Skip to main content
SpringerLink
Log in

Multi-color flow cytometric immunophenotyping for detection of minimal residual disease in AML: past, present and future

  • Review
  • Published:
Bone Marrow Transplantation Submit manuscript

Abstract

Current chemotherapeutic regimens achieve CR in a large percentage of patients with AML. However, relapse after CR remains a significant problem. The presence of leukemic cells at levels too low to be detected by conventional microscopy, termed minimal residual disease (MRD), has been associated with an increased risk of relapse and shortened survival. Detection of MRD requires the use of highly sensitive ancillary techniques. Multi-color flow cytometric immunophenotyping is a sensitive method for quick and accurate detection of MRD. Use of this method in patient management may result in lower rates of relapse and improved survival, and is an effective means of assessing novel therapeutic agents. This method can be used in the vast majority of patients with AML, regardless of the immunophenotypic, cytogenetic and molecular genetic abnormalities present. Unfortunately, conflicting data regarding optimum methods of measurement and reporting, as well as the expertize required to interpret results have limited broad application of this technique. We provide a broad overview of this technique, including its advantages and limitations, and discuss the methods employed at our institution. We also review several possible areas of future investigation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5

Similar content being viewed by others

References

  1. Estey EH . Acute myeloid leukemia: 2013 update on risk-stratification and management. Am J Hematol 2013; 88: 318–327.

    Article  CAS  Google Scholar 

  2. Ravandi F . Relapsed acute myeloid leukemia: why is there no standard of care? Best Pract Res Clin Haematol 2013; 26: 253–259.

    Article  Google Scholar 

  3. Bachas C, Schuurhuis GJ, Assaraf YG, Kwidama ZJ, Kelder A, Wouters F et al. The role of minor subpopulations within the leukemic blast compartment of AML patients at initial diagnosis in the development of relapse. Leukemia 2012; 26: 1313–1320.

    Article  CAS  Google Scholar 

  4. San Miguel JF, Martínez A, Macedo A, Vidriales MB, López-Berges C, González M et al. Immunophenotyping investigation of minimal residual disease is a useful approach for predicting relapse in acute myeloid leukemia patients. Blood 1997; 90: 2465–2470.

    CAS  PubMed  Google Scholar 

  5. Döhner H, Estey EH, Amadori S, Appelbaum FR, Büchner T, Burnett AK et al. Diagnosis and management of acute myeloid leukemia in adults: recommendations from an international expert panel, on behalf of the European LeukemiaNet. Blood 2010; 15: 453–474.

    Article  Google Scholar 

  6. Grossmann V, Schnittger S, Kohlmann A, Eder C, Roller A, Dicker F et al. A novel hierarchical prognostic model of AML solely based on molecular mutations. Blood 2012; 120: 2963–2972.

    Article  CAS  Google Scholar 

  7. Buccisano F, Maurillo L, Del Principe MI, Del Poeta G, Sconocchia G, Lo-Coco F et al. Prognostic and therapeutic implications of minimal residual disease detection in acute myeloid leukemia. Blood 2012; 119: 332–341.

    Article  CAS  Google Scholar 

  8. Hourigan CS, Karp JE . Minimal residual disease in acute myeloid leukaemia. Nat Rev Clin Oncol 2013; 10: 460–471.

    Article  CAS  Google Scholar 

  9. Jorgensen JL, Chen SS . Monitoring of minimal residual disease in acute myeloid leukemia: methods and best applications. Clin Lymphoma Myeloma Leuk 2011; 11: S49–S53.

    Article  Google Scholar 

  10. Harris R . Leukaemia antigens and immunity in man. Nature 1973; 241: 95–100.

    Article  CAS  Google Scholar 

  11. Baker MA, Ramachandar K, Taub RN . Specificity of heteroantisera to human acute leukemia-associated antigens. J Clin Invest 1974; 54: 1273–1278.

