Skip to main content

Advertisement

SpringerLink
Log in

Controversies in the Assessment of Minimal Residual Disease in Multiple Myeloma: Clinical Significance of Minimal Residual Disease Negativity Using Highly Sensitive Techniques

  • Multiple Myeloma (R Niesvizky, Section Editor)
  • Published:
Current Hematologic Malignancy Reports Aims and scope Submit manuscript

Abstract

Minimal residual disease (MRD) assessment has gained importance in the response evaluation of multiple myeloma. As discussed in part 1 of this two-part series, techniques such as multiparameter flow cytometry, polymerase chain reaction, and next-generation sequencing, of both bone marrow and peripheral blood, have the potential to achieve a high level of sensitivity, up to 1 in 10−6 cells, enabling analysis of genetically diverse subclones. Here, we review the clinical utility of MRD assessment using these techniques. Specifically, we review the association between MRD-negativity and progression-free or overall survival in various clinical settings (post-induction, post-auto or allo-stem cell transplant, transplant ineligible, maintenance, and relapsed/refractory). Currently, the goal of assessing MRD in multiple myeloma (MM) is to allow for a risk-stratified approach to therapy and for earlier identification of response to novel agents, particularly in the setting of clinical trials.

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

Fig. 1

Similar content being viewed by others

References

  1. Cavo M et al. Prospective, randomized study of single compared with double autologous stem-cell transplantation for multiple myeloma: Bologna 96 clinical study. J Clin Oncol : Off J Am Soc Clin Oncol. 2007;25(17):2434–41.

    Article  Google Scholar 

  2. Alvares CL et al. Long-term outcomes of previously untreated myeloma patients: responses to induction chemotherapy and high-dose melphalan incorporated within a risk stratification model can help to direct the use of novel treatments. Br J Haematol. 2005;129(5):607–14.

    Article  CAS  PubMed  Google Scholar 

  3. Barlogie B et al. Total therapy with tandem transplants for newly diagnosed multiple myeloma. Blood. 1999;93(1):55–65.

    CAS  PubMed  Google Scholar 

  4. Child JA et al. High-dose chemotherapy with hematopoietic stem-cell rescue for multiple myeloma. N Engl J Med. 2003;348(19):1875–83.

    Article  CAS  PubMed  Google Scholar 

  5. Richardson PG et al. Lenalidomide, bortezomib, and dexamethasone combination therapy in patients with newly diagnosed multiple myeloma. Blood. 2010;116(5):679–86.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  6. Attal M et al. Lenalidomide maintenance after stem-cell transplantation for multiple myeloma. N Engl J Med. 2012;366(19):1782–91.

    Article  CAS  PubMed  Google Scholar 

  7. McCarthy PL et al. Lenalidomide after stem-cell transplantation for multiple myeloma. N Engl J Med. 2012;366(19):1770–81.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  8. Mateos MV et al. Bortezomib, melphalan, and prednisone versus bortezomib, thalidomide, and prednisone as induction therapy followed by maintenance treatment with bortezomib and thalidomide versus bortezomib and prednisone in elderly patients with untreated multiple myeloma: a randomised trial. Lancet Oncol. 2010;11(10):934–41.

    Article  CAS  PubMed  Google Scholar 

  9. Kumar S et al. Randomized, multicenter, phase 2 study (EVOLUTION) of combinations of bortezomib, dexamethasone, cyclophosphamide, and lenalidomide in previously untreated multiple myeloma. Blood. 2012;119(19):4375–82.

    Article  CAS  PubMed  Google Scholar 

  10. Ladetto, M., et al., Next-generation sequencing and real-time quantitative PCR for minimal residual disease detection in B-cell disorders. Leukemia, 2013

  11. Cavo M et al. Molecular monitoring of minimal residual disease in patients in long-term complete remission after allogeneic stem cell transplantation for multiple myeloma. Blood. 2000;96(1):355–7.

