In Silico screening of circulating tumor DNA, circulating microRNAs, and long non-coding RNAs as diagnostic molecular biomarkers in ovarian cancer: A comprehensive meta-analysis

Linlin Zhang, Chenyan Hu, Zhongping Huang, Zhijia Li, Qin Zhang and Yang He

PLOS ONE, 2021, vol. 16, issue 4, 1-19

Abstract: Background: Ovarian cancer (OC) is a leading cause of death in gynecological malignancies worldwide. Multitudinous studies have suggested the potential of circulating tumor DNA (ctDNA), circulating microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) as novel diagnostic molecular biomarkers for OC. Here, we include three updated meta-analysis methods using different molecular biomarkers to evaluate their discriminative value in OC diagnosis. Methods: We conducted three meta-analyses after searching different databases, and 23 eligible articles, including 8 concerning ctDNA, 11 concerning miRNAs, and 4 concerning lncRNAs, were found. Further, we pooled data concerning the sensitivity, specificity, and other indicators of accuracy for ctDNA/miRNAs/lncRNAs in the diagnosis of OC. The heterogeneity was further explored by meta-regressions and subgroup analyses, and Deeks’ funnel plots were used to measure the publication bias of these three meta-analyses. Results: In all, this meta-analysis included 1732 OC patients and 3958 controls. The sensitivity of ctDNA for OC diagnosis was superior to that of lncRNA and miRNA (84% vs. 81% vs. 78%). Moreover, the specificity and area under the receiver-operating characteristic (ROC) curve (AUC) of ctDNA were 91% and 94%, which were significantly higher than those of miRNA and lncRNAs (78% and 85%; 78% and 86%, respectively). No significant difference was observed among the two meta-analyses of ctDNA and lncRNA (P > 0.05) with regard to publication bias, while the meta-analysis of miRNA observed a significantly small publication bias (P

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0250717

DOI: 10.1371/journal.pone.0250717

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