Department of General Surgery, Shangluo Central Hospital, Shangluo, Shaanxi 726000, P.R. China.
Department of Pathology, Weinan Central Hospital, Weinan, Shaanxi 714000, P.R. China.
Mol Med Rep. 2018 Dec;18(6):5579-5593. doi: 10.3892/mmr.2018.9567. Epub 2018 Oct 22.
The present study aimed to identify a long non‑coding (lnc) RNAs‑based signature for prognosis assessment in gastric cancer (GC) patients. By integrating gene expression data of GC and normal samples from the National Center for Biotechnology Information Gene Expression Omnibus, the EBI ArrayExpress and The Cancer Genome Atlas (TCGA) repositories, the common RNAs in Genomic Spatial Event (GSE) 65801, GSE29998, E‑MTAB‑1338, and TCGA set were screened and used to construct a weighted correlation network analysis (WGCNA) network for mining GC‑related modules. Consensus differentially expressed RNAs (DERs) between GC and normal samples in the four datasets were screened using the MetaDE method. From the overlapped lncRNAs shared by preserved WGCNA modules and the consensus DERs, an lncRNAs signature was obtained using L1‑penalized (lasso) Cox‑proportional hazard (PH) model. LncRNA‑mRNA networks were constructed for these signature lncRNAs, followed by functional annotation. A total of 14,824 common mRNAs and 2,869 common lncRNAs were identified in the 4 sets and 5 GC‑associated WGCNA modules were preserved across all sets. MetaDE method identified 1,121 consensus DERs. A total of 50 lncRNAs were shared by preserved WGCNA modules and the consensus DERs. Subsequently, an 11‑lncRNA signature was identified by LASSO‑based Cox‑PH model. The lncRNAs signature‑based risk score could divide patients into 2 risk groups with significantly different overall survival and recurrence‑free survival times. The predictive capability of this signature was verified in an independent set. These signature lncRNAs were implicated in several biological processes and pathways associated with the immune response, the inflammatory response and cell cycle control. The present study identified an 11‑lncRNA signature that could predict the survival rate for GC.
本研究旨在鉴定一种基于长非编码（lnc）RNAs 的标志，用于评估胃癌（GC）患者的预后。通过整合来自国家生物技术信息中心基因表达综合数据库、欧洲生物信息研究所 ArrayExpress 和癌症基因组图谱（TCGA）数据库的 GC 和正常样本的基因表达数据，筛选出 Genomic Spatial Event（GSE）65801、GSE29998、E-MTAB-1338 和 TCGA 数据集中共有的 RNA，并用于构建加权相关网络分析（WGCNA）网络，以挖掘 GC 相关模块。使用 MetaDE 方法筛选来自四个数据集的 GC 与正常样本之间的共识差异表达 RNA（DER）。从保留的 WGCNA 模块和共识 DER 之间共享的重叠 lncRNAs 中，使用 L1 惩罚（lasso）Cox 比例风险（PH）模型获得 lncRNAs 标志。为这些标志 lncRNAs 构建 lncRNA-mRNA 网络，并进行功能注释。在这四个数据集和 5 个 GC 相关的 WGCNA 模块中，共鉴定出 14824 个共同的 mRNAs 和 2869 个共同的 lncRNAs。MetaDE 方法鉴定出 1121 个共识 DER。共有 50 个 lncRNAs 存在于保留的 WGCNA 模块和共识 DER 之间。随后，基于 LASSO 的 Cox-PH 模型确定了一个 11-lncRNA 标志。lncRNAs 标志的风险评分可将患者分为两组，两组的总生存率和无复发生存时间有显著差异。在独立队列中验证了该标志的预测能力。这些标志 lncRNAs 与免疫反应、炎症反应和细胞周期控制等多个生物学过程和途径有关。本研究鉴定了一个可预测 GC 生存率的 11-lncRNA 标志。
