Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Manuscript
  • Published:

Gene Expression Profile in AML

Gene expression profile reveals deregulation of genes with relevant functions in the different subclasses of acute myeloid leukemia

Leukemia volume 19, pages 402–409 (2005)Cite this article

Abstract

Bone marrow samples from 43 adult patients with de novo diagnosed acute myeloid leukemia (AML) – 10 acute promyelocytic leukemias (APL) with t(15;17), four AML with inv(16), seven monocytic leukemias and 22 nonmonocytic leukemias – were analyzed using high-density oligonucleotide microarrays. Hierarchical clustering analysis segregated APL, AML with inv(16), monocytic leukemias and the remaining AML into separate groups. A set of only 21 genes was able to assign AML to one of these three classes: APL, inv(16) and other AML subtype without a specific translocation. Quantitative RT-PCR performed for 18 out of these predictor genes confirmed microarray results. APL expressed high levels of FGF13 and FGFR1 as well as two potent angiogenic factors, HGF and VEGF. AML with inv(16) showed an upregulation of MYH11 and a downregulation of a gene encoding a core-binding factor protein, RUNX3. Genes involved in cell adhesion represented the most altered functional category in monocytic leukemias. Two major groups emerged from the remaining 22 AML: cluster A with 10 samples and cluster B with 12. All the eight leukemias that were either refractory to treatment or that relapsed afterwards were assigned to cluster B. In the latter cluster, CD34 upregulation and serine proteases downregulation is consistent with a maturation arrest and lack of granulocytic differentiation.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2

Similar content being viewed by others

References

  1. Vardiman JW, Harris NL, Brunning RD . The World Health Organization (WHO) classification of the myeloid neoplasms. Blood 2002; 100: 2292–2302.

    Article  CAS  Google Scholar 

  2. Grimwade D, Walker H, Oliver F, Wheatley K, Harrison C, Harrison G et al. The importance of diagnostic cytogenetics on outcome in AML: analysis of 1,612 patients entered into the MRC AML 10 trial. The Medical Research Council Adult and Children's Leukaemia Working Parties. Blood 1998; 92: 2322–2333.

    CAS  Google Scholar 

  3. Slovak ML, Kopecky KJ, Cassileth PA, Harrington DH, Theil KS, Mohamed A et al. Karyotypic analysis predicts outcome of preremission and postremission therapy in adult acute myeloid leukemia: a Southwest Oncology Group/Eastern Cooperative Oncology Group Study. Blood 2000; 96: 4075–4083.

    CAS  PubMed  Google Scholar 

  4. Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 1999; 286: 531–537.

    Article  CAS  Google Scholar 

  5. Schoch C, Kohlmann A, Schnittger S, Brors B, Dugas M, Mergenthaler S et al. Acute myeloid leukemias with reciprocal rearrangements can be distinguished by specific gene expression profiles. Proc Natl Acad Sci USA 2002; 99: 10008–10013.

    Article  CAS  Google Scholar 

  6. Debernardi S, Lillington DM, Chaplin T, Tomlinson S, Amess J, Rohatiner A et al. Genome-wide analysis of acute myeloid leukemia with normal karyotype reveals a unique pattern of homeobox gene expression distinct from those with translocation-mediated fusion events. Genes Chromosomes Cancer 2003; 37: 149–158.

    Article  CAS  Google Scholar 

  7. Kohlmann A, Schoch C, Schnittger S, Dugas M, Hiddemann W, Kern W et al. Molecular characterization of acute leukemias by use of microarray technology. Genes Chromosomes Cancer 2003; 37: 396–405.

    Article  CAS  Google Scholar 

  8. Valk PJ, Verhaak RG, Beijen MA, Erpelinck CA, van Waalwijk van Doorn-Khosrovani SB, Boer JM et al. Prognostically useful gene-expression profiles in acute myeloid leukemia. N Engl J Med 2004; 350: 1617–1628.

    Article  CAS  Google Scholar 

  9. Bullinger L, Dohner K, Bair E, Frohling S, Schlenk RF, Tibshirani R et al. Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia. N Engl J Med 2004; 350: 1605–1616.

    Article  CAS  Google Scholar 

  10. Armstrong SA, Staunton JE, Silverman LB, Pieters R, Den Boer ML, Minden MD et al. MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia. Nat Genet 2002; 30: 41–47.

    Article  CAS  Google Scholar 

  11. Virtaneva K, Wright FA, Tanner SM, Yuan B, Lemon WJ, Caligiuri MA et al. Expression profiling reveals fundamental biological differences in acute myeloid leukemia with isolated trisomy 8 and normal cytogenetics. Proc Natl Acad Sci USA 2001; 98: 1124–1129.

    Article  CAS  Google Scholar 

  12. Qian Z, Fernald AA, Godley LA, Larson RA, Le Beau MM . Expression profiling of CD34+ hematopoietic stem/progenitor cells reveals distinct subtypes of therapy-related acute myeloid leukemia. Proc Natl Acad Sci USA 2002; 99: 14925–14930.

