A comparison between protein profiles of B cell subpopulations and mantle cell lymphoma cells
© Stranneheim et al; licensee BioMed Central Ltd. 2009
Received: 15 June 2009
Accepted: 23 November 2009
Published: 23 November 2009
B-cell lymphomas are thought to reflect different stages of B-cell maturation. Based on cytogenetics and molecular markers, mantle cell lymphoma (MCL) is presumed to derive predominantly from naïve, pre-germinal centre (pre-GC) B lymphocytes. The aim of this study was to develop a method to investigate the similarity between MCL cells and different B-cell compartments on a protein expression level.
Subpopulations of B cells representing the germinal centre (GC), the pre-GC mantle zone and the post-GC marginal zone were isolated from tonsils using automated magnetic cell sorting (AutoMACS) of cells based on their expression of CD27 and IgD. Protein profiling of the B cell subsets, of cell lines representing different lymphomas and of primary MCL samples was performed using top-down proteomics profiling by surface-enhanced laser detection/ionization time-of-flight mass spectrometry (SELDI-TOF-MS).
Quantitative MS data of significant protein peaks (p-value < 0.05) separating the three B-cell subpopulations were generated. Together, hierarchical clustering and principal component analysis (PCA) showed that the primary MCL samples clustered together with the pre- and post-GC subpopulations. Both primary MCL cells and MCL cell lines were clearly separated from the B cells representing the GC compartment.
AutoMACS sorting generates sufficient purity to enable a comparison between protein profiles of B cell subpopulations and malignant B lymphocytes applying SELDI-TOF-MS. Further validation with an increased number of patient samples and identification of differentially expressed proteins would enable a search for possible treatment targets that are expressed during the early development of MCL.
In the last decade, several studies of lymphomas have been performed using microarray analysis of global gene expression . Genomic profiling has proven to be of both diagnostic and prognostic value. However, the correlation between mRNA and protein expression is generally poor, and regulation of many physiological processes is post-transcriptional. Protein analysis is therefore essential for the elucidation of biological mechanisms behind e.g. lymphoma formation. Proteomic profiling using liquid chromatography-MS/MS has been applied to a limited number of lymphomas of different origin . The high throughput top-down method of SELDI-TOF-MS, which is based on chip-binding of intact proteins and endogenous peptides, has been used to differentiate follicular lymphoma from Burkitt's lymphoma  and to distinguish between diffuse large B-cell lymphoma, follicular lymphoma and mantle cell lymphoma (MCL) . This method is optimal for the detection of peptides or small proteins in the mass range of 1000-25000 Daltons . Many proteins and peptides that have regulatory roles in proliferation, differentiation, apoptosis and cell signaling are found within this range.
We have applied this approach in the comparison of MCL cells with subpopulations of normal B lymphocytes. MCL is a relatively rare malignancy that represents 5-10% of all non-Hodgkins lymphomas . Although several genetic and molecular mechanisms involved in the pathogenesis of MCL have been defined, there is currently no effective standard treatment for the disease, and the clinical outcome is poor [7, 8]. While most human B-cell lymphomas are derived from cells at the GC or post-GC stage of development , MCL has been thought to originate from naïve, pre-GC B cells . However, approximately 20% of the MCL cells, which are abundant in the mantle zone of lymphoid follicles , have undergone somatic hypermutations in the immunoglobulin variable heavy-chain genes, suggesting a heterogeneous origin .
In the present study, we used SELDI-TOF-MS to generate expression profiles of intact proteins and peptides. MCL cells and cell lines representing other B cell malignancies were compared with subpopulations of B-cells representing the three major compartments of peripheral lymphoid organs; the GC, the pre-GC mantle zone and the post-GC marginal zone.
Materials and methods
This study was approved by the Ethics committee at Karolinska Institutet, Etikkommitté syd, #689/03.
