Department of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland.
Medical University of Gdansk, Gdansk, Poland.
J Mol Diagn. 2024 Jan;26(1):37-48. doi: 10.1016/j.jmoldx.2023.09.010. Epub 2023 Oct 20.
Several panels of circulating miRNAs have been reported as potential biomarkers of early lung cancer, yet the overlap of components between different panels is limited, and the universality of proposed biomarkers has been minimal across proposed panels. To assess the stability of the diagnostic potential of plasma miRNA signature of early lung cancer among different cohorts, a panel of 24 miRNAs tested in the frame of one lung cancer screening study (MOLTEST-2013, Poland) was validated with material collected in the frame of two other screening studies (MOLTEST-BIS, Poland; and SMAC, Italy) using the same standardized analytical platform (the miRCURY LNA miRNA PCR assay). On analysis of selected miRNAs, two associated with lung cancer development, miR-122 and miR-21, repetitively differentiated healthy participants from individuals with lung cancer. Additionally, miR-144 differentiated controls from cases specifically in subcohorts with adenocarcinoma. Other tested miRNAs did not overlap in the three cohorts. Classification models based on neither a single miRNA nor multicomponent miRNA panels (24-mer and 7-mer) showed classification performance sufficient for a standalone diagnostic biomarker (AUC, 75%, 71%, and 53% in MOLTEST-2013, SMAC, and MOLTEST-BIS, respectively, in the 7-mer model). The performance of classification in the MOLTEST-BIS cohort with the lowest contribution of adenocarcinomas was increased when only this cancer type was considered (AUC, 60% in 7-mer model).
已有多个循环 miRNA 面板被报道为早期肺癌的潜在生物标志物,但不同面板之间的组成部分重叠有限,且不同面板中提出的生物标志物的普遍性也很低。为了评估不同队列中早期肺癌血浆 miRNA 特征的诊断潜力的稳定性,在一项肺癌筛查研究(波兰的 MOLTEST-2013)框架中测试的 24 个 miRNA 面板,使用相同的标准化分析平台(miRCURY LNA miRNA PCR 测定法),在另外两项筛查研究(波兰的 MOLTEST-BIS 和意大利的 SMAC)中收集的材料中进行了验证。对选定的 miRNA 进行分析,与肺癌发生相关的两个 miRNA(miR-122 和 miR-21)可重复性地将健康参与者与肺癌患者区分开来。此外,miR-144 特异性地在腺癌亚组中区分了对照组和病例组。其他测试的 miRNA 在三个队列中没有重叠。基于单个 miRNA 或多成分 miRNA 面板(24 -mer 和 7-mer)的分类模型均未显示出足够的分类性能,无法作为独立的诊断生物标志物(AUC 分别为 75%、71%和 53%,在 7-mer 模型中,MOLTEST-2013、SMAC 和 MOLTEST-BIS)。当仅考虑这种癌症类型时,MOLTEST-BIS 队列中分类性能(7-mer 模型中的 AUC 为 60%)有所提高,该队列中腺癌的贡献最低。