    Article  CAS  Google Scholar 

  13. Staal FJ, van der Burg M, Wessels LF, Barendregt BH, Baert MR, van den Burg CM et al. DNA microarrays for comparison of gene expression profiles between diagnosis and relapse in precursor-B acute lymphoblastic leukemia: choice of technique and purification influence the identification of potential diagnostic markers. Leukemia 2003; 17: 1324–1332.

    Article  CAS  Google Scholar 

  14. Chillón MC, Fernández C, García-Sanz R, Balanzategui A, Ramos F, Fernández-Calvo J et al. FLT3-activating mutations are associated with poor prognostic features in AML at diagnosis but they are not an independent prognostic factor. Hematol J 2004; 5: 239–246.

    Article  Google Scholar 

  15. Sanz MA, Martín G, Rayón C, Esteve J, González M, Díaz-Mediavilla J et al. A modified AIDA protocol with anthracycline-based consolidation results in high antileukemic efficacy and reduced toxicity in newly diagnosed PML/RARalpha-positive acute promyelocytic leukemia. PETHEMA group. Blood 1999; 94: 3015–3021.

    CAS  PubMed  Google Scholar 

  16. Eisen MB, Spellman PT, Brown PO, Botstein D . Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 1998; 95: 14863–14868.

    Article  CAS  Google Scholar 

  17. Borg I, Groenen PM . Modern Multidimensional Scaling: Theory and Applications. New York: Springer Verlag, 1997.

    Book  Google Scholar 

  18. Tusher VG, Tibshirani R, Chu G . Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA 2001; 98: 5116–5121.

    Article  CAS  Google Scholar 

  19. Tibshirani R, Hastie T, Narasimhan B, Chu G . Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc Natl Acad Sci USA 2002; 99: 6567–6572.

    Article  CAS  Google Scholar 

  20. Furey TS, Cristianini N, Duffy N, Bednarski DW, Schummer M, Haussler D . Support vector machine classification and validation of cancer tissue samples using microarray expression data. Bioinformatics 2000; 16: 906–914.

    Article  CAS  Google Scholar 

  21. Ririe KM, Rasmussen RP, Wittwer CT . Product differentiation by analysis of DNA melting curves during the polymerase chain reaction. Anal Biochem 1997; 245: 154–160.

    Article  CAS  Google Scholar 

  22. Leung KH, Pippalla V, Kreutter A, Chandler M . Functional effects of FGF-13 on human lung fibroblasts, dermal microvascular endothelial cells, and aortic smooth muscle cells. Biochem Biophys Res Commun 1998; 250: 137–142.

    Article  CAS  Google Scholar 

  23. Inhorn RC, Aster JC, Roach SA, Slapak CA, Soiffer R, Tantravahi R et al. A syndrome of lymphoblastic lymphoma, eosinophilia, and myeloid hyperplasia/malignancy associated with t(8;13)(p11;q11): description of a distinctive clinicopathologic entity. Blood 1995; 85: 1881–1887.

    CAS  PubMed  Google Scholar 

  24. Macdonald D, Reiter A, Cross NC . The 8p11 myeloproliferative syndrome: a distinct clinical entity caused by constitutive activation of FGFR1. Acta Haematol 2002; 107: 101–107.

    Article  CAS  Google Scholar 

  25. Cross NC, Reiter A . Tyrosine kinase fusion genes in chronic myeloproliferative diseases. Leukemia 2002; 16: 1207–1212.

    Article  CAS  Google Scholar 

  26. Jiang W, Hiscox S, Matsumoto K, Nakamura T . Hepatocyte growth factor/scatter factor, its molecular, cellular and clinical implications in cancer. Crit Rev Oncol Hematol 1999; 29: 209–248.

    Article  CAS  Google Scholar 

  27. Verstovsek S, Kantarjian H, Estey E, Aguayo A, Giles FJ, Manshouri T et al. Plasma hepatocyte growth factor is a prognostic factor in patients with acute myeloid leukemia but not in patients with myelodysplastic syndrome. Leukemia 2001; 15: 1165–1170.

    Article  CAS  Google Scholar 

  28. Kini AR, Peterson LA, Tallman MS, Lingen MW . Angiogenesis in acute promyelocytic leukemia: induction by vascular endothelial growth factor and inhibition by all-trans retinoic acid. Blood 2001; 97: 3919–3924.

    Article  CAS  Google Scholar 

  29. Moehler TM, Ho AD, Goldschmidt H, Barlogie B . Angiogenesis in hematologic malignancies. Crit Rev Oncol Hematol 2003; 45: 227–244.

    Article  CAS  Google Scholar 

  30. Giles FJ, Stopeck AT, Silverman LR, Lancet JE, Cooper MA, Hannah AL et al. SU5416, a small molecule tyrosine kinase receptor inhibitor, has biologic activity in patients with refractory acute myeloid leukemia or myelodysplastic syndromes. Blood 2003; 102: 795–801.

