Diagnostic Accuracy of Exosomal Long Noncoding RNAs in Diagnosis of NSCLC: A Meta-Analysis.

Abstract

Purpose: Globally, non-small cell lung cancer (NSCLC) is the primary cause of cancer-related mortality, both early and accurate diagnosis are essential for effective treatment and improved patient outcomes. Exosomal noncoding RNAs (ncRNAs) have emerged as promising biomarkers for NSCLC diagnosis. This meta-analysis aims to assess the diagnostic accuracy of exosomal long noncoding RNAs (lncRNAs) for diagnosing NSCLC.

Methods: A comprehensive literature search was conducted to identify relevant studies that assessed the diagnostic performance of exosomal lncRNAs in NSCLC. Quality assessment and data extraction were performed independently by two reviewers. Pooled sensitivity, specificity, and other relevant diagnostic parameters were calculated using a bivariate random-effects model. Subgroup analyses and meta-regression were conducted to explore potential sources of heterogeneity.

Results: Sixteen studies, comprising 1843 NSCLC cases and 1298 controls, were included in this meta-analysis. The pooled sensitivity and specificity of nine exosomal lncRNAs for diagnosing NSCLC were 0.74 [95% confidence interval (CI) 0.69-0.79] and 0.78 (95% CI 0.68-0.85). The pooled area under the receiver operating characteristic curve (AUC) for fifteen lncRNAs was 0.80 (95% CI 0.768-0.831). Meta-regression could not find any source for interstudy heterogeneity.

Conclusion: Exosomal lncRNAs, particularly AL139294.1, GAS5, LUCAT1, and SOX2-OT, have excellent diagnostic accuracy and promising diagnostic potential in NSCLC. Therefore, they can be used as diagnostic tools for early detection of NSCLC.