College of Public Health, Guangdong Pharmaceutical University, Guangzhou 510006, China.
Guangdong Provincial TCM Precision Medicine Big Data Engineering Technology Research Center, Guangzhou 510006, China.
Biomed Res Int. 2021 Feb 11;2021:4093426. doi: 10.1155/2021/4093426. eCollection 2021.
Increasing evidence has shown that noncoding RNAs play significant roles in the initiation, progression, and metastasis of tumours via participating in competing endogenous RNA (ceRNA) networks. However, the survival-associated ceRNA in lung adenocarcinoma (LUAD) remains poorly understood. In this study, we aimed to investigate the regulatory mechanisms underlying ceRNA in LUAD to identify novel prognostic factors. mRNA, lncRNA, and miRNA sequencing data obtained from the GDC data portal were utilized to identify differentially expressed (DE) RNAs. Survival-related RNAs were recognized using univariate Kaplan-Meier survival analysis. We performed functional enrichment analysis of survival-related mRNAs using the clusterProfiler package of R and STRING. lncRNA-miRNA and miRNA-mRNA interactions were predicted based on miRcode, Starbase, and miRanda. Subsequently, the survival-associated ceRNA network was constructed for LUAD. Multivariate Cox regression analysis was used to identify prognostic factors. Finally, we acquired 15 DE miRNAs, 49 DE lncRNAs, and 843 DE mRNAs associated with significant overall survival. Functional enrichment analysis indicated that survival-related DE mRNAs were enriched in cell cycle. The survival-associated lncRNA-miRNA-mRNA ceRNA network was constructed using five miRNAs, 49 mRNAs, and 21 lncRNAs. Furthermore, seven hub RNAs (LINC01936, miR-20a-5p, miR-31-5p, , , , and ) were identified based on the ceRNA network. LINC01936 and miR-31-5p were found to be significant using the multifactorial Cox regression model. In conclusion, we successfully constructed a survival-related lncRNA-miRNA-mRNA ceRNA regulatory network in LUAD and identified seven hub RNAs, which provide novel insights into the regulatory molecular mechanisms associated with survival of LUAD, and identified two independent prognostic predictors for LUAD.
越来越多的证据表明,非编码 RNA 通过参与竞争性内源 RNA (ceRNA) 网络,在肿瘤的发生、进展和转移中发挥重要作用。然而,肺腺癌 (LUAD) 中与生存相关的 ceRNA 仍知之甚少。在这项研究中,我们旨在探讨 LUAD 中 ceRNA 的调控机制,以鉴定新的预后因素。利用 GDC 数据门户获得的 mRNA、lncRNA 和 miRNA 测序数据来识别差异表达 (DE) 的 RNA。使用单变量 Kaplan-Meier 生存分析识别与生存相关的 RNA。我们使用 R 中的 clusterProfiler 包和 STRING 对与生存相关的 mRNA 进行功能富集分析。基于 miRcode、Starbase 和 miRanda 预测 lncRNA-miRNA 和 miRNA-mRNA 相互作用。随后,构建了 LUAD 的生存相关 ceRNA 网络。使用多变量 Cox 回归分析鉴定预后因素。最后,我们获得了 15 个与总生存期显著相关的 DE miRNA、49 个 DE lncRNA 和 843 个 DE mRNA。功能富集分析表明,与生存相关的 DE mRNAs 富集在细胞周期中。使用 5 个 miRNA、49 个 mRNAs 和 21 个 lncRNAs 构建了与生存相关的 lncRNA-miRNA-mRNA ceRNA 网络。此外,根据 ceRNA 网络,鉴定了七个枢纽 RNA (LINC01936、miR-20a-5p、miR-31-5p、、、和 )。基于多因素 Cox 回归模型,发现 LINC01936 和 miR-31-5p 具有显著性。总之,我们成功构建了 LUAD 中与生存相关的 lncRNA-miRNA-mRNA ceRNA 调控网络,并鉴定了七个枢纽 RNA,为 LUAD 生存相关的调控分子机制提供了新的见解,并确定了 LUAD 的两个独立预后预测因子。