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.

  • Article
  • Published:

CHRONIC MYELOGENOUS LEUKEMIA

Droplet digital PCR for the detection of second-generation tyrosine kinase inhibitor-resistant BCR::ABL1 kinase domain mutations in chronic myeloid leukemia

Leukemia volume 36, pages 2250–2260 (2022)Cite this article

Subjects

Abstract

One of the indications for BCR::ABL1 mutation testing in chronic myeloid leukemia (CML) is when tyrosine kinase inhibitor therapy (TKI) needs to be changed for unsatisfactory response. In this study, we evaluated a droplet digital PCR (ddPCR)-based multiplex strategy for the detection and quantitation of transcripts harbouring mutations conferring resistance to second-generation TKIs (2GTKIs). Parallel quantitation of e13a2, e14a2 and e1a2 BCR::ABL1 fusion transcripts enables to express results as percentage of mutation positive- over total BCR::ABL1 transcripts. We determined the limit of blank in 60 mutation-negative samples. Accuracy was demonstrated by further analysis of 48 samples already studied by next generation sequencing (NGS). Mutations could be called down to 0.5% and across 3-logs of BCR::ABL1 levels. Retrospective review of BCR::ABL1 NGS results in 513 consecutive CML patients with non-optimal response to first- or second-line TKI therapy suggested that a ddPCR-based approach targeted against 2GTKI-resistant mutations would score samples as mutation-negative in 22% of patients with warning response to imatinib but only in 6% of patients with warning response to 2GTKIs. We conclude ddPCR represents an attractive method for easy, accurate and rapid screening for 2GTKI-resistant mutations impacting on TKI selection, although ddPCR cannot identify compound mutations.

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

Fig. 1: Schematic representation of the expected output for tube 1, 2, and 3.
Fig. 2: Representative results obtained with serial dilutions of mutated into unmutated BCR::ABL1-positive cell lines.
Fig. 3: Results obtained with serial dilutions of mutated into unmutated BCR::ABL1-positive cell lines and BCR::ABL1-negative cell lines mimicking different BCR::ABL1/ABL1 transcript levels.
Fig. 4: Representative examples of 2D plots.
Fig. 5: Mutation kinetics by ddPCR and by NGS in three representative patients who developed 2GTKI-resistant mutations on therapy.

Similar content being viewed by others

Data availability

Materials described in this manuscript, including all relevant raw data, will be freely available upon request to any researcher wishing to use them for non-commercial purposes.

References

  1. Bavaro L, Martelli M, Cavo M, Soverini S. Mechanisms of Disease Progression and Resistance to Tyrosine Kinase Inhibitor Therapy in Chronic Myeloid Leukemia: An Update. Int J Mol Sci. 2019;20. https://doi.org/10.3390/ijms20246141

  2. Hochhaus A, Baccarani M, Silver RT, Schiffer C, Apperley JF, Cervantes F, et al. European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. Leukemia 2020;34:966–84. https://doi.org/10.1038/s41375-020-0776-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Cortes JE, Kantarjian H, Shah NP, Bixby D, Mauro MJ, Flinn I, et al. Ponatinib in refractory Philadelphia chromosome-positive leukemias. N Engl J Med. 2012;367:2075–88. https://doi.org/10.1056/NEJMoa1205127

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Hughes TP, Mauro MJ, Cortes JE, Minami H, Rea D, DeAngelo DJ, et al. Asciminib in Chronic Myeloid Leukemia after ABL Kinase Inhibitor Failure. N Engl J Med. 2019;381:2315–26. https://doi.org/10.1056/NEJMoa1902328

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Soverini S, Hochhaus A, Nicolini FE, Gruber F, Lange T, Saglio G, et al. BCR-ABL kinase domain mutation analysis in chronic myeloid leukemia patients treated with tyrosine kinase inhibitors: recommendations from an expert panel on behalf of European LeukemiaNet. Blood 2011;118:1208–15. https://doi.org/10.1182/blood-2010-12-326405

    Article  CAS  PubMed  Google Scholar 

  6. Soverini S, De Benedittis C, Machova Polakova K, Brouckova A, Horner D, Iacono M, et al. Unraveling the complexity of tyrosine kinase inhibitor-resistant populations by ultra-deep sequencing of the BCR-ABL kinase domain. Blood 2013;122:1634–48. https://doi.org/10.1182/blood-2013-03-487728

    Article  CAS  PubMed  Google Scholar 

  7. Machova Polakova K, Kulvait V, Benesova A, Linhartova J, Klamova H, Jaruskova M, et al. Next-generation deep sequencing improves detection of BCR-ABL1 kinase domain mutations emerging under tyrosine kinase inhibitor treatment of chronic myeloid leukemia patients in chronic phase. J Cancer Res Clin Oncol. 2015;141:887–99. https://doi.org/10.1007/s00432-014-1845-6

