Plasma Cell Separation Algorithm from Bone Marrow Samples
Authors:
I. Burešová 1; D. Kyjovská 1,2; L. Kovářová 2; J. Moravcová 1; R. Suská 2; T. Perutka 1; J. Čumová 1; R. Hájek 1,2,3
Authors place of work:
Babákův výzkumný institut, LF MU Brno
1; Oddělení klinické hematologie, Laboratoř experimentální hematologie a buněčné imunoterapie, FN Brno
2; Interní hematoonkologická klinika FN Brno
3
Published in the journal:
Klin Onkol 2011; 24(1): 35-40
Category:
Original Articles
Summary
Backgrounds:
The aim of this paper is to present an algorithm for plasma cell separation from bone marrow samples of multiple myeloma patients. The main prerequisite for applying modern research methods in this disease is gaining pure cell populations.
Material and Methods:
Bone marrow samples were collected from outpatients or inpatients of the Internal Haematology and Oncology Clinic of the Faculty Hospital Brno, after they had signed an Informed Consent Form. The bone marrow was first depleted of red cells (by density gradient centrifugation or erythrolysis), plasma cells were labelled by monoclonal antibody against syndecan-1 (CD138) and separated either magnetically or by cell sorter. The purity of separated population was evaluated by flow cytometry or, alternatively, morfologically.
Results:
We processed 28 bone marrow samples, in parallel, by magnetic or fluorescence-based separation, and we evaluated the purity of the separated fractions. Based on a statistical evaluation of resulting purities in the entire sample set as well as the individual groups divided according to the initial plasma cell content, a separation algorithm was proposed with a cut-off value of 5% of plasma cells in mononuclear fraction of bone marrow: samples with less than 5% of plasma cells are henceforth separated on cell sorter, samples with more than 5% are separated magnetically. The effectiveness of this algorithm was evaluated after the first year of its application on a dataset of 210 bone marrow samples: median purity of the separated plasma cells increased from 62.4% (0.4–99.6%) to 94.0% (23.9–100%).
Conclusion:
The introduction of a fluorescence-based separation markedly increased the effectiveness of plasma cell separation from bone marrow samples, mainly in samples with low plasma cell content where magnetic separation used thus far is not sufficient. This finding also opened a door for plasma cell separation of bone marrow samples from patients with monoclonal gammopathy of undetermined significance, where plasma cell count is typically below or just over one percent.
Key words:
multiple myeloma – plasma cell separation – monoclonal gammopathy of undetermined significance – magnetic separation – cell sorter
Zdroje
1. Fillola G, Müller C, Bousquet R et al. Isolation of bone marrow plasma cells by negative selection with immunomagnetic beads. J Immunol Methods 1996; 190(1): 127–131.
2. Tai YT, Teoh G, Shima Y et al. Isolation and characterization of human multiple myeloma cell enriched populations. J Immunol Methods 2000; 235(1–2): 11–19.
3. Avet-Loiseau H, Facon T, Daviet A et al. 14q32 translocations and monosomy 13 observed in monoclonal gammopathy of undetermined significance delineate a multistep process for the oncogenesis of multiple myeloma. Intergroupe Francophone du Myélome. Cancer Res 1999; 59(18): 4546–4550.
4. Draube A, Pfister R, Vockerodt M et al. Immunomagnetic enrichment of CD138 positive cells from weakly infiltrated myeloma patients samples enables the determination of the tumor clone specific IgH rearrangement. Ann Hematol 2001; 80(2): 83–89.
5. Davies FE, Dring AM, Li C et al. Insights into the multistep transformation of MGUS to myeloma using microarray expression analysis. Blood 2003; 102(13): 4504–4511.
6. Rasillo A, Tabernero MD, Sánchez ML et al. Fluorescence in situ hybridization analysis of aneuploidization patterns in monoclonal gammopathy of undetermined dignificance versus multiple myeloma and plasma cell leukemia. Cancer 2003; 97(3): 601–609.
7. Fišerová S, Hájek R, Doubek M et al. Imunomagnetická separace myelomových buněk. Klin Onkol 2001; 14(2): 46–50.
8. Cumova J, Kovarova L, Potacova A et al. Optimalization of myeloma cell selection from bone marrow purified by magnetic-activated cell sorting. V přípravě.
9. Wijdenes J, Vooijs WC, Clément C et al. A plasmocyte selective monoclonal antibody (B-B4) recognizes syndecan-1. Br J Haematol 1996; 94(2): 318–323.
10. Fonseca R, Barlogie B, Bataille R et al. Genetics and cytogenetics of multiple myeloma: A workshop report. Cancer Res 2004; 64(4): 1546–1558.
11. Witzig T, Kimlinger T, Stenson M et al. Syndecan-1 expression on malignant cells from the blood and marrow of patients with plasma cell proliferative disorders and B-cell chronic lymphocytic leukemia. Leuk Lymphoma 1998; 31(1–2): 167–175.
12. Jourdan M, Ferlin M, Legouffe E et al. The myeloma cell antigen syndecan-1 is lost by apoptotic myeloma cells. Br J Haematol 1998; 100(4): 637–646.
13. Paulus U, Dreger P, Viehmann K et al. Purging Peripheral Blood Progenitor Cell Grafts from lymphoma cells: quantitative comparison of immunomagnetic CD34+ selection systems. Stem Cells 1997; 15(4): 297–304.
14. Kuglík P, Filková H, Vranová V et al. Detection of chromosome 13 abnormalities and 14q32 translocations in multiple myeloma using simultaneous immunofluorescent labelling of malignant plasma cells and FISH. Europ J Hum Genet 2004; 12 (Suppl): 170.
15. Ross FM, Avet-Loiseau H, Drach J et al. European myeloma network recommendations for FISH in myeloma (Abstract). Haematologica 2007; 92 (Suppl 2): 100-101.
16. Zhan F, Huang Y, Colla S et al. The molecular classification of multiple myeloma. Blood 2006; 108(6): 2020–2028.
17. Shaughnessy JD Jr, Zhan F, Burington BE et al. A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1. Blood 2007; 109(6): 2276–2284.
18. Decaux O, Lodé L, Magrangeas F et al. Intergroupe Francophone du Myélome. Prediction of survival in multiple myeloma based on gene expression profiles reveals cell cycle and chromosomal instability signatures in high-risk patients and hyperdiploid signatures in low-risk patients: a study of the Intergroupe Francophone du Myélome. J Clin Oncol 2008; 26(29): 4798–4805.
19. Ansorgová V, Mačingová Z, Priester P et al. Nádorové kmenové buňky a „niche“ – jako limitující faktor karcinogeneze. Klin Onkol 2009; 22(1): 11–16.
20. Huff CA, Matsui W. Multiple myeloma cancer stem cells. J Clin Oncol 2008; 26(17): 2895–2900.
Štítky
Paediatric clinical oncology Surgery Clinical oncologyČlánok vyšiel v časopise
Clinical Oncology
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