    Article  CAS  Google Scholar 

  12. Greaves MF . Proceedings: surface antigens of leukaemic cells. Br J Cancer 1975; 32: 280–281.

    Article  CAS  Google Scholar 

  13. Terstappen LW, Safford M, Könemann S, Loken MR, Zurlutter K, Büchner T et al. Flow cytometric characterization of acute myeloid leukemia. Part II. Phenotypic heterogeneity at diagnosis. Leukemia 1992; 6: 70–80.

    CAS  PubMed  Google Scholar 

  14. Drach J, Drach D, Glassl H, Gattringer C, Huber H . Flow cytometric determination of atypical antigen expression in acute leukemia for the study of minimal residual disease. Cytometry 1992; 13: 893–901.

    Article  CAS  Google Scholar 

  15. Reading CL, Estey EH, Huh YO, Claxton DF, Sanchez G, Terstappen LW et al. Expression of unusual immunophenotype combinations in acute myelogenous leukemia. Blood 1993; 81: 3083–3090.

    CAS  PubMed  Google Scholar 

  16. Macedo A, Orfão A, Vidriales MB, López-Berges MC, Valverde B, González M et al. Characterization of aberrant phenotypes in acute myeloblastic leukemia. Ann Hematol 1995; 70: 189–194.

    Article  CAS  Google Scholar 

  17. San Miguel JF, Vidriales MB, López-Berges C, Díaz-Mediavilla J, Gutiérrez N, Cañizo C et al. Early immunophenotypical evaluation of minimal residual disease in acute myeloid leukemia identifies different patient risk groups and may contribute to postinduction treatment stratification. Blood 2001; 98: 1746–1751.

    Article  CAS  Google Scholar 

  18. Al-Mawali A, Gillis D, Hissaria P, Lewis I . Incidence, sensitivity, and specificity of leukemia-associated phenotypes in acute myeloid leukemia using specific five-color multiparameter flow cytometry. Am J Clin Pathol 2008; 129: 934–945.

    Article  Google Scholar 

  19. Al-Mawali A, Gillis D, Lewis I . The role of multiparameter flow cytometry for detection of minimal residual disease in acute myeloid leukemia. Am J Clin Pathol 2009; 131: 16–26.

    Article  Google Scholar 

  20. Baer MR, Stewart CC, Dodge RK, Leget G, Sulé N, Mrózek K et al. High frequency of immunophenotype changes in acute myeloid leukemia at relapse: implications for residual disease detection (Cancer and Leukemia Group B Study 8361). Blood 2001; 97: 3574–3580.

    Article  CAS  Google Scholar 

  21. Langebrake C, Brinkmann I, Teigler-Schlegel A, Creutzig U, Griesinger F, Puhlmann U et al. Immunophenotypic differences between diagnosis and relapse in childhood AML: implications for MRD monitoring. Cytometry B Clin Cytom 2005; 63: 1–9.

    Article  Google Scholar 

  22. Payne KJ, Crooks GM . Human hematopoietic lineage commitment. Immunol Rev 2002; 187: 48–64.

    Article  Google Scholar 

  23. Wood B . Multicolor immunophenotyping: human immune system hematopoiesis. Methods Cell Biol 2004; 75: 559–576.

    Article  Google Scholar 

  24. Sievers EL, Lange BJ, Alonzo TA, Gerbing RB, Bernstein ID, Smith FO et al. Immunophenotypic evidence of leukemia after induction therapy predicts relapse: results from a prospective Children's Cancer Group study of 252 patients with acute myeloid leukemia. Blood 2003; 101: 3398–3406.

    Article  CAS  Google Scholar 

  25. Loken MR, Alonzo TA, Pardo L, Gerbing RB, Raimondi SC, Hirsch BA et al. Residual disease detected by multidimensional flow cytometry signifies high relapse risk in patients with de novo acute myeloid leukemia: a report from Children's Oncology Group. Blood 2012; 120: 1581–1588.

