综合性血和外体长非编码RNA分析对诊断非小细胞肺癌具有前景
Na Wang1,2, Cong Yao3, Changliang Luo1,4
1Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, P.R. China.
Clinical chemistry and laboratory medicine
|June 30, 2023
概括
使用循环长非编码RNA (lncRNAs) 的新诊断模型显示了早期非小细胞肺癌 (NSCLC) 检测的前景. 这种基于生物标志物的方法为改善NSCLC诊断和患者结果提供了潜在的工具.
科学领域:
- 在瘤学瘤学.
- 分子生物学分子生物学
- 生物标志物发现发现
背景情况:
- 非小细胞肺癌 (NSCLC) 是最常见的肺癌类型,早期诊断对于改善生存率至关重要.
- 目前对NSCLC的诊断方法缺乏足够的灵敏度和特异性,突出了对新型有效生物标志物的需求.
- 循环长非编码RNAs (lncRNAs) 已成为潜在的生物标志物,因为它们的稳定性和存在于体液中.
研究的目的:
- 开发和验证一种有效的NSCLC诊断模型,利用循环中的lncRNAs的组合.
- 在血和外体中识别特定的lncRNAs,它们在NSCLC患者中表达的差异化.
- 在临床样本中评估开发的多标志物模型的诊断性能.
主要方法:
- 在NSCLC中放松调节的lncRNA被识别使用基因表达综合 (GEO) 和癌症基因组图谱 (TCGA) 数据库的数据.
- 候选lncRNAs的差异表达在NSCLC患者的血和外体样本中得到了验证.
- 使用LASSO和后勤回归分析来选择关键生物标志物并构建一个多标志物诊断模型,使用ROC曲线,校准图和决策曲线分析进行评估.
主要成果:
- 在组织,血和外体样本中一致确定了三个lncRNA (PGM5-AS1,SFTA1P和CTA-384D8.35).
- 开发了一种多标志物模型,包括血和外体 lncRNA,以及传统的瘤标志物 (CEA,CA125,SCC,NSE).
- 最终的诊断模型在训练和验证组中都表现出NSCLC的高预测能力,达到0.97.9的曲线下面面积 (AUC).
结论:
- 基于循环lncRNA和其他生物标志物的诊断模型显示了NSCLC检测的巨大潜力.
- 开发的模型在临床环境中表现出强大的预测能力,提供了一个有前途的非侵入性诊断工具.
- 这项研究通过识别和应用新的循环生物标志物,有助于提升早期NSCLC诊断.
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