title: Microarray-based classification of a consecutive series of 121 childhood acute leukemias: prediction of leukemic and genetic subtype as well as of minimal residual disease status.
abstract: Gene expression analyses were performed on 121 consecutive childhood leukemias (87 B-lineage acute lymphoblastic leukemias (ALLs), 11 T-cell ALLs and 23 acute myeloid leukemias (AMLs)), investigated during an 8-year period at a single center. The supervised learning algorithm k-nearest neighbor was utilized to build gene expression predictors that could classify the ALLs/AMLs according to clinically important subtypes with high accuracy. Validation experiments in an independent data set verified the high prediction accuracies of our classifiers. B-lineage ALLs with uncharacteristic cytogenetic aberrations or with a normal karyotype displayed heterogeneous gene expression profiles, resulting in low prediction accuracies. Minimal residual disease status (MRD) in T-cell ALLs with a high (>0.1%) MRD at day 29 could be classified with 100% accuracy already at the time of diagnosis. In pediatric leukemias with uncharacteristic cytogenetic aberrations or with a normal karyotype, unsupervised analysis identified two novel subgroups: one consisting mainly of cases remaining in complete remission (CR) and one containing a few patients in CR and all but one of the patients who relapsed. This study of a consecutive series of childhood leukemias confirms and extends further previous reports demonstrating that global gene expression profiling provides a valuable tool for genetic and clinical classification of childhood leukemias.
authors.affiliation: Department of Clinical Genetics, Lund University Hospital, Lund, Sweden. anna.andersson@med.lu.se
authors.forename: A
authors.initials: A
authors.lastname: Andersson
authors.forename: C
authors.initials: C
authors.lastname: Ritz
authors.forename: D
authors.initials: D
authors.lastname: Lindgren
authors.forename: P
authors.initials: P
authors.lastname: Edén
authors.forename: C
authors.initials: C
authors.lastname: Lassen
authors.forename: J
authors.initials: J
authors.lastname: Heldrup
authors.forename: T
authors.initials: T
authors.lastname: Olofsson
authors.forename: J
authors.initials: J
authors.lastname: Råde
authors.forename: M
authors.initials: M
authors.lastname: Fontes
authors.forename: A
authors.initials: A
authors.lastname: Porwit-Macdonald
authors.forename: M
authors.initials: M
authors.lastname: Behrendtz
authors.forename: M
authors.initials: M
authors.lastname: Höglund
authors.forename: B
authors.initials: B
authors.lastname: Johansson
authors.forename: T
authors.initials: T
authors.lastname: Fioretos
mesh_terms: D000208:Acute Disease; D000465:Algorithms; D002648:Child; D020869:Gene Expression Profiling; D018816:Genes, cdc; D006801:Humans; D007938:Leukemia / Q000145:classification* / Q000235:genetics*; D015448:Leukemia, B-Cell; D007951:Leukemia, Myeloid; D015458:Leukemia, T-Cell; D018365:Neoplasm, Residual / Q000175:diagnosis*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011237:Predictive Value of Tests; D012008:Recurrence; D012074:Remission Induction