Department of Gastrointestinal Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, People's Republic of China.
Department of Pathology, Daping Hospital, Army Military Medical University, Chongqing, 400042, People's Republic of China.
J Cancer Res Clin Oncol. 2023 Nov;149(16):14745-14760. doi: 10.1007/s00432-023-05234-8. Epub 2023 Aug 17.
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.
lncRNAs 和 DNA 甲基化都是肿瘤发生和免疫调节的关键调节因子。然而，lncRNA 与 DNA 甲基化之间的相互作用、它们的调控以及它们在胃癌（GC）中的临床和免疫相关性仍不清楚。
在本研究中，我们通过 The Cancer Genome Atlas 数据集的 Pearson 相关分析确定了 DNA 甲基化调节相关的 lncRNAs。单因素 Cox 回归用于筛选 DNA 甲基化相关的预后 lncRNAs。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 lncRNAs 的预后模型。生存分析和受试者工作特征曲线分析验证了该模型预测 GC 患者生存的准确性。单因素和多因素分析也证实，从风险模型获得的风险评分可作为 GC 患者的独立预后因素。此外，基于风险评分和其他可作为独立预后因素的临床病理特征，我们构建了一个诺模图，可以准确确定每位患者的生存时间。此外，使用主成分分析算法构建了 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 评分表明预后较差，与肿瘤突变负担降低和免疫抑制有关。较低的 lncRNA 评分与新抗原负荷增加和抗 PD-L1/CTLA4 免疫治疗反应增加有关。此外，较低的 lncRNA 评分与显著的治疗优势和临床获益有关。
本研究描述了一个 DNA 甲基化调节相关的 lncRNA 特征模型，为预测 GC 的治疗反应和患者分层提供了新方法。评估个体肿瘤中的 lncRNA 表达模式将有助于增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。
