长链非编码RNA（lncRNA）和DNA甲基化是肿瘤发生和免疫调节的关键调节因子。然而，在胃癌（GC）中，lncRNA与DNA甲基化的相互作用、调节机制以及其在临床和免疫上的相关性仍不清楚。本研究通过The Cancer Genome Atlas数据集中的Pearson相关分析来鉴定DNA甲基化调控相关的lncRNA。使用单变量Cox回归筛选DNA甲基化相关的预后lncRNA。进一步，通过最小绝对收缩和选择算子Cox回归，建立了基于13个lncRNA的预后模型。生存分析和受试者工作特征曲线分析验证了模型在预测GC患者生存上的准确性。单变量和多变量分析还证实，通过风险模型得到的风险评分可以作为GC患者的独立预后因子。此外，基于风险评分和其他可作为独立预后因子的临床病理特征，我们构建了一个能够准确确定每位患者生存时间的Nomogram。此外，我们使用主成分分析算法构建了一个lncRNA评分，以量化个体肿瘤的DNA甲基化相关lncRNA表达模式。我们发现，较高的lncRNA评分意味着较差的预后，并与较低的肿瘤突变负荷和免疫抑制有关。而较低的lncRNA评分则与新抗原负荷增加以及抗-PDL1/CTLA4免疫疗法反应增加相关。此外，较低的lncRNA评分与显著的治疗优势和临床效益相关。本研究描述了一个与DNA甲基化调控相关的lncRNA标志模型，为GC患者的治疗反应预测和分层提供了新方法。评估个体肿瘤中lncRNA表达模式将有助于加强我们对肿瘤微环境浸润的理解，并指导更有效的免疫治疗策略。© 2023年，作者（们），在 Springer-Verlag GmbH Germany 独家授权下，Springer Nature 的一部分。

LncRNAs and DNA methylation are both key regulators of tumorigenesis and immune regulation. However, the interaction between lncRNA and DNA methylation, their regulation and their clinical and immune relevance in gastric cancer (GC) remain unclear.In this study, we identified DNA methylation regulator-related lncRNAs through Pearson correlation analysis in The Cancer Genome Atlas datasets. Univariate Cox regression was used to screen DNA methylationrelated prognostic lncRNAs. Further, through least absolute shrinkage and selection operator Cox regression, a prognostic model based on 13 lncRNAs was established. Survival analysis and receiver operating characteristic curve analysis verified the accuracy of the model in predicting the survival of GC patients. Univariate and multivariate analyses also confirmed that the risk score obtained from the risk model could be applied as an independent prognostic factor for patients with GC. Furthermore, based on the risk score and other clinicopathological characteristics that can be used as independent prognostic factors, we constructed a nomogram that could accurately determine the survival time of each patient. In addition, a lncRNA score was constructed using a principal component analysis algorithm to quantify the DNA methylation-related lncRNA expression patterns of individual tumors.We found that a higher lncRNA score indicated a worse the prognosis and was associated with a reduced tumor mutation burden and immunosuppression. A low lncRNA score was related to an increase in neoantigen load and an increase in the anti-PDL1/CTLA4 immunotherapy response. Additionally, a low lncRNA score was related to a significant therapeutic advantage and clinical benefit.This study describes a DNA methylation regulator-related lncRNA signature model, which provides a new approach for predicting therapeutic response and patient stratification in GC. Assessing lncRNA expression patterns in individual tumors will contribute to enhancing our understanding of tumor microenvironment infiltration and guide more effective immunotherapy strategies.© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.