Abstract

Background: Numerous studies reported that RAS-association domain family 1 isoform A (RASSF1A) methylation might act as diagnostic biomarker for breast cancer (BC), this meta-analysis aimed to evaluate the value of RASSF1A methylation for diagnosing BC.Methods: Such databases as PubMed, Cochrane Library and Web of Science databases were searched for literatures until May 2019. A meta-analysis was performed utilizing STATA and Revman softwares. Furthermore, subgroup analysis was adopted to determine likely sources of heterogeneity.Results: Totally 19 literatures with 1849 patients and 1542 controls were included in the present study. Sensitivity, specificity, diagnostic odds ratio (DOR) and the area under the summary receiver operating characteristic curve (AUC) of RASSF1A methylation for diagnosing BC were 0.49, 0.95, 19.0 and 0.83, respectively. The sensitivity (0.54 vs 0.43), DOR (30.0 vs 10.0) and AUC (0.84 vs 0.81) of RASSF1A methylation in Caucasian were higher than other ethnicities. The sensitivity (0.64 vs 0.57), DOR (21.0 vs 14.0) and AUC (0.89 vs 0.86) of methylation-specific PCR (MSP) were superior to other methods (q-MSP, OS-MSP and MethyLight). The sensitivity, DOR and AUC of serum RASSF1A methylation vs RASSF1A methylation in other samples (tissue or plasma) were 0.55 vs 0.40, 22.0 vs 14.0 and 0.86 vs 0.74, respectively.Conclusions: RASSF1A methylation might be a potential diagnostic biomarker for BC. Considering its low sensitivity and high specificity, it should combine with others to upgrade the sensitivity. Besides, under such conditions, MSP detection, serum RASSF1A methylation and Caucasian are shown to be more effective and suitable for diagnosing BC.

Highlights

  • Received: 09 April 2019Revised: 06 June 2019Accepted: 12 June 2019Accepted Manuscript Online: Version of Record published: Breast cancer (BC) is the most popular cancer and the most common reason for cancer death in female worldwide [1]

  • 874 literatures were excluded as they did not satisfy the inclusion criteria: 269 literatures were excluded owing to duplication, 443 literatures were excluded after screening the title and abstract; 162 literatures were excluded after assessing the full-text,19 literatures were included in this meta-analysis (Figure 1)

  • Three literatures analyzed two different studies and eventually 22 studies were included in the meta-analysis

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Summary

Methods

Such databases as PubMed, Cochrane Library and Web of Science databases were searched for literatures until May 2019. Subgroup analysis was adopted to determine likely sources of heterogeneity

Results
Conclusions
Introduction
Method
Discussion

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