ArticleDiscover oncology2024
Neutrophil extracellular traps-related lncRNAs prognostic signature for gastric cancer and immune infiltration: potential biomarkers for predicting overall survival and clinical therapy.
Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Value of the systemic immune inflammation index in predicting the efficacy of neoadjuvant chemotherapy in patients with gastric cancer: a multicenter retrospective clinical study.Journal of gastrointestinal oncology · 2025Article
- The heterogeneous roles of neutrophils in gastric cancer: scaffold or target?Cellular & molecular biology letters · 2025Review
- Bioinformatic analysis indicated that LINC01150 might be a novel neutrophil extracellular traps-related biomarker of gastric cancer.Scientific reports · 2025Article
- Article
- NETs - as predictors and targets of supportive therapy for cancer treatment.Frontiers in immunology · 2025Review
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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