Consensus guidelines on plasma cell myeloma minimal residual disease analysis and reporting

Cytometry Part B - Clinical Cytometry

Volumn 90, Issue 1, 2016, Pages 31-39

  Arroz, Maria ^a   Came, Neil ^b   Lin, Pei ^c   Chen, Weina ^d   Yuan, Constance ^e   Lagoo, Anand ^f   Monreal, Mariela ^g   de Tute, Ruth ^h   Vergilio, Jo Anne ⁱ   Rawstron, Andy C ^h   Paiva, Bruno ^j  

^a HOSPITAL DE SÃO FRANCISCO XAVIER   (Portugal)

^b PETER MACCALLUM CANCER CENTRE   (Australia)

^c UNIVERSITY OF TEXAS MD ANDERSON CANCER CENTER   (United States)

^d UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER   (United States)

^e NATIONAL CANCER INSTITUTE   (United States)

^f DUKE UNIVERSITY MEDICAL CENTER   (United States)

^g Interpflow Corporation   (United States)

^h St James's Institute of Oncology   (United Kingdom)

ⁱ UNIVERSITY OF MICHIGAN HEALTH SYSTEM   (United States)

^j UNIVERSITY OF NAVARRA   (Spain)

more..

Author keywords

flow cytometry; minimal residual disease; plasma cell myeloma

Indexed keywords

CD19 ANTIGEN; CD27 ANTIGEN; CD28 ANTIGEN; CD38 ANTIGEN; CD45 ANTIGEN; CD56 ANTIGEN; CD81 ANTIGEN; STEM CELL FACTOR RECEPTOR; SYNDECAN 1; ANTINEOPLASTIC AGENT; LEUKOCYTE ANTIGEN;

ANTIGEN EXPRESSION; ARTICLE; BONE MARROW CELL; CANCER CELL; CELL COMPARTMENTALIZATION; CELLULAR PARAMETERS; COMPARATIVE STUDY; CONSENSUS DEVELOPMENT; CONTROLLED STUDY; FLOW CYTOMETRY; HUMAN; HUMAN CELL; IMMUNOPHENOTYPING; LIMIT OF DETECTION; LIMIT OF QUANTITATION; MINIMAL RESIDUAL DISEASE; MULTIPLE MYELOMA; PRACTICE GUIDELINE; REPRODUCIBILITY; DRUG EFFECTS; GENETICS; IMMUNOLOGY; METHODOLOGY; NEOPLASM, RESIDUAL; PATHOLOGY; PLASMA CELL; PROGNOSIS; REMISSION; SOFTWARE; STANDARDS;

ANTIGENS, CD; ANTINEOPLASTIC AGENTS; BONE MARROW CELLS; FLOW CYTOMETRY; HUMANS; IMMUNOPHENOTYPING; LIMIT OF DETECTION; MULTIPLE MYELOMA; NEOPLASM, RESIDUAL; PLASMA CELLS; PROGNOSIS; REMISSION INDUCTION; RESEARCH DESIGN; SOFTWARE;

EID: 84930408858     PISSN: 15524949     EISSN: 15524957     Source Type: Journal    
DOI: 10.1002/cyto.b.21228     Document Type: Article

References (30)

