Suppr超能文献

用于胃癌和免疫浸润的中性粒细胞胞外诱捕网相关长链非编码RNA预后特征:预测总生存期和临床治疗的潜在生物标志物

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

作者信息

Yang Shuhan, Liang Jiahui, Wang Xin, Qi Yijun, Chan Shixin, Song Yonghu, Pei Xiaohan, Ren Zhiyao

机构信息

Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 218 JiXi Avenue, Hefei, 230022, Anhui, People's Republic of China.

Faculty of Medicine and Health Sciences, Ghent University, 9000, Ghent, Belgium.

出版信息

Discov Oncol. 2024 Jul 19;15(1):291. doi: 10.1007/s12672-024-01164-0.

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.

摘要

胃癌(GC)是世界上最常见的消化道恶性肿瘤之一。在初次诊断时,它常常伴有局部或远处转移,导致患者预后不良。中性粒细胞胞外陷阱(NETs)是中性粒细胞采用的一种机制,与肿瘤进展、预后以及对免疫治疗和化疗的反应密切相关。尽管如此,NETs相关的长链非编码RNA(lncRNAs)在胃癌中的具体作用仍不清楚。通过相关性分析、COX回归分析和最小绝对收缩和选择算子回归(LASSO)分析构建了NETs相关lncRNAs的预后模型。使用Kaplan-Meier生存曲线、受试者工作特征(ROC)曲线评估该模型的预测性能,以促进对胃癌发病与预后关系的探索。此外,还分析了高风险组和低风险组胃癌患者肿瘤微环境及对免疫治疗反应的差异。此外,还开发了一个将风险评分与相关临床病理参数相结合的预后列线图。本研究中源自NETs相关lncRNAs的胃癌预后预测模型具有强大的预后能力,可作为传统肿瘤分期的有价值辅助手段。该模型有望为胃癌的精准治疗提供新的指导方针,从而有可能改善患者预后。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c31/11264613/93c76b39a8c4/12672_2024_1164_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验