Chronic myelogenous leukemia

Analysis of chronic myeloid leukaemia during deep molecular response by genomic PCR: a traffic light stratification model with impact on treatment-free remission


This work investigated patient-specific genomic BCR-ABL1 fusions as markers of measurable residual disease (MRD) in chronic myeloid leukaemia, with a focus on relevance to treatment-free remission (TFR) after achievement of deep molecular response (DMR) on tyrosine kinase inhibitor (TKI) therapy. DNA and mRNA BCR-ABL1 measurements by qPCR were compared in 2189 samples (129 patients) and by digital PCR in 1279 sample (62 patients). A high correlation was found at levels of disease above MR4, but there was a poor correlation for samples during DMR. A combination of DNA and RNA MRD measurements resulted in a better prediction of molecular relapse-free survival (MRFS) after TKI stop (n = 17) or scheduled interruption (n = 25). At 18 months after treatment cessation, patients with stopped or interrupted TKI therapy who were DNA negative/RNA negative during DMR maintenance (green group) had an MRFS of 80% and 100%, respectively, compared with those who were DNA positive/RNA negative (MRFS = 57% and 67%, respectively; yellow group) or DNA positive/RNA positive (MRFS = 20% for both cohorts; red group). Thus, we propose a “traffic light” stratification as a TFR predictor based on DNA and mRNA BCR-ABL1 measurements during DMR maintenance before TKI cessation.

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Fig. 1: Comparison of BCR-ABL1RelDg data at mRNA and DNA levels.
Fig. 2: Correlation of the individual parameter estimates of mRNA and DNA BCR-ABL1 samples using the bi-exponential mixed effects models.
Fig. 3: Effects of covariates on the individual parameter estimates of mRNA and DNA BCR-ABL1 samples using the bi-exponential mixed effects models.
Fig. 4: Rates of DMR maintenance and molecular relapse after TKI cessation/interruption in three groups of patients that were divided according to DNA and mRNA BCR-ABL1RelDg MRD pattern evaluated by the deterministic model in samples measured by ddPCR before TKI stop/interruption in EURO-SKI and INTReg patients.
Fig. 5: Probability of molecular relapse-free survival after TKI cessation/interruption according to traffic light stratification model.


  1. 1.

    Cross NC, White HE, Colomer D, Ehrencrona H, Foroni L, Gottardi E, et al. Laboratory recommendations for scoring deep molecular responses following treatment for chronic myeloid leukemia. Leukemia. 2015;29:999–1003.

    CAS  Article  Google Scholar 

  2. 2.

    Saussele S, Richter J, Guilhot J, Gruber FX, Hjorth-Hansen H, Almeida A, et al. Discontinuation of tyrosine kinase inhibitor therapy in chronic myeloid leukaemia (EURO-SKI): a prespecified interim analysis of a prospective, multicentre, non-randomised, trial. Lancet Oncol. 2018;19:747–57.

    CAS  Article  Google Scholar 

  3. 3.

    Shah N, Gutiérrez JVG, Jiménez-Velasco A, Larson SE, Saussele S, Rea D, et al. Updated 18-month results from Dasfree: a study evaluating dasatinib discontinuation in patients with dhronic myeloid leukemia in chronic phase and deep molecular response. Blood. 2018;132:4253.

    Article  Google Scholar 

  4. 4.

    Clark RE, Polydoros F, Apperley JF, Milojkovic D, Pocock C, Smith G, et al. De-escalation of tyrosine kinase inhibitor dose in patients with chronic myeloid leukaemia with stable major molecular response (DESTINY): an interim analysis of a non-randomised, phase 2 trial. Lancet Haematol. 2017;4:e310–6.

    Article  Google Scholar 

  5. 5.

    Mori S, Vagge E, le Coutre P, Abruzzese E, Martino B, Pungolino E, et al. Age and dPCR can predict relapse in CML patients who discontinued imatinib: the ISAV study. Am J Hematol. 2015;90:910–4.

    CAS  Article  Google Scholar 

  6. 6.

    Ross DM, Masszi T, Gómez Casares MT, Hellmann A, Stentoft J, Conneally E, et al. Durable treatment-free remission in patients with chronic myeloid leukemia in chronic phase following frontline nilotinib: 96-week update of the ENESTfreedom study. J Cancer Res Clin Oncol. 2018;144:945–54.

    CAS  Article  Google Scholar 

  7. 7.

    Mahon FX, Boquimpani C, Kim DW, Benyamini N, Clementino NCD, Shuvaev V, et al. Treatment-free remission after second-line nilotinib treatment in patients with chronic myeloid leukemia in chronic phase: results from a single-group, phase 2, open-label study. Ann Intern Med. 2018;168:461–70.

    Article  Google Scholar 

  8. 8.

