Gastric cancer is one of the most common malignant tumors and has a poor prognosis. Hypoxia is related to the poor prognosis of cancer patients. We searched for hypoxia-related long non-coding RNAs (lncRNAs) to predict both overall survival (OS) and disease-free survival (DFS) of gastric cancer patients.

We obtained hypoxia-related lncRNA expression profiles and clinical follow-up data of patients with gastric cancer from The Cancer Genome Atlas and the Molecular Signatures Database. The patients were randomly divided into a training group, test group and combined group. The hypoxia-related prognostic signature was constructed by Lasso regression and Cox regression models, the prognoses in different groups were compared by Kaplan–Meier (K-M) analysis, and the accuracy of the prognostic model was assessed by receiver operating characteristic (ROC) analysis.

A hypoxia-related prognostic signature comprising 10 lncRNAs was constructed to predict both OS and DFS in gastric cancer. In the training, test and combined groups, patients were divided into high- and low-risk groups according to the formula. Kaplan–Meier analysis showed that patients in the high-risk group have poor prognoses, and the difference was significant in the subgroup analyses. Receiver operating characteristic analysis revealed that the predictive power of the model prediction is more accurate than that of standard benchmarks. The signature differed across Helicobacter pylori (Hp) status and T stages. Multivariate Cox analysis showed that the signature is an independent risk factor for both OS and DFS. A clinically predictive nomogram combining the lncRNA signature and clinical features was constructed; the nomogram accurately predicted both OS and DFS and had high clinical application value. Weighted correlation network analysis combined with enrichment analysis showed that the primary pathways were the PI3K-Akt, JAK-STAT, and IL-17 signaling pathways. The target genes NOX4, COL8A1, and CHST1 were associated with poor prognosis in the Gene Expression Profiling Interactive Analysis, Gene Expression Omnibus, and K-M Plotter databases.

Our 10-lncRNA prognostic signature and nomogram are accurate, reliable tools for predicting both OS and DFS in gastric cancer.

胃癌是最常见的恶性肿瘤之一，预后较差。缺氧与癌症患者预后不良有关。我们搜索了与缺氧相关的长链非编码 RNA (lncRNA) 来预测胃癌患者的总生存期 (OS) 和无病生存期 (DFS)。

我们从癌症基因组图谱和分子特征数据库中获得了胃癌患者的缺氧相关 lncRNA 表达谱和临床随访数据。将患者随机分为训练组、试验组和联合组。通过 Lasso 回归和 Cox 回归模型构建缺氧相关的预后特征，通过 Kaplan-Meier（KM）分析比较不同组的预后，通过接受者操作特征（ROC）分析评估预后模型的准确性。

构建了一个包含 10 个 lncRNA 的缺氧相关预后特征来预测胃癌的 OS 和 DFS。在训练组、测试组和联合组中，根据公式将患者分为高危组和低危组。Kaplan-Meier 分析显示，高危组患者预后较差，在亚组分析中差异显着。接收者操作特征分析表明，模型预测的预测能力比标准基准的预测能力更准确。签名不同幽门螺杆菌(Hp) 状态和 T 阶段。多变量 Cox 分析表明，该特征是 OS 和 DFS 的独立风险因素。构建了结合 lncRNA 特征和临床特征的临床预测列线图；列线图准确预测OS和DFS，具有较高的临床应用价值。加权相关网络分析结合富集分析表明主要通路为PI3K-Akt、JAK-STAT和IL-17信号通路。在 Gene Expression Profiling Interactive Analysis、Gene Expression Omnibus 和 KM Plotter 数据库中，靶基因 NOX4、COL8A1 和 CHST1 与不良预后相关。

我们的 10-lncRNA 预后特征和列线图是预测胃癌 OS 和 DFS 的准确、可靠的工具。