Molecular signatures in childhood acute leukemia and their correlations to expression patterns in normal hematopoietic subpopulations.

Global expression profiles of a consecutive series of 121 childhood acute leukemias (87 B lineage acute lymphoblastic leukemias, 11 T cell acute lymphoblastic leukemias, and 23 acute myeloid leukemias), six normal bone marrows, and 10 normal hematopoietic subpopulations of different lineages and maturations were ascertained by using 27K cDNA microarrays. Unsupervised analyses revealed segregation according to lineages and primary genetic changes, i.e., TCF3(E2A)/PBX1, IGH@/MYC, ETV6(TEL)/RUNX1(AML1), 11q23/MLL, and hyperdiploidy (>50 chromosomes). Supervised discriminatory analyses were used to identify differentially expressed genes correlating with lineage and primary genetic change. The gene-expression profiles of normal hematopoietic cells were also studied. By using principal component analyses (PCA), a differentiation axis was exposed, reflecting lineages and maturation stages of normal hematopoietic cells. By applying the three principal components obtained from PCA of the normal cells on the leukemic samples, similarities between malignant and normal cell lineages and maturations were investigated. Apart from showing that leukemias segregate according to lineage and genetic subtype, we provide an extensive study of the genes correlating with primary genetic changes. We also investigated the expression pattern of these genes in normal hematopoietic cells of different lineages and maturations, identifying genes preferentially expressed by the leukemic cells, suggesting an ectopic activation of a large number of genes, likely to reflect regulatory networks of pathogenetic importance that also may provide attractive targets for future directed therapies.

[1]  B. Calabretta,et al.  Post-transcriptional mechanisms in BCR/ABL leukemogenesis: role of shuttling RNA-binding proteins , 2002, Oncogene.

[2]  T. Barrette,et al.  Meta-analysis of microarrays: interstudy validation of gene expression profiles reveals pathway dysregulation in prostate cancer. , 2002, Cancer research.

[3]  J. Downing,et al.  Gene Expression Profiling of Pediatric Acute Myelogenous Leukemia Materials and Methods , 2022 .

[4]  S. Raimondi,et al.  Prognostic factors in children and adolescents with acute myeloid leukemia (excluding children with Down syndrome and acute promyelocytic leukemia): univariate and recursive partitioning analysis of patients treated on Pediatric Oncology Group (POG) Study 8821 , 2000, Leukemia.

[5]  D. Grimwade.  The clinical significance of cytogenetic abnormalities in acute myeloid leukaemia. , 2001, Best practice & research. Clinical haematology.

[6]  B. Johansson,et al.  Cytogenetic abnormalities in childhood acute myeloid leukaemia: a Nordic series comprising all children enrolled in the NOPHO‐93‐AML trial between 1993 and 2001 , 2003, British journal of haematology.

[7]  Su-Jae Lee,et al.  Regulation of leukemic cell adhesion, proliferation, and survival by beta-catenin. , 2002, Blood.

[8]  G. Gustafsson,et al.  Improving outcome through two decades in childhood ALL in the Nordic countries: the impact of high-dose methotrexate in the reduction of CNS irradiation , 2000, Leukemia.

[9]  R. Verhaak,et al.  Prognostically useful gene-expression profiles in acute myeloid leukemia. , 2004, The New England journal of medicine.

[10]  M. Boermeester,et al.  Clinical significance of translocation. , 1994, Gut.

[11]  Misao Ohki,et al.  Identification of a gene expression signature associated with pediatric AML prognosis. , 2003, Blood.

[12]  J. Downing,et al.  Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. , 2002, Cancer cell.

[13]  B Johansson,et al.  Gene expression profiling of leukemic cell lines reveals conserved molecular signatures among subtypes with specific genetic aberrations , 2005, Leukemia.

[14]  Misao Ohki,et al.  Two distinct gene expression signatures in pediatric acute lymphoblastic leukemia with MLL rearrangements. , 2003, Cancer research.

[15]  Douglas A. Hosack,et al.  Identifying biological themes within lists of genes with EASE , 2003, Genome Biology.

[16]  J. Cleveland,et al.  Bcl-2 is an apoptotic target suppressed by both c-Myc and E2F-1 , 2001, Oncogene.

[17]  L. Resar,et al.  HMG-I/Y, a New c-Myc Target Gene and Potential Oncogene , 2000, Molecular and Cellular Biology.

[18]  J. Downing,et al.  Classification of pediatric acute lymphoblastic leukemia by gene expression profiling. , 2003, Blood.

[19]  S. Sallan,et al.  Newly diagnosed childhood acute lymphoblastic leukemia: update on prognostic factors and treatment , 2003, Current opinion in hematology.

[20]  B. Johansson,et al.  Formation of trisomies and their parental origin in hyperdiploid childhood acute lymphoblastic leukemia. , 2003, Blood.

[21]  L. Freedman,et al.  p21 is a transcriptional target of HOXA10 in differentiating myelomonocytic cells. , 2000, Genes & development.

[22]  M. Borowitz,et al.  Surface antigen phenotype can predict TEL-AML1 rearrangement in childhood B-precursor ALL: a Pediatric Oncology Group study , 1998, Leukemia.

[23]  B. Johansson,et al.  Clinical and biological importance of cytogenetic abnormalities in childhood and adult acute lymphoblastic leukemia , 2004, Annals of medicine.

[24]  Jonathan J. Shuster,et al.  Poor prognosis of children with pre-B acute lymphoblastic leukemia is associated with the t(1;19)(q23;p13): a Pediatric Oncology Group study , 1990 .

[25]  N. Heerema,et al.  Clinical significance of translocation t(1;19) in childhood acute lymphoblastic leukemia in the context of contemporary therapies: a report from the Children's Cancer Group. , 1998, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[26]  G. Gustafsson,et al.  Treatment stratification based on initial in vivo response in acute myeloid leukaemia in children without Down's syndrome: results of NOPHO‐AML trials , 2003, British journal of haematology.

[27]  E. Lander,et al.  Expression analysis with oligonucleotide microarrays reveals that MYC regulates genes involved in growth, cell cycle, signaling, and adhesion. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[28]  J. Mesirov,et al.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.

[29]  S. Dudoit,et al.  Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. , 2002, Nucleic acids research.

[30]  K. Anderson,et al.  Distinct patterns of hematopoietic stem cell involvement in acute lymphoblastic leukemia , 2005, Nature Medicine.

[31]  J. Shuster,et al.  Predictability of the t(1;19)(q23;p13) from surface antigen phenotype: implications for screening cases of childhood acute lymphoblastic leukemia for molecular analysis: a Pediatric Oncology Group study. , 1993, Blood.

[32]  W. Hiddemann,et al.  Global approach to the diagnosis of leukemia using gene expression profiling. , 2005, Blood.

[33]  A. Stoker,et al.  Protein tyrosine phosphatases and signalling. , 2005, The Journal of endocrinology.

[34]  A I Saeed,et al.  TM4: a free, open-source system for microarray data management and analysis. , 2003, BioTechniques.

[35]  Cheng Cheng,et al.  Acute lymphoblastic leukemia with TEL-AML1 fusion has lower expression of genes involved in purine metabolism and lower de novo purine synthesis. , 2004, Blood.

[36]  R. Tibshirani,et al.  Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia. , 2004, The New England journal of medicine.