Shenglan Huang, Kan Liu, Queling Liu, Si Tao, Hua Wang
{"title":"Comprehensive analysis of ferroptosis-related long non-coding RNA and its association with tumor progression and ferroptosis in gastric cancer.","authors":"Shenglan Huang, Kan Liu, Queling Liu, Si Tao, Hua Wang","doi":"10.1186/s12876-025-03951-7","DOIUrl":null,"url":null,"abstract":"<p><p>Gastric cancer (GC) is one of the most common malignant tumors with a poor prognosis. Ferroptosis is an distinct type of non-apoptotic cell death that is closely associated with tumor prognosis. Thus, we aimed to develop an novel prognosis risk model based on ferroptosis-related lncRNAs and excavate novel diagnostic markers. In this study, eight ferroptosis-related lncRNAs were obtained for constructing the prognosis model in GC based on TCGA database. The patients in the high-risk group had worse survival than those in the low-risk group, and the risk-grouping could be used as an independent prognostic factor for OS. Receiver operating characteristic curve analysis demonstrated this risk model was superior to traditional clinicopathological features in predicting GC prognosis. GSEA revealed that these lncRNAs were mainly involved in cell adhesion, cancer pathways, and immune function regulation. The key gene HAGLR of this risk signature was up-regulated in GC tissues and cells. Function assays showed that knockdown of HAGLR could effectively inhibit the GC cells proliferation and migration, whereas silencing HAGLR accelerated apoptosis and ferroptosis cell death process. In conclusion, we established a novel ferroptosis-related prognostic risk signature including eight lncRNAs, which may improve prognostic predictive accuracy for patients with GC.</p>","PeriodicalId":9129,"journal":{"name":"BMC Gastroenterology","volume":"25 1","pages":"349"},"PeriodicalIF":2.5000,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12063400/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Gastroenterology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12876-025-03951-7","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Gastric cancer (GC) is one of the most common malignant tumors with a poor prognosis. Ferroptosis is an distinct type of non-apoptotic cell death that is closely associated with tumor prognosis. Thus, we aimed to develop an novel prognosis risk model based on ferroptosis-related lncRNAs and excavate novel diagnostic markers. In this study, eight ferroptosis-related lncRNAs were obtained for constructing the prognosis model in GC based on TCGA database. The patients in the high-risk group had worse survival than those in the low-risk group, and the risk-grouping could be used as an independent prognostic factor for OS. Receiver operating characteristic curve analysis demonstrated this risk model was superior to traditional clinicopathological features in predicting GC prognosis. GSEA revealed that these lncRNAs were mainly involved in cell adhesion, cancer pathways, and immune function regulation. The key gene HAGLR of this risk signature was up-regulated in GC tissues and cells. Function assays showed that knockdown of HAGLR could effectively inhibit the GC cells proliferation and migration, whereas silencing HAGLR accelerated apoptosis and ferroptosis cell death process. In conclusion, we established a novel ferroptosis-related prognostic risk signature including eight lncRNAs, which may improve prognostic predictive accuracy for patients with GC.
期刊介绍:
BMC Gastroenterology is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of gastrointestinal and hepatobiliary disorders, as well as related molecular genetics, pathophysiology, and epidemiology.