Cell lines and primary MCL
The MCL cell lines Jvm-2 [12, 13], Rec-1 [14, 15], Granta 519  and JeKo-1 , the precursor leukemia cell line Nalm-6  representing the pre-GC stage, the Burkitt's lymphoma cell lines Radji  and Namalwa  representing GC and the plasma cell line SKMM-2 [21, 22] representing post-GC were used in the study. All cell lines were tested for mycoplasma and were found to be free from infection. The tests were performed with MycoAlert Mycoplasma Detection Kit (LT07-218, Cambrex, USA) on a Thermo Luminoskan Ascent (Thermo Fischer Scientific, Inc, USA). The cell lines were cultured in RPMI 1640 GlutaMaxtm-1 (72400-021, Invitrogen, USA), supplemented with 10% FBS (16140-071, Invitrogen, USA) and 50 μg/mL gentamicin (15750-045, Invitrogen, USA) at 37°C using a 5% CO2 atmosphere, except JeKo-1, which was cultured using a 20% FBS supplement. The cells were harvested in the exponential phase, snap frozen in liquid nitrogen and stored as pellets at -70°C. In addition, two primary MCL tumors, with confirmed t(11;14)(q13;q32) cyclin D1 translocation and immunophenotype of CD5+/CD23-, indicative of MCL , were included in the study. The primary MCL tumours contained >80% tumor cells, as verified using the CD5 and CD23 markers in a FACScan (BD, USA) (not shown). Biological triplicates were used for the primary cells except MCL tumours, that were analyzed in duplicate due to lack of availability of samples.
Isolation of B cell populations from healthy individuals
The normal B cell populations were extracted from fresh tonsils obtained from patients undergoing tonsillectomies at the surgical department, Karolinska University Hospital, Huddinge. The tonsils were dissected and then homogenized using a Medimachine (Dako Denmark A/S, Glostrup, Denmark). The resulting cell suspension was purified from erythrocytes by treatment with a lysis buffer containing ammonium chloride for 8 minutes and subsequent filtration to remove cellular debris. The B cell population was separated from T cells by negative selection. The pan T cell CD3+ surface receptor was conjugated with magnetic anti-CD3+ microbeads (130-050-101, Miltenyi Biotec, Germany), which were sorted by an AutoMACS sorter (Miltenyi Biotec, Germany) using column 130-021-101 (Miltenyi Biotec, Germany). The purity of the T and B cell fractions was validated by using the pan B cell surface receptor CD19+  and the T cell CD3+ receptor. The B cell fractions were >90% CD19+ as determined by incubating with fluorescent CD3+/FITC + CD19+/RPE antibodies (FR866, DAKO, Denmark) and analyzing with a FACScan (BD, USA) (not shown). The total B cell extracts were snap frozen in liquid nitrogen and stored as pellets at -70°C.
Isolation of B cell subpopulations representing pre-GC, GC and post-GC
In order to separate pre-GC, GC and post-GC populations from the tonsils, the total B cell populations from the AutoMACS separation were incubated with magnetic CD27+ microbeads (130-051-601, Miltenyi Biotec, Germany), generating a post-GC CD27+ population and a CD27- population consisting of both pre-GC and GC B cells. The CD27- population was then further sorted using an anti-IgD+-FITC antibody and Anti-FITC microbeads (130-048-701, Miltenyi Biotec, Germany), to isolate the pre-GC and GC fractions.
Protein preparation and concentration determination
Cell pellets from cell lines and isolated primary B cell populations were subjected to a lysis buffer (150 mM NaCl, 50 mM Tris-HCL pH 7,5, 0,1% Triton X-100, 1% CHAPS) and repeatedly immersed in liquid nitrogen to lyse the cells and release the proteins. Protein concentrations were determined using a BCA protein assay kit (23225, PIERCE, USA) according to the manufacturer's instructions.
Analysis of proteins using SELDI-TOF
The samples were dissolved to a final concentration of 0.15 ug/ul in 50 mM ammonium acetate pH 4.5 and 0.1% Triton X-100. 100 μl of the prepared protein solutions were analyzed using a cation exchange (CM 10, pH 4,5) protein-chip (Biorad Inc., USA) . Standard protocols recommended by the manufacturer were used in the experiments. Mass spectra were collected using SELDI-TOF Protein Biology System IIC using three different laser intensity and time lag focusing settings creating three data sets; 3-6 kDa, 6-10 kDa and 10-40 kDa (optimization of M/Z regions and of time lag focusing). The design of the experimental protocol was based on pilot experiments, to optimize peak number and minimize detector saturation from intense peaks at 5 kDa and 9 kDa. The data analysis was performed using CE software package Ciphergen Biosystems, CA, USA. All spectra were baseline corrected and peak detection was performed using signal/noise value of 3 and a valley depth of value of 2 (first pass).