    Nicolini FE, Dulucq S, Boureau L, Cony-Makhoul P, Charbonnier A, Escoffre-Barbe M, et al. The evaluation of residual disease by digital PCR, and TKI duration are critical predictive factors for molecular recurrence after for stopping imatinib first-line in chronic phase CML patients: results of the STIM2 study. Blood. 2018;132:462.

    Article  Google Scholar 

  9. 9.

    Cross NC, White HE, Müller MC, Saglio G, Hochhaus A. Standardized definitions of molecular response in chronic myeloid leukemia. Leukemia. 2012;26:2172–5.

    CAS  Article  Google Scholar 

  10. 10.

    Mahon FX, Réa D, Guilhot J, Guilhot F, Huguet F, Nicolini F, et al. Discontinuation of imatinib in patients with chronic myeloid leukaemia who have maintained complete molecular remission for at least 2 years: the prospective, multicentre Stop Imatinib (STIM) trial. Lancet Oncol. 2010;11:1029–35.

    CAS  Article  Google Scholar 

  11. 11.

    Ross DM, Branford S, Seymour JF, Schwarer AP, Arthur C, Yeung DT, et al. Safety and efficacy of imatinib cessation for CML patients with stable undetectable minimal residual disease: results from the TWISTER study. Blood. 2013;122:515–22.

    CAS  Article  Google Scholar 

  12. 12.

    Imagawa J, Tanaka H, Okada M, Nakamae H, Hino M, Murai K, et al. Discontinuation of dasatinib in patients with chronic myeloid leukaemia who have maintained deep molecular response for longer than 1 year (DADI trial): a multicentre phase 2 trial. Lancet Haematol. 2015;2:e528–35.

    Article  Google Scholar 

  13. 13.

    Chu S, McDonald T, Lin A, Chakraborty S, Huang Q, Snyder DS, et al. Persistence of leukemia stem cells in chronic myelogenous leukemia patients in prolonged remission with imatinib treatment. Blood. 2011;118:5565–72.

    CAS  Article  Google Scholar 

  14. 14.

    Ross DM, Branford S, Seymour JF, Schwarer AP, Arthur C, Bartley PA, et al. Patients with chronic myeloid leukemia who maintain a complete molecular response after stopping imatinib treatment have evidence of persistent leukemia by DNA PCR. Leukemia. 2010;24:1719–24.

    CAS  Article  Google Scholar 

  15. 15.

    Branford S, Yeung DT, Ross DM, Prime JA, Field CR, Altamura HK, et al. Early molecular response and female sex strongly predict stable undetectable BCR-ABL1, the criteria for imatinib discontinuation in patients with CML. Blood. 2013;121:3818–24.

    CAS  Article  Google Scholar 

  16. 16.

    Horn M, Glauche I, Müller MC, Hehlmann R, Hochhaus A, Loeffler M, et al. Model-based decision rules reduce the risk of molecular relapse after cessation of tyrosine kinase inhibitor therapy in chronic myeloid leukemia. Blood. 2013;121:378–84.

    CAS  Article  Google Scholar 

  17. 17.

    Ross DM, Pagani IS, Shanmuganathan N, Kok CH, Seymour JF, Mills AK, et al. Long-term treatment-free remission of chronic myeloid leukemia with falling levels of residual leukemic cells. Leukemia. 2018;32:2572–9.

    CAS  Article  Google Scholar 

  18. 18.

    Pagani IS, Dang P, Saunders VA, Grose R, Shanmuganathan N, Kok CH, et al. Lineage of measurable residual disease in patients with chronic myeloid leukemia in treatment-free remission. Leukemia. 2019.

  19. 19.

    Kumari A, Brendel C, Hochhaus A, Neubauer A, Burchert A. Low BCR-ABL expression levels in hematopoietic precursor cells enable persistence of chronic myeloid leukemia under imatinib. Blood. 2012;119:530–9.

    CAS  Article  Google Scholar 

  20. 20.

    Chomel JC, Sorel N, Guilhot J, Guilhot F, Turhan AG. BCR-ABL expression in leukemic progenitors and primitive stem cells of patients with chronic myeloid leukemia. Blood. 2012;119:2964–5.

    CAS  Article  Google Scholar 

  21. 21.

    Hovorkova L, Zaliova M, Venn NC, Bleckmann K, Trkova M, Potuckova E, et al. Monitoring of childhood ALL using BCR-ABL1 genomic breakpoints identifies a subgroup with CML-like biology. Blood. 2017;129:2771–81.

    CAS  Article  Google Scholar 

  22. 22.

    van der Velden VH, Cazzaniga G, Schrauder A, Hancock J, Bader P, Panzer-Grumayer ER, et al. Analysis of minimal residual disease by Ig/TCR gene rearrangements: guidelines for interpretation of real-time quantitative PCR data. Leukemia. 2007;21:604–11.

    Article  Google Scholar 

  23. 23.

