Gene expression profiling in MDS and AML: potential and future avenues

Today, the classification systems for myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) already incorporate cytogenetic and molecular genetic aberrations in an attempt to better reflect disease biology. However, in many MDS/AML patients no genetic aberrations have been identified yet, and even within some cytogenetically well-defined subclasses there is considerable clinical heterogeneity. Recent advances in genomics technologies such as gene expression profiling (GEP) provide powerful tools to further characterize myeloid malignancies at the molecular level, with the goal to refine the MDS/AML classification system, incorporating as yet unknown molecular genetic and epigenetic pathomechanisms, which are likely reflected by aberrant gene expression patterns. In this study, we provide a comprehensive review on how GEP has contributed to a refined molecular taxonomy of MDS and AML with regard to diagnosis, prediction of clinical outcome, discovery of novel subclasses and identification of novel therapeutic targets and novel drugs. As many challenges remain ahead, we discuss the pitfalls of this technology and its potential including future integrative studies with other genomics technologies, which will continue to improve our understanding of malignant transformation in myeloid malignancies and thereby contribute to individualized risk-adapted treatment strategies for MDS and AML patients.

[1]  Bas J. Wouters,et al.  Prediction of molecular subtypes in acute myeloid leukemia based on gene expression profiling , 2009, Haematologica.

[2]  M. Caligiuri,et al.  MicroRNA expression in cytogenetically normal acute myeloid leukemia. , 2008, The New England journal of medicine.

[3]  Y. Hayashi,et al.  Age‐associated difference in gene expression of paediatric acute myelomonocytic lineage leukaemia (FAB M4 and M5 subtypes) and its correlation with prognosis , 2009, British journal of haematology.

[4]  M. Caligiuri,et al.  BAALC and ERG expression levels are associated with outcome and distinct gene and microRNA expression profiles in older patients with de novo cytogenetically normal acute myeloid leukemia: a Cancer and Leukemia Group B study. , 2010, Blood.

[5]  Bob Löwenberg,et al.  Review Articles (434 articles) , 2008 .

[6]  Zhen-yi Wang,et al.  Acute promyelocytic leukemia: from highly fatal to highly curable. , 2008, Blood.

[7]  M. Cazzola,et al.  Haploinsufficiency of RPS14 in 5q− syndrome is associated with deregulation of ribosomal- and translation-related genes , 2008, British journal of haematology.

[8]  Dirce M Carraro,et al.  Gene stage-specific expression in the microenvironment of pediatric myelodysplastic syndromes. , 2007, Leukemia research.

[9]  Monica L Guzman,et al.  Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data. , 2008, Blood.

[10]  K. Döhner,et al.  Molecular characterization of acute myeloid leukemia , 2008, Haematologica.

[11]  L. Bullinger,et al.  Molecular characterization of AML with ins(21;8)(q22;q22q22) reveals similarity to t(8;21) AML , 2011, Genes, chromosomes & cancer.

[12]  D. Grimwade,et al.  Acute promyelocytic leukemia: a paradigm for differentiation therapy. , 2010, Cancer treatment and research.

[13]  Ulrich Mansmann,et al.  An 86-probe-set gene-expression signature predicts survival in cytogenetically normal acute myeloid leukemia. , 2008, Blood.

[14]  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.

[15]  Nicholas T. Ingolia,et al.  Mammalian microRNAs predominantly act to decrease target mRNA levels , 2010, Nature.

[16]  Maqc Consortium The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements , 2006, Nature Biotechnology.

[17]  Qing‐Yu He,et al.  Transcriptomic and proteomic approach to studying SNX‐2112‐induced K562 cells apoptosis and anti‐leukemia activity in K562‐NOD/SCID mice , 2009, FEBS letters.

[18]  L. Bullinger,et al.  Gene expression profiling in AML with normal karyotype can predict mutations for molecular markers and allows novel insights into perturbed biological pathways , 2010, Leukemia.

[19]  C. Felix,et al.  The molecular basis of leukemia. , 2004, Hematology. American Society of Hematology. Education Program.

[20]  W. Kamps,et al.  High VEGFC expression is associated with unique gene expression profiles and predicts adverse prognosis in pediatric and adult acute myeloid leukemia. , 2010, Blood.

[21]  Stefan Fröhling,et al.  Disclosure of candidate genes in acute myeloid leukemia with complex karyotypes using microarray-based molecular characterization. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[22]  B. Porse,et al.  A conceptual framework for the identification of candidate drugs and drug targets in acute promyelocytic leukemia , 2010, Leukemia.

