| Literature DB >> 25082786 |
Axel Benner1, Larry Mansouri2, Davide Rossi3, Aneela Majid4, Kerstin Willander5, Anton Parker6, Gareth Bond7, Sarka Pavlova8, Holger Nückel9, Olaf Merkel10, Paolo Ghia11, Emili Montserrat12, Mohd Arifin Kaderi13, Richard Rosenquist2, Gianluca Gaidano3, Martin J S Dyer4, Peter Söderkvist5, Mats Linderholm5, David Oscier6, Zuzana Tvaruzkova8, Sarka Pospisilova8, Ulrich Dührsen9, Richard Greil10, Hartmut Döhner14, Stephan Stilgenbauer14, Thorsten Zenz15.
Abstract
A number of single nucleotide polymorphisms have been associated with disease predisposition in chronic lymphocytic leukemia. A single nucleotide polymorphism in the MDM2 promotor region, MDM2SNP309, was shown to soothe the p53 pathway. In the current study, we aimed to clarify the effect of the MDM2SNP309 on chronic lymphocytic leukemia characteristics and outcome. We performed a meta-analysis of data from 2598 individual patients from 10 different cohorts. Patients' data and genetic analysis for MDM2SNP309 genotype, immunoglobulin heavy chain variable region mutation status and fluorescence in situ hybridization results were collected. There were no differences in overall survival based on the polymorphism (log rank test, stratified by study cohort; P=0.76; GG genotype: cohort-adjusted median overall survival of 151 months; TG: 153 months; TT: 149 months). In a multivariable Cox proportional hazards regression analysis, advanced age, male sex and unmutated immunoglobulin heavy chain variable region genes were associated with inferior survival, but not the MDM2 genotype. The MDM2SNP309 is unlikely to influence disease characteristics and prognosis in chronic lymphocytic leukemia. Studies investigating the impact of individual single nucleotide polymorphisms on prognosis are often controversial. This may be due to selection bias and small sample size. A meta-analysis based on individual patient data provides a reasonable strategy for prognostic factor analyses in the case of small individual studies. Individual patient data-based meta-analysis can, therefore, be a powerful tool to assess genetic risk factors in the absence of large studies. Copyright© Ferrata Storti Foundation.Entities:
Mesh:
Substances:
Year: 2014 PMID: 25082786 PMCID: PMC4116826 DOI: 10.3324/haematol.2013.101170
Source DB: PubMed Journal: Haematologica ISSN: 0390-6078 Impact factor: 9.941