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Minimal/Measurable Residual Disease Detection in Acute Leukemias by Multiparameter Flow Cytometry

  • Molecular Testing and Diagnostics (J Khoury, Section Editor)
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Abstract

Purpose of Review

Minimal or measurable residual disease (MRD) detected by multiparameter flow cytometry (MFC) is an independent prognostic indicator in acute leukemia. However, the predictive value of MFC MRD is affected by technical challenges, interpretive complexities, and inadequate standardization, particularly in acute myeloid leukemia (AML). Here, we critically review the methodological principles of the MFC MRD assay and discuss clinical implications of MRD.

Recent Findings

Key components of MFC MRD assays to be discussed include the principles of MFC, panel selection, analysis approaches, level of quantifiable MRD and calculation, reporting, and areas of improvements. Key components of clinical implications include context-dependent detection threshold and the integral role of MRD assessment by MFC in the era of ever-expanding molecular testing.

Summary

With advancements in technology and standardization, MFC along with molecular assays will continue to play an important role in MRD assessment to evaluate treatment response and risk stratification.

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References

Papers of particular interest, published recently, have been highlighted as: • Of importance

  1. Walter RB. Minimal residual disease testing after induction chemotherapy for acute myeloid leukemia: moving beyond prognostication? J Clin Oncol. 2018;36(15):1463–5. https://doi.org/10.1200/JCO.2018.78.3266.

    Article  PubMed  Google Scholar 

  2. Zhou Y, Wood BL. Methods of detection of measurable residual disease in AML. Curr Hematol Malig Rep. 2017;12(6):557–67. https://doi.org/10.1007/s11899-017-0419-5.

    Article  PubMed  Google Scholar 

  3. Schuurhuis GJ, Heuser M, Freeman S, Bene MC, Buccisano F, Cloos J, et al. Minimal/measurable residual disease in AML: a consensus document from the European LeukemiaNet MRD Working Party. Blood. 2018;131(12):1275–91. https://doi.org/10.1182/blood-2017-09-801498.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Jongen-Lavrencic M, Grob T, Hanekamp D, Kavelaars FG, Al Hinai A, Zeilemaker A, et al. Molecular minimal residual disease in acute myeloid leukemia. N Engl J Med. 2018;378(13):1189–99. https://doi.org/10.1056/NEJMoa1716863.

    Article  CAS  PubMed  Google Scholar 

  5. Freeman SD, Virgo P, Couzens S, Grimwade D, Russell N, Hills RK, et al. Prognostic relevance of treatment response measured by flow cytometric residual disease detection in older patients with acute myeloid leukemia. J Clin Oncol. 2013;31(32):4123–31. https://doi.org/10.1200/JCO.2013.49.1753.

    Article  PubMed  Google Scholar 

  6. 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(2):332–41. https://doi.org/10.1182/blood-2011-08-363291.

    Article  CAS  PubMed  Google Scholar 

  7. Ravandi F, Jorgensen J, Borthakur G, Jabbour E, Kadia T, Pierce S, et al. Persistence of minimal residual disease assessed by multiparameter flow cytometry is highly prognostic in younger patients with acute myeloid leukemia. Cancer. 2017;123(3):426–35. https://doi.org/10.1002/cncr.30361.

    Article  CAS  PubMed  Google Scholar 

  8. Terwijn M, van Putten WL, Kelder A, van der Velden VH, Brooimans RA, Pabst T, et al. High prognostic impact of flow cytometric minimal residual disease detection in acute myeloid leukemia: data from the HOVON/SAKK AML 42A study. J Clin Oncol. 2013;31(31):3889–97. https://doi.org/10.1200/JCO.2012.45.9628.

