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:

Multiple myeloma, gammopathies

Multiple myeloma clonal evolution in homogeneously treated patients

Leukemia volume 32, pages 2636–2647 (2018)Cite this article

Subjects

Abstract

Clonal evolution drives tumor progression, chemoresistance and relapse in cancer. Little is known about clonal selection induced by therapeutic pressure in multiple myeloma. To address this issue, we performed large targeted sequencing of bone marrow plasma cells in 43 multiple myeloma patients at diagnosis and at relapse from exactly the same intensive treatment. The most frequently mutated genes at diagnosis were KRAS (35%), NRAS (28%), DIS3 (16%), BRAF, and LRP1B (12% each). At relapse, the mutational burden was unchanged. Many of the mutations were present at the subclonal level at both time points, including driver ones. According to patients and mutations, we observed different scenarios: selection of a very rare subclone present at diagnosis, appearance, or disappearance of mutations, but also stability. Our data highlight that chemoresistance and relapse could be induced by newly acquired mutations in myeloma drivers but also by (sub)clonal mutations preexisting to the treatment. Importantly, no specific mutation or rearrangement was observed at relapse, demonstrating that intensive treatment has a nonspecific effect on clonal selection in multiple myeloma. Finally, we identified 22 cases of biallelic event, including a double event deletion 17p/TP53mut.

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
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Palumbo A, Anderson K. Multiple myeloma. N Engl J Med. 2011;364:1046–60.

    Article  CAS  Google Scholar 

  2. Bolli N, Avet-Loiseau H, Wedge DC, Van Loo P, Alexandrov LB, Martincorena I, et al. Heterogeneity of genomic evolution and mutational profiles in multiple myeloma. Nat Commun. 2014;5:2997.

    Article  Google Scholar 

  3. Lohr JG, Stojanov P, Carter SL, Cruz-Gordillo P, Lawrence MS, Auclair D, et al. Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy. Cancer Cell. 2014;25:91–101.

    Article  CAS  Google Scholar 

  4. Walker BA, Boyle EM, Wardell CP, Murison A, Begum DB, Dahir NM, et al. Mutational spectrum, copy number changes, and outcome: results of a sequencing study of patients with newly diagnosed myeloma. J Clin Oncol. 2015;33:3911–20.

    Article  CAS  Google Scholar 

  5. Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S, Biankin AV, et al. Signatures of mutational processes in human cancer. Nature. 2013;500:415–21.

    Article  CAS  Google Scholar 

  6. Egan JB, Shi C-X, Tembe W, Christoforides A, Kurdoglu A, Sinari S, et al. Whole-genome sequencing of multiple myeloma from diagnosis to plasma cell leukemia reveals genomic initiating events, evolution, and clonal tides. Blood 2012. 2012;120:1060–6.

    CAS  Google Scholar 

  7. Walker BA, Wardell CP, Melchor L, Hulkki S, Potter NE, Johnson DC, et al. Intraclonal heterogeneity and distinct molecular mechanisms characterize the development of t(4;14) and t(11;14) myeloma. Blood. 2012;120:1077–86.

    Article  CAS  Google Scholar 

  8. Keats JJ, Chesi M, Egan JB, Garbitt VM, Palmer SE, Braggio E, et al. Clonal competition with alternating dominance in multiple myeloma. Blood 2012. 2012;120:1067–76.

    CAS  Google Scholar 

  9. Magrangeas F, Avet-Loiseau H, Gouraud W, Lode L, Decaux O, Godmer P, et al. Minor clone provides a reservoir for relapse in multiple myeloma. Leukemia. 2013;27:473–81.

    Article  CAS  Google Scholar 

  10. Walker BA, Wardell CP, Melchor L, Brioli A, Johnson DC, Kaiser MF, et al. Intraclonal heterogeneity is a critical early event in the development of myeloma and precedes the development of clinical symptoms. Leukemia. 2014;28:384–90.

