Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, China.
Department of Thoracic Surgery, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, China.
BMC Cancer. 2021 Apr 23;21(1):457. doi: 10.1186/s12885-021-08207-7.
Accumulating evidence has revealed that long non-coding RNAs (lncRNAs) play vital roles in the progression of non-small cell lung cancer (NSCLC). But the relationship between lncRNAs and survival outcome of NSCLC remains to be explored. Therefore, we attempt to figure out their survival roles and molecular connection in NSCLC.
By analyzing the transcriptome profiling of NSCLC from TCGA databases, we divided patients into three groups, and identified differentially expressed lncRNAs (DELs) of each group. Next, we explored the prognostic roles of common DELs by univariate and multivariate Cox analysis, Lasson, and Kaplan-Meier analysis. Additionally, we assessed and compared the prognostic accuracy of 5 lncRNAs through ROC curves and AUC values. Ultimately, we detected their potential function by enrichment analysis and molecular connection through establishing a competing endogenous RNA (ceRNA) network.
One hundred ninety-seven common DELs were spotted. And we successfully screened out 5 lncRNAs related to the patient's survival, including LINC01833, AC112206.2, FAM83A-AS1, BANCR, and HOTAIR. Combing with age and AJCC stage, we constructed a nomogram that prognostic prediction was superior to the traditional parameters. Furthermore, 275 qualified mRNAs related to 5 lncRNAs were spotted. Functional analysis indicates that these lncRNAs act key roles in the progression of NSCLC, such as P53 and cell cycle signaling pathway. And ceRNA network also suggests that these lncRNAs are tightly connected with tumor progression.
A nomogram and ceRNA network based on 5 lncRNAs indicate that there can effectively predict the overall survival of NSCLC and potentially serve as a therapeutic guide for NSCLC.
越来越多的证据表明，长链非编码 RNA（lncRNA）在非小细胞肺癌（NSCLC）的进展中发挥着重要作用。但是，lncRNA 与 NSCLC 患者生存结局之间的关系仍有待探索。因此，我们试图确定它们在 NSCLC 中的生存作用和分子联系。
通过分析 TCGA 数据库中 NSCLC 的转录组谱，我们将患者分为三组，并鉴定了每组的差异表达 lncRNA（DEL）。接下来，我们通过单变量和多变量 Cox 分析、Lasson 和 Kaplan-Meier 分析，探讨了常见 DEL 的预后作用。此外，我们通过 ROC 曲线和 AUC 值评估和比较了 5 个 lncRNA 的预后准确性。最终，我们通过建立竞争性内源 RNA（ceRNA）网络来评估它们的潜在功能和分子联系。
发现了 197 个常见 DEL。我们成功筛选出 5 个与患者生存相关的 lncRNA，包括 LINC01833、AC112206.2、FAM83A-AS1、BANCR 和 HOTAIR。将年龄和 AJCC 分期与这些 lncRNA 相结合，构建了一个预测预后的列线图，其预测效果优于传统参数。此外，发现了与 5 个 lncRNA 相关的 275 个合格的 mRNAs。功能分析表明，这些 lncRNA 在 NSCLC 的进展中起着关键作用，如 P53 和细胞周期信号通路。ceRNA 网络也表明，这些 lncRNA 与肿瘤进展密切相关。
基于 5 个 lncRNA 的列线图和 ceRNA 网络可以有效地预测 NSCLC 患者的总体生存率，并且可能为 NSCLC 提供治疗指导。
