Construction of a prognostic model for lung adenocarcinoma based on disulfidptosis-related lncRNAs.

IF 1.5 4区 医学 Q4 ONCOLOGY
Translational cancer research Pub Date : 2025-06-30 Epub Date: 2025-06-27 DOI:10.21037/tcr-2024-2256
Man Sun, Dan Zang, Chen-Guang Liu, Huan Zhou, Jun Chen
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引用次数: 0

Abstract

Background: Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, and it has a high incidence and poor prognosis. Disulfidptosis is a novel form of death induced by disulfide stress caused by excessive intracellular cystine accumulation under glucose starvation conditions. This study investigated the significance of disulfidptosis-related long non-coding RNAs (DRlncRNAs) in the risk assessment and prognosis prediction of LUAD.

Methods: RNA sequencing data and clinical information of LUAD patients were obtained from The Cancer Genome Atlas database. Differentially expressed genes associated with disulfidptosis were screened using univariate Cox regression analysis. A prognostic model was constructed using the least absolute shrinkage and selection operator and the Cox regression analysis to classify patients into high- and low-risk groups. Time-dependent receiver operating characteristic, C-index, and Kaplan-Meier curves were plotted and compared to evaluate the predictive ability of the prognostic model. Functional gene set enrichment analysis (GSEA) and single-sample GSEA were used to explore the characteristics of enrichment pathways, immune-related functions, and treatment response in the high- and low-risk groups.

Results: A risk prognostic model was constructed consisting of eight DRlncRNAs (ATXN1-AS1, AC018645.3, AC096733.2, AL049836.1, LINC01711, AF131215.5, AC027288.1, and AL606489.1). Univariate and multifactorial Cox analyses showed that the model was a prognostic factor independent of multiple clinicopathologic parameters.

Conclusions: The developed 8-lncRNA prognostic model serves as a valid biomarker for predicting LUAD prognosis and provides potential therapeutic insights. Targeting DRlncRNAs may contribute to improved prognosis and guide future therapeutic strategies.

基于二硫肺相关lncrna的肺腺癌预后模型构建
背景:肺腺癌(LUAD)是最常见的肺癌病理类型,发病率高,预后差。二硫中毒是葡萄糖饥饿条件下细胞内胱氨酸积累过多引起的二硫应激引起的一种新型死亡形式。本研究探讨了二硫塌陷相关长链非编码rna (DRlncRNAs)在LUAD风险评估和预后预测中的意义。方法:从The Cancer Genome Atlas数据库获取LUAD患者的RNA测序数据和临床信息。使用单因素Cox回归分析筛选与双翘症相关的差异表达基因。采用最小绝对收缩和选择算子以及Cox回归分析构建预后模型,将患者分为高危组和低危组。绘制并比较随时间变化的受试者工作特征、c指数和Kaplan-Meier曲线,以评估预后模型的预测能力。通过功能基因集富集分析(GSEA)和单样本GSEA,探讨高、低危组的富集途径、免疫相关功能和治疗反应的特点。结果:构建了由8个drlncrna (ATXN1-AS1、AC018645.3、AC096733.2、AL049836.1、LINC01711、AF131215.5、AC027288.1和AL606489.1)组成的风险预后模型。单因素和多因素Cox分析显示,该模型是一个独立于多种临床病理参数的预后因素。结论:建立的8-lncRNA预后模型可作为预测LUAD预后的有效生物标志物,并提供潜在的治疗见解。靶向DRlncRNAs可能有助于改善预后并指导未来的治疗策略。
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来源期刊
CiteScore
2.10
自引率
0.00%
发文量
252
期刊介绍: Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.
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