    Article  CAS  PubMed  Google Scholar 

  8. Baer C, Kern W, Koch S, Nadarajah N, Schindela S, Meggendorfer M, et al. Ultra-deep sequencing leads to earlier and more sensitive detection of the tyrosine kinase inhibitor resistance mutation T315I in chronic myeloid leukemia. Haematologica 2016;101:830–8. https://doi.org/10.3324/haematol.2016.145888

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Soverini S, De Benedittis C, Polakova KM, Linhartova J, Castagnetti F, Gugliotta G, et al. Next-generation sequencing for sensitive detection of BCR-ABL1 mutations relevant to tyrosine kinase inhibitor choice in imatinib-resistant patients. Oncotarget 2016;7:21982–90. https://doi.org/10.18632/oncotarget.8010

    Article  PubMed  PubMed Central  Google Scholar 

  10. Soverini S, De Benedittis C, Castagnetti F, Gugliotta G, Mancini M, Bavaro L, et al. In chronic myeloid leukemia patients on second-line tyrosine kinase inhibitor therapy, deep sequencing of BCR-ABL1 at the time of warning may allow sensitive detection of emerging drug-resistant mutants. BMC Cancer. 2016;16:572 https://doi.org/10.1186/s12885-016-2635-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kizilors A, Crisa E, Lea N, Passera R, Mian S, Anwar J, et al. Effect of low-level BCR-ABL1 kinase domain mutations identified by next-generation sequencing in patients with chronic myeloid leukaemia: A population-based study. Lancet Haematol. 2019;6:e276–e84. https://doi.org/10.1016/S2352-3026(19)30027-4

    Article  PubMed  Google Scholar 

  12. Soverini S, Bavaro L, De Benedittis C, Martelli M, Iurlo A, Orofino N, et al. Prospective assessment of NGS-detectable mutations in CML patients with nonoptimal response: the NEXT-in-CML study. Blood 2020;135:534–41. https://doi.org/10.1182/blood.2019002969

    Article  PubMed  Google Scholar 

  13. Zabriskie MS, Eide CA, Tantravahi SK, Vellore NA, Estrada J, Nicolini FE, et al. BCR-ABL1 compound mutations combining key kinase domain positions confer clinical resistance to ponatinib in Ph chromosome-positive leukemia. Cancer Cell. 2014;26:428–42. https://doi.org/10.1016/j.ccr.2014.07.006

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Byrgazov K, Lucini CB, Valent P, Hantschel O, Lion T. BCR-ABL1 compound mutants display differential and dose-dependent responses to ponatinib. Haematologica 2018;103:e10–e2. https://doi.org/10.3324/haematol.2017.176347

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Soverini S, Martelli M, Bavaro L, De Benedittis C, Sica S, Sora F, et al. BCR-ABL1 compound mutants: prevalence, spectrum and correlation with tyrosine kinase inhibitor resistance in a consecutive series of Philadelphia chromosome-positive leukemia patients analyzed by NGS. Leukemia 2021;35:2102–7. https://doi.org/10.1038/s41375-020-01098-w

    Article  CAS  PubMed  Google Scholar 

  16. Flach J, Shumilov E, Joncourt R, Porret N, Novak U, Pabst T, et al. Current concepts and future directions for hemato-oncologic diagnostics. Crit Rev Oncol Hematol. 2020;151:102977 https://doi.org/10.1016/j.critrevonc.2020.102977

    Article  PubMed  Google Scholar 

  17. Olmedillas-Lopez S, Olivera-Salazar R, Garcia-Arranz M, Garcia-Olmo D. Current and Emerging Applications of Droplet Digital PCR in Oncology: An Updated Review. Mol Diagn Ther. 2022;26:61–87. https://doi.org/10.1007/s40291-021-00562-2

    Article  CAS  PubMed  Google Scholar 

  18. Huggett JF. The Digital MIQE Guidelines Update: Minimum Information for Publication of Quantitative Digital PCR Experiments for 2020. Clin Chem. 2020;66:1012–29. https://doi.org/10.1093/clinchem/hvaa125

    Article  PubMed  Google Scholar 

  19. Baccarani M, Deininger MW, Rosti G, Hochhaus A, Soverini S, Apperley JF, et al. European LeukemiaNet recommendations for the management of chronic myeloid leukemia: 2013. Blood 2013;122:872–84. https://doi.org/10.1182/blood-2013-05-501569

