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MDM2 promotor polymorphism and disease characteristics in chronic lymphocytic leukemia: results of an individual patient data-based meta-analysis

A. Benner, L. Mansouri, D. Rossi, A. Majid, K. Willander, A. Parker, G. Bond, S. Pavlova, H. Nückel, O. Merkel, P. Ghia, E. Montserrat, MA. Kaderi, R. Rosenquist, G. Gaidano, MJ. Dyer, P. Söderkvist, M. Linderholm, D. Oscier, Z. Tvaruzkova, S....

. 2014 ; 99 (8) : 1285-91.

Jazyk angličtina Země Itálie

Typ dokumentu časopisecké články, metaanalýza

Perzistentní odkaz   https://www.medvik.cz/link/bmc15023183

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.

Department of Cancer Studies and Molecular Medicine MRC Toxicology Unit University of Leicester UK

Department of Clinical and Experimental Medicine Linköping University Sweden

Department of Hematology Royal Bournemouth Hospital UK

Department of Hematology University Hospital University of Duisburg Essen Essen Germany

Department of Immunology Genetics and Pathology Science for Life Laboratory Uppsala University Sweden

Department of Immunology Genetics and Pathology Science for Life Laboratory Uppsala University Sweden Department of Biomedical Sciences Kull Allied Health Sciences International Islamic University Malaysia Kuantan Pahang Malaysia

Department of Internal Medicine 3 University of Ulm Germany

Department of Translational Oncology National Center for Tumor Diseases Heidelberg Germany Department of Internal Medicine 5 University Hospital Heidelberg Germany

Division of Biostatistics German Cancer Research Center Heidelberg Germany

Division of Hematology Department of Translational Medicine Amedeo Avogadro University of Eastern Piedmont Novara Italy

Institute of Hematology and Oncology Department of Hematology Hospital Clínic IDIBAPS University of Barcelona Spain

Laboratory for Immunological and Molecular Cancer Research University Clinics of Internal Medicine 3 with Hematology Oncology Hemostaseology Infectious Disease and Rheumatology Oncologic Center Paracelus Medical University Salzburg Austria

Laboratory of B Cell Neoplasia Division of Molecular Oncology Ospedale San Raffaele Istituto Scientifico San Raffale Fondazione Centro San Raffaele Università Bita Salute San Raffaele Milan Italy

Ludwig Institute for Cancer Research University of Oxford UK

University Hospital Brno and Central European Institute of Technology Masaryk University Brno Czech Republic

Citace poskytuje Crossref.org

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