    Article  PubMed  Google Scholar 

  9. Freeman SD, Hills RK, Virgo P, Khan N, Couzens S, Dillon R, et al. Measurable residual disease at induction redefines partial response in acute myeloid leukemia and stratifies outcomes in patients at standard risk without NPM1 mutations. J Clin Oncol. 2018;36(15):1486–97. https://doi.org/10.1200/JCO.2017.76.3425.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Coustan-Smith E, Song G, Clark C, Key L, Liu P, Mehrpooya M, et al. New markers for minimal residual disease detection in acute lymphoblastic leukemia. Blood. 2011;117(23):6267–76. https://doi.org/10.1182/blood-2010-12-324004.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Borowitz MJ, Devidas M, Hunger SP, Bowman WP, Carroll AJ, Carroll WL, et al. Clinical significance of minimal residual disease in childhood acute lymphoblastic leukemia and its relationship to other prognostic factors: a Children’s Oncology Group study. Blood. 2008;111(12):5477–85. https://doi.org/10.1182/blood-2008-01-132837.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Bjorklund E, Mazur J, Soderhall S, Porwit-MacDonald A. Flow cytometric follow-up of minimal residual disease in bone marrow gives prognostic information in children with acute lymphoblastic leukemia. Leukemia. 2003;17(1):138–48. https://doi.org/10.1038/sj.leu.2402736.

    Article  CAS  PubMed  Google Scholar 

  13. Borowitz MJ, Wood BL, Devidas M, Loh ML, Raetz EA, Salzer WL, et al. Prognostic significance of minimal residual disease in high risk B-ALL: a report from Children’s Oncology Group study AALL0232. Blood. 2015;126(8):964–71. https://doi.org/10.1182/blood-2015-03-633685.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Campana D, Pui CH. Minimal residual disease-guided therapy in childhood acute lymphoblastic leukemia. Blood. 2017;129(14):1913–8. https://doi.org/10.1182/blood-2016-12-725804.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Gupta S, Devidas M, Loh ML, Raetz EA, Chen S, Wang C, et al. Flow-cytometric vs. -morphologic assessment of remission in childhood acute lymphoblastic leukemia: a report from the Children’s Oncology Group (COG). Leukemia. 2018;32(6):1370–9. https://doi.org/10.1038/s41375-018-0039-7.

    Article  PubMed  PubMed Central  Google Scholar 

  16. • Dohner H, Estey E, Grimwade D, Amadori S, Appelbaum FR, Buchner T, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood. 2017;129(4):424–47. https://doi.org/10.1182/blood-2016-08-733196 Provides updated recommendations of the European LeukemiaNet (ELN) for diagnosis and management of acute myeloid leukemia (AML) in adults, which were prompted by the recent development of new assays for genetic testing and minimal residual disease (MRD) testing as well as the development of novel antileukemic agents. The recommendations include a revised version of the ELN genetic categories, a proposal for a response category based on MRD status, and criteria for progressive disease.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Chen X, Wood BL. Monitoring minimal residual disease in acute leukemia: technical challenges and interpretive complexities. Blood Rev. 2017;31(2):63–75. https://doi.org/10.1016/j.blre.2016.09.006.

    Article  PubMed  Google Scholar 

  18. Paietta E. Consensus on MRD in AML? Blood. 2018;131(12):1265–6. https://doi.org/10.1182/blood-2018-01-828145.

    Article  CAS  PubMed  Google Scholar 

  19. Wood B. Multicolor immunophenotyping: human immune system hematopoiesis. Methods Cell Biol. 2004;75:559–76.

    Article  PubMed  Google Scholar 

  20. Craig FE, Foon KA. Flow cytometric immunophenotyping for hematologic neoplasms. Blood. 2008;111(8):3941–67. https://doi.org/10.1182/blood-2007-11-120535.

    Article  CAS  PubMed  Google Scholar 

  21. Chen W, Luu HS. Immunophenotyping by multiparameter flow cytometry. Methods Mol Biol. 2017;1633:51–73. https://doi.org/10.1007/978-1-4939-7142-8_4.

