Meta-analysis Identifies The Potential Value Of MicroRNAs That Diagnose Gastric Cancer

[Background]Gastric cancer has been identified as one of the most common malignancies.In recent years,the incidence and mortality of gastric cancer are still high in the world,especially in east Asia,where the incidence is relatively higher.Due to the lack of typical symptoms and diagnostic methods in the early stage,most gastric cancer patients are diagnosed in the middle and late stage,with poor treatment effect and prognosis.The 5-year survival rate is significantly lower than that of patients with early gastric cancer.Thus,it is particularly necessary to find a technique for the early diagnosis of gastric cancer.Many studies on the molecular mechanism of gastric cancer have shown that micro RNAs are involved in the development of tumors by regulating the expression of oncogenes and tumor suppressor genes,which makes it a potential molecular marker for the early diagnosis of gastric cancer and even a potential new target for drug development.Earlier recognition of the diagnostic value of micro RNA in gastric cancer as well as early clinical application will provide new ideas for the diagnosis and treatment of gastric cancer.[Objective]We comprehensively searched literature about micro RNA and the diagnosis of gastric cancer,and evaluated the diagnostic value of micro RNA in gastric cancer systematically by summarizing and analyzing existing studies.This study aims to provide theoretical basis for the further search of new molecular markers for the diagnosis of gastric cancer.[Method]In order to understand the relationship between micro RNA and the diagnosis of gastric cancer,we comprehensively searched all literature about micro RNA and the diagnosis of gastric cancer published before January 2020 from English databases such as Pub Med and Embase.We selected appropriate studies according to inclusion criteria and exclusion criteria.The quality of the studies was scored with the Quality Assessment of Diagnostic Accuracy Studies(QUADAS).And relevant data in the literature were extracted,including the first author,published year,country,the sample size and mean age of the gastric cancer group and control group,the types and number of micro RNA samples,the sensitivity and specificity,etc.The statistical analysis were performed by STATA(version 15.0).The pooled sensitivity and specificity,diagnostic odds ratio(DOR)and area under the curve(AUC)were calculated to evaluate the diagnostic value of micro RNA.The Subgroup analysis was conducted to explore the possible sources of heterogeneity and publication bias analysis was published to evaluate the stability of the results.[Result]A total of 53 studies were included in this study,including 4341 gastric cancer patients and 3389 controls.And a total of 89 micro RNAs were included in the analysis.All of studies were included in this meta-analysis.The diagnostic value of micro RNA in gastric cancer was systematically evaluated.The results showed a pooled sensitivity of 0.77(95%CI: 0.74-0.80)and specificity of 0.82(95%CI: 0.79-0.85),with the diagnostic odds ratio(DOR)of 15.22(95%CI: 12.27-18.89).The corresponding area under the curve(AUC)was 0.86.The results of subgroup analysis based on the sample size of gastric cancer group showed that the studies with a large sample size had better diagnostic efficacy and higher diagnostic accuracy.According to the types of micro RNA samples,the subgroup of serum micro RNA had the highest diagnostic value in gastric cancer.And the subgroup analysis performed according to the number of micro RNA samples showed that the micro RNA combination analysis provided a more satisfactory diagnostic efficacy.According to the subgroup analysis of micro RNA expression,there was no significant difference in the accuracy of diagnosis between the high-expression group and the low-expression group.[Conclusion]Micro RNAs have important value in the diagnosis of gastric cancer.The Serum-based micro RNA detection is more effective than plasma or whole blood.The micro RNA combination analysis has a more satisfactory diagnostic efficacy than single micro RNA analysis.