Plasma extracellular vesicle microRNAs for pulmonary ground‐glass nodules. Issue 1 (18th September 2019)

• Record Type: Journal Article
• Authors: Zhang, Jia‐Tao; Qin, Hao; Cheung, Fiona Ka Man; Su, Jian; Zhang, Da‐Dong; Liu, Shi‐Yi; Li, Xiao‐Fang; Qin, Jing; Lin, Jun‐Tao; Jiang, Ben‐Yuan; Dong, Song; Liao, Ri‐Qiang; Qiang, Nie; Yang, Xue‐Ning; Tu, Hai‐Yan; Zhou, Qing; Yang, Jin‐Ji; Zhang, Xu‐Chao; Zhang, Ya‐Nan; Wu, Yi‐Long; Zhong, Wen‐Zhao
• Is Part Of: Journal of extracellular vesicles. Volume 8:Issue 1(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-09-18
• Subjects: Ground‐glass nodule -- extracellular vesicles -- microRNA -- biomarker -- support vector machine; Cells -- Mechanical properties -- Periodicals; Transport Vesicles; Cells -- Mechanical properties; Periodicals; Fulltext; Internet Resources; Periodicals; Electronic journals; Periodicals; 571.63
• DOI: 10.1080/20013078.2019.1663666
• Languages: English
• ISSNs: 2001-3078

Abstract

ABSTRACT: In this study, we evaluated the diagnostic value and molecular characteristics of plasma extracellular vesicles (EVs)‐derived miRNAs for patients with solitary pulmonary nodules (SPNs), particularly ground‐glass nodules (GGNs). This study was registered at www.clinicaltrials.gov under registration number NCT03230019. Small RNA sequencing was performed to assess plasma EVs miRNAs in 59 patients, including 12 patients with benign nodules (2017, training set). MiRNA profiles of 40 an additional individuals were sequenced (2018, validation set). Overall, 16 pure GGNs, 21 mixed GGNs, and 42 solid nodules were included, with paired post‐operative plasma samples available for 20 patients. The target miRNA/reference miRNA ratio was used to construct a support vector machine (SVM) model. The SVM model with the best specificity showed 100% specificity in both the training and validation sets independently. The model with the best sensitivity showed 100% and 96.9% sensitivity in the training and validation sets, respectively. Principal component analysis revealed that pure GGN distributions were distinct from those of solid nodules, and mixed GGNs had a diffuse distribution. Among differentially expressed miRNAs, miR‐500a‐3p, miR‐501‐3p, and miR‐502‐3p were upregulated in tumor tissues and enhanced overall survival. The SVM classifier accurately distinguished malignant GGNs and benign nodules. The distinct profile characteristics of miRNAs provided insights into the feasibility of EVs miRNAs as prognostic factors in lung cancer.