Umar
1Shenzhen Key Laboratory of Microbial Genetic Engineering, College of Life Sciences and Oceanography, Carson International Cancer Center, Shenzhen University, Shenzhen, 518060 Guangdong China.
2Military College of Signals, National University of Science and Technology (NUST), Khadim Hussain Rd, Rawalpindi, Pakistan.
Cancer Cell Int. 2019 Apr 8;19:89. doi: 10.1186/s12935-019-0804-3. eCollection 2019.
Hepatocellular carcinoma (HCC) is one of the leading cause of cancer associated deaths worldwide. Independent studies have proposed altered DNA methylation pattern and aberrant microRNA (miRNA) levels leading to abnormal expression of different genes as important regulators of disease onset and progression in HCC. Here, using systems biology approaches, we aimed to integrate methylation, miRNA profiling and gene expression data into a regulatory methylation-miRNA-mRNA (meth-miRNA-mRNA) network to better understand the onset and progression of the disease.
Patients' gene methylation, miRNA expression and gene expression data were retrieved from the NCBI GEO and TCGA databases. Differentially methylated genes, and differentially expressed miRNAs and genes were identified by comparing respective patients' data using two tailed Student's t-test. Functional annotation and pathway enrichment, miRNA-mRNA inverse pairing and gene set enrichment analyses (GSEA) were performed using DAVID, miRDIP v4.1 and GSEA tools respectively. meth-miRNA-mRNA network was constructed using Cytoscape v3.5.1. Kaplan-Meier survival analyses were performed using R script and significance was calculated by Log-rank (Mantel-Cox) test.
We identified differentially expressed mRNAs, miRNAs, and differentially methylated genes in HCC as compared to normal adjacent tissues by analyzing gene expression, miRNA expression, and methylation profiling data of HCC patients and integrated top miRNAs along with their mRNA targets and their methylation profile into a regulatory meth-miRNA-mRNA network using systems biology approach. Pathway enrichment analyses of identified genes revealed suppressed metabolic pathways and hyperactive cell cycle signaling as key features of HCC onset and progression which we validated in 10 different HCC patients' datasets. Next, we confirmed the inverse correlation between gene methylation and its expression, and between miRNA and its targets' expression in various datasets. Furthermore, we validated the clinical significance of identified methylation, miRNA and mRNA signatures by checking their association with clinical features and survival of HCC patients.
Overall, we suggest that simultaneous (1) reversal of hyper-methylation and/or oncogenic miRNA driven suppression of genes involved in metabolic pathways, and (2) induction of hyper-methylation and/or tumor suppressor miRNA driven suppression of genes involved in cell cycle signaling have potential of inhibiting disease aggressiveness, and predicting good survival in HCC.
肝细胞癌（HCC）是全球癌症相关死亡的主要原因之一。独立研究表明，DNA甲基化模式改变和异常的微小RNA（miRNA）水平导致不同基因的异常表达，是HCC疾病发生和进展的重要调节因素。在此，我们使用系统生物学方法，旨在将甲基化、miRNA谱和基因表达数据整合到一个调控性甲基化-miRNA-信使核糖核酸（meth-miRNA-mRNA）网络中，以更好地理解该疾病的发生和进展。
从NCBI基因表达综合数据库（GEO）和癌症基因组图谱（TCGA）数据库中检索患者的基因甲基化、miRNA表达和基因表达数据。使用双尾学生t检验比较各患者的数据，以鉴定差异甲基化基因、差异表达的miRNA和基因。分别使用DAVID、miRDIP v4.1和基因集富集分析（GSEA）工具进行功能注释和通路富集、miRNA-信使核糖核酸反向配对以及基因集富集分析。使用Cytoscape v3.5.1构建meth-miRNA-mRNA网络。使用R脚本进行Kaplan-Meier生存分析，并通过对数秩（Mantel-Cox）检验计算显著性。
通过分析HCC患者的基因表达、miRNA表达和甲基化谱数据，我们鉴定出与正常相邻组织相比，HCC中差异表达的信使核糖核酸、miRNA和差异甲基化基因，并使用系统生物学方法将顶级miRNA及其信使核糖核酸靶标以及它们的甲基化谱整合到一个调控性meth-miRNA-mRNA网络中。对鉴定出的基因进行通路富集分析，结果显示代谢通路受抑制和细胞周期信号过度活跃是HCC发生和进展的关键特征，我们在10个不同的HCC患者数据集里验证了这一点。接下来，我们在多个数据集中证实了基因甲基化与其表达之间、miRNA与其靶标表达之间呈负相关。此外，我们通过检查它们与HCC患者临床特征和生存的关联，验证了所鉴定的甲基化、miRNA和信使核糖核酸特征的临床意义。
总体而言，我们认为（1）同时逆转参与代谢途径的基因的高甲基化和/或致癌miRNA驱动的抑制，以及（2）诱导参与细胞周期信号传导的基因的高甲基化和/或肿瘤抑制miRNA驱动的抑制，具有抑制疾病侵袭性和预测HCC患者良好生存的潜力。
