Department of Pathology, Guangdong Medical University, Zhanjiang, China.
Department of Pathology, The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Biomed Res Int. 2020 Oct 10;2020:1468980. doi: 10.1155/2020/1468980. eCollection 2020.
Increasing evidence indicated that aberrant expression of long noncoding RNAs (lncRNAs) are involved in tumorigenesis of nasopharyngeal carcinoma (NPC). The purpose of this study was to construct a lncRNA-mediated ceRNA network based on weighted correlation network analysis (WGCNA). First, modules with highly correlated genes were identified from GSE102349 via WGCNA, and the preservation of the modules was evaluated by GSE68799. Then, the differentially expressed lncRNAs and mRNAs identified from GSE12452 which belonged to the same WGCNA modules and the differentially expressed miRNAs identified from GSE32960 were used to construct a ceRNA network. The prognostic value of the network was evaluated by survival analysis. Furthermore, a risk score model for predicting progression-free survival (PFS) of NPC patients was established via LASSO-penalized Cox regression, and the differences in the expression of the lncRNAs between high- and low-risk groups were investigated. Finally, 14 stable modules were identified, and a ceRNA network composed of 11 lncRNAs, 15 miRNAs, and 40 mRNAs was established. The lncRNAs and mRNAs in the network belonged to the turquoise and salmon modules. Survival analysis indicated that ZNF667-AS1, LDHA, LMNB2, TPI1, UNG, and hsa-miR-142-3p were significantly correlated with the prognosis of NPC. Gene set enrichment analysis indicated that the upregulation of ZNF667-AS1 was associated with some immune-related pathways. Besides, a risk score model consisting of 12 genes was constructed and showed a good performance in predicting PFS for NPC patients. Among the 11 lncRNAs in the ceRNA network, SNHG16, SNHG17, and THAP9-AS1 were upregulated in the high-risk group of NPC, while ZNF667-AS1 was downregulated in the high-risk group of NPC. These results will promote our understanding of the crosstalk among lncRNAs, miRNAs, and mRNAs in the tumorigenesis and progression of NPC.
越来越多的证据表明，长非编码 RNA（lncRNA）的异常表达与鼻咽癌（NPC）的发生有关。本研究旨在基于加权相关网络分析（WGCNA）构建一个 lncRNA 介导的 ceRNA 网络。首先，通过 WGCNA 从 GSE102349 中识别出具有高度相关基因的模块，并通过 GSE68799 评估模块的保存情况。然后，从 GSE12452 中识别出属于同一 WGCNA 模块的差异表达 lncRNA 和 mRNAs，以及从 GSE32960 中识别出差异表达的 miRNAs，用于构建 ceRNA 网络。通过生存分析评估网络的预后价值。此外，通过 LASSO 惩罚 Cox 回归建立 NPC 患者无进展生存（PFS）预测的风险评分模型，并研究高低风险组之间 lncRNA 表达的差异。最后，鉴定出 14 个稳定模块，并建立了一个包含 11 个 lncRNA、15 个 miRNA 和 40 个 mRNA 的 ceRNA 网络。该网络中的 lncRNA 和 mRNAs 属于绿松石和三文鱼模块。生存分析表明，ZNF667-AS1、LDHA、LMNB2、TPI1、UNG 和 hsa-miR-142-3p 与 NPC 的预后显著相关。基因集富集分析表明，ZNF667-AS1 的上调与一些免疫相关通路有关。此外，构建了一个由 12 个基因组成的风险评分模型，该模型在预测 NPC 患者 PFS 方面表现良好。在 ceRNA 网络中的 11 个 lncRNA 中，SNHG16、SNHG17 和 THAP9-AS1 在 NPC 的高危组中上调，而 ZNF667-AS1 在 NPC 的高危组中下调。这些结果将促进我们对 lncRNA、miRNA 和 mRNAs 在 NPC 发生和进展中相互作用的理解。