The significant differentially expressed protein peaks were identified using nonparametric t-test, using in pair-wise comparison Mann-Whitney and in group-wise comparison Kruskal Wallis test. The peaks with p-value < 0,05 were considered as significant differentially expressed proteins peaks.
Clustering of protein profiles
Unsupervised hierarchical clustering of the primary populations and cell lines was performed using all peaks detected within each mass range. To distinguish between pre-GC, GC and post-GC populations, all peaks detected within the three populations which had p-value < 0,05 were considered significant and were used to cluster these primary populations within each data set. The corresponding peaks in the primary MCL samples and MCL cell lines were then included to generate a hierarchical clustering of MCL samples within the pre-GC, GC and post-GC populations. The peaks were analyzed by heat map and principal component analysis (PCA). Ciphergen Express software, Ciphergen, CA, USA, was used for both hierarchical clustering and PCA.
Isolation of B cell subpopulations representing pre-GC, GC and post-GC
Hierarchical clustering and principal component analysis of primary cells and cell lines
In the present study, we used AutoMACS sorting in order to isolate subpopulations of B cells reflecting the pre-GC, GC and post-GC stage. In the subsequent analysis of protein expression, the cation exchange protein-chip array CM 10 was used at pH 4,5. A previous study including MCL samples has shown that the same chip surface resulted in detection of the highest number of peaks . In the initial analysis, the primary MCL samples A and B clustered together with the pre-GC subpopulations in the 3-10 kDa range. Two of the MCL cell lines, Rec-1 and Jvm-2, clustered together with the primary MCL, while Granta 519 and JeKo did not. Using global gene expression analysis, the MCL cell lines Granta 519, SP53 and NCEB1 have earlier been shown to cluster closely to primary MCL samples . Overall, the other cell lines did not cluster together with the B cell subpopulations they were supposed to represent, based on their origin. In the 6-15 kDa range, all of the cell lines clustered together, indicating the presence of proteins that show similar expression levels exclusively in the cell lines, despite their different origin. One factor influencing the expression pattern could be cell culture conditions. However, the NOEK population of primary MCL cells that had been cultured under identical conditions to the MCL cell lines for one week did not cluster together with them. Neither is EBV-transformation likely to account for the similarity of the cell lines in the 6-15 kDa range, as both the JeKo-1 and Rec-1 cell lines, which clustered together with the other cell lines, are EBV-negative. This observation indicates that studies based on cell lines must be interpreted with caution and emphasize the need to analyze patient samples in order to understand the biology behind diseases. In an extensive gene expression study using 60 cell lines of different origin, it has earlier been shown that the majority of the cell lines were poor representatives of their cellular origin .
The subpopulations of the biological triplicates from tonsil that were labeled with the same set of antibodies clustered together when peaks that significantly distinguished the subpopulations (p-value < 0,05) were analyzed following SELDI-TOF-MS. Thus, the purity of the subpopulations following AutoMACS sorting was sufficient to generate reproducible protein profiles from each stage. The GC-population clustered separately from the pre-GC and post-GC populations. This could reflect up-regulation of the expression of specific proteins required for GC maturation and down-regulating of others. When separating the post-GC CD27+ population using CD27+ microbeads, the post-GC fraction contained mostly CD27+/IgD-, but also 10-25% CD27+/IgD+ B cells representing early memory cells. IgD is a pre-GC marker, and the presence of IgD+ early memory cells might also influence the clustering together of the pre-GC and post-GC populations.
In the hierarchical clustering and PCA of peaks that significantly (p < 0.05) distinguished the B cell subsets, the primary MCL samples and the cultured primary MCL cells NOEK clustered together with the pre- and post-GC subpopulations. The similarity between MCL cells and pre-GC cells is in accordance with the prevailing assumptions about the pathology of MCL . However, the present study needs to be expanded in order to determine if proteome profiling using SELDI-TOF-MS supports a pre-GC or heterogeneous origin of MCL cells. Interestingly, the GC subpopulations were clearly separated from both the primary MCL samples and the MCL cell lines in PCA. Thus, it appears as if the biology of MCL cells differs from that of B cells residing in the GC compartment.
