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Acute Leukemias

Discriminant function analysis as decision support system for the diagnosis of acute leukemia with a minimal four color screening panel and multiparameter flow cytometry immunophenotyping

Abstract

Despite several recommendations for standardization of multiparameter flow cytometry (MFC) the number, specificity and combinations of reagents used by diagnostic laboratories for the diagnosis and classification of acute leukemias (AL) are still very diverse. Furthermore, the current diagnostic interpretation of flow cytometry readouts is influenced arbitrarily by individual experience and knowledge. We determined the potential value of a minimal four-color combination panel of 13 monoclonal antibodies (mAbs) with a CD45/sideward light scatter-gating strategy for a standardized MFC immunophenotyping of the clinically most relevant subgroups of AL. Bone marrow samples from 155 patients with acute myeloid leukemia (AML, n=79), B-cell precursor acute lymphoblastic leukemia (BCP-ALL, n=29), T-cell precursor acute lymphoblastic leukemia (T-ALL, n=12) and normal bone marrow donors (NBMD, n=35) were analyzed. A knowledge-based learning algorithm was generated by comparing the results of the minimal panel with the actual diagnosis, using discriminative function analysis. Correct classification of the test sample according to lineage, that is, BCP-ALL, T-ALL, AML and differentiation of NBMD was achieved in 97.2% of all cases with only six of the originally applied 13 mAbs of the panel. This provides evidence that discriminant function analysis can be utilized as a decision support system for interpretation of flow cytometry readouts.

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References

  1. Weinkauff R, Estey EH, Starostik P, Hayes K, Huh YO, Hirsch Ginsberg C et al. Use of peripheral blood blasts vs bone marrow blasts for diagnosis of acute leukemia. Am J Clin Pathol 1999; 111: 733–740.

    Article  CAS  PubMed  Google Scholar 

  2. Jennings CD, Foon KA . Recent advances in flow cytometry: application to the diagnosis of hematologic malignancy. Blood 1997; 90: 2863–2892.

    CAS  PubMed  Google Scholar 

  3. Shapiro HM . The evolution of cytometers. Cytometry A 2004; 58: 13–20.

    Article  PubMed  Google Scholar 

  4. Roederer M, De Rosa S, Gerstein R, Anderson M, Bigos M, Stovel R et al. 8 color, 10-parameter flow cytometry to elucidate complex leukocyte heterogeneity. Cytometry 1997; 29: 328–339.

    Article  CAS  PubMed  Google Scholar 

  5. Basso G, Buldini B, De Zen L, Orfao A . New methodologic approaches for immunophenotyping acute leukemias. Haematologica 2001; 86: 675–692.

    CAS  PubMed  Google Scholar 

  6. Baumgarth N, Roederer M . A practical approach to multicolor flow cytometry for immunophenotyping. J Immunol Methods 2000; 243: 77–97.

    Article  CAS  PubMed  Google Scholar 

  7. Owens MA, Vall HG, Hurley AA, Wormsley SB . Validation and quality control of immunophenotyping in clinical flow cytometry. J Immunol Methods 2000; 243: 33–50.

    Article  CAS  PubMed  Google Scholar 

  8. Kluin Nelemans J, Van Wering E, Van Der Schoot C, Adriaansen H, Van'T Veer M, Van Dongen J et al. SIHONSCORE: a scoring system for external quality control of leukaemia/lymphoma immunophenotyping measuring all analytical phases of laboratory performance. Br J Haematol 2001; 112: 337–343.

    Article  CAS  PubMed  Google Scholar 

  9. Gratama JW, Bolhuis RL, Van'T Veer MB . Quality control of flow cytometric immunophenotyping of haematological malignancies. Clin Lab Haematol 1999; 21: 155–160.

    Article  CAS  PubMed  Google Scholar 

  10. Braylan RC, Orfao A, Borowitz MJ, Davis BH . Optimal number of reagents required to evaluate hematolymphoid neoplasias: results of an international consensus meeting. Cytometry 2001; 46: 23–27.

    Article  CAS  PubMed  Google Scholar 

  11. Weir EG, Cowan K, LeBeau P, Borowitz MJ . A limited antibody panel can distinguish B-precursor acute lymphoblastic leukemia from normal B precursors with four color flow cytometry: implications for residual disease detection. Leukemia 1999; 13: 558–567.

    Article  CAS  PubMed  Google Scholar 

  12. Stewart CC, Behm FG, Carey JL, Cornbleet J, Duque RE, Hudnall SD et al. US-Canadian Consensus recommendations on the immunophenotypic analysis of hematologic neoplasia by flow cytometry: selection of antibody combinations. Cytometry 1997; 30: 231–235.

    Article  CAS  PubMed  Google Scholar 

  13. Weir EG, Borowitz MJ . Flow cytometry in the diagnosis of acute leukemia. Semin Hematol 2001; 38: 124–138.

    Article  CAS  PubMed  Google Scholar 

  14. Kraan J, Gratama JW, Keeney M, D'Hautcourt JL . Setting up and calibration of a flow cytometer for multicolor immunophenotyping. J Biol Regul Homeost Agents 2003; 17: 223–233.

