Tumor-specific and Proliferation-specific Gene Expression Typifies Murine Transgenic B Cell Lymphomagenesis
2006; Elsevier BV; Volume: 282; Issue: 7 Linguagem: Inglês
10.1074/jbc.m605870200
ISSN1083-351X
AutoresMarc E. Lenburg, Anupama Sinha, Douglas V. Faller, Gerald V. Denis,
Tópico(s)CAR-T cell therapy research
ResumoThe dual bromodomain protein Brd2 is closely related to the basal transcription factor TAFII250, which is essential for cyclin A transactivation and mammalian cell cycle progression. In transgenic mice, constitutive lymphoid expression of Brd2 causes a malignancy most similar to human diffuse large B cell lymphoma. We compare the genome-wide transcriptional expression profiles of these lymphomas with those of proliferating and resting normal B cells. Transgenic tumors reproducibly show differential expression of a large number of genes important for cell cycle control and lymphocyte biology; expression patterns are either tumor-specific or proliferation-specific. Several of their human orthologs have been implicated in human lymphomagenesis. Others correlate with human disease survival time. BRD2 is underexpressed in some subtypes of human lymphoma and these subtypes display a number of similarities to the BRD2-mediated murine tumors. We illustrate with a high degree of detail that cancer is more than rampant cellular proliferation, but involves the additional transcriptional mobilization of many genes, some of them poorly characterized, which show a tumor-specific pattern of gene expression. The dual bromodomain protein Brd2 is closely related to the basal transcription factor TAFII250, which is essential for cyclin A transactivation and mammalian cell cycle progression. In transgenic mice, constitutive lymphoid expression of Brd2 causes a malignancy most similar to human diffuse large B cell lymphoma. We compare the genome-wide transcriptional expression profiles of these lymphomas with those of proliferating and resting normal B cells. Transgenic tumors reproducibly show differential expression of a large number of genes important for cell cycle control and lymphocyte biology; expression patterns are either tumor-specific or proliferation-specific. Several of their human orthologs have been implicated in human lymphomagenesis. Others correlate with human disease survival time. BRD2 is underexpressed in some subtypes of human lymphoma and these subtypes display a number of similarities to the BRD2-mediated murine tumors. We illustrate with a high degree of detail that cancer is more than rampant cellular proliferation, but involves the additional transcriptional mobilization of many genes, some of them poorly characterized, which show a tumor-specific pattern of gene expression. Diffuse large cell lymphoma (DLCL) 2The abbreviations used are: DLCL, diffuse large cell lymphoma; FACS, flow cytometry; FDR, false discovery rate; FITC, fluorescein isothiocyanate; FL, follicular lymphoma; GC, germinal center; HAT, histone acetyltransferase; HBSS, Hank's buffered salt solution; Ig, immunoglobulin; NHL, non-Hodgkin's lymphoma; PBS, phosphate-buffered saline; PCA, principal component analysis; PE, phycoerythrin; Tg, transgenic. is an aggressive B cell malignancy that accounts for 40% of non-Hodgkin's lymphomas (NHL) and is the most common type of lymphoma in adults (1.Edwards B.K. Brown M.L. Wingo P.A. Howe H.L. Ward E. Ries L.A.G. Schrag D. Jamison P.M. Jemal A. Wu X.C. Friedman C. Harlan L. Warren J. Anderson R.N. Pickle L.W. J. Nat. Cancer Inst. 2005; 97: 1407-1427Crossref PubMed Scopus (837) Google Scholar). NHL incidence rates have roughly doubled since 1970 (2.Hennessy B.T. Hanrahan E.O. Daly P.A. Lancet Oncol. 