Abstract
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.