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使用唾液miRNAs表达和临床特征诊断肺癌

Negar Alizadeh¹, Hoda Zahedi¹, Maryam Koopaie²

¹Department of Oral Medicine, School of Dentistry, Tehran University of Medical Sciences, North Kargar St, P.O.BOX:14395 -433, Tehran, 14399-55991, Iran.

BMC pulmonary medicine

|January 25, 2025

概括

唾液微RNAs (miRNAs) 在非侵入性肺癌 (LC) 诊断方面表现有前途. 使用let-7a-2,miR-221和miR-20a的多重逻辑回归 (MLR) 模型在将肺癌亚型与健康对照区分时取得了高准确性.

科学领域:

在瘤学瘤学.
生物标志物生物标志物
分子诊断学分子诊断

背景情况:

肺癌 (LC) 是全球癌症死亡的主要原因.
唾液为生物标志物发现提供一种非侵入性,可访问性和经济高效的生物流体.
唾液中的微RNA (miRNA) 是各种疾病的潜在诊断指标,包括LC.

研究的目的:

为了评估唾液中let-7a-2,miR-221和miR-20a表达在肺癌中的诊断效果.
评估结合这些miRNA的多重逻辑回归 (MLR) 模型在肺癌诊断中的实用性.

主要方法:

从40名肺癌患者 (腺癌和状细胞癌) 和20名健康对照患者收集唾液样本.
使用定量逆转录聚合酶链反应 (RT-qPCR) 来测量miRNA表达水平.
采用接收器操作特征 (ROC) 曲线分析,MLR,主要组件分析和机器学习来评估诊断性能.

主要成果:

与对照组相比,不同肺癌亚型的个别miRNA显示出不同的诊断几率比率 (DOR).
一个结合miR-221,let-7a-2,miR-20a和吸烟状态的MLR模型将小细胞肺癌与肺腺癌区分开来,准确度为0.725 (AUC=0.795).
一个综合的MLR模型包含了唾液小RNA的主要影响和双向相互作用,从健康对照中准确诊断了LUAD和SCLC (0.90准确度,AUC=0.90).

结论:

唾液miRNA表达分析,特别是使用MLR模型,为肺癌提供了一个有希望的非侵入性诊断策略.
这种方法为高危无症状个体提供了潜在的查工具.
这些发现支持唾液miRNAs作为早期肺癌检测生物标志物的临床实用性.

关键词:

生物标志物生物标志物肺部腺癌瘤是肺部腺癌.肺癌是一种肺癌.这是唾液.小细胞肺癌 (small-cell lung carcinoma) 是一种小细胞肺癌.这是一个微型RNA.

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