| Literature DB >> 26992216 |
Jianting Long1, Shi Fang2, Qiangsheng Dai1, Xiaolian Liu3, Wanshou Zhu3, Shenming Wang4.
Abstract
Although a number of studies suggested that WT1 rs16754 polymorphism might be related to decreased relapse free survival (RFS) and overall survival (OS). The results remain controversial. Published reports were searched in PubMed, EMBASE, and Google Scholar. Twelve publications with 3903 patients had met the inclusion criteria and were subjected to further examination. We found WT1 rs16754 polymorphism was significantly associated with OS in AML (OR = 0.62; 95% CI 0.52 - 0.75; p < 0.00001; I2 = 47%). WT1 rs16754 polymorphism was also significantly associated with RFS in AML (OR = 0.69; 95% CI 0.57 - 0.83; p < 0.001; I2 = 46%). In the subgroup analyses of age, race, and subtype of AML, WT1 rs16754 polymorphism was a independent favorable-risk marker. In conclusion, WT1 rs16754 polymorphism is associated with better survival of AML. It could be used as a cost-effective prognostic biomarker for AML.Entities:
Keywords: Wilms’ tumor gene 1; acute myeloid leukemia; association; meta-analysis
Mesh:
Substances:
Year: 2016 PMID: 26992216 PMCID: PMC5077998 DOI: 10.18632/oncotarget.8117
Source DB: PubMed Journal: Oncotarget ISSN: 1949-2553
Figure 1Study flow diagram of included studies
Characteristics of the included studies
| No. | First author | Year | Study design | Race | Age | Female (%) | Subtype | Sample size | Adjusted for OS | Adjusted for RFS |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Damm | 2010 | Cohort | Caucasian | 45 | 48 | CN-AML | 249 | NPM1/FLT3 mutation status, age, Platelet, CEBPA mutation status, WBC | NPM1/FLT3 mutation status, Platelet, CEBPA mutation status, WBC |
| 2 | Hollink | 2010 | Cohort | Caucasian | 9 | 40 | Mix | 272 | NA | NA |
| 3 | Wagner | 2010 | Cohort | Caucasian | 49 | 83 | CN-AML | 275 | Age, IDH1 SNP rs11554137, NPM1/FLT3 mutation status, Platelets | NPM1 mutation status, CEBPA mutation status |
| 4 | Becker | 2011 | Cohort | Mix | 62 | 50 | CN-AML | 433 | NA | NA |
| 5 | Ho | 2011 | Cohort | Mix | 10 | 45 | NA | 790 | Risk group, WBC, race | Risk group, WBC, race |
| 6 | Renneville | 2011 | Cohort | Caucasian | 51 | 46 | Mix | 511 | NA | NA |
| 7 | Damm | 2012 | Cohort | Caucasian | 47 | 48 | CN-AML | 269 | ID1, age, BAALC expression, Platelets, FLT3-ITD, CEBPA mutation | ID1, Platelets, NPM1 mutation, CEBPA mutation |
| 8 | Choi | 2012 | Cohort | Asian | 42 | 63 | CN-AML | 73 | NA | NA |
| 9 | Luna | 2012 | Cohort | Caucasian | 62 | 43 | de novo AML | 175 | NPM1, FLT3-ITD, and CEBPA, expression levels of WT1, age, WBC count, platelet count, hemoglobin level, percentage of blood blasts, cytogenetic risk group, and FAB classification | NPM1, FLT3-ITD, and CEBPA, expression levels of WT1, age, WBC count, platelet count, hemoglobin level, percentage of blood blasts, cytogenetic risk group, and FAB classification |
| 10 | Luo | 2014 | Cohort | Asian | 45 | 58 | de novo non-M3 AML | 182 | Age, percentage of blood blasts, WT1 expression, WBC, FLT3 | Age, percentage of blood blasts, WT1 expression, WBC, FLT3 |
| 11 | Niavarani | 2015 | Cohort | Caucasian | 45 | 55 | CN-AML | 469 | Age, sex, WBC, secondary disease, performance status, FLT3-ITD, and NPM1 mutations | Age, sex, WBC, secondary disease, performance status, FLT3-ITD, and NPM1 mutations |
| 12 | Zhang | 2015 | Cohort | Asian | 40 | 46 | Mix | 205 | Risk stratification, allogeneic hematopoietic stem cell transplantation | Risk stratification, allogeneic hematopoietic stem cell transplantation |
Figure 2Meta-analysis of the association between WT1 rs16754 polymorphism and OS of AML
Results of the meta-analysis
| OR (95% CI) | ||||
|---|---|---|---|---|
| OS | 0.62 (0.52-0.75) | <0.00001 | 47 | 0.04 |
| Subtype | ||||
| de novo AML | 0.40 (0.24-0.67) | 0.0004 | 0 | 0.82 |
| CN-AML | 0.60 (0.43-0.84) | 0.003 | 67 | 0.009 |
| Race | ||||
| Asian | 0.61 (0.43-0.85) | 0.004 | 0 | 0.61 |
| Caucasian | 0.60 (0.44-0.81) | 0.001 | 69 | 0.004 |
| Age | ||||
| <18 years | 0.67 (0.51-0.88) | 0.004 | 0 | 0.50 |
| >18 years | 0.60 (0.47-0.75) | <0.0001 | 55 | 0.02 |
| RFS | 0.69 (0.57-0.83) | <0.001 | 46 | 0.04 |
| Subtype | ||||
| de novo AML | 0.42 (0.26-0.68) | 0.0004 | 0 | 0.49 |
| CN-AML | 0.74 (0.62-0.88) | 0.007 | 36 | 0.12 |
| Race | ||||
| Asian | 0.61 (0.42-0.88) | 0.008 | 0 | 0.65 |
| Caucasian | 0.64 (0.49-0.85) | 0.002 | 63 | 0.001 |
| Age | ||||
| <18 years | 0.74 (0.55-1.00) | 0.05 | 0 | 0.50 |
| >18 years | 0.68 (0.54-0.85) | 0.0006 | 55 | 0.02 |
Figure 3Meta-analysis of the association between WT1 rs16754 polymorphism and RFS of AML
Figure 4Sensitivity analysis of the association between WT1 rs16754 polymorphism and OS of AML
Figure 5Sensitivity analysis of the association between WT1 rs16754 polymorphism and RFS of AML
Figure 6Funnel plot of the association between WT1 rs16754 polymorphism and OS of AML
Figure 7Funnel plot of the association between WT1 rs16754 polymorphism and RFS of AML