    Article  CAS  PubMed  Google Scholar 

  22. Chen W, Karandikar NJ, McKenna RW, Kroft SH. Stability of leukemia-associated immunophenotypes in precursor B-lymphoblastic leukemia/lymphoma: a single institution experience. Am J Clin Pathol. 2007;127(1):39–46. https://doi.org/10.1309/7R6MU7R9YWJBY5V4.

    Article  PubMed  Google Scholar 

  23. Wood BL. Principles of minimal residual disease detection for hematopoietic neoplasms by flow cytometry. Cytometry B Clin Cytom. 2016;90(1):47–53. https://doi.org/10.1002/cyto.b.21239.

    Article  PubMed  Google Scholar 

  24. Wood B, Jevremovic D, Bene MC, Yan M, Jacobs P, Litwin V, et al. Validation of cell-based fluorescence assays: practice guidelines from the ICSH and ICCS - part V - assay performance criteria. Cytometry B Clin Cytom. 2013;84(5):315–23. https://doi.org/10.1002/cyto.b.21108.

    Article  CAS  PubMed  Google Scholar 

  25. Barnett D, Louzao R, Gambell P, De J, Oldaker T, Hanson CA, et al. Validation of cell-based fluorescence assays: practice guidelines from the ICSH and ICCS - part IV - postanalytic considerations. Cytometry B Clin Cytom. 2013;84(5):309–14. https://doi.org/10.1002/cyto.b.21107.

    Article  CAS  PubMed  Google Scholar 

  26. Tanqri S, Vall H, Kaplan D, Hoffman B, Purvis N, Porwit A, et al. Validation of cell-based fluorescence assays: practice guidelines from the ICSH and ICCS - part III - analytical issues. Cytometry B Clin Cytom. 2013;84(5):291–308. https://doi.org/10.1002/cyto.b.21106.

    Article  Google Scholar 

  27. Davis BH, Dasgupta A, Kussick S, Han JY, Estrellado A, Group IIW. Validation of cell-based fluorescence assays: practice guidelines from the ICSH and ICCS - part II - preanalytical issues. Cytometry B Clin Cytom. 2013;84(5):286–90. https://doi.org/10.1002/cyto.b.21105.

    Article  CAS  PubMed  Google Scholar 

  28. Davis BH, Wood B, Oldaker T, Barnett D. Validation of cell-based fluorescence assays: practice guidelines from the ICSH and ICCS - part I - rationale and aims. Cytometry B Clin Cytom. 2013;84(5):282–5. https://doi.org/10.1002/cyto.b.21104.

    Article  CAS  PubMed  Google Scholar 

  29. Kalina T, Flores-Montero J, van der Velden VH, Martin-Ayuso M, Bottcher S, Ritgen M, et al. EuroFlow standardization of flow cytometer instrument settings and immunophenotyping protocols. Leukemia. 2012;26(9):1986–2010. https://doi.org/10.1038/leu.2012.122.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. van Dongen JJ, Lhermitte L, Bottcher S, Almeida J, van der Velden VH, Flores-Montero J, et al. EuroFlow antibody panels for standardized n-dimensional flow cytometric immunophenotyping of normal, reactive and malignant leukocytes. Leukemia. 2012;26(9):1908–75. https://doi.org/10.1038/leu.2012.120.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. van der Velden VH, Jacobs DC, Wijkhuijs AJ, Comans-Bitter WM, Willemse MJ, Hahlen K, et al. Minimal residual disease levels in bone marrow and peripheral blood are comparable in children with T cell acute lymphoblastic leukemia (ALL), but not in precursor-B-ALL. Leukemia. 2002;16(8):1432–6. https://doi.org/10.1038/sj.leu.2402636.

    Article  PubMed  Google Scholar 

  32. Coustan-Smith E, Sancho J, Hancock ML, Razzouk BI, Ribeiro RC, Rivera GK, et al. Use of peripheral blood instead of bone marrow to monitor residual disease in children with acute lymphoblastic leukemia. Blood. 2002;100(7):2399–402. https://doi.org/10.1182/blood-2002-04-1130.

