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Plasma Extracellular Vesicle miRNAs Can Identify Lung Cancer, Current Smoking Status, and Stable COPD

Authors :
Kwun M. Fong
Hannah E. O’Farrell
Ian A. Yang
Rayleen V. Bowman
Source :
International Journal of Molecular Sciences, Vol 22, Iss 5803, p 5803 (2021), International Journal of Molecular Sciences, Volume 22, Issue 11
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

Lung cancer remains the leading cause of cancer related mortality worldwide. We aimed to test whether a simple blood biomarker (extracellular vesicle miRNAs) can discriminate between cases with and without lung cancer. Methods: plasma extracellular vesicles (EVs) were isolated from four cohorts (n = 20 in each): healthy non-smokers, healthy smokers, lung cancer, and stable COPD participants. EV miRNA expression was evaluated using the miRCURY LNA miRNA Serum/Plasma assay for 179 specific targets. Significantly dysregulated miRNAs were assessed for discriminatory power using ROC curve analysis. Results: 15 miRNAs were differentially expressed between lung cancer and healthy non-smoking participants, with the greatest single miRNA being miR-205-5p (AUC 0.850), improving to AUC 0.993 in combination with miR-199a-5p. Moreover, 26 miRNAs were significantly dysregulated between lung cancer and healthy smoking participants, with the greatest single miRNA being miR-497-5p (AUC 0.873), improving to AUC 0.953 in combination with miR-22-5p<br />14 miRNAs were significantly dysregulated between lung cancer and stable COPD participants, with the greatest single miRNA being miR-27a-3p (AUC 0.803), with two other miRNAs (miR-106b-3p and miR-361-5p) further improving discriminatory power (AUC 0.870). Conclusion: this case control study suggests miRNAs in EVs from plasma holds key biological information specific for lung cancer and warrants further prospective assessment.

Details

Language :
English
ISSN :
16616596 and 14220067
Volume :
22
Issue :
5803
Database :
OpenAIRE
Journal :
International Journal of Molecular Sciences
Accession number :
edsair.doi.dedup.....e0ab040cc27d5cc75e1339fcbfcd593a