The value of metabolic LncRNAs in predicting prognosis and immunotherapy efficacy of gastric cancer

Frontiers in Oncology

Oncology

Rajan Patel¹  Yi Liu²  Cheng’en Hu³  Peizhun Du³  Guangjian Huang³  Pengcheng Liu³  Shiyu Chen⁴ 

[1] A1 Legend, Privia Health, Gaithersburg, MD, United States;Department of Digestive Disease, Huashan Hospital, Fudan University, Shanghai, China;Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, China;Department of Pathology, Huashan Hospital, Fudan University, Shanghai, China;

关键词: lncRNA;    gastric cancer;    prognosis;    metabolism;    immune microenviroment;   

DOI  :  10.3389/fonc.2022.1019909

 received in 2022-08-15, accepted in 2022-11-29,  发布年份 2023

来源: Frontiers

【 摘 要 】

IntroductionAs a unique feature of malignant tumors, abnormal metabolism can regulate the immune microenvironment of tumors. However, the role of metabolic lncRNAs in predicting the prognosis and immunotherapy of gastric cancer (GC) has not been explored.MethodsWe downloaded the metabolism-related genes from the GSEA website and identified the metabolic lncRNAs. Co-expression analysis and Lasso Cox regression analysis were utilized to construct the risk model. To value the reliability and sensitivity of the model, Kaplan–Meier analysis and receiver operating characteristic curves were applied. The immune checkpoints, immune cell infiltration and tumor mutation burden of low- and high-risk groups were compared. Tumor Immune Dysfunction and Exclusion (TIDE) score was conducted to evaluate the response of GC patients to immunotherapy.ResultsTwenty-three metabolic lncRNAs related to the prognosis of GC were obtained. Three cluster patterns based on metabolic lncRNAs could distinguish GC patients with different overall survival time (OS) effectively (p<0.05). The risk score model established by seven metabolic lncRNAs was verified as an independent prognostic indicator for predicting the OS of GC. The AUC value of the risk model was higher than TNM staging. The high-risk patients were accompanied by significantly increased expression of immune checkpoint molecules (including PD-1, PD-L1 and CTLA4) and increased tumor tolerant immune cells, but significantly decreased tumor mutation burden (TMB). Consistently, TIDE values of low-risk patients were significantly lower than that of high-risk patients.DiscussionThe metabolic lncRNAs risk model can reliably and independently predict the prognosis of GC. The feature that simultaneously map the immune status of tumor microenvironment and TMB gives risk model great potential to serve as an indicator of immunotherapy.

【 授权许可】

Unknown   
Copyright © 2023 Du, Liu, Patel, Chen, Hu, Huang and Liu