Abstract
Background
Exosomal microRNAs (miRNAs) are proposed to be excellent candidate biomarkers for clinical applications. However, little is known about their potential value as diagnostic biomarkers for metastatic non-small cell lung cancer (NSCLC).
Methods
In this study, microarrays were used to determine distinct miRNA profiles of plasma exosomes in a discovery cohort of healthy donors, metastatic NSCLC and nonmetastatic NSCLC patients. Three potential candidate miRNAs were selected based on the differential expression profiles. The discovery set data were validated by quantitative real-time polymerase chain reaction using a validation cohort.
Results
NSCLC patients (n = 80) and healthy controls (n = 30) had different exosome-related miRNA profiles in plasma. Results demonstrated that the level of let-7f-5p was decreased in plasma exosomes of NSCLC patients (p < 0.0001). Further analysis of three differentially expressed miRNAs revealed that miR-320a, miR-622 and let-7f-5p levels could significantly segregate patients with metastatic NSCLC from patients with nonmetastatic NSCLC (p < 0.0001, p < 0.0001 and p = 0.023, respectively). In addition, the combination of let-7f-5p, CEA and Cyfra21-1 generated an area under the curve (AUC) of 0.981 for the diagnosis of NSCLC patients, and the combination of miR-320a, miR-622, CEA and Cyfra21-1 had an AUC of 0.900 for the diagnosis of patients with metastatic NSCLC.
Conclusions
This novel study demonstrated that plasma exosomal miRNAs are promising noninvasive diagnostic biomarkers for metastatic NSCLC.
Acknowledgments
We thank all authors for contributing to the intellectual content of this paper and meeting the following requirements that significant contributions to the conception and design, acquisition of data or analysis and interpretation of data and drafting or revising the article for intellectual content.
Author contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following requirements that significant contributions to the conception and design, acquisition of data or analysis and interpretation of data and drafting or revising the article for intellectual content. All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: This work was supported by the National Natural Science Foundation of P.R. China (funder id: http://dx.doi.org/10.13039/501100001809, 81773237 and 81672104), the Shandong Provincial Key Research and Development Program (2017GSF18183, 2017CXGC1207 and 2016GSF201151) and the Medicine and Health Science Technology development program of Shandong province (2017WS001).
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
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Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2019-1329).
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