In conclusion, this pilot study has shown that purifying B lymphocytes using AutoMACS-sorting combined with profiling of intact proteins using SELDI-TOF-MS allows a comparison to be made between the protein expression of MCL cells and subpopulations of B-cells representing the three major compartments of peripheral lymphoid organs. Further studies based on a larger patient cohort and followed by MS-based identification of proteins may contribute to the understanding of the molecular pathogenesis of MCL and other B cell malignancies, and conceivably suggest new potential treatment targets.
This work was supported by grants from the Cancer Society in Stockholm, the European Commission (6th FP CHEMORES-project, 7th FP APOSYS-project), the Swedish Cancer Society and the Karolinska Institutet Funds. We are grateful to Åsa-Lena Dackland, CCA, for assistance with flow cytometric analysis and to Gareth Morgan for carefully reading the manuscript.
- Leich E, Hartmann EM, Burek C, Ott G, Rosenwald A: Diagnostic and prognostic significance of gene expression profiling in lymphomas. APMIS 2007,115(10):1135–1146. 10.1111/j.1600-0463.2007.apm_867.xml.xPubMedView ArticleGoogle Scholar
- Lim MS, Elenitoba-Johnson KS: Mass spectrometry-based proteomic studies of human anaplastic large cell lymphoma. Mol Cell Proteomics 2006,5(10):1787–1798. 10.1074/mcp.R600005-MCP200PubMedView ArticleGoogle Scholar
- Fan G, Molstad M, Braziel RM, Standley M, Huang J, Rodgers W, Nagalla S: Proteomic profiling of mature CD10+ B-cell lymphomas. Am J Clin Pathol 2005,124(6):920–929. 10.1309/UEDXPHAAP740B61DPubMedView ArticleGoogle Scholar
- Jansen C, Hebeda KM, Linkels M, Grefte JM, Raemaekers JM, van Krieken JH, Groenen PJ: Protein profiling of B-cell lymphomas using tissue biopsies: A potential tool for small samples in pathology. Cell Oncol 2008,30(1):27–38.PubMedGoogle Scholar
- Wright GL Jr: SELDI proteinchip MS: a platform for biomarker discovery and cancer diagnosis. Expert Rev Mol Diagn 2002,2(6):549–563. 10.1586/14737126.96.36.1999PubMedView ArticleGoogle Scholar
- Kuppers R: Mechanisms of B-cell lymphoma pathogenesis. Nat Rev Cancer 2005,5(4):251–262. 10.1038/nrc1589PubMedView ArticleGoogle Scholar
- Jares P, Colomer D, Campo E: Genetic and molecular pathogenesis of mantle cell lymphoma: perspectives for new targeted therapeutics. Nat Rev Cancer 2007,7(10):750–762. 10.1038/nrc2230PubMedView ArticleGoogle Scholar
- Bertoni F, Zucca E, Cotter FE: Molecular basis of mantle cell lymphoma. Br J Haematol 2004,124(2):130–140. 10.1046/j.1365-2141.2003.04761.xPubMedView ArticleGoogle Scholar
- Kuppers R, Klein U, Hansmann ML, Rajewsky K: Cellular origin of human B-cell lymphomas. N Engl J Med 1999,341(20):1520–1529. 10.1056/NEJM199911113412007PubMedView ArticleGoogle Scholar
- Thorselius M, Walsh S, Eriksson I, Thunberg U, Johnson A, Backlin C, Enblad G, Sundstrom C, Roos G, Rosenquist R: Somatic hypermutation and V(H) gene usage in mantle cell lymphoma. Eur J Haematol 2002,68(4):217–224. 10.1034/j.1600-0609.2002.01662.xPubMedView ArticleGoogle Scholar
- Bertoni F, Ponzoni M: The cellular origin of mantle cell lymphoma. Int J Biochem Cell Biol 2007,39(10):1747–1753. 10.1016/j.biocel.2007.04.026PubMedView ArticleGoogle Scholar
