Department of Obstetrics and Gynecology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Biochem Genet. 2024 Apr;62(2):741-760. doi: 10.1007/s10528-023-10443-4. Epub 2023 Jul 10.
Endometrial cancer (EC) is a common group of malignant epithelial tumors that mainly occur in the female endometrium. Lactate is a key regulator of signal pathways in normal and malignant tissues. However, there is still no research on lactate metabolism-related lncRNA in EC. Here, we intended to establish a prognostic risk model for EC based on lactate metabolism-related lncRNA to forecast the prognosis of EC patients. First, we found that 38 lactate metabolism-associated lncRNAs were significantly overall survival through univariate Cox regression analysis. Using minimum absolute contraction and selection operator (LASSO) regression analysis and multivariate Cox regression analysis, six lactate metabolism-related lncRNAs were established as independent predictor in EC patients and were used to establish a prognostic risk signature. We next used multifactorial COX regression analysis and receiver operating characteristic (ROC) curve analysis to confirm that risk score was an independent prognostic factor of overall patient survival. The survival time of patients with EC in different high-risk populations was obviously related to clinicopathological factors. In addition, lactate metabolism-related lncRNA in high-risk population participated in multiple aspects of EC malignant progress through Gene Set Enrichment Analysis, Genomes pathway and Kyoto Encyclopedia of Genes and Gene Ontology. And risk scores were strongly associated with tumor mutation burden, immunotherapy response and microsatellite instability. Finally, we chose a lncRNA SRP14-AS1 to validate the model we have constructed. Interestingly, we observed that the expression degree of SRP14-AS1 was lower in tumor tissues of EC patients than in normal tissues, which was consistent with our findings in the TCGA database. In conclusion, our study constructed a prognostic risk model through lactate metabolism-related lncRNA and validated the model, confirming that the model can be used to predict the prognosis of EC patients and providing a molecular analysis of potential prognostic lncRNA for EC.
子宫内膜癌（EC）是一组常见的恶性上皮性肿瘤，主要发生在女性子宫内膜。乳酸是正常和恶性组织中信号通路的关键调节剂。然而，目前还没有关于 EC 中与乳酸代谢相关的 lncRNA 的研究。在这里，我们旨在基于与乳酸代谢相关的 lncRNA 建立一个 EC 的预后风险模型，以预测 EC 患者的预后。首先，我们通过单因素 Cox 回归分析发现 38 个与乳酸代谢相关的 lncRNA 与总体生存率显著相关。使用最小绝对收缩和选择算子（LASSO）回归分析和多因素 Cox 回归分析，我们建立了 6 个独立预测 EC 患者的与乳酸代谢相关的 lncRNA，并用于建立预后风险特征。我们接下来使用多因素 COX 回归分析和接收器操作特征（ROC）曲线分析来确认风险评分是总患者生存的独立预后因素。不同高危人群 EC 患者的生存时间与临床病理因素明显相关。此外，通过基因集富集分析（Gene Set Enrichment Analysis）、基因组通路（Genomes pathway）和京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Gene Ontology），高风险人群中的与乳酸代谢相关的 lncRNA 参与了 EC 恶性进展的多个方面。风险评分与肿瘤突变负担、免疫治疗反应和微卫星不稳定性密切相关。最后，我们选择了 lncRNA SRP14-AS1 来验证我们构建的模型。有趣的是，我们观察到 EC 患者肿瘤组织中 SRP14-AS1 的表达程度低于正常组织，这与我们在 TCGA 数据库中的发现一致。总之，我们通过与乳酸代谢相关的 lncRNA 构建了一个预后风险模型，并验证了该模型，证实该模型可用于预测 EC 患者的预后，并为 EC 提供了潜在的预后 lncRNA 的分子分析。