    Article  CAS  PubMed  Google Scholar 

  33. Bruggemann M, Kotrova M. Minimal residual disease in adult ALL: technical aspects and implications for correct clinical interpretation. Blood Adv. 2017;1(25):2456–66. https://doi.org/10.1182/bloodadvances.2017009845.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Maurillo L, Buccisano F, Spagnoli A, Del Poeta G, Panetta P, Neri B, et al. Monitoring of minimal residual disease in adult acute myeloid leukemia using peripheral blood as an alternative source to bone marrow. Haematologica. 2007;92(5):605–11.

    Article  PubMed  Google Scholar 

  35. Keegan A, Charest K, Schmidt R, Briggs D, Deangelo DJ, Li B, et al. Flow cytometric minimal residual disease assessment of peripheral blood in acute lymphoblastic leukaemia patients has potential for early detection of relapsed extramedullary disease. J Clin Pathol. 2018;71(7):653–8. https://doi.org/10.1136/jclinpath-2017-204828.

    Article  CAS  PubMed  Google Scholar 

  36. Salina TD, Ferreira YA, Alves EB, Ferreira CM, De Paula EV, Mira MT, et al. Role of peripheral blood minimum residual disease at day 8 of induction therapy in high-risk pediatric patients with acute lymphocytic leukemia. Sci Rep. 2016;6:31179. https://doi.org/10.1038/srep31179.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Setiadi A, Owen D, Tsang A, Milner R, Vercauteren S. The significance of peripheral blood minimal residual disease to predict early disease response in patients with B-cell acute lymphoblastic leukemia. Int J Lab Hematol. 2016;38(5):527–34. https://doi.org/10.1111/ijlh.12535.

    Article  CAS  PubMed  Google Scholar 

  38. Garnache Ottou F, Chandesris MO, Lhermitte L, Callens C, Beldjord K, Garrido M, et al. Peripheral blood 8 colour flow cytometry monitoring of hairy cell leukaemia allows detection of high-risk patients. Br J Haematol. 2014;166(1):50–9. https://doi.org/10.1111/bjh.12839.

    Article  CAS  PubMed  Google Scholar 

  39. Wood BL. Flow cytometric monitoring of residual disease in acute leukemia. Methods Mol Biol. 2013;999:123–36. https://doi.org/10.1007/978-1-62703-357-2_8.

    Article  CAS  PubMed  Google Scholar 

  40. 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;3:e129. https://doi.org/10.1038/bcj.2013.27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Hosen N, Park CY, Tatsumi N, Oji Y, Sugiyama H, Gramatzki M, et al. CD96 is a leukemic stem cell-specific marker in human acute myeloid leukemia. Proc Natl Acad Sci U S A. 2007;104(26):11008–13. https://doi.org/10.1073/pnas.0704271104.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. 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(7):2659–66. https://doi.org/10.1182/blood-2007-03-083048.

    Article  CAS  PubMed  Google Scholar 

  43. van Rhenen A, Moshaver B, Kelder A, Feller N, Nieuwint AW, Zweegman S, et al. Aberrant marker expression patterns on the CD34+CD38- stem cell compartment in acute myeloid leukemia allows to distinguish the malignant from the normal stem cell compartment both at diagnosis and in remission. Leukemia. 2007;21(8):1700–7. https://doi.org/10.1038/sj.leu.2404754.

    Article  CAS  PubMed  Google Scholar 

  44. Zeijlemaker W, Kelder A, Oussoren-Brockhoff YJ, Scholten WJ, Snel AN, Veldhuizen D, et al. A simple one-tube assay for immunophenotypical quantification of leukemic stem cells in acute myeloid leukemia. Leukemia. 2016;30(2):439–46. https://doi.org/10.1038/leu.2015.252.