    Article  Google Scholar 

  11. Morgan GJ, Walker BA, Davies FE. The genetic architecture of multiple myeloma. Nat Rev Cancer. 2012;12:335–48.

    Article  CAS  Google Scholar 

  12. Nowell PC. The clonal evolution of tumor cell populations. Science. 1976;194:23–8.

    Article  CAS  Google Scholar 

  13. Burrell RA, McGranahan N, Bartek J, Swanton C. The causes and consequences of genetic heterogeneity in cancer evolution. Nature. 2013;501:338–45.

    Article  CAS  Google Scholar 

  14. Greaves M, Maley CC. Clonal evolution in cancer. Nature. 2012;481:306–13.

    Article  CAS  Google Scholar 

  15. Corre J, Munshi N, Avet-Loiseau H. Genetics of multiple myeloma: another heterogeneity level? Blood. 2015;125:1870–6.

    Article  CAS  Google Scholar 

  16. Robiou du Pont S, Cleynen A, Fontan C, Attal M, Munshi N, Corre J, et al. Genomics of multiple myeloma. J Clin Oncol. 2017;35:963–7.

    Article  Google Scholar 

  17. Bolli N, Li Y, Sathiaseelan V, Raine K, Jones D, Ganly P, et al. A DNA target-enrichment approach to detect mutations, copy number changes and immunoglobulin translocations in multiple myeloma. Blood Cancer J. 2016;6:e467.

    Article  CAS  Google Scholar 

  18. Li H, Durbin R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics. 2010;26:589–95.

    Article  Google Scholar 

  19. Cibulskis K, Lawrence MS, Carter SL, Sivachenko A, Jaffe D, Sougnez C, et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat Biotechnol. 2013;31:213–9.

    Article  CAS  Google Scholar 

  20. Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucl Acids Res. 2010;38:e164.

    Article  Google Scholar 

  21. Chen K, Wallis JW, McLellan MD, Larson DE, Kalicki JM, Pohl CS, et al. BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat Methods. 2009;6:677–81.

    Article  CAS  Google Scholar 

  22. Ding L, Ley TJ, Larson DE, Miller CA, Koboldt DC, Welch JS, et al. Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing. Nature. 2012;481:506–10.

    Article  CAS  Google Scholar 

  23. Johnson BE, Mazor T, Hong C, Barnes M, Aihara K, McLean CY, et al. Mutational analysis reveals the origin and therapy-driven evolution of recurrent glioma. Science. 2014;343:189–93.

    Article  CAS  Google Scholar 

  24. Devarakonda S, Govindan R. Clonal evolution: multiregion sequencing of esophageal adenocarcinoma before and after chemotherapy. Cancer Discov. 2015;5:796–8.

    Article  CAS  Google Scholar 

  25. Weinhold N, Ashby C, Rasche L, Chavan SS, Stein C, Stephens OW, et al. Clonal selection and double-hit events involving tumor suppressor genes underlie relapse in myeloma. Blood. 2016;128:1735–44.

    Article  CAS  Google Scholar 

  26. McGranahan N, Swanton C. Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. Cancer Cell. 2015;27:15–26.

    Article  CAS  Google Scholar 

  27. O’Hare T, Eide CA, Deininger MW. Bcr-Abl kinase domain mutations, drug resistance, and the road to a cure for chronic myeloid leukemia. Blood. 2007;110:2242–9.

    Article  Google Scholar 

  28. Woyach JA, Furman RR, Liu TM, Ozer HG, Zapatka M, Ruppert AS, et al. Resistance mechanisms for the Bruton’s tyrosine kinase inhibitor ibrutinib. N Engl J Med. 2014;370:2286–94.

    Article  Google Scholar 

  29. Amirouchene-Angelozzi N, Swanton C, Bardelli A. Tumor evolution as a therapeutic target. Cancer Discover. 2017. Cancer Discovery 2017;7:805-17.

    Article  Google Scholar 

  30. Carter SL, Cibulskis K, Helman E, McKenna A, Shen H, Zack T, et al. Absolute quantification of somatic DNA alterations in human cancer. Nat Biotechnol. 2012;30:413–21.

    Article  CAS  Google Scholar 

  31. Kortum KM, Langer C, Monge J, Bruins L, Egan JB, Zhu YX, et al. Targeted sequencing using a 47 gene multiple myeloma mutation panel (M(3) P) in -17p high risk disease. Br J Haematol. 2015;168:507–10.