    CAS  PubMed  Google Scholar 

  12. Corradini P et al. Molecular remission after myeloablative allogeneic stem cell transplantation predicts a better relapse-free survival in patients with multiple myeloma. Blood. 2003;102(5):1927–9.

    Article  CAS  PubMed  Google Scholar 

  13. Fenk R et al. Levels of minimal residual disease detected by quantitative molecular monitoring herald relapse in patients with multiple myeloma. Haematologica. 2004;89(5):557–66.

    CAS  PubMed  Google Scholar 

  14. Durie BG, Salmon SE. A clinical staging system for multiple myeloma. Correlation of measured myeloma cell mass with presenting clinical features, response to treatment, and survival. Cancer. 1975;36(3):842–54.

    Article  CAS  PubMed  Google Scholar 

  15. Klein B et al. Interleukin-6 in human multiple myeloma. Blood. 1995;85:863–72.

    CAS  PubMed  Google Scholar 

  16. Chanan-Khan AA, Giralt S. Importance of achieving a complete response in multiple myeloma, and the impact of novel agents. J Clin Oncol : Off J Am Soc Clin Oncol. 2010;28(15):2612–24.

    Article  CAS  Google Scholar 

  17. Hoering A et al. Complete remission in multiple myeloma examined as time-dependent variable in terms of both onset and duration in Total Therapy protocols. Blood. 2009;114(7):1299–305.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  18. Kim JS et al. Complete remission status before autologous stem cell transplantation is an important prognostic factor in patients with multiple myeloma undergoing upfront single autologous transplantation. Biol Blood Marrow Transplant : J Am Soc Blood Marrow Transplant. 2009;15(4):463–70.

    Article  CAS  Google Scholar 

  19. Desikan R et al. Results of high-dose therapy for 1000 patients with multiple myeloma: durable complete remissions and superior survival in the absence of chromosome 13 abnormalities. Blood. 2000;95(12):4008–10.

    CAS  PubMed  Google Scholar 

  20. Attal M et al. A prospective, randomized trial of autologous bone marrow transplantation and chemotherapy in multiple myeloma. Intergroupe Francais du Myelome New England J Med. 1996;335(2):91–7.

    Article  CAS  Google Scholar 

  21. Niesvizky R et al. The relationship between quality of response and clinical benefit for patients treated on the bortezomib arm of the international, randomized, phase 3 APEX trial in relapsed multiple myeloma. Br J Haematol. 2008;143(1):46–53.

    Article  CAS  PubMed  Google Scholar 

  22. Attal M et al. Single versus double autologous stem-cell transplantation for multiple myeloma. N Engl J Med. 2003;349(26):2495–502.

    Article  CAS  PubMed  Google Scholar 

  23. van de Velde HJ et al. Complete response correlates with long-term survival and progression-free survival in high-dose therapy in multiple myeloma. Haematologica. 2007;92(10):1399–406.

    Article  PubMed  Google Scholar 

  24. Gay F et al. Complete response correlates with long-term progression-free and overall survival in elderly myeloma treated with novel agents: analysis of 1175 patients. Blood. 2011;117(11):3025–31.

    Article  CAS  PubMed  Google Scholar 

  25. Haessler J et al. Benefit of complete response in multiple myeloma limited to high-risk subgroup identified by gene expression profiling. Clin Cancer Res : Off J Am Assoc Cancer Res. 2007;13(23):7073–9.

    Article  CAS  Google Scholar 

  26. Lachin JM. Statistical considerations in the intent-to-treat principle. Control Clin Trials. 2000;21(3):167–89.

    Article  CAS  PubMed  Google Scholar 

  27. Durie BG et al. Magnitude of response with myeloma frontline therapy does not predict outcome: importance of time to progression in southwest oncology group chemotherapy trials. J Clin Oncol : Off J Am Soc Clin Oncol. 2004;22(10):1857–63.

    Article  Google Scholar 

  28. Kapoor P et al. Importance of achieving stringent complete response after autologous stem-cell transplantation in multiple myeloma. J Clin Oncol : Off J Am Soc Clin Oncol. 2013;31(36):4529–35.