    Article  CAS  PubMed  Google Scholar 

  45. Jan M, Chao MP, Cha AC, Alizadeh AA, Gentles AJ, Weissman IL, et al. Prospective separation of normal and leukemic stem cells based on differential expression of TIM3, a human acute myeloid leukemia stem cell marker. Proc Natl Acad Sci U S A. 2011;108(12):5009–14. https://doi.org/10.1073/pnas.1100551108.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Xu Y, McKenna RW, Wilson KS, Karandikar NJ, Schultz RA, Kroft SH. Immunophenotypic identification of acute myeloid leukemia with monocytic differentiation. Leukemia. 2006;20(7):1321–4. https://doi.org/10.1038/sj.leu.2404242.

    Article  CAS  PubMed  Google Scholar 

  47. Yang DT, Greenwood JH, Hartung L, Hill S, Perkins SL, Bahler DW. Flow cytometric analysis of different CD14 epitopes can help identify immature monocytic populations. Am J Clin Pathol. 2005;124(6):930–6.

    Article  CAS  PubMed  Google Scholar 

  48. • Keeney M, Wood BL, Hedley BD, DiGiuseppe JA, Stetler-Stevenson M, Paietta E, et al. A QA program for MRD testing demonstrates that systematic education can reduce discordance among experienced interpreters. Cytometry B Clin Cytom. 2018;94(2):239–49. https://doi.org/10.1002/cyto.b.21528 Suggests that implementation of the Children’s Oncology Group (COG) standardized methodology for MFC MRD B-ALL testing in North American into widespread clinical laboratories may be possible but will require strong educational components to ensure correct identification of MRD, especially in a background containing hematogones. The rate of discordance between laboratories significantly decreased from 26% (2nd phase of the study) to 9% (3rd phase) after a specific educational program was implemented.

    Article  PubMed  Google Scholar 

  49. CONTEXFLO, DiGiuseppe JM. Development of a 10-color user-defined screening tube for B-cell neoplasia. BD Biosciences; 2018. https://www.youtube.com/watch?v=vEelV9IHJV4

  50. Nagant C, Casula D, Janssens A, Nguyen VTP, Cantinieaux B. Easy discrimination of hematogones from lymphoblasts in B-cell progenitor acute lymphoblastic leukemia patients using CD81/CD58 expression ratio. Int J Lab Hematol. 2018. https://doi.org/10.1111/ijlh.12912.

  51. Fuhrmann S, Schabath R, Moricke A, Zimmermann M, Kunz JB, Kulozik AE, et al. Expression of CD56 defines a distinct subgroup in childhood T-ALL with inferior outcome. Results of the ALL-BFM 2000 trial. Br J Haematol. 2018. https://doi.org/10.1111/bjh.15503.

  52. Wang YZ, Hao L, Chang Y, Jiang Q, Jiang H, Zhang LP, et al. A seven-color panel including CD34 and TdT could be applied in >97% patients with T cell lymphoblastic leukemia for minimal residual disease detection independent of the initial phenotype. Leuk Res. 2018;72:12–9. https://doi.org/10.1016/j.leukres.2018.07.012.

    Article  PubMed  Google Scholar 

  53. Fuda RMF, Xu Y, Karandikar NT. USCAP Annual Meeting Abstracts. 1047 All cases of precursor T acute lymphoblastic leukemia/lymphoma (T-ALL) exhibit multiple immunophenotypic aberrancies. Mod Pathol. 2006;19:225A. https://doi.org/10.1038/sj.modpathol.3800849.

    Article  Google Scholar 

  54. Shah NN, Stevenson MS, Yuan CM, Richards K, Delbrook C, Kreitman RJ, et al. Characterization of CD22 expression in acute lymphoblastic leukemia. Pediatr Blood Cancer. 2015;62(6):964–9. https://doi.org/10.1002/pbc.25410.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Cherian S, Miller V, McCullouch V, Dougherty K, Fromm JR, Wood BL. A novel flow cytometric assay for detection of residual disease in patients with B-lymphoblastic leukemia/lymphoma post anti-CD19 therapy. Cytometry B Clin Cytom. 2018;94(1):112–20. https://doi.org/10.1002/cyto.b.21482.

