Assessment of minimal residual disease in myeloma and the need for a consensus approach

Cytometry Part B - Clinical Cytometry

Volumn 90, Issue 1, 2016, Pages 21-25

  Rawstron, Andy C ^a   Paiva, Bruno ^b,c,d   Stetler Stevenson, Maryalice ^e  

^a LEEDS TEACHING HOSPITALS NHS TRUST   (United Kingdom)

^b UNIVERSITY CLINIC OF NAVARRA   (Spain)

^c UNIVERSITY OF NAVARRA   (Spain)

^d IdiSNA Navarra Institute for Health Research   (Spain)

^e NATIONAL CANCER INSTITUTE   (United States)

Author keywords

flow cytometry; high throughput sequencing; minimal residual disease; PCR; plasma cell myeloma; quantification; rare event detection

Indexed keywords

ARTICLE; COMPARATIVE STUDY; CONSENSUS DEVELOPMENT; FLOW CYTOMETRY; HIGH THROUGHPUT SEQUENCING; HUMAN; LIMIT OF DETECTION; LIMIT OF QUANTITATION; MINIMAL RESIDUAL DISEASE; MULTIPARAMETER FLOW CYTOMETRY; MYELOMA; OVERALL SURVIVAL; POLYMERASE CHAIN REACTION; PROGRESSION FREE SURVIVAL; QUANTITATIVE ANALYSIS; REPRODUCIBILITY; SENSITIVITY ANALYSIS; THERAPY EFFECT; AUTOTRANSPLANTATION; CONSENSUS; DRUG EFFECTS; GENE EXPRESSION; GENETIC POLYMORPHISM; GENETICS; HEMATOPOIETIC STEM CELL TRANSPLANTATION; IMMUNOLOGY; MORTALITY; MULTIPLE MYELOMA; NEOPLASM, RESIDUAL; PATHOLOGY; PLASMA CELL; PROGNOSIS; REAL TIME POLYMERASE CHAIN REACTION; REMISSION; SURVIVAL ANALYSIS; TREATMENT OUTCOME;

ANTINEOPLASTIC AGENT; IMMUNOGLOBULIN HEAVY CHAIN; LEUKOCYTE ANTIGEN;

ANTIGENS, CD; ANTINEOPLASTIC AGENTS; ANTINEOPLASTIC COMBINED CHEMOTHERAPY PROTOCOLS; CONSENSUS; FLOW CYTOMETRY; GENE EXPRESSION; HEMATOPOIETIC STEM CELL TRANSPLANTATION; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; IMMUNOGLOBULIN HEAVY CHAINS; MULTIPLE MYELOMA; NEOPLASM, RESIDUAL; PLASMA CELLS; POLYMORPHISM, GENETIC; PROGNOSIS; REAL-TIME POLYMERASE CHAIN REACTION; REMISSION INDUCTION; SURVIVAL ANALYSIS; TRANSPLANTATION, AUTOLOGOUS; TREATMENT OUTCOME;

EID: 84945318582     PISSN: 15524949     EISSN: 15524957     Source Type: Journal    
DOI: 10.1002/cyto.b.21272     Document Type: Article

References (31)