    Article  CAS  Google Scholar 

  31. Drabkin HA, Parsy C, Ferguson K, Guilhot F, Lacotte L, Roy L et al. Quantitative HOX expression in chromosomally defined subsets of acute myelogenous leukemia. Leukemia 2002; 16: 186–195.

    Article  CAS  Google Scholar 

  32. Owens BM, Hawley RG . HOX and non-HOX omeobox genes in leukemic hematopoiesis. Stem Cells 2002; 20: 364–379.

    Article  CAS  Google Scholar 

  33. Thorsteinsdottir U, Kroon E, Jerome L, Blasi F, Sauvageau G . Defining roles for HOX and MEIS1 genes in induction of acute myeloid leukemia. Mol Cell Biol 2001; 21: 224–234.

    Article  CAS  Google Scholar 

  34. Kawagoe H, Kawagoe R, Sano K . Targeted down-regulation of MLL-AF9 with antisense oligodeoxyribonucleotide reduces the expression of the HOXA7 and -A10 genes and induces apoptosis in a human leukemia cell line, THP-1. Leukemia 2001; 15: 1743–1749.

    Article  CAS  Google Scholar 

  35. Hernández JM, Martín G, Gutiérrez NC, Cervera J, Ferro MT, Calasanz MJ et al. Additional cytogenetic changes do not influence the outcome of patients with newly diagnosed acute promyelocytic leukemia treated with an ATRA plus anthracyclin based protocol. A report of the Spanish group PETHEMA. Haematologica 2001; 86: 807–813.

    PubMed  Google Scholar 

  36. van der Reijden BA, Lombardo M, Dauwerse HG, Giles RH, Muhlematter D, Bellomo MJ et al. RT-PCR diagnosis of patients with acute nonlymphocytic leukemia and inv(16)(p13q22) and identification of new alternative splicing in CBFB-MYH11 transcripts. Blood 1995; 86: 277–282.

    CAS  PubMed  Google Scholar 

  37. Cleveland DW, Yen TJ . Multiple determinants of eukaryotic mRNA stability. New Biol 1989; 1: 121–126.

    CAS  PubMed  Google Scholar 

  38. van der Reijden BA, Massop M, Tonnissen E, van de Locht L, Muus P, De Witte T et al. Rapid identification of CBFB-MYH11-positive acute myeloid leukemia (AML) cases by one single MYH11 real-time RT-PCR. Blood 2003; 101: 5085–5086.

    Article  CAS  Google Scholar 

  39. Li QL, Ito K, Sakakura C, Fukamachi H, Inoue K, Chi XZ et al. Causal relationship between the loss of RUNX3 expression and gastric cancer. Cell 2002; 109: 113–124.

    Article  CAS  Google Scholar 

  40. Lutz PG, Houzel-Charavel A, Moog-Lutz C, Cayre YE . Myeloblastin is an Myb target gene: mechanisms of regulation in myeloid leukemia cells growth-arrested by retinoic acid. Blood 2001; 97: 2449–2456.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank Mark Anderson of the University Technology Transfer Office and M Ángeles Hernández, Amador Crego, Ana Simón, Laura Hierro and Estela Hernández for technical assistance. We are grateful to Fenghuang Zhan and John Shaughnessy for technical support on microarray analysis. This study was partially supported by ‘Ministerio de Ciencia y Tecnología’ Grant (SAF2001-1687) and Spanish FIS Grant (02/1358). NCG, RLP and JLG were partially supported by grants from ‘Fundación Española de Hematología y Hemoterapia’, ‘Asociación Española contra el Cáncer’ and Spanish FIS (01/3153), respectively.

Author information

Authors and Affiliations

  1. Servicio de Hematología, Hospital Universitario de Salamanca and Centro de Investigación del Cáncer (CIC), Universidad de Salamanca-CSIC, Spain

    N C Gutiérrez, R López-Pérez, J M Hernández, I Isidro, B González, M Delgado, E Fermiñán, J L García, L Vázquez, M González & J F San Miguel

Authors
  1. N C Gutiérrez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. R López-Pérez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J M Hernández
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. I Isidro
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. B González
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. M Delgado
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. E Fermiñán
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. J L García
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. L Vázquez
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. M González
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. J F San Miguel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J F San Miguel.

Additional information

Supplementary Information

Supplementary Information accompanies the paper on the Leukemia website (http://www.nature.com/leu)

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gutiérrez, N., López-Pérez, R., Hernández, J. et al. Gene expression profile reveals deregulation of genes with relevant functions in the different subclasses of acute myeloid leukemia. Leukemia 19, 402–409 (2005). https://doi.org/10.1038/sj.leu.2403625

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/sj.leu.2403625

Keywords

Search

Advanced search

Quick links