    Article  Google Scholar 

  32. Kortum KM, Mai EK, Hanafiah NH, Shi CX, Zhu YX, Bruins L, et al. Targeted sequencing of refractory myeloma reveals a high incidence of mutations in CRBN and Ras pathway genes. Blood. 2016;128:1226–33.

    Article  CAS  Google Scholar 

  33. Surget S, Lemieux-Blanchard E, Maiga S, Descamps G, Le Gouill S, Moreau P, et al. Bendamustine and melphalan kill myeloma cells similarly through reactive oxygen species production and activation of the p53 pathway and do not overcome resistance to each other. Leuk Lymphoma. 2014;55:2165–73.

    Article  CAS  Google Scholar 

  34. Lu S, Wang J. The resistance mechanisms of proteasome inhibitor bortezomib. Biomark Res. 2013;1:13.

    Article  Google Scholar 

  35. Keats J, Fonseca R, Chesi M, Schop R, Baker A, Chng W, et al. Promiscuous mutations activate the noncanonical NF-kappaB pathway in multiple myeloma. Cancer Cell. 2007;12:131–44.

    Article  CAS  Google Scholar 

  36. Gundem G, Van Loo P, Kremeyer B, Alexandrov LB, Tubio JM, Papaemmanuil E, et al. The evolutionary history of lethal metastatic prostate cancer. Nature. 2015;520:353–7.

    Article  CAS  Google Scholar 

  37. de Haart SJ, Willems SM, Mutis T, Koudijs MJ, van Blokland MT, Lokhorst HM, et al. Comparison of intramedullary myeloma and corresponding extramedullary soft tissue plasmacytomas using genetic mutational panel analyses. Blood Cancer J. 2016;6:e426.

    Article  Google Scholar 

  38. Rasche L, Chavan SS, Stephens OW, Patel PH, Tytarenko R, Ashby C, et al. Spatial genomic heterogeneity in multiple myeloma revealed by multi-region sequencing. Nat Commun. 2017;8:268.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by NIH grants PO1-155258 and P50-100707 (NM, HAL); Department of Veterans Affairs Merit Review Award 1 I01BX001584-01 (NM) and the CAPTOR program. The CRCT Team 13 is labeled by ARC. We thank the Intergroupe Francophone du Myelome for providing patient samples and clinical data.

Author contributions

JC, AC, NM, and HAL conceived the project, JC, AC, SR, and HAL analyzed the data, AC performed bioinformatics analysis, LB performed experiments, NB conceived the sequencing targeted panel, MA provided samples and clinical data, AC, JC, NM, and HAL wrote the manuscript which was reviewed and edited by the other co-authors.

Author information

Authors and Affiliations

  1. IUC-Oncopole, and CRCT INSERM U1037, 31100, Toulouse, France

    Jill Corre, Sébastien Robiou du Pont, Laure Buisson, Michel Attal & Hervé Avet-Loiseau

  2. Institut Montpellierain Alexander Grothendieck, CNRS, Univ. Montpellier, 34090, Montpellier, France

    Alice Cleynen

  3. Department of Oncology and Onco-Hematology, University of Milan, 20122, Milan, Italy

    Niccolo Bolli

  4. Department of medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

    Niccolo Bolli

  5. Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02115, USA

    Nikhil Munshi

  6. VA Boston Healthcare System, West Roxbury, MA, 02215, USA

    Nikhil Munshi

Authors
  1. Jill Corre
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alice Cleynen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sébastien Robiou du Pont
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Laure Buisson
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Niccolo Bolli
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Michel Attal
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Nikhil Munshi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Hervé Avet-Loiseau
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hervé Avet-Loiseau.

Ethics declarations

Conflict of interest

NB received honoraria and personal fees from Celgene Corporation. The remaining authors declare that they have no conflict of interest.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Corre, J., Cleynen, A., Robiou du Pont, S. et al. Multiple myeloma clonal evolution in homogeneously treated patients. Leukemia 32, 2636–2647 (2018). https://doi.org/10.1038/s41375-018-0153-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41375-018-0153-6

This article is cited by

Search

Advanced search

Quick links