    Article  CAS  PubMed  Google Scholar 

  56. Shaver AC, Seegmiller AC. B lymphoblastic leukemia minimal residual disease assessment by flow cytometric analysis. Clin Lab Med. 2017;37(4):771–85. https://doi.org/10.1016/j.cll.2017.07.005.

    Article  PubMed  Google Scholar 

  57. Reichard K, Kroft SH. Flow cytometry in the assessment of hematologic disorders. In: Atilio Orazi KF, Knowles D, Weiss L, editors. Knowles’ neoplastic hematopathology. Third ed. Philadelphia: Lipincott, Williams, and Wilkins; 2014. p. 119–45.

    Google Scholar 

  58. Pedreira CE, Costa ES, Lecrevisse Q, van Dongen JJ, Orfao A, EuroFlow C. Overview of clinical flow cytometry data analysis: recent advances and future challenges. Trends Biotechnol. 2013;31(7):415–25. https://doi.org/10.1016/j.tibtech.2013.04.008.

    Article  CAS  PubMed  Google Scholar 

  59. Pedreira CE, Costa ES, Barrena S, Lecrevisse Q, Almeida J, van Dongen JJ, et al. Generation of flow cytometry data files with a potentially infinite number of dimensions. Cytometry A. 2008;73(9):834–46. https://doi.org/10.1002/cyto.a.20608.

    Article  PubMed  Google Scholar 

  60. Roshal M, Fromm JR, Winter S, Dunsmore K, Wood BL. Immaturity associated antigens are lost during induction for T cell lymphoblastic leukemia: implications for minimal residual disease detection. Cytometry B Clin Cytom. 2010;78(3):139–46. https://doi.org/10.1002/cyto.b.20511.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Voskova D, Schoch C, Schnittger S, Hiddemann W, Haferlach T, Kern W. Stability of leukemia-associated aberrant immunophenotypes in patients with acute myeloid leukemia between diagnosis and relapse: comparison with cytomorphologic, cytogenetic, and molecular genetic findings. Cytometry B Clin Cytom. 2004;62(1):25–38. https://doi.org/10.1002/cyto.b.20025.

    Article  PubMed  Google Scholar 

  62. 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):1–9. https://doi.org/10.1002/cyto.b.20037.

    Article  PubMed  Google Scholar 

  63. Dworzak MN, Gaipa G, Schumich A, Maglia O, Ratei R, Veltroni M, et al. Modulation of antigen expression in B-cell precursor acute lymphoblastic leukemia during induction therapy is partly transient: evidence for a drug-induced regulatory phenomenon. Results of the AIEOP-BFM-ALL-FLOW-MRD-Study Group. Cytometry B Clin Cytom. 2010;78(3):147–53. https://doi.org/10.1002/cyto.b.20516.

    Article  CAS  PubMed  Google Scholar 

  64. Baer MR, Stewart CC, Dodge RK, Leget G, Sule N, Mrozek 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(11):3574–80.

    Article  CAS  PubMed  Google Scholar 

  65. Zeijlemaker W, Gratama JW, Schuurhuis GJ. Tumor heterogeneity makes AML a “moving target” for detection of residual disease. Cytometry B Clin Cytom. 2014;86(1):3–14. https://doi.org/10.1002/cyto.b.21134.

    Article  CAS  PubMed  Google Scholar 

  66. Ho TC, LaMere M, Stevens BM, Ashton JM, Myers JR, O'Dwyer KM, et al. Evolution of acute myelogenous leukemia stem cell properties after treatment and progression. Blood. 2016;128(13):1671–8. https://doi.org/10.1182/blood-2016-02-695312.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Hedley BD, Keeney M. Technical issues: flow cytometry and rare event analysis. Int J Lab Hematol. 2013;35(3):344–50. https://doi.org/10.1111/ijlh.12068.

