Clinical significance of long noncoding RNA MNX1-AS1 in human cancers: a meta-analysis of cohort studies and bioinformatics analysis based on TCGA datasets

ABSTRACT

MNX1-AS1 expression has been proposed to be abnormally upregulated in multiple human malignancies and be linked with the survival outcome of patients. However, relevant conclusions were yielded based on the limited samples. Therefore, we herein implemented a meta-analysis of the published cohort studies to further decipher the relationship of MNX1-AS1 level to prognosis and clinicopathological features in various cancers. Additionally, using The Cancer Genome Atlas (TCGA) datasets we carried out a bioinformatics analysis to make a further evaluation on the prognostic value of MNX1-AS1 expression. The results of meta-analysis indicated elevated MNX1-AS1 level closely correlated with poorer overall survival (OS) (HR = 1.97, 95% CI, 1.73–2.24; P < 0.00001), and disease-free survival (DFS) (HR = 2.24, 95% CI, 1.48–3.38; P = 0.0001) in cancers, which was confirmed by the bioinformatics analysis. Besides, it was observed the upregulated MNX1-AS1 level was significantly related to invasion depth, disease stage, tumor metastasis, and differentiation. Collectively, high MNX1-AS1 level correlated with poor survival outcome and aggressive clinicopathological characteristics in various cancers, suggesting that MNX1-AS1 may be applied as a prognostic marker and even a therapeutic target. Nevertheless, more high-quality studies designed with a large sample size should be conducted to further determine the clinical role of MNX1-AS1 in specific cancer types.

Graphical abstract

KEYWORDS:

• MNX1-AS1
• cancer
• prognosis
• meta-analysis

Highlights

Increased MNX1-AS1 level correlated with worse overall survival in cancers

Elevated MNX1-AS1 level correlated with poor disease-free survival in cancers

High MNX1-AS1 expression was related to tumor metastasis

Disclosure statement

All authors have declared no conflict of interest exists for this study.

Author contributions

Hai-peng Liu designed this study. Kang Chen and Gan Jian-xin Gan extracted the data and analyzed the data; Kang Chen and Ze-ping Huang drafted the manuscript. Kang Chen and Jun Liu revised the manuscript. All authors have read and confirmed the final manuscript.

Ethics approval and consent to participate

This study is a meta-analysis and bioinformatics analysis, so it is unnecessary to obtain Ethical Approval.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

The study was supported by the Training Program of Lanzhou University Second Hospital Cuiying postgraduate supervisor in 2019 (NO. CYDSPY201907).