    Article  Google Scholar 

  26. Paietta E . Minimal residual disease in acute myeloid leukemia: coming of age. Hematology Am Soc Hematol Educ Program 2012; 2012: 35–42.

    PubMed  Google Scholar 

  27. Venditti A, Buccisano F, Del Poeta G, Maurillo L, Tamburini A, Cox C et al. Level of minimal residual disease after consolidation therapy predicts outcome in acute myeloid leukemia. Blood 2000; 96: 3948–3952.

    CAS  PubMed  Google Scholar 

  28. Langebrake C, Creutzig U, Dworzak M, Hrusak O, Mejstrikova E, Griesinger F et al. Residual disease monitoring in childhood acute myeloid leukemia by multiparameter flow cytometry: the MRD-AML-BFM Study Group. J Clin Oncol 2006; 24: 3686–3692.

    Article  Google Scholar 

  29. Kern W, Voskova D, Schoch C, Schnittger S, Hiddemann W, Haferlach T . Prognostic impact of early response to induction therapy as assessed by multiparameter flow cytometry in acute myeloid leukemia. Haematologica 2004; 89: 528–540.

    PubMed  Google Scholar 

  30. Kern W, Voskova D, Schoch C, Hiddemann W, Schnittger S, Haferlach T . Determination of relapse risk based on assessment of minimal residual disease during complete remission by multiparameter flow cytometry in unselected patients with acute myeloid leukemia. Blood 2004; 104: 3078–3085.

    Article  CAS  Google Scholar 

  31. Rubnitz JE, Inaba H, Dahl G, Ribeiro RC, Bowman WP, Taub J et al. Minimal residual disease-directed therapy for childhood acute myeloid leukaemia: results of the AML02 multicentre trial. Lancet Oncol 2010; 11: 543–552.

    Article  CAS  Google Scholar 

  32. Inaba H, Coustan-Smith E, Cao X, Pounds SB, Shurtleff SA, Wang KY et al. Comparative analysis of different approaches to measure treatment response in acute myeloid leukemia. J Clin Oncol 2012; 30: 3625–3632.

    Article  Google Scholar 

  33. Walter RB, Buckley SA, Pagel JM, Wood BL, Storer BE, Sandmaier BM et al. Significance of minimal residual disease before myeloablative allogeneic hematopoietic cell transplantation for AML in first and second complete remission. Blood 2013; 10: 1813–1821.

    Article  Google Scholar 

  34. Hokland P, Ommen HB . Towards individualized follow-up in adult acute myeloid leukemia in remission. Blood 2011; 117: 2577–2584.

    Article  CAS  Google Scholar 

  35. Coustan-Smith E, Campana D . Should evaluation for minimal residual disease be routine in acute myeloid leukemia? Curr Opin Hematol 2013; 20: 86–92.

    Article  Google Scholar 

  36. Grimwade D, Jovanovic JV, Hills RK, Nugent EA, Patel Y, Flora R et al. Prospective minimal residual disease monitoring to predict relapse of acute promyelocytic leukemia and to direct pre-emptive arsenic trioxide therapy. J Clin Oncol 2009; 27: 3650–3658.

    Article  CAS  Google Scholar 

  37. Grimwade D, Vyas P, Freeman S . Assessment of minimal residual disease in acute myeloid leukemia. Curr Opin Oncol 2010; 22: 656–663.

    Article  Google Scholar 

  38. Al-Mawali A, Gillis D, Lewis I . The use of receiver operating characteristic analysis for detection of minimal residual disease using five-color multiparameter flow cytometry in acute myeloid leukemia identifies patients with high risk of relapse. Cytometry B Clin Cytom 2009; 76: 91–101.

    Article  Google Scholar 

  39. Feller N, van der Velden VH, Brooimans RA, Boeckx N, Preijers F, Kelder A et al. Defining consensus leukemia-associated immunophenotypes for detection of minimal residual disease in acute myeloid leukemia in a multicenter setting. Blood Cancer J 2013; advance online publication 2 August 2013, doi:10.1038/bcj.2013.27.

