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Genome‐wide genotype‐based risk model for survival in acute myeloid leukaemia patients with normal karyotype
Author(s) -
Choi Hangseok,
Jung Chulwon,
Sohn Sang Kyun,
Kim Seonwoo,
Kim HyeoungJoon,
Kim YeoKyeoung,
Kim TaeHyung,
Zhang Zhaolei,
Shin EunSoon,
Lee JongEun,
Moon Joon Ho,
Kim Sung Hyun,
Kim Kyoung Ha,
Mun YeungChul,
Kim Hawk,
Park Jinny,
Kim Jhingook,
Kim Dennis D. H.
Publication year - 2013
Publication title -
british journal of haematology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.907
H-Index - 186
eISSN - 1365-2141
pISSN - 0007-1048
DOI - 10.1111/bjh.12492
Subject(s) - single nucleotide polymorphism , snp , genotyping , oncology , snp array , genotype , tag snp , medicine , genome wide association study , snp genotyping , biology , genetics , gene
Summary Single nucleotide polymorphisms ( SNP ) are inter‐individual genetic variations that could explain inter‐individual differences of response/survival to chemotherapy. The present study was performed to build up a risk model for survival in 247 patients with acute myeloid leukaemia ( AML ) with normal karyotype ( AML ‐ NK ). Genome‐wide Affymetrix SNP array 6.0 was used for genotyping in discovery set ( n = 118). After identifying significant SNP s for overall survival ( OS ) in single SNP analysis, a risk model was constructed. Out of 632 957 autosomal SNP s analysed, finally four SNP s (rs2826063, rs12791420, rs11623492 and rs2575369) were introduced into the risk model. The model could stratify the patients according to their OS in discovery set ( P = 1·053656 × 10 −4 ). Replication was performed using Sequenom platform for genotyping in the validation cohort ( n = 129). The model incorporated with clinical and four SNP risk score was successfully replicated in a validation set ( P = 5·38206 × 10 −3 ). The integration of four SNP s and clinical factors into the risk model showed higher area under the curve ( AUC ) reults than in the model incorporating only clinical or only four SNP s, suggesting improved prognostic stratification power by combination of four SNP s and clinical factors. In conclusion , a genome‐wide SNP ‐based risk model in 247 patients with AML ‐ NK can identify a group of high risk patients with poor survival.