MicroRNAs As A Novel Class Of Diagnostic Biomarkers In Detection Of Hepatocellular Carcinoma:a Meta-analysis

Background:Hepatocellular carcinoma (HCC) is the most common malignancy of the liver, the fifth most common cancer, the third leading cause of cancer death worldwide, and the second leading cause of cancer deaths in China. Its incidence and mortality is increasing year by year. The high mortality of HCC is mainly attributed to frequent tumour metastasis and recurrence after surgical intervention. Because of its exact mechanism is still not clear, there is still lack of effective means of prevention and treatment. So it is the most important and urgent issues to explore the molecular mechanisms of metastasis and effective prevention and treatment measures in the field of oncology research.MicroRNAs (miRNAs) are an abundant class of endogenous, highly conserved, noncoding20-23nt small RNAs, that have been shown to regulate gene expression and mediat complex biological processes, including cellular differentiation, apoptosis, metabolism and proliferation through directly binding to the3’-untranslated region (3’UTR) of target mRNAs in a wide range of organisms. Emerging evidence demonstrates that dysregulation of miRNAs is linked to many disease states including cancer and acts as oncogenes or tumour suppressor genes. Recently, correlation between miRNAs expression and tumour metastasis also has aroused widespread concern in several types of cancers. Numerous miRNAs have been shown to play important role in metastasis through regulation of the cell adhesion, matrix degradation, EMT, angiogenesis. MicroRNAs (miRNAs) have been proposed as promising diagnostic biomarkers for many diseases, particularly in the field of cancer research. Numerous studies have explored the use of miRNAs in the detection of hepatocellular carcinoma (HCC), with some reporting inconsistent results.Objective:we conducted this meta-analysis to evaluate the potential diagnostic value of miRNAs in HCC.Search method and collection:All relevant literature was collected from the PubMed and other databases before June3,2014. The summary receiver operator characteristic (SROC) curve and other parameters were used to estimate overall predictive performance.Results:Fourteen studies involving1,848cases with HCC and1,187controls (576healthy controls and611individuals with chronic liver diseases) were included in this meta-analysis. SROC analyses for the diagnostic power of miRNAs yielded an area under the curve (AUC) of0.93with86%sensitivity and86%specificity in discriminating patients with HCC from healthy subjects and an AUC of0.88with79%sensitivity and83%specificity in differentiating patients with HCC from those with chronic liver diseases (CLDs). Furthermore, subgroup analyses showed that miRNA panels yielded excellent diagnostic characteristics, with an AUC of0.99(96%sensitivity and96%specificity) for detection of HCC from healthy controls and an AUC of0.93(85%sensitivity and88%specificity) for HCC from those with CLDs.Conclusion:MiRNAs might be novel potential biomarkers for the diagnosis of HCC, and a combination of multiple miRNAs could significantly improve the diagnostic accuracy.