  40. Béné MC, Nebe T, Bettelheim P, Buldini B, Bumbea H, Kern W et al. Immunophenotyping of acute leukemia and lymphoproliferative disorders: a consensus proposal of the European LeukemiaNet Work Package 10. Leukemia 2011; 25: 567–574.

    Article  Google Scholar 

  41. Freeman SD, Jovanovic JV, Grimwade D . Development of minimal residual disease-directed therapy in acute myeloid leukemia. Semin Oncol 2008; 35: 388–400.

    Article  CAS  Google Scholar 

  42. Pedreira CE, Costa ES, Arroyo ME, Almeida J, Orfao A . A multidimensional classification approach for the automated analysis of flow cytometry data. IEEE Trans Biomed Eng 2008; 55: 1155–1162.

    Article  Google Scholar 

  43. Fišer K, Sieger T, Schumich A, Wood B, Irving J, Mejstříková E et al. Detection and monitoring of normal and leukemic cell populations with hierarchical clustering of flow cytometry data. Cytometry A 2012; 81: 25–34.

    Article  Google Scholar 

  44. Aghaeepour N, Finak G, Hoos H, Mosmann TR . FlowCAP Consortium, DREAM Consortium Critical assessment of automated flow cytometry data analysis techniques. Nat Methods 2013; 10: 228–238.

    Article  CAS  Google Scholar 

  45. Bonnet D, Dick JE . Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat Med 1997; 3: 730–737.

    Article  CAS  Google Scholar 

  46. Hope KJ, Jin L, Dick JE . Acute myeloid leukemia originates from a hierarchy of leukemic stem cell classes that differ in self-renewal capacity. Nat Immunol 2004; 5: 738–743.

    Article  CAS  Google Scholar 

  47. van Rhenen A, van Dongen GA, Kelder A, Rombouts EJ, Feller N, Moshaver B et al. The novel AML stem cell associated antigen CLL-1 aids in discrimination between normal and leukemic stem cells. Blood 2007; 110: 2659–2666.

    Article  CAS  Google Scholar 

  48. Majeti R, Chao MP, Alizadeh AA, Pang WW, Jaiswal S, Gibbs KD Jr. et al. CD47 is an adverse prognostic factor and therapeutic antibody target on human acute myeloid leukemia stem cells. Cell 2009; 138: 286–299.

    Article  CAS  Google Scholar 

  49. Majeti R . Monoclonal antibody therapy directed against human acute myeloid leukemia stem cells. Oncogene 2011; 30: 1009–1019.

    Article  CAS  Google Scholar 

  50. Hokland P, Ommen HB, Nyvold CG, Roug AS . Sensitivity of minimal residual disease in acute myeloid leukaemia in first remission–methodologies in relation to their clinical situation. Br J Haematol 2012; 158: 569–580.

    Article  Google Scholar 

  51. Jawad M, Yu N, Seedhouse C, Tandon K, Russell NH, Pallis M . Targeting of CD34+CD38− cells using Gemtuzumab ozogamicin (Mylotarg) in combination with tipifarnib (Zarnestra) in acute myeloid leukaemia. BMC Cancer 2012; 12: 431.

    Article  CAS  Google Scholar 

  52. Cilloni D, Gottardi E, De Micheli D, Serra A, Volpe G, Messa F et al. Quantitative assessment of WT1 expression by real time quantitative PCR may be a useful tool for monitoring minimal residual disease in acute leukemia patients. Leukemia 2002; 16: 2115–2121.

    Article  CAS  Google Scholar 

  53. Lapillonne H, Renneville A, Auvrignon A, Flamant C, Blaise A, Perot C et al. High WT1 expression after induction therapy predicts high risk of relapse and death in pediatric acute myeloid leukemia. J Clin Oncol 2006; 24: 1507–1515.