    Article  CAS  PubMed  Google Scholar 

  68. Subira D, Castanon S, Aceituno E, Hernandez J, Jimenez-Garofano C, Jimenez A, et al. Flow cytometric analysis of cerebrospinal fluid samples and its usefulness in routine clinical practice. Am J Clin Pathol. 2002;117(6):952–8. https://doi.org/10.1309/123P-CE6V-WYAK-BB1F.

    Article  PubMed  Google Scholar 

  69. • Theunissen P, Mejstrikova E, Sedek L, van der Sluijs-Gelling AJ, Gaipa G, Bartels M, et al. Standardized flow cytometry for highly sensitive MRD measurements in B-cell acute lymphoblastic leukemia. Blood. 2017;129(3):347–57. https://doi.org/10.1182/blood-2016-07-726307 Developed a fully standardized EuroFlow 8-color antibody panel and laboratory procedure that detects and measures MRD in B-ALL with a sensitivity of ≤ 10 −5 , comparable to RQ-PCR molecular-based MRD detection via antigen-receptor rearrangements. As this is a high-throughput MFC-MRD test that requires evaluating at least four million cells, the authors not only present data to support their conclusions; they provide a description of new procedures that enable adequate assessment of such large cell numbers, such as a new EuroFlow erythrocyte bulk-lysis procedure.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Rawstron AC, Fazi C, Agathangelidis A, Villamor N, Letestu R, Nomdedeu J, et al. A complementary role of multiparameter flow cytometry and high-throughput sequencing for minimal residual disease detection in chronic lymphocytic leukemia: an European Research Initiative on CLL study. Leukemia. 2016;30(4):929–36. https://doi.org/10.1038/leu.2015.313.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Rawstron AC, Bottcher S, Letestu R, Villamor N, Fazi C, Kartsios H, et al. Improving efficiency and sensitivity: European Research Initiative in CLL (ERIC) update on the international harmonised approach for flow cytometric residual disease monitoring in CLL. Leukemia. 2013;27(1):142–9. https://doi.org/10.1038/leu.2012.216.

    Article  CAS  PubMed  Google Scholar 

  72. Nieto WG, Almeida J, Romero A, Teodosio C, Lopez A, Henriques AF, et al. Increased frequency (12%) of circulating chronic lymphocytic leukemia-like B-cell clones in healthy subjects using a highly sensitive multicolor flow cytometry approach. Blood. 2009;114(1):33–7. https://doi.org/10.1182/blood-2009-01-197368.

    Article  CAS  PubMed  Google Scholar 

  73. Arroz M, Came N, Lin P, Chen W, Yuan C, Lagoo A, et al. Consensus guidelines on plasma cell myeloma minimal residual disease analysis and reporting. Cytometry B Clin Cytom. 2016;90(1):31–9. https://doi.org/10.1002/cyto.b.21228.

    Article  CAS  PubMed  Google Scholar 

  74. Cardinali JL, Linden M. ICCS e-Newsletter: CAP flow cytometry checklist; difficult and new items. Spring. 2015. https://www.cytometry.org/public/newsletters/eICCS-6-2/article5.php

  75. Hourigan CS, Gale RP, Gormley NJ, Ossenkoppele GJ, Walter RB. Measurable residual disease testing in acute myeloid leukaemia. Leukemia. 2017;31(7):1482–90. https://doi.org/10.1038/leu.2017.113.

    Article  CAS  PubMed  Google Scholar 

  76. Hrabovsky S, Folber F, Horacek JM, Stehlikova O, Jelinkova H, Salek C, et al. Comparison of real-time quantitative polymerase chain reaction and eight-color flow cytometry in assessment of minimal residual disease in adult acute lymphoblastic leukemia. Clin Lymphoma Myeloma Leuk. 2018. https://doi.org/10.1016/j.clml.2018.06.030.