1. Mateos M-V, San Miguel JF. How should we treat newly diagnosed multiple myeloma patients? Hematology Am Soc Hematol Educ Program 2013;2013:488–495.
2. Landgren O, Gormley N, Turley D, Owen RG, Rawstron AC, Paiva B, Barnett D, Arroz M, Wallace P, Durie BGM, et al. Flow cytometry detection of minimal residual disease in multiple myeloma: Lessons learned at FDA-NCI roundtable symposium. Am J Hematol 2014;89:1159–1160.
3. Durie BGM, Harousseau J-L, Miguel JS, Bladé J, Barlogie B, Anderson K, Gertz M, Dimopoulos M, Westin J, Sonneveld P, et al. International uniform response criteria for multiple myeloma. Leukemia 2006;20:1467–1473.
4. San Miguel JF, Almeida J, Mateo G, Bladé J, López-Berges C, Caballero D, Hernández J, Moro MJ, Fernández-Calvo J, Díaz-Mediavilla J, et al. Immunophenotypic evaluation of the plasma cell compartment in multiple myeloma: A tool for comparing the efficacy of different treatment strategies and predicting outcome. Blood 2002;99:1853–1856.
5. Rawstron AC, Davies FE, DasGupta R, Ashcroft AJ, Patmore R, Drayson MT, Owen RG, Jack AS, Child JA, Morgan GJ. Flow cytometric disease monitoring in multiple myeloma: The relationship between normal and neoplastic plasma cells predicts outcome after transplantation. Blood 2002;100:3095–3100.
6. Rawstron AC, Child JA, de Tute RM, Davies FE, Gregory WM, Bell SE, Szubert AJ, Navarro-Coy N, Drayson MT, Feyler S, 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 2013;31:2540–2547.
7. Paiva B, Vidriales M-B, Cerveró J, Mateo G, Pérez JJ, Montalbán MA, Sureda A, Montejano L, Gutiérrez NC, García de Coca A, et al.; GEM (Grupo Español De MM)/PETHEMA (Programa Para El Estudio De La Terapéutica En Hemopatías Malignas) Cooperative Study Groups. Multiparameter flow cytometric remission is the most relevant prognostic factor for multiple myeloma patients who undergo autologous stem cell transplantation. Blood 2008;112:4017–4023.
8. Paiva B, Martinez-Lopez J, Vidriales M-B, Mateos M-V, Montalban M-A, Fernandez-Redondo E, Alonso L, Oriol A, Teruel A-I, de Paz R, et al. Comparison of immunofixation, serum free light chain, and immunophenotyping for response evaluation and prognostication in multiple myeloma. J Clin Oncol 2011;29:1627–1633.
9. Paiva B, Gutiérrez NC, Rosiñol L, Vídriales M-B, Montalbán M-Á, Martínez-López J, Mateos M-V, Cibeira M-T, Cordón L, Oriol A, et al.; PETHEMA/GEM (Programa Para El Estudio De La Terapéutica En Hemopatías Malignas/Grupo Español De Mieloma) Cooperative Study Groups. 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;119:687–691.
10. Martinez-Lopez J, Lahuerta JJ, Pepin F, González M, Barrio S, Ayala R, Puig N, Montalban MA, Paiva B, Weng L, et al. Prognostic value of deep sequencing method for minimal residual disease detection in multiple myeloma. Blood 2014;123:3073–3079.
11. Martinez-Lopez J, Fernández-Redondo E, García-Sánz R, Montalbán MA, Martínez-Sánchez P, Pavia B, Mateos MV, Rosiñol L, Martín M, Ayala R, et al.; The GEM (Grupo Español Multidisciplinar De Melanoma)/PETHEMA (Programa Para El Estudio De La Terapéutica En Hemopatías Malignas) Cooperative Study Group. Clinical applicability and prognostic significance of molecular response assessed by fluorescent-PCR of immunoglobulin genes in multiple myeloma. Results from a GEM/PETHEMA study. Br J Haematol 2013;163:581–589.
12. Rawstron AC, Gregory WM, de Tute RM, Davies FE, Bell SE, Drayson MT, Cook G, Jackson GH, Morgan GJ, Child JA, et al. Minimal residual disease in myeloma by flow cytometry: Independent prediction of survival benefit per log reduction. Blood 2015;125:1932–1935.
13. Puig N, Sarasquete ME, Alcoceba M, Balanzategui A, Chillón MC, Sebastián E, Díaz MG, San Miguel JF, García-Sanz R. Kappa deleting element as an alternative molecular target for minimal residual disease assessment by real-time quantitative PCR in patients with multiple myeloma. Eur J Haematol 2012;89:328–335.
14. Van der Velden VHJ, Hochhaus A, Cazzaniga G, Szczepanski T, Gabert J, van Dongen JJM. Detection of minimal residual disease in hematologic malignancies by real-time quantitative PCR: Principles, approaches, and laboratory aspects. Leukemia 2003;17:1013–1034.
15. Rawstron AC, Orfao A, Beksac M, Bezdickova L, Brooimans RA, Bumbea H, Dalva K, Fuhler G, Gratama J, Hose D, et al. Report of the European Myeloma Network on multiparametric flow cytometry in multiple myeloma and related disorders. Haematologica 2008;93:431–438.
16. Puig N, Sarasquete ME, Balanzategui A, Martínez J, Paiva B, García H, Fumero S, Jiménez C, Alcoceba M, Chillón MC, et al. Critical evaluation of ASO RQ-PCR for minimal residual disease evaluation in multiple myeloma. A comparative analysis with flow cytometry. Leukemia 2014;28:391–397.
