Clinicopathological significance and prognosis of long noncoding RNA SNHG16 expression in human cancers: a meta-analysis

BackgroundRecent studies have highlighted the important role of long non-coding RNA SNHG16 in various human cancers. Here, we conducted a meta-analysis to investigate the effect of SNHG16 expression on clinicopathological features and prognosis in patients with different kinds of human cancers.MethodsWe performed a systematic search in electronic databases including PubMed, EMBASE, Cochrane Library and Web of Science, to investigate the potential association between SNHG16 expression and prognostic significance and clinical features in cancer patients. Odds ratios (ORs) or hazards ratios (HRs) with corresponding 95% confidence intervals (95% CIs) were pooled to estimate the prognosis value of SNHG16 by StataSE 15.0 software.ResultsA total of 16 eligible studies with 1299 patients were enrolled in our meta-analysis. The results revealed that increased expression level of SNHG16 was significantly associated with larger tumor size (OR: 3.357; 95% CI: 2.173-5.185; P<0.001), advanced TNM stage (OR: 2.930; 95% CI: 1.522-5.640; P=0.001) and poor histological grade (OR: 3.943; 95% CI: 1.955-7.952; P<0.001), but not correlated with smoking status (P=0.489), sex (P=0.932), distant metastasis (P=0.052), or lymph node metastasis (P=0.155). Moreover, the pooled HR showed that elevated expression SNHG16 was associated with a significantly poorer overall survival (OS) (HR=1.866, 95% CI: 1.571-2.216, P<0.001). For the set of cancer types, high expression of SNHG16 was significantly associated with shorter OS in patients with cancers of the urinary system (HR: 2.523, 95% CI:1.540-4.133; P <0.001), digestive system (HR: 2.406, 95% CI:1.556-3.721; P <0.001), and other cancers (including glioma and non-small cell lung cancer) (HR: 1.786, 95% CI:1.406-2.267; P <0.001).ConclusionsLncRNA SNHG16 overexpression might serve as an unfavorable prognostic factor, which provides a basis for medical workers to evaluate the prognosis of patients and to help the decision-making process.