Long non-coding RNA NEAT1 overexpression is associated with poor prognosis in cancer patients: a systematic review and meta-analysis

Objectives: Long non-coding RNAs (lncRNAs) are playing important roles in cancer progression and metastasis. Recent studies have demonstrated that the lncRNA, nuclear paraspeckle assembly transcript 1 (NEAT1), was aberrantly up-regulated in various types of cancers and was reported to be associated with unfavorable prognosis in cancer patients. This study examined the relationship between NEAT1 and relevant clinical outcomes. Results: A total of 1354 patients from 11 eligible studies were included in the meta-analysis. The results showed that high expression level of NEAT1 was significantly associated with shorter overall survival in cancer patients (hazard ratio (HR) = 1.53, 95% confidence interval (CI) = 1.36-1.71); in the subgroup analysis, the positive association was also found in patients with hepato-gastroenterol cancers (HR = 1.79, 95% CI = 1.48-2.16), non-small cell lung cancer (HR = 1.35, 95% CI = 1.04-1.76), ovarian cancer (HR = 1.41, 95% CI = 1.11-1.79) and other types of cancers (HR = 1.42, 95% CI = 1.11-1.81). The clinicopathological parameters analysis further showed that increased expression level of NEAT1 was positively correlated with larger tumor size (odds ratio (OR) = 1.74, 95% CI = 1.26-2.41), lymph node metastasis (OR = 2.29, 95% CI = 1.71-3.06), advanced TNM stage (OR = 3.60, 95% CI = 2.27-5.72), poor tumor differentiation (OR = 2.16, 95% CI = 1.58-2.93), distant metastasis (OR = 3.51, 95% CI = 1.75-7.01), and invasion depth (OR = 1.94, 95% CI = 1.36-2.75). Materials and Methods: A comprehensive search was performed in Pubmed, Embase, Web of Science and CNKI databases, and eligible studies were included based on defined exclusion and inclusion criteria to perform meta-analysis. Conclusions: The meta-analysis results from present study suggested that increased expression level of NEAT1 was associated with unfavorable prognosis and may serve as a predictive factor for clinicopathological features in various cancers.