Meta-analysis and Database Validation of Exosomal MicroRNAs and Prognosis in Gastric Cancer Patients

• Published in: Current medicinal chemistry
• Main Authors: Liang, Tong, Ding, Chengqing, Yang, Zhong, Da, Mingxu
• Format: Journal Article
• Language: English
• Published: United Arab Emirates 29.07.2025
• Subjects: GEO; meta-analysis; microRNA; Prognosis; Gastric cancer
• ISSN: 1875-533X
• DOI: 10.2174/0109298673356200250612183707

Exosomal microRNAs (miRNAs) have been identified as pivotal regulators in the progression of diverse oncogenic processes. However, the relationship between exosomal miRNAs and the clinicopathological characteristics of gastric cancer (GC) patients remains a subject of debate. The present study was designed to meticulously assess the link between exosomal miRNAs and GC through a meticulous meta-analysis and rigorous database validation. The case-control studies about the relationship between exosomal miRNAs and GC were retrieved from CNKI, SinoMed, Embase, Web of Science, the Cochrane Library and PubMed database. The retrieval time was from inception to November, 2023. Two researchers independently screened the literature, extracted the data and evaluated the quality of the included studies. The meta-analysis of the included literature was conducted by the Stata 12.0 software. The database of Kaplan-Meier plotter predicted that the expression of miRNA was correlated with prognostic value in GC patients. The study protocol has been registered in PROSPERO (CRD42023490351). A total of 24 studies, involving 3490 participants, were included in this analysis. The meta-analysis results indicated that there was no significant decrease in the incidence of clinicopathological parameters associated with exosomal miRNAs in GC patients. However, analysis of the Kaplan-Meier plotter database revealed that high expression levels of hsa-mir-134, hsa-mir-100, hsa-mir-552, hsa-mir-30a, and hsa-mir-23b were associated with poor prognosis in GC patients, with hazard ratios (HRs) of 1.45 (95% confidence interval [CI]: 1.06-1.99, p=0.021), 1.67 (95% CI: 1.23-2.27, p=0.00098), 1.63 (95% CI: 1.11-2.40, p=0.012), 1.56 (95% CI: 1.08-2.26, p=0.017), and 1.52 (95% CI: 1.12-2.06, p=0.0066), respectively. These findings align with prior studies highlighting the role of specific miRNAs in tumor progression but diverge regarding their diagnostic utility for clinicopathological features. Future research should explore the functional mechanisms of these miRNAs in GC biology and validate their prognostic value in larger, diverse cohorts to inform personalized treatment strategies.