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Soverini S, Abruzzese E, Bocchia M, Bonifacio M, Galimberti S, Gozzini A, et al. Next-generation sequencing for BCR-ABL1 kinase domain mutation testing in patients with chronic myeloid leukemia: a position paper. J Hematol Oncol. 2019;12:131 https://doi.org/10.1186/s13045-019-0815-5

    Article  PubMed  PubMed Central  Google Scholar 

  21. Regan JF, Kamitaki N, Legler T, Cooper S, Klitgord N, Karlin-Neumann G, et al. A rapid molecular approach for chromosomal phasing. PLoS One. 2015;10:e0118270 https://doi.org/10.1371/journal.pone.0118270

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Vannuffel P, Bavaro L, Nollet F, Aynaci A, Martelli M, Devos H, et al. Droplet Digital PCR Phasing (DROP-PHASE): A Novel Method for Straightforward Detection of BCR-ABL1 Compound Mutations in Tyrosine Kinase Inhibitors Resistant Chronic Myeloid Leukemia (CML) and Acute Lymphoblastic Leukemia (ALL). Blood 2019;134:4660.

    Article  Google Scholar 

  23. Soverini S, De Benedittis C, Papayannidis C, Polakova KM, Venturi C, Russo D, et al. Clinical impact of low-burden BCR-ABL1 mutations detectable by amplicon deep sequencing in Philadelphia-positive acute lymphoblastic leukemia patients. Leukemia 2016;30:1615–9. https://doi.org/10.1038/leu.2016.17

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The study was supported by Novartis through the European Treatment and Outcome Study (EUTOS) for CML. ddPCR assays were provided by Bio-Rad Laboratories.

Author information

Author notes

  1. These authors contributed equally: Sara De Santis, Margherita Martelli, Cecilia Monaldi.

Authors and Affiliations

  1. Dipartimento di Medicina Specialistica, Diagnostica e Sperimentale, Istituto di Ematologia “Seràgnoli”, Università di Bologna, Bologna, Italy

    Simona Soverini, Sara De Santis, Margherita Martelli, Cecilia Monaldi & Samantha Bruno

  2. IRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, Dipartimento di Medicina Specialistica, Diagnostica e Sperimentale, Università di Bologna, Bologna, Italy

    Fausto Castagnetti & Michele Cavo

  3. IRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, Bologna, Italy

    Gabriele Gugliotta, Cristina Papayannidis, Manuela Mancini & Claudia Venturi

  4. Institute of Hematology and Blood Transfusion, Prague, Czechia

    Katerina Machova Polakova

  5. Abteilung Hämatologie/Onkologie, Klinik für Innere Medizin II, Universitätsklinikum Jena, Jena, Germany

    Thomas Ernst

  6. Bio-Rad Laboratories, Digital Biology Group, Pleasanton, CA, USA

    Dianna Maar

  7. Bio-Rad Laboratories, Digital Biology Group, Peterborough, UK

    Adam Corner

Authors
  1. Simona Soverini
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sara De Santis
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Margherita Martelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Cecilia Monaldi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Fausto Castagnetti
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Gabriele Gugliotta
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Cristina Papayannidis
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Manuela Mancini
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Samantha Bruno
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Claudia Venturi
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Katerina Machova Polakova
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Thomas Ernst
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Dianna Maar
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Adam Corner
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Michele Cavo
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

SS: designed the study, analyzed and interpreted results, contributed to writing the report; SDS, MMartelli, CM, SB, MMancini, CV: performed the study, contributed to data analysis and interpretation, prepared the figures and tables; FC, GG, CP: performed patient and sample selection, contributed to data analysis and interpretation; KMP, TE: provided important study materials, contributed to data analysis and interpretation, contributed to writing the report; DM, AC: provided reagents, contributed to experimental protocol set up and optimization; MC, designed the study, coordinated the clinical and research groups, contributed to writing the report. All authors read and approved the manuscript for submission.

Corresponding author

Correspondence to Simona Soverini.

Ethics declarations

Competing interests

ddPCR assays for this study were provided by Bio-Rad Laboratories. Bio-Rad Laboratories had no role in the design of the study, collection and analysis of data and decision to publish. DM and AC are Bio-Rad’s employees. The remaining authors declare no conflicts of interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Soverini, S., De Santis, S., Martelli, M. et al. Droplet digital PCR for the detection of second-generation tyrosine kinase inhibitor-resistant BCR::ABL1 kinase domain mutations in chronic myeloid leukemia. Leukemia 36, 2250–2260 (2022). https://doi.org/10.1038/s41375-022-01660-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41375-022-01660-8

This article is cited by

Search

Advanced search

Quick links