    Article  Google Scholar 

  29. Singhal S et al. The relationship between the serum free light chain assay and serum immunofixation electrophoresis, and the definition of concordant and discordant free light chain ratios. Blood. 2009;114(1):38–9.

    Article  CAS  PubMed  Google Scholar 

  30. Ludwig H et al. Immunoglobulin heavy/light chain ratios improve paraprotein detection and monitoring, identify residual disease and correlate with survival in multiple myeloma patients. Leukemia. 2013;27(1):213–9.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  31. Tovar N et al. Prognostic impact of serum immunoglobulin heavy/light chain ratio in patients with multiple myeloma in complete remission after autologous stem cell transplantation. Biol Blood Marrow Transplant : J Am Soc Blood Marrow Transplant. 2012;18(7):1076–9.

    Article  CAS  Google Scholar 

  32. Rawstron AC et al. Minimal residual disease assessed by multiparameter flow cytometry in multiple myeloma: impact on outcome in the Medical Research Council Myeloma IX Study. J Clin Oncol : Off J Am Soc Clin Oncol. 2013;31(20):2540–7.

    Article  Google Scholar 

  33. Paiva B et al. High-risk cytogenetics and persistent minimal residual disease by multiparameter flow cytometry predict unsustained complete response after autologous stem cell transplantation in multiple myeloma. Blood. 2012;119(3):687–91.

    Article  CAS  PubMed  Google Scholar 

  34. Morgan GJ et al. The role of maintenance thalidomide therapy in multiple myeloma: MRC Myeloma IX results and meta-analysis. Blood. 2012;119(1):7–15.

    Article  CAS  PubMed  Google Scholar 

  35. Paiva B et al. Comparison of immunofixation, serum free light chain, and immunophenotyping for response evaluation and prognostication in multiple myeloma. J Clin Oncol : Off J Am Soc Clin Oncol. 2011;29(12):1627–33.

    Article  CAS  Google Scholar 

  36. Leung-Hagesteijn C et al. Xbp1s-negative tumor B cells and pre-plasmablasts mediate therapeutic proteasome inhibitor resistance in multiple myeloma. Cancer Cell. 2013;24(3):289–304.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  37. Martinez-Lopez J et al. Clinical applicability and prognostic significance of molecular response assessed by fluorescent-PCR of immunoglobulin genes in multiple myeloma. Results GEM/PETHEMA Stud British J Haematol. 2013;163(5):581–9.

    Article  CAS  Google Scholar 

  38. Galimberti S et al. Prognostic role of minimal residual disease in multiple myeloma patients after non-myeloablative allogeneic transplantation. Leuk Res. 2005;29(8):961–6.

    Article  CAS  PubMed  Google Scholar 

  39. Davies FE et al. The impact of attaining a minimal disease state after high-dose melphalan and autologous transplantation for multiple myeloma. Br J Haematol. 2001;112(3):814–9.

    Article  CAS  PubMed  Google Scholar 

  40. Sarasquete ME et al. Minimal residual disease monitoring in multiple myeloma: a comparison between allelic-specific oligonucleotide real-time quantitative polymerase chain reaction and flow cytometry. Haematologica. 2005;90(10):1365–72.

    CAS  PubMed  Google Scholar 

  41. Davies FE et al. Minimal residual disease monitoring in multiple myeloma. Best Pract Res Clin Haematol. 2002;15(1):197–222.

    Article  CAS  PubMed  Google Scholar 

  42. Lioznov M et al. Monitoring of minimal residual disease in multiple myeloma after allo-SCT: flow cytometry vs PCR-based techniques. Bone Marrow Transplant. 2008;41(10):913–6.

    Article  CAS  PubMed  Google Scholar 

  43. Mason KD, Juneja S. Go with the flow for monitoring response in myeloma with minimal residual disease. Leuk Lymphoma. 2008;49(2):177–8.

