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.