生物
长非编码RNA
腺癌
核糖核酸
细胞外小泡
肿瘤科
前瞻性队列研究
肺
生物标志物
内科学
胞外囊泡
比例危险模型
队列
预测值
Lasso(编程语言)
放化疗
试验预测值
生物信息学
接收机工作特性
基因间区
癌症研究
小RNA
生存分析
病理
RNA结合蛋白
计算生物学
基因表达谱
签名(拓扑)
肺癌
转录组
生物信息学
小核仁RNA
作者
Rui Meng,Yanjun Gao,Zheng Peng,Hua Chen,Yida Li,Yu Liu,Lanxiao Shen,Huanle Pan,Liangcheng Zheng,Dezhi Cheng,Xiaoming Lin,Weihong Sun,Congying Xie
标识
DOI:10.1186/s12943-025-02524-2
摘要
This study developed and validated a diagnostic signature comprising five small extracellular vesicle (sEV)-derived long RNAs (ATF4, GRAP2, MCL1, PAK2, PIK3CB) for distinguishing early-stage lung adenocarcinoma (LUAD) from benign pulmonary nodules and assessing prognosis in advanced LUAD. Utilizing a multi-center cohort of 698 participants, researchers employed RNA sequencing and quantitative PCR to analyze plasma sEV RNA profiles. Differentially expressed mRNAs and long intergenic non-coding RNAs (lincRNAs) were identified using LASSO regression to construct a diagnostic model. The signature demonstrated high diagnostic accuracy with an area under the curve (AUC) of 0.971 in the validation cohort and 0.950 in the prospective cohort. It also surpassed low-dose CT sensitivity (95.24% vs. 71.43%), specificity (100% vs. 93.96%), positive predictive value (100% vs. 45.45%) and negative predictive value (99.67% vs. 97.90%) in the prospective cohort. In advanced LUAD patients undergoing chemoradiotherapy or PD-L1 inhibitor therapy, lower expression of these RNAs correlated with improved progression-free survival (PFS; HR = 0.38-0.39). The signature integrates non-invasively detected sEV RNAs to complement LDCT, addressing its high false-positive rate, and offers prognostic insights for personalized treatment strategies. These findings highlight the clinical potential of sEV-derived long RNAs in early LUAD detection and precision oncology.
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