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Leukemia. 2015 Feb;29(2):297-303. doi: 10.1038/leu.2014.205. Epub 2014 Jul 3.

Genomic profiling of thousands of candidate polymorphisms predicts risk of relapse in 778 Danish and German childhood acute lymphoblastic leukemia patients.

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Center for Biological Sequence Analysis, Technical University of Denmark, Kgs. Lyngby, Denmark.
Pediatrics and Adolescent Medicine, The Juliane Marie Centre, The University Hospital Rigshospitalet, Copenhagen, Denmark.
Department of Pediatric Hematology and Oncology, HC Andersen Children's Hospital, Odense University Hospital, Odense, Denmark.
Centre for GeoGenetics, Natural History Museum of Denmark, The University of Copenhagen, Copenhagen, Denmark.
Institute of Clinical Medicine, Århus University Hospital, Århus, Denmark.
Department of Human Genetics, University of Heidelberg, Heidelberg, Germany.
Department of General Pediatrics, University Medical Center Schleswig-Holstein, Kiel, Germany.
Pediatric Hematology and Oncology, Hannover Medical School, Hannover, Germany.
Department of Clinical Immunology, Diagnostic Centre, The University Hospital Rigshospitalet, Copenhagen, Denmark.
1] Pediatrics and Adolescent Medicine, The Juliane Marie Centre, The University Hospital Rigshospitalet, Copenhagen, Denmark [2] Institute of Clinical Medicine, Faculty of Health and Medical Sciences, The University of Copenhagen, Copenhagen, Denmark.


Childhood acute lymphoblastic leukemia survival approaches 90%. New strategies are needed to identify the 10-15% who evade cure. We applied targeted, sequencing-based genotyping of 25 000 to 34 000 preselected potentially clinically relevant single-nucleotide polymorphisms (SNPs) to identify host genome profiles associated with relapse risk in 352 patients from the Nordic ALL92/2000 protocols and 426 patients from the German Berlin-Frankfurt-Munster (BFM) ALL2000 protocol. Patients were enrolled between 1992 and 2008 (median follow-up: 7.6 years). Eleven cross-validated SNPs were significantly associated with risk of relapse across protocols. SNP and biologic pathway level analyses associated relapse risk with leukemia aggressiveness, glucocorticosteroid pharmacology/response and drug transport/metabolism pathways. Classification and regression tree analysis identified three distinct risk groups defined by end of induction residual leukemia, white blood cell count and variants in myeloperoxidase (MPO), estrogen receptor 1 (ESR1), lamin B1 (LMNB1) and matrix metalloproteinase-7 (MMP7) genes, ATP-binding cassette transporters and glucocorticosteroid transcription regulation pathways. Relapse rates ranged from 4% (95% confidence interval (CI): 1.6-6.3%) for the best group (72% of patients) to 76% (95% CI: 41-90%) for the worst group (5% of patients, P<0.001). Validation of these findings and similar approaches to identify SNPs associated with toxicities may allow future individualized relapse and toxicity risk-based treatments adaptation.

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