[23]  C. Mayr,et al.  Widespread Shortening of 3′UTRs by Alternative Cleavage and Polyadenylation Activates Oncogenes in Cancer Cells , 2009, Cell.

[24]  Bob Löwenberg,et al.  A 2-gene classifier for predicting response to the farnesyltransferase inhibitor tipifarnib in acute myeloid leukemia. , 2007, Blood.

[25]  Gordon B Mills,et al.  Functional proteomic profiling of AML predicts response and survival. , 2009, Blood.

[26]  Bulent Ozpolat,et al.  Comparative proteomic analysis of all-trans-retinoic acid treatment reveals systematic posttranscriptional control mechanisms in acute promyelocytic leukemia. , 2004, Blood.

[27]  S. Fröhling,et al.  Gene mutations and response to treatment with all-trans retinoic acid in elderly patients with acute myeloid leukemia. Results from the AMLSG Trial AML HD98B , 2009, Haematologica.

[28]  M. Caligiuri,et al.  Prognostic Importance of MN 1 Transcript Levels , and Biologic Insights From MN 1-Associated Gene and MicroRNA Expression Signatures in Cytogenetically Normal Acute Myeloid Leukemia : A Cancer and Leukemia Group B Study , 2009 .

[29]  L. Bullinger,et al.  Gene expression with prognostic implications in cytogenetically normal acute myeloid leukemia. , 2008, Seminars in oncology.

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

[31]  M. Boix-Chornet,et al.  DNA methylation-independent loss of RARA gene expression in acute myeloid leukemia. , 2008, Blood.

[32]  Claudio Lottaz,et al.  Gene-expression profiling identifies distinct subclasses of core binding factor acute myeloid leukemia , 2007 .

[33]  Paul A Clemons,et al.  The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease , 2006, Science.

[34]  B. Löwenberg,et al.  A decade of genome-wide gene expression profiling in acute myeloid leukemia: flashback and prospects. , 2009, Blood.

[35]  M. Nelson,et al.  Quantitative DNA methylation predicts survival in adult acute myeloid leukemia. , 2010, Blood.

[36]  S. Shurtleff,et al.  Clinical utility of microarray-based gene expression profiling in the diagnosis and subclassification of leukemia: report from the International Microarray Innovations in Leukemia Study Group. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[37]  M. Cazzola,et al.  Gene expression profiling of erythroblasts from refractory anaemia with ring sideroblasts (RARS) and effects of G‐CSF , 2009, British journal of haematology.

[38]  J. Miguel,et al.  Gene expression profile reveals deregulation of genes with relevant functions in the different subclasses of acute myeloid leukemia , 2005, Leukemia.

[39]  Li Wang,et al.  Gene expression profiles of CD34+ cells in myelodysplastic syndromes: involvement of interferon-stimulated genes and correlation to FAB subtype and karyotype. , 2006, Blood.

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

[41]  C. Plass,et al.  Epigenetics in acute myeloid leukemia. , 2008, Seminars in oncology.

[42]  J. Reeves,et al.  Phase 2 study of lenalidomide in transfusion-dependent, low-risk, and intermediate-1 risk myelodysplastic syndromes with karyotypes other than deletion 5q. , 2008, Blood.

[43]  S. Nimer Myelodysplastic syndromes. , 2008, Blood.

[44]  L. Hood,et al.  Dysregulated gene expression networks in human acute myelogenous leukemia stem cells , 2009, Proceedings of the National Academy of Sciences.

[45]  A. Ganser,et al.  Proteomic patterns predict acute graft-versus-host disease after allogeneic hematopoietic stem cell transplantation. , 2007, Blood.

[46]  H. Saluz,et al.  Childhood acute myelogenous leukaemia: association between PRAME, apoptosis- and MDR-related gene expression. , 2006, European journal of cancer.

[47]  E. Lander,et al.  MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia , 2002, Nature Genetics.

[48]  S. Fröhling,et al.  Phase III study of all-trans retinoic acid in previously untreated patients 61 years or older with acute myeloid leukemia , 2004, Leukemia.

[49]  Robert Tibshirani,et al.  Gene expression profiles at diagnosis in de novo childhood AML patients identify FLT3 mutations with good clinical outcomes. , 2004, Blood.

