The potential diagnostic value of extracellular vesicle miRNA for human non-small cell lung cancer: a systematic review and meta-analysis

ABSTRACT

Background: This meta-analysis aimed to evaluate the diagnostic accuracy of extracellular vesicles (EV) miRNAs for non‐small cell lung cancer (NSCLC).Methods: All eligible studies were searched in an online database. Stata 15.0, Meta-disc 14.0 and Review Manager 5.2 software packages were used to perform all statistical analysis.Results: The analysis included 16 articles and 70 studies. Pooled sensitivity (SEN) and specificity (SPE), positive predictive value and negative predictive value were 0.77 (95% CI: 0.72–0.80), 0.83 (95% CI: 0.78–0.86), 0.88 (95% CI: 0.86–0.90) and 0.63 (95% CI: 0.58–0.68), respectively. The overall diagnostic odds ratio (DOR) was 16 (95% CI: 11–21) and the area under the curve (AUC) was 0.86 (95% CI: 0.83–0.89). 3 EV miRNAs could identify metastatic NSCLC from healthy, and 10 distinguish early-stage NSCLC. The respective targets of EV miR-21, miR-210, and miR-1290 could activate PI3K/AKT-related pathway.Conclusion: EV miRNAs had high diagnostic accuracy (AUC = 0.86) for NSCLC, especially metastatic NSCLC (AUC = 0.90), and early-stage NSCLC (AUC = 0.88). Besides, multitudinous EV miRNAs combined showed higher diagnostic value than alone. EV miR-21, miR-210, and miR-1290 might be associated with PI3K/AKT-related pathway and the valuable diagnostic biomarkers for NSCLC.

KEYWORDS:

• EV miRNAs
• NSCLC
• biomarkers
• diagnosis
• meta-analysis

Notes on contributors

Hairong Huang, Jinyuan Zhu, Yong Lin, Zhexiao Zhang, Jie Liu and Chenfei Wang drafted the manuscript. Hongfu Wu and Tangbin Zou revised the manuscript critically for important intellectual content. All authors read and approved the final manuscript.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer Disclosures

Peer reviewers in this manuscript have no relevant financial or other relationships to disclose.

Supplementary material

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Additional information

Funding

This work was supported by the National Natural Science Foundation of China (81874260), the Natural Science Foundation of Guangdong Province (2019A1515011567) and the Young Innovative Talents Projects of Universities in Guangdong (2018KQNCX097, 4SG19003Gj).