    Article  PubMed  Google Scholar 

  44. Bakkus MH et al. Post-transplantation tumour load in bone marrow, as assessed by quantitative ASO-PCR, is a prognostic parameter in multiple myeloma. Br J Haematol. 2004;126(5):665–74.

    Article  PubMed  Google Scholar 

  45. Putkonen M et al. Depth of response assessed by quantitative ASO-PCR predicts the outcome after stem cell transplantation in multiple myeloma. Eur J Haematol. 2010;85(5):416–23.

    Article  PubMed  Google Scholar 

  46. Martinelli G et al. Molecular remission after allogeneic or autologous transplantation of hematopoietic stem cells for multiple myeloma. J Clin Oncol : Off J Am Soc Clin Oncol. 2000;18(11):2273–81.

    CAS  Google Scholar 

  47. Corradini P et al. Molecular and clinical remissions in multiple myeloma: role of autologous and allogeneic transplantation of hematopoietic cells. J Clin Oncol : Off J Am Soc Clin Oncol. 1999;17(1):208–15.

    CAS  Google Scholar 

  48. Martinelli G et al. Polymerase chain reaction-based detection of minimal residual disease in multiple myeloma patients receiving allogeneic stem cell transplantation. Haematologica. 2000;85(9):930–4.

    CAS  PubMed  Google Scholar 

  49. Cremer FW et al. Evaluation of the kinetics of the bone marrow tumor load in the course of sequential high-dose therapy assessed by quantitative PCR as a predictive parameter in patients with multiple myeloma. Bone Marrow Transplant. 2000;26(8):851–8.

    Article  CAS  PubMed  Google Scholar 

  50. Lemoli RM et al. Engraftment, clinical, and molecular follow-up of patients with multiple myeloma who were reinfused with highly purified CD34+ cells to support single or tandem high-dose chemotherapy. Blood. 2000;95(7):2234–9.

    CAS  PubMed  Google Scholar 

  51. Martinez-Lopez J et al. Prognostic value of deep sequencing method for minimal residual disease detection in multiple myeloma. Blood. 2014;123(20):3073–9.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  52. Polzer B, Klein CA. Metastasis awakening: the challenges of targeting minimal residual cancer. Nat Med. 2013;19(3):274–5.

    Article  CAS  PubMed  Google Scholar 

  53. Yu M et al. RNA sequencing of pancreatic circulating tumour cells implicates WNT signalling in metastasis. Nature. 2012;487(7408):510–3.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  54. Bianchi G et al. High levels of peripheral blood circulating plasma cells as a specific risk factor for progression of smoldering multiple myeloma. Leukemia. 2013;27(3):680–5.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  55. Kumar S et al. Prognostic value of circulating plasma cells in monoclonal gammopathy of undetermined significance. J Clin Oncol. 2005;23(24):5668–74.

    Article  PubMed  Google Scholar 

  56. Nowakowski GS et al. Circulating plasma cells detected by flow cytometry as a predictor of survival in 302 patients with newly diagnosed multiple myeloma. Blood. 2005;106(7):2276–9.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  57. Peceliunas V et al. Circulating plasma cells predict the outcome of relapsed or refractory multiple myeloma. Leuk Lymphoma. 2012;53(4):641–7.

    Article  CAS  PubMed  Google Scholar 

  58. Paiva B et al. Detailed characterization of multiple myeloma circulating tumor cells shows unique phenotypic, cytogenetic, functional, and circadian distribution profile. Blood. 2013;122(22):3591–8.

    Article  CAS  PubMed  Google Scholar 

  59. Vij R et al. Deep sequencing reveals myeloma cells in peripheral blood in majority of multiple myeloma patients. Clin Lymphoma Myeloma Leuk. 2014;14(2):131–139 e1.

