CircRNAs as promising biomarker in diagnosis of breast cancer: An updated meta-analysis

Abstract

Background: Circular RNAs (circRNAs) have been identified to be involved in onset and progression of multiple malignant tumors. The present study aimed to systematically evaluate the diagnostic values of circRNAs in breast cancer.

Methods: The PubMed, Web of Science, Embase, CNKI, and Wanfang online databases were searched for the relevant studies before December 31, 2020. Statistical analysis of the diagnostic tests was performed based on STATA 16.0, Meta-DiSc 1.4, and RevMan 5.3 software. The threshold effect and publication bias were measured by the Spearman correlation and Deeks' funnel plot asymmetry test, respectively.

Results: Twenty-one studies from 13 articles were included in this meta-analysis. The pooled sensitivity and specificity were 0.77 and 0.71, respectively. The pooled positive likelihood ratio (PLR), negative likelihood ratio (NLR), and overall diagnostic odds ratio (DOR) were 2.6, 0.33, and 8, respectively. Furthermore, the area under the summary receiver operator characteristic curve was 0.80. In addition, down-regulated circRNAs achieved a diagnostic performance higher than up-regulated circRNAs, with area under curve (AUC) values of 0.81 and 0.74, respectively. Studies based on tissue samples presented better diagnostic accuracy than those based on plasma samples, with AUC values of 0.80 and 0.67. In addition, two circRNAs, including circ_0001073 and circTADA2A-E5/E6, showed higher diagnostic values, with AUC value of 0.990 and 0.937, respectively. According to the results of meta-regression, the case size (p<0.05) might be the source of the heterogeneity.

Conclusion: CircRNAs exhibited a high diagnostic value for breast cancer and may function as potential diagnostic biomarkers for breast cancer.

Keywords: biomarker; breast cancer; circular RNA; diagnosis; meta-analysis.

FIGURE 1

Steps for screening eligible articles

FIGURE 2

Quality assessment of eligible studies. “Low” means “at low risk of bias” or having “low concern regarding applicability”; “High” means “at risk of bias” or having “concerns regarding applicability”; and “unclear” means insufficient data for judgment

FIGURE 3

Forest plots of sensitivity and specificity of circRNAs in the diagnosis of breast cancer. (A) Pooled sensitivity for circRNAs. (B) Pooled specificity for circRNAs

FIGURE 4

The summary receiver operator characteristic (SROC) curve of circRNAs in the diagnosis of breast cancer. The study case numbers inside of the graphics represent the corresponding articles we used for the meta‐analysis, which can refer to Table 1

FIGURE 5

Sensitivity analysis to assess the stability results. Sensitivity analysis was performed by omitting each study one by one, and the omitted studies were shown on the left side of the graphics

FIGURE 6

The Deeks’ funnel plot asymmetry test for publication bias. Each point represents a separate study for the indicated association. The study case numbers inside of the graphics represent the corresponding articles we used for meta‐analysis, which can refer to Table 1