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. 2020 Feb 5:12:819-839.
doi: 10.2147/CMAR.S200687. eCollection 2020.

The Significance of miRNAs as a Prognostic Biomarker for Survival Outcome in T Cell - Acute Lymphoblastic Leukemia Patients: A Systematic Review and Meta-Analysis

Shanthi Sabarimurugan  1 , Chellan Kumarasamy  2 , Madurantakam Royam Madhav  3 , Suja Samiappan  4 , Rama Jayaraj  5
Affiliations

The Significance of miRNAs as a Prognostic Biomarker for Survival Outcome in T Cell - Acute Lymphoblastic Leukemia Patients: A Systematic Review and Meta-Analysis

Shanthi Sabarimurugan et al. Cancer Manag Res. .

Abstract

Purpose: T-cell acute lymphoblastic leukemia (T-ALL) affects lymphoid cells. Previous studies have reported that miRNAs play a significant role in T-ALL prognosis and have the potential to function as biomarkers in T-ALL. Therefore, this systematic review and meta-analysis study was designed to evaluate the overall prognostic impact of miRNAs in T-ALL patients.

Methods: Eligible studies published between Jan 2010 and April 2018 were retrieved from online bibliographic databases based on multiple keywords to generate search strings. Meta-analysis was performed using the outcome measure, Hazard Ratio (HR). A survival analysis of all studies was conducted and a subsequent forest plot was generated to evaluate the pooled effect size, across all T-ALL patients. Subgroup analysis was conducted based on demographic characteristics and commonly represented miRNAs among the included studies.

Results: A total of 17 studies were included for systematic review, among which 16 studies were eligible for meta-analysis, which, in total discussed 32 different miRNAs. The mean effect size of HR value was 0.929 (CI 0.878-0984), which indicates a decrease in risk of death by 7.1%. The analysis was based on the random effects model with the heterogeneity measure index (I2) being 84.92%. The pooled effect size (HR) of upregulated and downregulated miRNA expressions on survival outcome in the T-ALL patient was 0.787 (CI 0.732-0.845) and 1.225 (CI 1.110-1.344) respectively. The subgroup analysis was performed based on demographic characteristics (age, gender, lactate dehydrogenase, WBC count) and expression of miR221 and miR46a.

Conclusion: Our systematic review and meta-analysis findings suggest that the overall miRNA expression is potentially associated with a decreased likelihood of death in T-ALL patients. Although our findings are inconclusive, the results point toward miRNA expression allowing for prognostic evaluation of T-ALL patients.

Keywords: PRISMA; biomarkers; microRNAs; prognosis; survival analysis.

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Conflict of interest statement

The authors report no conflicts of interest in this work.

Figures

Figure 1
Figure 1
Flowchart for study selection and data acquisition. Notes: The flow diagram explains the information on the different phases of the articles selection criteria in systematic review and side boxes explain the reason why the particular articles were removed. Each excluded articles were defined with appropriate excluded numbers.
Figure 2
Figure 2
Forest plot for survival outcome of miRNAs in T-ALL patients. Notes: The pooled hazard ratios of HR values of T-ALL prognostic data were calculated and analysed using CMA software (version 3.3.070, USA). The black diamond represents the combined effect estimate of survival for T-ALL patients randomly assigned to miRNA evaluation. The red square with line indicates the effect size of miRNA of the included studies with 95% confidence interval. The risk ratio of 1 suggests no difference in risk of T-ALL patients’ survival. A risk ratio > 1 indicates an increased risk of patients’ survival, whereas a risk ratio < 1 suggests a reduced risk of patients’ survival. Favours Survival refers to better survival and Favours death indicates worse survival.
Figure 3
Figure 3
Funnel plot of studies correlating the overall patient survival and miRNA expression. Notes: The funnel plot measures the study size standard error and precision on the vertical axis and function of effect size on the horizontal axis. The dots represent the individual study, and most of this area contains regions of high significance, which reveals that publication bias would be described in the form of asymmetry. This states the fact that smaller studies which appear toward the bottom are more likely to be published if they have larger than average effects and spreads on the right side of the plot, which makes them more likely to meet the criterion for statistical significance due to non-even distribution of studies.
Figure 4
Figure 4
Funnel plot with observed and imputed studies. Notes: Large studies appear outside the funnel and tend to cluster on one side of the funnel plot. Smaller studies appear toward the top of the graph, and (since there is more sampling variation in effect size estimates in the smaller studies) will be dispersed across a range of values.
Figure 5
Figure 5
Subgroup analysis on WBC.
Figure 6
Figure 6
Subgroup analysis for lactate dehydrogenase.
Figure 7
Figure 7
Subgroup analysis for age at diagnosis.
Figure 8
Figure 8
Subgroup analysis for gender variables.
Figure 9
Figure 9
Subgroup analysis of miRNA expression in survival outcome of T-ALL patients exclusively.
Figure 10
Figure 10
Subgroup analysis of miRNA221.
Figure 11
Figure 11
Subgroup analysis of miRNA146a.
Figure 12
Figure 12
Subgroup analysis on patient's ethnicity.
See this image and copyright information in PMC

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