    Glauche I, Kuhn M, Baldow C, Schulze P, Rothe T, Liebscher H, et al. Quantitative prediction of long-term molecular response in TKI-treated CML—lessons from an imatinib versus dasatinib comparison. Sci Rep. 2018;8:12330.

    Article  Google Scholar 

  24. 24.

    Ilander M, Olsson-Strömberg U, Schlums H, Guilhot J, Brück O, Lähteenmäki H, et al. Increased proportion of mature NK cells is associated with successful imatinib discontinuation in chronic myeloid leukemia. Leukemia. 2017;31:1108–16.

    CAS  Article  Google Scholar 

  25. 25.

    Schütz C, Inselmann S, Sausslele S, Dietz CT, Müller MC, Eigendorff E, et al. Expression of the CTLA-4 ligand CD86 on plasmacytoid dendritic cells (pDC) predicts risk of disease recurrence after treatment discontinuation in CML. Leukemia. 2017;32:1–8.

    Google Scholar 

  26. 26.

    Pagani IS, Dang P, Kommers IO, Goyne JM, Nicola M, Saunders VA, et al. BCR-ABL1 genomic DNA PCR response kinetics during first-line imatinib treatment of chronic myeloid leukemia. Haematologica. 2018;103:2026–32.

    CAS  Article  Google Scholar 

  27. 27.

    Fassoni AC, Baldow C, Roeder I, Glauche I. Reduced tyrosine kinase inhibitor dose is predicted to be as effective as standard dose in chronic myeloid leukemia: a simulation study based on phase III trial data. Haematologica. 2018;103:1825–34.

    CAS  Article  Google Scholar 

  28. 28.

    Roeder I, Horn M, Glauche I, Hochhaus A, Mueller MC, Loeffler M. Dynamic modeling of imatinib-treated chronic myeloid leukemia: functional insights and clinical implications. Nat Med. 2006;12:1181–4.

    CAS  Article  Google Scholar 

  29. 29.

    Wilson A, Laurenti E, Oser G, van der Wath RC, Blanco-Bose W, Jaworski M, et al. Hematopoietic stem cells reversibly switch from dormancy to self-renewal during homeostasis and repair. Cell. 2008;135:1118–29.

    CAS  Article  Google Scholar 

  30. 30.

    Hochhaus A, Saglio G, Hughes TP, Larson RA, Kim DW, Issaragrisil S, et al. Long-term benefits and risks of frontline nilotinib vs imatinib for chronic myeloid leukemia in chronic phase: 5-year update of the randomized ENESTnd trial. Leukemia. 2016;30:1044–54.

    CAS  Article  Google Scholar 

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This work was funded by the Project Grants #15–31540A and #16–30186A from the Czech Health Research Council and by the European Treatment and Outcome study (EUTOS) for CML. The authors thank for the institutional support #00023736 (Institute of Hematology and Blood Transfusion) and #00064203 (University Hospital Motol) from Ministry of Health of the Czech Republic and the Czech Leukaemia Study Group for Life. This work was further supported by ERA-Net ERACoSysMed JTC-2 project “prediCt” (project number 031L0136A) to IR. We would like to thank to Dr. Milada Småstuen (Oslo Metropolitan University) for the consolations on statistical analysis. The authors are grateful to the patients for providing their samples for this study.

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KMP designed the study, interpreted results and wrote the paper; HZ and EM performed ddPCR and qPCR analyses, analyzed data and provided data management; JZ supervised DNA PCR analysis, contributed to the writing of the paper; LH performed LD-PCR and characterized DNA BCR-ABL1 fusions; AG and IG performed statistical analysis using bi-exponential mixed effect models, interpreted results and reviewed the paper; JK performed bioinformatics of NGS data, designed primers and probes; PP performed statistical analysis; HK, MSM and DS supervised patient’s visits, evaluated and provided clinical data; AB and VP performed NGS analysis; TJ performed qPCR analysis; DZ and JM supervised patient’s visits, evaluated and provided clinical data; TE designed probes for NGS analysis; FXM and SS supervised the EURO-SKI study; IR supervised statistical analysis, advised the concept of the paper and critically reviewed the paper; NCPC contributed to the concept of the paper and the paper writing; AH supervised the work; all authors critically reviewed and approved the paper.

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Correspondence to Katerina Machova Polakova.

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Conflict of interest

KMP, TE, NCPC and AH received support by Novartis through the European Treatment and Outcome Study (EUTOS) for CML. The authors declare that they have no conflict of interest.

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This work was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the Ethics Committees of the Institute of Hematology and Blood Transfusion, Prague and Faculty Hospital Brno.

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All patients provided written informed consent for the use of their samples for this research.

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Machova Polakova, K., Zizkova, H., Zuna, J. et al. Analysis of chronic myeloid leukaemia during deep molecular response by genomic PCR: a traffic light stratification model with impact on treatment-free remission. Leukemia 34, 2113–2124 (2020).

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