Zhang Jie, Shi Keqing, Huang Weiguo, Weng Wanqing, Zhang Zhongjing, Guo Yangyang, Deng Tuo, Xiang Yukai, Ni Xiaofeng, Chen Bicheng, Zhou Mengtao
1Key Laboratory of Diagnosis and Treatment of Severe Hepato-Pancreatic Diseases of Zhejiang Province, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, 325015 Zhejiang Province People's Republic of China.
2Precision Medicine Center, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, 325015 Zhejiang Province People's Republic of China.
Cancer Cell Int. 2019 Apr 23;19:107. doi: 10.1186/s12935-019-0828-8. eCollection 2019.
Compelling lines of evidence indicate that DNA methylation of non-coding RNAs (ncRNAs) plays critical roles in various tumour progression. In addition, the differential methylation of ncRNAs can predict prognosis of patients. However, little is known about the clear relationship between DNA methylation profile of ncRNAs and the prognosis of pancreatic adenocarcinoma (PAC) patients.
The data of DNA methylation, RNA-seq, miRNA-seq and clinical features of PAC patients were collected from TCGA database. The DNA methylation profile was obtained using the Infinium HumanMethylation450 BeadChip array. LASSO regression was performed to construct two methylation-based classifiers. The risk score of methylation-based classifiers was calculated for each patient, and the accuracy of the classifiers in predicting overall survival (OS) was examined by ROC curve analysis. In addition, Cox regression models were utilized to assess whether clinical variables and the classifiers were independent prognostic factors for OS. The targets of miRNA and the genes co-expressed with lncRNA were identified with DIANA microT-CDS and the Multi-Experiment Matrix (MEM), respectively. Moreover, DAVID Bioinformatics Resources were applied to analyse the functional enrichment of these targets and co-expressed genes.
A total of 4004 CpG sites of miRNA and 11,259 CpG sites of lncRNA were screened. Among these CpG sites, 8 CpG sites of miRNA and 7 CpG sites of lncRNA were found with regression coefficients. By multiplying the sum of methylation degrees of the selected CpGs with these coefficients, two methylation-based classifiers were constructed. The classifiers have shown good performance in predicting the survival rate of PAC patients at varying follow-up times. Interestingly, both of these two classifiers were predominant and independent factors for OS. Furthermore, functional enrichment analysis demonstrated that aberrantly methylated miRNAs and lncRNAs are related to calcium ion transmembrane transport and MAPK, Ras and calcium signalling pathways.
In the present study, we identified two methylation-based classifiers of ncRNA associated with OS in PAC patients through a comprehensive analysis of miRNA and lncRNA profiles. We are the first group to demonstrate a relationship between the aberrant DNA methylation of ncRNAs and the prognosis of PAC, and this relationship would contribute to individualized PAC therapy.
有力的证据表明，非编码RNA（ncRNA）的DNA甲基化在各种肿瘤进展中起关键作用。此外，ncRNA的差异甲基化可以预测患者的预后。然而，关于ncRNA的DNA甲基化谱与胰腺腺癌（PAC）患者预后之间的明确关系知之甚少。
从TCGA数据库收集PAC患者的DNA甲基化、RNA测序、miRNA测序和临床特征数据。使用Infinium HumanMethylation450 BeadChip阵列获得DNA甲基化谱。进行LASSO回归以构建两个基于甲基化的分类器。为每位患者计算基于甲基化的分类器的风险评分，并通过ROC曲线分析检查分类器预测总生存期（OS）的准确性。此外，利用Cox回归模型评估临床变量和分类器是否为OS的独立预后因素。分别使用DIANA microT-CDS和多实验矩阵（MEM）鉴定miRNA的靶标和与lncRNA共表达的基因。此外，应用DAVID生物信息学资源分析这些靶标和共表达基因的功能富集情况。
共筛选出4004个miRNA的CpG位点和11259个lncRNA的CpG位点。在这些CpG位点中，发现8个miRNA的CpG位点和7个lncRNA的CpG位点具有回归系数。通过将所选CpG的甲基化程度总和与这些系数相乘，构建了两个基于甲基化的分类器。这些分类器在预测不同随访时间的PAC患者生存率方面表现出良好的性能。有趣的是，这两个分类器都是OS的主要和独立因素。此外，功能富集分析表明，异常甲基化的miRNA和lncRNA与钙离子跨膜转运以及MAPK、Ras和钙信号通路有关。
在本研究中，我们通过对miRNA和lncRNA谱的综合分析，鉴定了两个与PAC患者OS相关的基于甲基化的ncRNA分类器。我们是第一组证明ncRNA的异常DNA甲基化与PAC预后之间关系的研究团队，这种关系将有助于PAC的个体化治疗。
