Neutrophil extracellular traps-related lncRNAs prognostic signature for gastric cancer and immune infiltration: potential biomarkers for predicting overall survival and clinical therapy

被引:3
作者
Yang, Shuhan [1 ]
Liang, Jiahui [1 ]
Wang, Xin [2 ]
Qi, Yijun [1 ]
Chan, Shixin [1 ]
Song, Yonghu [1 ]
Pei, Xiaohan [3 ,4 ]
Ren, Zhiyao [2 ]
机构
[1] Anhui Med Univ, Affiliated Hosp 1, Dept Gen Surg, 218 JiXi Ave, Hefei 230022, Anhui, Peoples R China
[2] Univ Ghent, Fac Med & Hlth Sci, B-9000 Ghent, Belgium
[3] Univ Sci & Technol China, Affiliated Hosp 1, Dept Pathol, Div Life Sci & Med, Hefei 230036, Anhui, Peoples R China
[4] Univ Sci & Technol China, Intelligent Pathol Inst, Div Life Sci & Med, Hefei 230036, Anhui, Peoples R China
关键词
Gastric cancer; Neutrophil extracellular traps; LncRNA; Prognostic model; Bioinformatics; CELLS; RNAS;
D O I
10.1007/s12672-024-01164-0
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Gastric cancer (GC) is one of the most common digestive tract malignant tumors in the world. At the time of initial diagnosis, it frequently presents with local or distant metastasis, contributing to poor prognosis in patients. Neutrophil extracellular traps (NETs) constitute a mechanism employed by neutrophils that is intricately associated with tumor progression, prognosis, and response to immunotherapy and chemotherapy. Despite this, the specific involvement of NETs-related long non-coding RNAs (lncRNAs) in gastric cancer remains unclear. A prognostic model for NETs-related lncRNAs was constructed through correlation analysis, COX regression analysis, and least absolute shrinkage and selection operator regression (LASSO) analysis. The predictive performance of the model was assessed using Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, facilitating the exploration of the relationship between disease onset and prognosis in gastric cancer. Additionally, differences in the tumor microenvironment and response to immunotherapy among gastric cancer patients across high- and low-risk groups were analyzed. Furthermore, a prognostic nomogram integrating the risk score with relevant clinicopathological parameters was developed. The prognostic prediction model for gastric cancer, derived from NETs-related lncRNAs in this study, demonstrates robust prognostic capabilities, serving as a valuable adjunct to traditional tumor staging. This model holds promise in offering novel guidelines for the precise treatment of gastric cancer, thereby potentially improving patient outcomes.
引用
收藏
页数:18
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