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Meta-Analysis
. 2015 Sep 30;5(9):e008653.
doi: 10.1136/bmjopen-2015-008653.

Clinical value of lncRNA MALAT1 as a prognostic marker in human cancer: systematic review and meta-analysis

Xiaoling Tian  1 , Guoxiong Xu  2
Affiliations
Meta-Analysis

Clinical value of lncRNA MALAT1 as a prognostic marker in human cancer: systematic review and meta-analysis

Xiaoling Tian et al. BMJ Open. .

Abstract

Background: Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is found to be overexpressed and associated with clinicopathological features in patients with cancer.

Objectives: To evaluate the clinical value of MALAT1 as a prognostic marker in human cancers by a comprehensive meta-analysis of published studies.

Data sources: The data on the prognostic impact of MALAT1 in cancer were collected from 11 September 2003 to 10 July 2015.

Setting and participants: Fourteen eligible studies with a total of 1373 patients conducted in 3 countries (9 in China, 3 in Japan and 2 in Germany) were matched to our inclusion criteria.

Outcome measures: Pooled HRs with 95% CIs were calculated to estimate the strength of the link between MALAT1 and clinical prognoses. The combined HRs heterogeneity was tested using a χ(2)-based Cochran Q test and Higgins I(2) statistic. Publication bias was evaluated using a funnel plot with Egger's bias indicator test.

Results: A significant association between MALAT1 overexpression and poor overall survival (OS) (HR=1.95; 95% CI 1.57 to 2.41) was observed. Residence region (Germany and China), cancer type (respiratory, digestive or other system disease), sample size and paper quality did not alter the predictive value of MALAT1 on OS in investigated cancers. MALAT1 expression was an independent prognostic marker for OS in patients with cancer using univariate and multivariate analyses. Subgroup analysis showed that the elevated MALAT1 appeared to be a powerful prognostic marker for patients with respiratory, digestive and other system cancers. A similar effect was also seen in different regions. Furthermore, the overexpression of MALAT1 was associated with disease-free, recurrence-free and progression-free survivals.

Conclusions: MALAT1 may potentially be used as a new prognostic marker to predict poorer survival of patients with cancer. More clinical studies on the different types of human cancer not yet investigated need to be conducted.

Keywords: MOLECULAR BIOLOGY.

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Figures

Figure 1
Figure 1
Workflow of searching strategy in the meta-analysis.
Figure 2
Figure 2
Forest plot showing the subgroup analyses of the pooled HRs with elevated MALAT1 expression in the different types of cancer. Values of p and I2 and the HRs with their 95% CI of overall survival (OS) were analysed by the factors of country (A), cancer type (B), sample size (C), quality score (D), univariate analysis (E) and multivariate analysis (F). Each study is represented by a triangle; the centre of which denotes the HR with the horizontal lines showing the 95% CIs. The diamond gives the overall HR for combined results of subgroup studies; the centre denotes the HR and the extremities the 95% CIs. Weights are from random-effect (A–D) and fixed-effect (E and F) analyses.
Figure 3
Figure 3
Forest plot showing meta-analysis of the independent role of MALAT1 on overall survival (OS), recurrence-free survival (RFS)/progression-free survival (PFS) and disease-free survival (DFS) in the different types of cancer. Each study is represented by a triangle; the centre of which denotes the HR with the horizontal lines showing the 95% CIs. The diamond gives the overall HR for combined results of subgroup studies; the centre denotes the HR and the extremities the 95% CIs. Weights are from random-effect analyses.
Figure 4
Figure 4
Sensitivity analysis of the effect of the individual study on the pooled HRs for the correlation between MALAT1 expression and overall survival (OS) in patients with cancer by univariate and multivariate analyses. (A) Sensitivity analysis of the effect of the individual study on the pooled HRs of OS in the different types of cancer with MALAT1 overexpression. (B) Sensitivity analysis of the effect of the individual study on the independent role of MALAT1 on OS in the different types of cancer by univariate analysis. (C) Sensitivity analysis of the effect of the individual study on the independent role of MALAT-1 on OS in the different types of cancer by multivariate analysis.
Figure 5
Figure 5
Analysis of the correlation between MALAT1 expression and overall survival (OS) in patients with cancer by univariate and multivariate analyses. (A) Funnel plot of the publication bias for the analysis of the pooled HRs of OS in the different types of cancer with MALAT1 overexpression. (B) Funnel plot of the publication bias for the analysis of the independent role of MALAT1 on OS in the different types of cancer by univariate analysis. (C) Funnel plot of the publication bias for the analysis of the independent role of MALAT-1 on OS in the different types of cancer by multivariate analysis.
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References

    1. Cech TR, Steitz JA. The noncoding RNA revolution-trashing old rules to forge new ones. Cell 2014;157:77–94. 10.1016/j.cell.2014.03.008 - DOI - PubMed
    1. Holoch D, Moazed D. RNA-mediated epigenetic regulation of gene expression. Nat Rev Genet 2015;16:71–84. 10.1038/nrg3863 - DOI - PMC - PubMed
    1. Geisler S, Coller J. RNA in unexpected places: long non-coding RNA functions in diverse cellular contexts. Nat Rev Mol Cell Biol 2013;14:699–712. 10.1038/nrm3679 - DOI - PMC - PubMed
    1. Ørom UA, Shiekhattar R. Long noncoding RNAs usher in a new era in the biology of enhancers. Cell 2013;154:1190–3. 10.1016/j.cell.2013.08.028 - DOI - PMC - PubMed
    1. Akrami R, Jacobsen A, Hoell J et al. . Comprehensive analysis of long non-coding RNAs in ovarian cancer reveals global patterns and targeted DNA amplification. PLoS One 2013;8:e80306 10.1371/journal.pone.0080306 - DOI - PMC - PubMed

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