    Article  PubMed  Google Scholar 

  60. Bartel TB et al. F18-fluorodeoxyglucose positron emission tomography in the context of other imaging techniques and prognostic factors in multiple myeloma. Blood. 2009;114(10):2068–76.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  61. Zamagni E et al. Prognostic relevance of 18-F FDG PET/CT in newly diagnosed multiple myeloma patients treated with up-front autologous transplantation. Blood. 2011;118(23):5989–95.

    Article  CAS  PubMed  Google Scholar 

  62. Walker R et al. Magnetic resonance imaging in multiple myeloma: diagnostic and clinical implications. J Clin Oncol : Off J Am Soc Clin Oncol. 2007;25(9):1121–8.

    Article  Google Scholar 

  63. Waheed S et al. Standard and novel imaging methods for multiple myeloma: correlates with prognostic laboratory variables including gene expression profiling data. Haematologica. 2013;98(1):71–8.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  64. Cooke F et al. Use of quantitative ASO-PCR to predict relapse in multiple myeloma. Br J Haematol. 1999;105(1):317–9.

    Article  CAS  PubMed  Google Scholar 

  65. Ding C, Cantor CR. A high-throughput gene expression analysis technique using competitive PCR and matrix-assisted laser desorption ionization time-of-flight MS. Proc Natl Acad Sci U S A. 2003;100(6):3059–64.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  66. Radich JP. How I monitor residual disease in chronic myeloid leukemia. Blood. 2009;114(16):3376–81.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  67. Blade J, Kyle RA. Nonsecretory myeloma, immunoglobulin D myeloma, and plasma cell leukemia. Hematol/Oncol Clin North Am. 1999;13(6):1259–72.

    Article  CAS  Google Scholar 

  68. Snozek CL et al. Prognostic value of the serum free light chain ratio in newly diagnosed myeloma: proposed incorporation into the international staging system. Leukemia. 2008;22(10):1933–7.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  69. Dispenzieri A et al. Appraisal of immunoglobulin free light chain as a marker of response. Blood. 2008;111(10):4908–15.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  70. Novella E et al. Fluorescent polymerase chain reaction and capillary electrophoresis for IgH rearrangement and minimal residual disease evaluation in multiple myeloma. Haematologica. 2002;87(11):1157–64.

    CAS  PubMed  Google Scholar 

  71. Puig N et al. Critical evaluation of ASO RQ-PCR for minimal residual disease evaluation in multiple myeloma. Comp Anal Flow Cytometry Leuk. 2014;28(2):391–7.

    CAS  Google Scholar 

  72. Walker RC et al. Imaging of multiple myeloma and related plasma cell dyscrasias. J Nucl Med. 2012;53(7):1091–101.

    Article  PubMed  Google Scholar 

Download references

Compliance with Ethics Guidelines

Conflict of Interest

Dr. Noa Biran and Dr. Ajai Chari each declare no potential conflicts of interest.

Dr. Scott Ely reports U.S. Patent No. 8,603,763 issued and a patent pending (Docket No. 19,603/6040). He has received US$0 for these inventions.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Author information

Authors and Affiliations

  1. John Theurer Cancer Center, Hackensack University Medical Center, 92 Second Street, Suite 340, Hackensack, NJ, 07601, USA

    Noa Biran

  2. Division of Hematopathology, Department of Pathology and Laboratory Medicine, Weill Medical College of Cornell University, 525 East 68th Street, Starr Pavilion, 715, New York, NY, 10065, USA

    Scott Ely

  3. Division of Hematology and Medical Oncology, Department of Medicine and The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1185, New York, NY, 10029, USA

    Ajai Chari

Authors
  1. Noa Biran
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Scott Ely
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ajai Chari
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ajai Chari.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Biran, N., Ely, S. & Chari, A. Controversies in the Assessment of Minimal Residual Disease in Multiple Myeloma: Clinical Significance of Minimal Residual Disease Negativity Using Highly Sensitive Techniques. Curr Hematol Malig Rep 9, 368–378 (2014). https://doi.org/10.1007/s11899-014-0237-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11899-014-0237-y

Keywords

Search

Navigation