title: Long non-coding RNA NEAT1 overexpression is associated with poor prognosis in cancer patients: a systematic review and meta-analysis.
abstract: OBJECTIVE
  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).
  
  
  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.
authors.affiliation: Department of Clinical Laboratory, The First Affiliated Hospital of Xi'an Medical University, Xi'an City, Shaanxi Province, China.
authors.forename: Chao
authors.initials: C
authors.lastname: Yang
authors.affiliation: Department of Clinical Laboratory, The First Affiliated Hospital of Xi'an Medical University, Xi'an City, Shaanxi Province, China.
authors.forename: Zhuo
authors.initials: Z
authors.lastname: Li
authors.affiliation: Department of Neurology, The First Affiliated Hospital of Xi'an Medical University, Xi'an City, Shaanxi Province, China.
authors.forename: Yajun
authors.initials: Y
authors.lastname: Li
authors.affiliation: Department of Clinical Research, The First Affiliated Hospital of Xi'an Medical University, Xi'an City, Shaanxi Province, China.
authors.forename: Rui
authors.initials: R
authors.lastname: Xu
authors.affiliation: Department of Clinical Laboratory, The First Affiliated Hospital of Xi'an Medical University, Xi'an City, Shaanxi Province, China.
authors.forename: Yongfeng
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Department of Clinical Laboratory, The First Affiliated Hospital of Xi'an Medical University, Xi'an City, Shaanxi Province, China.
authors.forename: Yu
authors.initials: Y
authors.lastname: Tian
authors.affiliation: Department of Clinical Laboratory, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an City, Shaanxi Province, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Chen
mesh_terms: D014408:Biomarkers, Tumor; D015870:Gene Expression; D006801:Humans; D060787:Neoplasm Grading; D009367:Neoplasm Staging; D009369:Neoplasms / Q000235:genetics* / Q000401:mortality* / Q000473:pathology; D016017:Odds Ratio; D011379:Prognosis; D016016:Proportional Hazards Models; D017594:Publication Bias; D062085:RNA, Long Noncoding / Q000235:genetics*; D047368:Tumor Burden
chemical_list: D014408:Biomarkers, Tumor; D062085:RNA, Long Noncoding
keywords: NEAT1; cancer; lncRNA; meta-analysis; prognosis