The prognostic value of long noncoding RNA SNHG16 on clinical outcomes in human cancers: a systematic review and meta-analysis

Abstract

Background: Cancer has been a worldwide health problem with a high risk of morbidity and mortality, however ideal biomarkers for effective screening and diagnosis of cancer patients are still lacking. Small nucleolar RNA host gene 16 (SNHG16) is newly identified lncRNA with abnormal expression in several human malignancies. However, its prognostic value remains controversial. This meta-analysis aimed to synthesize available data to clarify the association between SNHG16 expression levels and clinical prognosis value in multiple cancers. Methods: Extensive literature retrieval was conducted to identify eligible studies, and data regarding SNHG16 expression levels on survival outcomes and clinicopathological features were extracted and pooled for calculation of the hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs). Forest plots were applied to show the association between SNHG16 expression and survival prognosis. Additionally, The Cancer Genome Atlas (TCGA) dataset was screened and extracted for validation of the results in this meta-analysis. Results: A total of eight studies comprising 568 patients were included in the final meta-analysis according to the inclusion and exclusion criteria. In the pooled analysis, high SNHG16 expression significantly predicted worse overall survival (OS) in various cancers (HR = 1.87, 95% CI 1.54-2.26, P < 0.001), and recurrence-free survival (RFS) in bladder cancer (HR = 1.68, 95% CI 1.01-2.79, P = 0.045). Meanwhile, stratified analyses revealed that the survival analysis method, tumor type, sample size, and cutoff value did not alter the predictive value of SNHG16 for OS in cancer patients. In addition, compared to the low SNHG16 expression group, patients with high SNHG16 expression were more prone to worse clinicopathological features, such as larger tumor size, advanced clinical stage, lymph node metastasis (LNM) and distant metastasis (DM). Exploration of TCGA dataset further validated that the upregulated SNHG16 expression predicted unfavorable OS and disease-free survival (DFS) in cancer patients. Conclusions: The present study implicated that aberrant expression of lncRNA SNHG16 was strongly associated with clinical survival outcomes in various cancers, and therefore might serve as a promising biomarker for predicting prognosis of human cancers.

The predictive value of lncRNA MIR31HG expression on clinical outcomes in patients with solid malignant tumors

“…Moreover, the P values for Begg's and Egger's test were 0.533 and 0.111, respectively, also indicating the absence of publication bias. Furthermore, the relationships between expression of MIR31HG and OS/DFS in lung cancers were validated in TCGA and GTEx dataset by using GEPIA as previously described [11]. The results indicated that high MIR31HG expression was correlated with significant shorter OS (HR = 1.3, P = 0.012), but not DFS (HR = 0.99, P = 0.96) ( Fig.…”

“…HRs (ORs) and 95% CIs were obtained from the original texts in eligible studies as provided. If not, Engauge Digitizer (version 4.1) would be used to calculate the HR through K-M survival curve as previously described [11].…”

“…Accumulating evidences have showed that aberrant expression of lncRNA could drive tumor phenotypes, including initiation, invasion, and metastasis, via interacting with other cellular macromolecules [9]. More recently, emerging lncRNAs have been identified and characterized as crucial factors in tumorigenesis, with certain reports highlighting them as biomarkers and targets in various cancers, such as breast cancer antiestrogen resistance 4 (BCAR4) [10], small nucleolar RNA host gene 16 (SNHG16) [11], and TTN antisense RNA 1 (TTN-AS1) [12].…”

The predictive value of lncRNA MIR31HG expression on clinical outcomes in patients with solid malignant tumors

“…Furthermore, the relationships between expression of MIR31HG and OS/ DFS in lung cancers were validated in TCGA and GTEx dataset by using GEPIA as previously described (11). The results indicated that high MIR31HG expression was correlated with significant shorter OS (HR=1.3, were not noted.…”

“…Accumulating evidences have showed that aberrant expression of lncRNA could drive tumor phenotypes, including initiation, invasion, and metastasis, via interacting with other cellular macromolecules (9). More recently, emerging lncRNAs have been identified and characterized as crucial factors in tumorigenesis, with certain reports highlighting them as biomarkers and targets in various cancers, such as breast cancer anti-estrogen resistance 4 (BCAR4) (10), small nucleolar RNA host gene 16 (SNHG16) (11), and TTN antisense RNA 1 (TTN-AS1) (12).…”