1. Tanqri S, Vall H, Kaplan D, Hoffman B, Purvis N, Porwit A, Hunsberger B, Shankey T. Validation of cell-based fluorescence assays: Practice guidelines from the ICSH and ICCS – Part III – analytical issues. Cytometry B Clin Cytom 2013;84:291–308.
2. Rawstron AC, Orfao A, Beksac M, Berdickova L, Brooimans R, 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.
3. van Dongen JJM, Lhermitte L, Böttcher S, Almeida J, van der Velden V, Flores-Montero J, Rawstron A, Asnafi V, Lécrevisse Q, Lucio P, et al. EuroFlow antibody panels for standardized n-dimensional flow cytometric immunophenotyping of normal, reactive and malignant leukocytes. Leukemia 2012;26:1908–1975
4. Cannizzo E, Bellio E, Sohani AR, Hasserjian RP, Ferry JA, Dorn ME, Sadowski C, Bucci JJ, Carulli G, Preffer F. Multiparameter immunophenotyping by flow cytometry in multiple myeloma; the diagnostic utility of defining ranges of normal antigenic expression in comparison to histology. Cytometry B Clin Cytom 2010;78:231–238.
5. Liu D, Lin P, Hu Y, Zhou Y, Tang G, Powers L, Medeiros LJ, Jorgensen JL, Wang SA. Immunophenotypic heterogeneity of normal plasma cells: Comparison with minimal residual plasma cell myeloma. J Clin Pathol 2012;65:823–829
6. Tembhare PR, Yuan CM, Venzon D, Braylan R, Korde N, Manasanch E, Zuchlinsky D, Calvo K, Kurlander R, Bhutani M, et al. Flow cytometric differentiation of abnormal and normal plasma cells in the bone marrow in patients with multiple myeloma and its precursor diseases. Leuk Res 2014;38:371–376
7. Cao W, Goolsby CL, Nelson BP, Singhal S, Mehta J, Peterson LC. Instability of immunophenotype in plasma cell myeloma. Am J Clin Pathol 2008;129: 926–933
8. 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.
9. Paíno T, Paiva B, Sayagués J, Mota I, Carvalheiro T, Corchete L, Aires-Mejia I, Peréz JJ, Sanchez ML, Barcena P, et al. Phenotypic identification of subclones in multiple myeloma with different chemoresistant, cytogenetic and clonogenic potential. Leukemia (in press). doi:10.1038/leu.2014.321
10. Wood BL, Arroz M, Barnett D, DiGiuseppe J, Greig B, Kussick SJ, Oldaker T, Shenkin M, Stone E, Wallace P. 2006 Bethesda International Consensus Recommendations on the Immunophenotypic Analysis of Hematolymphoid Neoplasia by Flow Cytometry: Optimal Reagents and Reporting for the Flow Cytometric Diagnosis of Hematopoietic Neoplasia. Cytometry B Clin Cytom 2007;72B:S14–S22
11. Wood B. 9-Color and 10-Color Flow Cytometry in the Clinical Laboratory. Arch Pathol Lab Med 2006;130:680–686
12. Costa ES, Pedreira CE, Barrena S, Lecrevisse Q, Flores J, Quijano S, Almeida J, del Carmen García-Macias M, Bottcher S, Van Dongen JJ, et al. Automated pattern-guided principal component analysis VS expert-based immunophenotypic classification of B-cell chronic lymphoproliferative disorders: A step forward in the stardardization of Immunophenotyping. Leukemia 2010;24:1927–1933
13. Liu D, Lin P,HuY, Zhou Y, Tang G, Powers L, Medeiros J, Jorgensen J, Wang S. Immunophenotypic heterogeneity of normal plasma cells: Comparison with minimal residual plasma cell myeloma. J Clin Pathol 2012;65:823–829.
14. Kozbor D, Moretta A, Messner H, Moretta L, Croce C. Tp44 molecules involved in antigen-independent T cell activation are expressed on human plasma cells. J Immunol 1987;138:4128–4132.
15. Aghaeepour N, Finak G, FlowCAP Consortium; DREAM Consortium, Hoos H, Mosmann TR, Brinkman R, Gottardo R, Scheuermann RH. Critical assessment of automated flow Cytometry data techniques. Nat Methods 2013;10:228–238
16. Pedreira CE, Costa ES, Lecrevisse Q, van Dongen JJM, Orfao A. Overview of clinical flow cytometry data analysis: Recente advances and future challenges. Trends Biotechnol 2013;31:415–425
17. Pedreira CE, Costa ES, Barrena S, Lecrevisse Q, Almeida J, van Dongen JJ, Orfao A. Generation of flow cytometry data files with a potentially infinite number of dimensions. Cytometry A 2008;73:834–846
18. Paiva B, Martinez-Lopez J, Vidriales MB, Mateos MV, Montalban MA, Fernandez-Redondo E, Alonso L, Oriol A, Teruel AI, 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
19. Paiva B, Gutierrez NC, Rosinol L, Vídriales MB, Montalbán MÁ, Martínez-López J, Mateos MV, Cibeira MT, Cordón L, Oriol A, 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;119:687–691
20. 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.
21. Paiva B, Vidriales MB, Cervero J, Mateo G, Pérez JJ, Montalbán MA, Sureda A, Montejano L, Gutiérrez NC, García de Coca A, et al. 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
22. Domingo E, Moreno C, Sánchez-Ibarrola A, Panizo E, Páramo JA, Merino J. Enhanced sensitivity of flow cytometry for routine assessment of minimal residual disease. Haematologica 2010;95:691–692
23. College of American Pathologists (CAP). Laboratory Accreditation Manual 2012 Edition. Illinois: College of American Pathologists; 2012.
24. Clinical and Laboratory Standards Institute (CLSI). Evaluation of Detection Capability for Clinical Laboratory Measurement Procedures; Approved Guideline, 2nd ed. CLSI document EP17-A2 (ISBN 1-56238-795-2). Pennsylvania: Clinical and Laboratory Standards Institute; 2012.
25. Jennings L, Van Deerlin VM, Gulley ML. Recommended practices and principles for validating clinical molecular pathology tests. Arch Pathol Lab Med 2009;133:743–755
26. Hedley BD, Keeney M. Technical issues: Flow cytometry and rare event analysis. Int J Lab Hematol 2013;35:344–350.
27. Subirá D, Castañón S, Aceituno E, Hernández J, Jiménez-Garófan C, Jiménez A, Jiménez AM, Romá A, Orfao A. Flow cytometric analysis of cerebrospinal fluid samples and its usefulness in routine clinical practice. Am J Clin Pathol 2002;117:952–958.
28. Rawstron A, Böttcher S, Letestu R, Villamor N, Fazi C, Kartsios H, de Tute RM, Shingles J, Ritgen M, Moreno C, et al. Improving efficiency and sensitivity: European Research Initiative in CLL (ERIC) update on the international harmonised approach for flow cytometric residual disease monitoring in CLL. Leukemia 2013;27:142–149.
29. Nieto WG, Almeida J, Romero A, Teodósio C, López A, Henriques AF, Sánchez ML, Jara-Acevedo M, Basilio A, González M, et al. Increased frequency (12%) of circulating chronic lymphocitic Leukemia-like B-cell clones in healthy subjects using a highly sensitive multicolor flow cytometry approach. Blood 2009;114:33–37
30. Paiva B, Vidriales MB, Mateo G, Pérez JJ, Montalbán MA, Sureda A, Montejano L, Gutiérrez NC, García de Coca A, de las Heras N, et al. 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