- Melo JV, Brito-Babapulle V, Foroni L, Robinson DS, Luzzatto L, Catovsky D: Two new cell lines from B-prolymphocytic leukaemia: characterization by morphology, immunological markers, karyotype and Ig gene rearrangement. Int J Cancer 1986,38(4):531–538. 10.1002/ijc.2910380413PubMedView ArticleGoogle Scholar
- Melo JV, Foroni L, Brito-Babapulle V, Luzzatto L, Catovsky D: The establishment of cell lines from chronic B cell leukaemias: evidence of leukaemic origin by karyotypic abnormalities and Ig gene rearrangement. Clin Exp Immunol 1988,73(1):23–28.PubMed CentralPubMedGoogle Scholar
- Raynaud SD, Bekri S, Leroux D, Grosgeorge J, Klein B, Bastard C, Gaudray P, Simon MP: Expanded range of 11q13 breakpoints with differing patterns of cyclin D1 expression in B-cell malignancies. Genes Chromosomes Cancer 1993,8(2):80–87. 10.1002/gcc.2870080204PubMedView ArticleGoogle Scholar
- Rimokh R, Berger F, Delsol G, Digonnet I, Rouault JP, Tigaud JD, Gadoux M, Coiffier B, Bryon PA, Magaud JP: Detection of the chromosomal translocation t(11;14) by polymerase chain reaction in mantle cell lymphomas. Blood 1994,83(7):1871–1875.PubMedGoogle Scholar
- Jadayel DM, Lukas J, Nacheva E, Bartkova J, Stranks G, De Schouwer PJ, Lens D, Bartek J, Dyer MJ, Kruger AR, et al.: Potential role for concurrent abnormalities of the cyclin D1, p16CDKN2 and p15CDKN2B genes in certain B cell non-Hodgkin's lymphomas. Functional studies in a cell line (Granta 519). Leukemia 1997,11(1):64–72. 10.1038/sj.leu.2400555PubMedView ArticleGoogle Scholar
- Drexler HG, MacLeod RA: Malignant hematopoietic cell lines: in vitro models for the study of mantle cell lymphoma. Leuk Res 2002,26(9):781–787. 10.1016/S0145-2126(02)00026-7PubMedView ArticleGoogle Scholar
- Hurwitz R, Hozier J, LeBien T, Minowada J, Gajl-Peczalska K, Kubonishi I, Kersey J: Characterization of a leukemic cell line of the pre-B phenotype. Int J C ancer 1979,23(2):174–180.View ArticleGoogle Scholar
- Pulvertaft JV: Cytology of Burkitt's Tumour (African Lymphoma). Lancet 1964,1(7327):238–240. 10.1016/S0140-6736(64)92345-1PubMedView ArticleGoogle Scholar
- Nadkarni JS, Nadkarni JJ, Clifford P, Manolov G, Fenyo EM, Klein E: Characteristics of new cell lines derived from Burkitt lymphomas. Cancer 1969,23(1):64–79. 10.1002/1097-0142(196901)23:1<64::AID-CNCR2820230107>3.0.CO;2-MPubMedView ArticleGoogle Scholar
- Eton O, Scheinberg DA, Houghton AN: Establishment and characterization of two human myeloma cell lines secreting kappa light chains. Leukemia 1989,3(10):729–735.PubMedGoogle Scholar
- Drexler HG, Matsuo Y: Malignant hematopoietic cell lines: in vitro models for the study of multiple myeloma and plasma cell leukemia. Leuk Res 2000,24(8):681–703. 10.1016/S0145-2126(99)00195-2PubMedView ArticleGoogle Scholar
- Hutchens YT: New desorption strategies for the masss spectrometric analysis of macromolecules. Rapid Commun Mass Spectrom 1993, 576–580. 10.1002/rcm.1290070703Google Scholar
- Ek S, Ortega E, Borrebaeck CA: Transcriptional profiling and assessment of cell lines as in vitro models for mantle cell lymphoma. Leuk Res 2005,29(2):205–213. 10.1016/j.leukres.2004.06.009PubMedView ArticleGoogle Scholar
- Sandberg R, Ernberg I: Assessment of tumor characteristic gene expression in cell lines using a tissue similarity index (TSI). Proc Natl Acad Sci USA 2005,102(6):2052–2057. 10.1073/pnas.0408105102PubMed CentralPubMedView ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.