    Article  CAS  Google Scholar 

  54. Cilloni D, Messa F, Arruga F, Defilippi I, Gottardi E, Fava M et al. Early prediction of treatment outcome in acute myeloid leukemia by measurement of WT1 transcript levels in peripheral blood samples collected after chemotherapy. Haematologica 2008; 93: 921–924.

    Article  Google Scholar 

  55. Candoni A, Tiribelli M, Toffoletti E, Cilloni D, Chiarvesio A, Michelutti A et al. Quantitative assessment of WT1 gene expression after allogeneic stem cell transplantation is a useful tool for monitoring minimal residual disease in acute myeloid leukemia. Eur J Haematol 2009; 82: 61–68.

    Article  CAS  Google Scholar 

  56. Válková V, Polák J, Marková M, Vítek A, Hájková H, Sálek C et al. Minimal residual disease detectable by quantitative assessment of WT1 gene before allogeneic stem cell transplantation in patients in first remission of acute myeloid leukemia has an impact on their future prognosis. Clin Transplant 2013; 27: E21–E29.

    Article  Google Scholar 

  57. Zhao XS, Yan CH, Liu DH, Xu LP, Liu YR, Liu KY et al. Combined use of WT1 and flow cytometry monitoring can promote sensitivity of predicting relapse after allogeneic HSCT without affecting specificity. Ann Hematol 2013; 92: 1111–1119.

    Article  CAS  Google Scholar 

  58. Cilloni D, Renneville A, Hermitte F, Hills RK, Daly S, Jovanovic JV et al. Real-time quantitative polymerase chain reaction detection of minimal residual disease by standardized WT1 assay to enhance risk stratification in acute myeloid leukemia: a European LeukemiaNet study. J Clin Oncol 2009; 27: 5195–5201.

    Article  CAS  Google Scholar 

  59. Buccisano F, Maurillo L, Spagnoli A, Del Principe MI, Fraboni D, Panetta P et al. Cytogenetic and molecular diagnostic characterization combined to postconsolidation minimal residual disease assessment by flow cytometry improves risk stratification in adult acute myeloid leukemia. Blood 2010; 116: 2295–2303.

    Article  CAS  Google Scholar 

  60. Jourdan E, Boissel N, Chevret S, Delabesse E, Renneville A, Cornillet P et al. Prospective evaluation of gene mutations and minimal residual disease in patients with core binding factor acute myeloid leukemia. Blood 2013; 121: 2213–2223.

    Article  CAS  Google Scholar 

  61. Kaplan D, Husel W, Meyerson H . Immunophenotypic analysis with enhanced sensitivity of detection by enzymatic amplification staining. Clin Lab Med 2001; 21: 763–778.

    CAS  PubMed  Google Scholar 

  62. Mattison RJ, Luger SM, Lazarus HM . New strategies for the evaluation of the nadir bone marrow following induction in acute myeloid leukemia. Curr Opin Hematol 2013; 20: 93–99.

    Article  CAS  Google Scholar 

  63. Liso V, Albano F, Pastore D, Carluccio P, Mele G, Lamacchia M et al. Bone marrow aspirate on the 14th day of induction treatment as a prognostic tool in de novo adult acute myeloid leukemia. Haematologica 2000; 85: 1285–1290.

    CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Hematopathology, University of Texas MD Anderson Cancer Center, Houston, TX, USA

    J M Jaso, S A Wang, J L Jorgensen & P Lin

Authors
  1. J M Jaso
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S A Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J L Jorgensen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. P Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to P Lin.

Ethics declarations

Competing interests

The authors declare no conflicts of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jaso, J., Wang, S., Jorgensen, J. et al. Multi-color flow cytometric immunophenotyping for detection of minimal residual disease in AML: past, present and future. Bone Marrow Transplant 49, 1129–1138 (2014). https://doi.org/10.1038/bmt.2014.99

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/bmt.2014.99

  • Springer Nature Limited

This article is cited by

Search

Navigation