[50]  A. Ganser,et al.  A Tagging-via-substrate Approach to Detect the Farnesylated Proteome Using Two-dimensional Electrophoresis Coupled with Western Blotting* , 2010, Molecular & Cellular Proteomics.

[51]  J. Qian,et al.  Gene expression profiling of the bone marrow mononuclear cells from patients with myelodysplastic syndrome. , 2005, Oncology reports.

[52]  T. Golub,et al.  Identification of AML1-ETO modulators by chemical genomics. , 2009, Blood.

[53]  L. Bullinger,et al.  Gene expression profiling in acute myeloid leukemia , 2022 .

[54]  Jeffrey T. Chang,et al.  A genomic strategy to elucidate modules of oncogenic pathway signaling networks. , 2009, Molecular cell.

[55]  Bas J. Wouters,et al.  Brief Report Results and Discussion , 2022 .

[56]  Luca Malcovati,et al.  The Role of the Iron Transporter ABCB7 in Refractory Anemia with Ring Sideroblasts , 2008, PloS one.

[57]  Sridhar Ramaswamy,et al.  Synthetic Lethal Interaction between Oncogenic KRAS Dependency and STK33 Suppression in Human Cancer Cells , 2009, Cell.

[58]  Robert Tibshirani,et al.  Relationship of differential gene expression profiles in CD34+ myelodysplastic syndrome marrow cells to disease subtype and progression. , 2009, Blood.

[59]  Rob Pieters,et al.  Evaluation of gene expression signatures predictive of cytogenetic and molecular subtypes of pediatric acute myeloid leukemia , 2011, Haematologica.

[60]  B. Nilsson,et al.  Cross-platform classification in microarray-based leukemia diagnostics. , 2006, Haematologica.

[61]  F. Ferrari,et al.  Identification of a molecular signature predictive of sensitivity to differentiation induction in acute myeloid leukemia , 2006, Leukemia.

[62]  Bob Löwenberg,et al.  MicroRNA expression profiling in relation to the genetic heterogeneity of acute myeloid leukemia. , 2008, Blood.

[63]  Torsten Haferlach,et al.  An international standardization programme towards the application of gene expression profiling in routine leukaemia diagnostics: the Microarray Innovations in LEukemia study prephase , 2008, British journal of haematology.

[64]  Torsten Haferlach,et al.  Microarray-based classifiers and prognosis models identify subgroups with distinct clinical outcomes and high risk of AML transformation of myelodysplastic syndrome. , 2009, Blood.

[65]  John T. Wei,et al.  Integrative genomic and proteomic analysis of prostate cancer reveals signatures of metastatic progression. , 2005, Cancer cell.

[66]  M. Gordon Lenalidomide in the Myelodysplastic Syndrome with Chromosome 5q Deletion , 2008 .

[67]  M. Caligiuri,et al.  Prognostic importance of MN1 transcript levels, and biologic insights from MN1-associated gene and microRNA expression signatures in cytogenetically normal acute myeloid leukemia: a cancer and leukemia group B study. , 2009, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[68]  C. Schoch,et al.  Clinical trial of valproic acid and all‐trans retinoic acid in patients with poor‐risk acute myeloid leukemia , 2005, Cancer.

[69]  J. Pollack,et al.  KIT mutations confer a distinct gene expression signature in core binding factor leukaemia , 2010, British journal of haematology.

[70]  Hartmut Döhner,et al.  Acute myeloid leukaemia , 2006, The Lancet.

[71]  V. Thorsson,et al.  Integrated Genomic and Proteomic Analyses of Gene Expression in Mammalian Cells*S , 2004, Molecular & Cellular Proteomics.

[72]  M. Minden,et al.  Myelodysplastic syndromes: the complexity of stem-cell diseases , 2007, Nature Reviews Cancer.

[73]  J. Rowley,et al.  Leukaemogenesis: more than mutant genes , 2010, Nature Reviews Cancer.

[74]  S. Armstrong,et al.  Chromatin maps, histone modifications and leukemia , 2009, Leukemia.

[75]  T. Golub,et al.  Distinct microRNA expression profiles in acute myeloid leukemia with common translocations , 2008, Proceedings of the National Academy of Sciences.

[76]  J. Kitzman,et al.  Acquired copy number alterations in adult acute myeloid leukemia genomes , 2009, Proceedings of the National Academy of Sciences.

[77]  K Holzmann,et al.  Identification of acquired copy number alterations and uniparental disomies in cytogenetically normal acute myeloid leukemia using high-resolution single-nucleotide polymorphism analysis , 2010, Leukemia.

