Objective: MicroRNAs (miRNAs) have become the focus of most recent efforts in cancer research. However, there have been inconsistencies in the literature regarding the suitability of circulating miRNAs for early detection of gastrointestinal cancers. This study aims to assess the diagnostic performance of circulating miRNAs in detection of gastrointestinal cancer through a meta-analysis.
Methods: Eligible studies were selected by conducting a systematic literature search of public databases. The sensitivity and specificity were used to plot the summary receiver operator characteristic (SROC) curve and calculate the area under the SROC curve (AUC). The between-study heterogeneity was evaluated by Q test and I2 statistics. Subgroup analyses and meta-regression were further performed to explore the potential sources of heterogeneity. All analyses were performed using the STATA 12.0 software.
Results: A total of 107 studies from 42 articles were included for the meta-analysis according to the inclusion criteria. The overall analysis of all gastrointestinal cancers showed that circulating miRNAs have a relatively good diagnostic performance in gastrointestinal cancers, with a sensitivity of 0.75, a specificity of 0.81 and an AUC of 0.85. In addition, subgroup analyses based on different type of miRNA assay suggested that single-miRNA assay displayed a relatively low diagnostic performance with the AUC values of 0.84 for gastric cancer (GC) and 0.79 for colorectal cancer (CRC), while multiple-miRNAs assay significantly improved the diagnosing accuracy with AUC rising to 0.92 for GC and 0.89 for CRC. Another interesting finding was that plasma-based miRNA assay reach a higher accuracy compared with serum-based one for GC, while opposite conclusion was drawn for CRC.
Conclusions: In conclusion, circulating miRNAs, particularly the combination of multiple miRNAs, may present as promising biomarkers for the diagnosis of gastrointestinal cancers. Further large-scale prospective studies are necessary to validate their potential applicability in human cancer diagnosis.