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标题：Development of a serum miRNA panel for detection of early stage non-small cell lung cancer
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作者：Lisha Ying ; Lingbin Du ; Ruiyang Zou 等
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2020
卷号：117
期号：40
页码：25036-25042
DOI：10.1073/pnas.2006212117
出版社：The National Academy of Sciences of the United States of America
摘要：Minimally invasive testing for early detection of lung cancer to improve patient survival is a major unmet clinical need. This study aimed to develop and validate a serum multi-microRNA (multimiR) panel as a minimally invasive test for early detection of nonsmall cell lung cancer (NSCLC) regardless of smoking status, gender, and ethnicity. Our study included 744 NSCLC cases and 944 matched controls, including smokers and nonsmokers, male and female, with Asian and Caucasian subjects. Using RT-qPCR and a tightly controlled workflow, we quantified the absolute expression of 520 circulating microRNAs (miRNAs) in a Chinese cohort of 180 early stage NSCLC cases and 216 healthy controls (male smokers). Candidate biomarkers were verified in two case-control cohorts of 432 Chinese and 218 Caucasians, respectively (including females and nonsmokers). A multimiR panel for NSCLC detection was developed using a twofold cross-validation and validated in three additional Asian cohorts comprising 642 subjects. We discovered 35 candidate miRNA biomarkers, verified 22 of them, and developed a five-miR panel that detected NSCLC with area under curve (AUC) of 0.936–0.984 in the discovery and verification cohorts. The panel was validated in three independent cohorts with AUCs of 0.973, 0.916, and 0.917. The sensitivity of five-miR test was 81.3% for all stages, 82.9% for stages I and II, and 83.0% for stage I NSCLC, when the specificity is at 90.7%. We developed a minimally invasive five-miR serum test for detecting early stage NSCLC and validated its performance in multiple patient cohorts independent of smoking status, gender, and ethnicity.
关键词：blood biomarker ; microRNA ; early detection