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. 2024 Apr 17:14:1357248.
doi: 10.3389/fonc.2024.1357248. eCollection 2024.

Diagnostic value of exosomal noncoding RNA in lung cancer: a meta-analysis

Affiliations

Diagnostic value of exosomal noncoding RNA in lung cancer: a meta-analysis

Yuxuan Cao et al. Front Oncol. .

Abstract

Background: Lung cancer is one of the most dangerous cancers in the world. Most lung cancer patients are diagnosed in the middle and later stages, which can lead to poor survival rates. The development of lung cancer is often accompanied by abnormal expression of exosomal non-coding RNAs, which means that they have the potential to serve as noninvasive novel molecular markers for lung cancer diagnosis.

Methods: For this study, we conducted a comprehensive literature search in PubMed, Web of science, Science direct, Embase, Cochrane, and Medline databases, and by reviewing published literature, The diagnostic capacity of exosomal microRNAs (miRNAs), long-chain non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) for lung cancer was evaluated. Functional enrichment analysis of miRNA target genes was performed.

Results: The study included 41 papers, a total of 68 studies. More than 60 miRNAs, 9 lncRNAs and 14 circRNAs were involved. The combined sensitivity and specificity were 0.83(95%CI, 0.80~0.86) and 0.83(95% CI,0.79~0.87); 0.71(95% CI,0.68~0.74) and 0.79(95%CI, 0.75~0.82); 0.79(95%CI,0.67~0.87) and 0.81(95%CI,0.74~0.86), and constructed overall subject operating characteristic curves with the summarized area under the curve values of 0.90, 0.82, and 0.86.

Conclusion: Our study shows that exosomes miRNAs, lncRNAs and circRNAs are effective in the diagnosis of lung cancer, providing evidence for studies related to novel lung cancer diagnostic markers.

Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023457087.

Keywords: circRNA; exosome; lncRNA; lung cancer; miRNA.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow chart of literature screening.
Figure 2
Figure 2
Diagnostic efficacy of exosomal miRNA in lung cancer patients. (A) Sensitivity and specificity. (B) Diagnostic likelihood ratios. (C) Diagnostic score and odds ratio. (D) SROC curve.
Figure 3
Figure 3
Diagnostic efficacy of exosomal lncRNA in lung cancer patients. (A) Sensitivity and specificity. (B) Diagnostic likelihood ratios. (C) Diagnostic score and odds ratio. (D) SROC curve.
Figure 4
Figure 4
Diagnostic efficacy of exosomal circRNA in lung cancer patients. (A) Sensitivity and specificity. (B) Diagnostic likelihood ratios. (C) Diagnostic score and odds ratio. (D) SROC curve.
Figure 5
Figure 5
Potential functional enrichment analysis of exosomal miRNA. (A) The downstream target genes of exosomal miRNA were screened from miRWalk, miRDB, TargetScan and mirDIP databases. (B) Target genes were obtained by intersection of differentially expressed genes and miRNA target genes in lung cancer. (C) GO analysis. (D) KEGG analysis.

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