17. Ladetto M, Brüggemann M, Monitillo L, Ferrero S, Pepin F, Drandi D, Barbero D, Palumbo A, Passera R, Boccadoro M, et al. Next-generation sequencing and real-time quantitative PCR for minimal residual disease detection in B-cell disorders. Leukemia 2014;28:1299–1307.
18. Wu D, Sherwood A, Fromm JR, Winter SS, Dunsmore KP, Loh ML, Greisman HA, Sabath DE, Wood BL, Robins H. High-throughput sequencing detects minimal residual disease in acute T lymphoblastic leukemia. Sci Transl Med 2012;4:134ra63.
19. Logan AC, Zhang B, Narasimhan B, Carlton V, Zheng J, Moorhead M, Krampf MR, Jones CD, Waqar AN, Faham M, et al. Minimal residual disease quantification using consensus primers and high-throughput IGH sequencing predicts post-transplant relapse in chronic lymphocytic leukemia. Leukemia 2013;27:1659–1665.
20. Paiva B, Vidriales M-B, Mateo G, Pérez JJ, Montalbán MA, Sureda A, Montejano L, Gutiérrez NC, García de Coca A, de las Heras N, et al.; GEM (Grupo Español De MM)/PETHEMA (Programa Para El Estudio De La Terapéutica En Hemopatías Malignas) Cooperative Study Groups. The persistence of immunophenotypically normal residual bone marrow plasma cells at diagnosis identifies a good prognostic subgroup of symptomatic multiple myeloma patients. Blood 2009;114:4369–4372.
21. Paiva B, Gutiérrez N-C, Chen X, Vídriales M-B, Montalbán M-Á, Rosiñol L, Oriol A, Martínez-López J, Mateos M-V, López-Corral L, et al.; GEM (Grupo Español De Mieloma)/PETHEMA (Programa Para El Estudio De La Terapéutica En Hemopatías Malignas) Cooperative. Clinical significance of CD81 expression by clonal plasma cells in high-risk smoldering and symptomatic multiple myeloma patients. Leukemia 2012;26:1862–1869.
22. Paiva B, Vídriales M-B, Montalbán M-Á, Pérez JJ, Gutiérrez NC, Rosiñol L, Martínez-López J, Mateos M-V, Cordón L, Oriol A, et al. Multiparameter flow cytometry evaluation of plasma cell DNA content and proliferation in 595 transplant-eligible patients with myeloma included in the Spanish GEM2000 and GEM2005 < 65y trials. Am J Pathol 2012;181:1870–1878.
23. Paiva B, Vídriales M-B, Rosiñol L, Martínez-López J, Mateos M-V, Ocio EM, Montalbán M-Á, Cordón L, Gutiérrez NC, Corchete L, et al.; Grupo Español De MM/Programa Para El Estudio De La Terapéutica En Hemopatías Malignas Cooperative Study Group. A multiparameter flow cytometry immunophenotypic algorithm for the identification of newly diagnosed symptomatic myeloma with an MGUS-like signature and long-term disease control. Leukemia 2013;27:2056–2061.
24. Paiva B, Pérez-Andrés M, Vídriales M-B, Almeida J, de las Heras N, Mateos M-V, López-Corral L, Gutiérrez NC, Blanco J, Oriol A, et al.; GEM (Grupo Español De MM)/PETHEMA (Programa Para El Estudio De La Terapéutica En Hemopatías Malignas), Myeloma Stem Cell Network (MSCNET). Competition between clonal plasma cells and normal cells for potentially overlapping bone marrow niches is associated with a progressively altered cellular distribution in MGUS vs. myeloma. Leukemia 2011;25:697–706.
25. Nowakowski GS, Witzig TE, Dingli D, Tracz MJ, Gertz MA, Lacy MQ, Lust JA, Dispenzieri A, Greipp PR, Kyle RA, et al. Circulating plasma cells detected by flow cytometry as a predictor of survival in 302 patients with newly diagnosed multiple myeloma. Blood 2005;106:2276–2279.
26. Chaidos A, Barnes CP, Cowan G, May PC, Melo V, Hatjiharissi E, Papaioannou M, Harrington H, Doolittle H, Terpos E, et al. Clinical drug resistance linked to interconvertible phenotypic and functional states of tumor-propagating cells in multiple myeloma. Blood 2013;121:318–328.
27. Paiva B, Paino T, Sayagues J-M, Garayoa M, San-Segundo L, Martín M, Mota I, Sanchez M-L, Bárcena P, Aires-Mejia I, et al. Detailed characterization of multiple myeloma circulating tumor cells shows unique phenotypic, cytogenetic, functional, and circadian distribution profile. Blood 2013;122:3591–3598.
28. Kumar S, Rajkumar SV, Kyle RA, Lacy MQ, Dispenzieri A, Fonseca R, Lust JA, Gertz MA, Greipp PR, Witzig TE. Prognostic value of circulating plasma cells in monoclonal gammopathy of undetermined significance. J Clin Oncol 2005;23:5668–5674.
29. Bianchi G, Kyle RA, Larson DR, Witzig TE, Kumar S, Dispenzieri A, Morice WG, Rajkumar SV. High levels of peripheral blood circulating plasma cells as a specific risk factor for progression of smoldering multiple myeloma. Leukemia 2013;27:680–685.
30. Kopp HG, Yildirim S, Weisel KC, Kanz L, Vogel W. Contamination of autologous peripheral blood progenitor cell grafts predicts overall survival after high-dose chemotherapy in multiple myeloma. J Cancer Res Clin Oncol 2009;135:637–642.
31. Dingli D, Nowakowski GS, Dispenzieri A, Lacy MQ, Hayman SR, Rajkumar SV, Greipp PR, Litzow MR, Gastineau DA, Witzig TE, et al. Flow cytometric detection of circulating myeloma cells before transplantation in patients with multiple myeloma: A simple risk stratification system. Blood 2006;107:3384–3388.