[78]  G. Mufti,et al.  Whole genome scanning as a cytogenetic tool in hematologic malignancies. , 2008, Blood.

[79]  Guido Marcucci,et al.  Independent confirmation of a prognostic gene-expression signature in adult acute myeloid leukemia with a normal karyotype: a Cancer and Leukemia Group B study. , 2006, Blood.

[80]  A. Kohlmann,et al.  Intraplatform reproducibility and technical precision of gene expression profiling in 4 laboratories investigating 160 leukemia samples: the DACH study. , 2008, Clinical chemistry.

[81]  K. Anderson,et al.  The molecular signature of MDS stem cells supports a stem-cell origin of 5q myelodysplastic syndromes. , 2007, Blood.

[82]  F. Weninger,et al.  Pattern robustness of diagnostic gene expression signatures in leukemia , 2005, Genes, chromosomes & cancer.

[83]  G. Morgan,et al.  Proteomics and the haematologist. , 2004, Clinical and laboratory haematology.

[84]  A. Kohlmann,et al.  Current status of gene expression profiling in the diagnosis and management of acute leukaemia , 2009, British journal of haematology.

[85]  J. Boultwood,et al.  Gene expression profiling in the myelodysplastic syndromes , 2005, Hematology.

[86]  Pu Zhang,et al.  Distinct gene expression profiles of acute myeloid/T-lymphoid leukemia with silenced CEBPA and mutations in NOTCH1. , 2007, Blood.

[87]  Bob Löwenberg,et al.  High EVI1 expression predicts poor survival in acute myeloid leukemia: a study of 319 de novo AML patients. , 2003, Blood.

[88]  J. Downing,et al.  Genomic analysis reveals few genetic alterations in pediatric acute myeloid leukemia , 2009, Proceedings of the National Academy of Sciences.

[89]  J. Downing,et al.  Pediatric acute myeloid leukemia with NPM1 mutations is characterized by a gene expression profile with dysregulated HOX gene expression distinct from MLL-rearranged leukemias , 2007, Leukemia.

[90]  H. Mano DNA micro-array analysis of myelodysplastic syndrome , 2006, Leukemia & lymphoma.

[91]  M. Cazzola,et al.  Gene expression profiling of CD34+ cells in patients with the 5q− syndrome , 2007, British journal of haematology.

[92]  K. Prabhash,et al.  Identification of PML/RARalpha fusion gene transcripts that showed no t(15;17) with conventional karyotyping and fluorescent in situ hybridization. , 2009, Genetics and molecular research : GMR.

[93]  P F Thall,et al.  Randomized phase II study of fludarabine + cytosine arabinoside + idarubicin +/- all-trans retinoic acid +/- granulocyte colony-stimulating factor in poor prognosis newly diagnosed acute myeloid leukemia and myelodysplastic syndrome. , 1999, Blood.

[94]  M. Cazzola,et al.  Deregulated Gene Expression Pathways in Myelodysplastic Syndrome Hematopoietic Stem Cells. , 2009 .

[95]  Pablo Tamayo,et al.  An Erythroid Differentiation Signature Predicts Response to Lenalidomide in Myelodysplastic Syndrome , 2008, PLoS medicine.

[96]  E. Zwarthoff,et al.  MN1 affects expression of genes involved in hematopoiesis and can enhance as well as inhibit RAR/RXR-induced gene expression. , 2008, Carcinogenesis.

[97]  Robert Tibshirani,et al.  An FLT3 gene-expression signature predicts clinical outcome in normal karyotype AML. , 2008, Blood.

[98]  Franco Locatelli,et al.  Gene expression-based classification as an independent predictor of clinical outcome in juvenile myelomonocytic leukemia. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

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

[100]  Crispin Miller,et al.  Quantitative Proteomics Analysis Demonstrates Post-transcriptional Regulation of Embryonic Stem Cell Differentiation to Hematopoiesis*S , 2008, Molecular & Cellular Proteomics.

[101]  K. Mills,et al.  FUS expression alters the differentiation response to all‐trans retinoic acid in NB4 and NB4R2 cells , 2007, British journal of haematology.

[102]  D. Scadden,et al.  The leukemic stem cell niche: current concepts and therapeutic opportunities. , 2009, Blood.

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

[104]  Fabien Campagne,et al.  DNA methylation signatures identify biologically distinct subtypes in acute myeloid leukemia. , 2010, Cancer cell.