  77. Huang YJ, Coustan-Smith E, Kao HW, Liu HC, Chen SH, Hsiao CC, et al. Concordance of two approaches in monitoring of minimal residual disease in B-precursor acute lymphoblastic leukemia: fusion transcripts and leukemia-associated immunophenotypes. J Formos Med Assoc. 2017;116(10):774–81. https://doi.org/10.1016/j.jfma.2016.12.002.

    Article  PubMed  Google Scholar 

  78. Gaipa G, Cazzaniga G, Valsecchi MG, Panzer-Grumayer R, Buldini B, Silvestri D, et al. Time point-dependent concordance of flow cytometry and real-time quantitative polymerase chain reaction for minimal residual disease detection in childhood acute lymphoblastic leukemia. Haematologica. 2012;97(10):1582–93. https://doi.org/10.3324/haematol.2011.060426.

    Article  PubMed  PubMed Central  Google Scholar 

  79. Thorn I, Forestier E, Botling J, Thuresson B, Wasslavik C, Bjorklund E, et al. Minimal residual disease assessment in childhood acute lymphoblastic leukaemia: a Swedish multi-centre study comparing real-time polymerase chain reaction and multicolour flow cytometry. Br J Haematol. 2011;152(6):743–53. https://doi.org/10.1111/j.1365-2141.2010.08456.x.

    Article  PubMed  Google Scholar 

  80. Ossenkoppele G, Schuurhuis GJ. MRD in AML: does it already guide therapy decision-making? Hematology Am Soc Hematol Educ Program. 2016;2016(1):356–65. https://doi.org/10.1182/asheducation-2016.1.356.

    Article  PubMed  PubMed Central  Google Scholar 

  81. 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(2):91–101. https://doi.org/10.1002/cyto.b.20444.

    Article  PubMed  Google Scholar 

  82. 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(10):3078–85. https://doi.org/10.1182/blood-2004-03-1036.

    Article  CAS  PubMed  Google Scholar 

  83. San Miguel JF, Vidriales MB, Lopez-Berges C, Diaz-Mediavilla J, Gutierrez N, Canizo 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(6):1746–51.

    Article  CAS  PubMed  Google Scholar 

  84. Campana D, Coustan-Smith E. Detection of minimal residual disease in acute leukemia by flow cytometry. Cytometry. 1999;38(4):139–52.

    Article  CAS  PubMed  Google Scholar 

  85. Porwit-MacDonald A, Bjorklund E, Lucio P, van Lochem EG, Mazur J, Parreira A, et al. BIOMED-1 concerted action report: flow cytometric characterization of CD7+ cell subsets in normal bone marrow as a basis for the diagnosis and follow-up of T cell acute lymphoblastic leukemia (T-ALL). Leukemia. 2000;14(5):816–25.

    Article  CAS  PubMed  Google Scholar 

  86. Lucio P, Gaipa G, van Lochem EG, van Wering ER, Porwit-MacDonald A, Faria T, et al. BIOMED-I concerted action report: flow cytometric immunophenotyping of precursor B-ALL with standardized triple-stainings. BIOMED-1 concerted action investigation of minimal residual disease in acute leukemia: international standardization and clinical evaluation. Leukemia. 2001;15(8):1185–92.

    Article  CAS  PubMed  Google Scholar 

  87. Walter RB, Appelbaum FR. Next-generation sequencing for measuring minimal residual disease in AML. Nat Rev Clin Oncol. 2018;15(8):473–4. https://doi.org/10.1038/s41571-018-0040-0.

    Article  CAS  PubMed  Google Scholar 

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Fuda, F., Chen, W. Minimal/Measurable Residual Disease Detection in Acute Leukemias by Multiparameter Flow Cytometry. Curr Hematol Malig Rep 13, 455–466 (2018). https://doi.org/10.1007/s11899-018-0479-1

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