    CAS  PubMed  Google Scholar 

  15. Ratei R, Karawajew L, Lacombe F, Jagoda K, Del Poeta G, Kraan J et al. Normal lymphocytes from leukemic samples as an internal quality control for fluorescence intensity in immunophenotyping of acute leukemias. Cytometry B Clin Cytom 2006; 70: 1–9.

    Article  PubMed  Google Scholar 

  16. Westgard JO, Groth T . A predictive value model for quality control: effects of the prevalence of errors on the performance of control procedures. Am J Clin Pathol 1983; 80: 49–56.

    Article  CAS  PubMed  Google Scholar 

  17. Rainer RO, Hodges L, Seltzer GT . CD 45 gating correlates with bone marrow differential. Cytometry 1995; 22: 139–145.

    Article  CAS  PubMed  Google Scholar 

  18. Lacombe F, Durrieu F, Briais A, Dumain P, Belloc F, Bascans E et al. Flow cytometry CD45 gating for immunophenotyping of acute myeloid leukemia. Leukemia 1997; 11: 1878–1886.

    Article  CAS  PubMed  Google Scholar 

  19. Tabachnick BG, Fidell LS . Discriminant function analysis. Using Multivariate Statistics, (4th ed.); Chapter 11 Allyn & Bacon: Boston, 2001, 461–519.

    Google Scholar 

  20. Stelzer GT, Shults KE, Loken MR . CD45 gating for routine flow cytometric analysis of human bone marrow specimens. Ann NY Acad Sci 1993; 677: 265–280.

    Article  CAS  PubMed  Google Scholar 

  21. Hrusak O, Porwit-MacDonald A . Antigen expression patterns reflecting genotype of acute leukemias. Leukemia 2002; 16: 1233–1258.

    Article  CAS  PubMed  Google Scholar 

  22. Casasnovas RO, Slimane FK, Garand R, Faure GC, Campos L, Deneys V et al. Immunological classification of acute myeloblastic leukemias: relevance to patient outcome. Leukemia 2003; 17: 515–527.

    Article  CAS  PubMed  Google Scholar 

  23. De Zen L, Bicciato S, te Kronnie G, Basso G . Computational analysis of flow-cytometry antigen expression profiles in childhood acute lymphoblastic leukemia: an MLL/AF4 identification. Leukemia 2003; 17: 1557–1565.

    Article  CAS  PubMed  Google Scholar 

  24. Zamir E, Geiger B, Cohen N, Kam Z, Katz BZ . Resolving and classifying haematopoietic bone-marrow cell populations by multi-dimensional analysis of flow-cytometry data. Br J Haematol 2005; 129: 420–431.

    Article  PubMed  Google Scholar 

  25. Costa ES, Arroyo ME, Pedreira CE, Garcia-Marcos MA, Tabernero MD, Almeida J et al. A new automated flow cytometry data analysis approach for the diagnostic screening of neoplastic B-cell disorders in peripheral blood samples with absolute lymphocytosis. Leukemia 2006; 20: 1221–1230.

    Article  CAS  PubMed  Google Scholar 

  26. Valet G, Valet M, Tschope D, Gabriel H, Rothe G, Kellermann W et al. White cell and thrombocyte disorders. Standardized, self-learning flow cytometric list mode data classification with the CLASSIF1 program system. Ann NY Acad Sci 1993; 677: 233–251.

    Article  CAS  PubMed  Google Scholar 

  27. Toedling J, Rhein P, Ratei R, Karawajew L, Spang R . Automated in-silico detection of cell populations in flow cytometry readouts and its application to leukemia disease monitoring. BMC Bioinform 2006; 7: 282.

    Article  Google Scholar 

  28. Bene MC, Castoldi G, Knapp W, Ludwig WD, Matutes E, Orfao A et al. Proposals for the immunological classification of acute leukemias. European Group for the Immunological Characterization of Leukemias (EGIL). Leukemia 1995; 9: 1783–1786.

    CAS  PubMed  Google Scholar 

  29. Bene MC, Bernier M, Casasnovas RO, Castoldi G, Knapp W, Lanza F et al. The reliability and specificity of c-kit for the diagnosis of acute myeloid leukemias and undifferentiated leukemias. The European Group for the Immunological Classification of Leukemias (EGIL). Blood 1998; 92: 596–599.

    CAS  PubMed  Google Scholar 

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Acknowledgements

Richard Ratei was supported by Wilhelm Sander Stiftung, grant 2004.072.1.

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Ratei, R., Karawajew, L., Lacombe, F. et al. Discriminant function analysis as decision support system for the diagnosis of acute leukemia with a minimal four color screening panel and multiparameter flow cytometry immunophenotyping. Leukemia 21, 1204–1211 (2007). https://doi.org/10.1038/sj.leu.2404675

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