2004; 5: 341-353Abstract Full Text Full Text PDF PubMed Scopus (172) Google Scholar), and 56,000 new cases will be diagnosed in 2006, with 19,000 deaths, making NHL the fifth ranking cause of cancer deaths in the United States (1.Edwards B.K. Brown M.L. Wingo P.A. Howe H.L. Ward E. Ries L.A.G. Schrag D. Jamison P.M. Jemal A. Wu X.C. Friedman C. Harlan L. Warren J. Anderson R.N. Pickle L.W. J. Nat. Cancer Inst. 2005; 97: 1407-1427Crossref PubMed Scopus (837) Google Scholar). Key features of DLCL are its extremely heterogeneous presentation (3.Shipp M.A. Ross K.N. Tamayo P. Weng A.P. Kutok J.L. Aguiar R.C. Gaasenbeek M. Angelo M. Reich M. Pinkus G.S. Ray T.S. Koval M.A. Last K.W. Norton A. Lister T.A. Mesirov J. Neuberg D.S. Lander E.S. Aster J.C. Golub T.R. Nat. Med. 2002; 8: 68-74Crossref PubMed Scopus (2039) Google Scholar, 4.Godwin J.E. Fisher R.I. Clin. Lymphoma. 2001; 2: 155-163Abstract Full Text PDF PubMed Scopus (3) Google Scholar, 5.Alizadeh A.A. Eisen M.B. 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Nature. 2000; 403: 503-511Crossref PubMed Scopus (8029) Google Scholar), making treatment decisions difficult (3.Shipp M.A. Ross K.N. Tamayo P. Weng A.P. Kutok J.L. Aguiar R.C. Gaasenbeek M. Angelo M. Reich M. Pinkus G.S. Ray T.S. Koval M.A. Last K.W. Norton A. Lister T.A. Mesirov J. Neuberg D.S. Lander E.S. Aster J.C. Golub T.R. Nat. Med. 2002; 8: 68-74Crossref PubMed Scopus (2039) Google Scholar, 5.Alizadeh A.A. Eisen M.B. Davis R.E. Ma C. Lossos I.S. Rosenwald A. Boldrick J.C. Sabet H. Tran T. Yu X. Powell J.I. Yang L. Marti G.E. Moore T. Hudson Jr., J Lu L. Lewis D.B. Tibshirani R. Sherlock G. Chan W.C. Greiner T.C. Weisenburger D.D. Armitage J.O. Warnke R. Levy R. Wilson W. Grever M.R. Byrd J.C. Botstein D. Brown P.O. Staudt L.M. Nature. 2000; 403: 503-511Crossref PubMed Scopus (8029) Google Scholar) and making a molecular understanding of the origin of this B cell malignancy a distant goal. We have published a transgenic (Tg) mouse model for DLCL, based on constitutive (Eμ), B lineage-restricted expression of a newly described oncogene, the double bromodomain protein Brd2 (6.Greenwald R.J. Tumang J.R. Sinha A. Currier N. Cardiff R.D. Rothstein T.L. Faller D.V. Denis G.V. Blood. 2004; 103: 1475-1484Crossref PubMed Scopus (90) Google Scholar), which is related to the basal transcription factor TAFII250 (7.Beck S. Hanson I. Kelly A. Pappin D.J.C. Trowsdale J. DNA Seq. 1992; 2: 203-210Crossref PubMed Scopus (74) Google Scholar), a key participant in the transcriptional control of cyclin A and cell cycle progression (8.Wang E.H. Zou S. Tjian R. Genes Dev. 1997; 11: 2658-2669Crossref PubMed Scopus (78) Google Scholar). The expression of cyclin A is up-regulated in Tg B cells (6.Greenwald R.J. Tumang J.R. Sinha A. Currier N. Cardiff R.D. Rothstein T.L. Faller D.V. Denis G.V. Blood. 2004; 103: 1475-1484Crossref PubMed Scopus (90) Google Scholar), and the cell cycle is destabilized. Tg models make it possible to examine the consequences of DLCL in an inbred animal strain with a single initiating genetic lesion. This feature provides a model for DLCL with the least possible intrinsic diversity. Murine lymphoma models have been well established for some time, such as Eμ-Myc mice (9.Adams J.M. Harris A.W. Pinkert C.A. Corcoran L.M. Alexander W.S. Cory S. Palmiter R.D. Brinster R.L. Nature. 1985; 318: 533-538Crossref PubMed Scopus (1332) Google Scholar). However, the Eμ-Myc phenotype includes malignancies at several stages of lymphocyte development and greater cellular diversity than is seen in Eμ-BRD2 (Tg) mice. Unlike Eμ-Myc mice, which frequently develop fatal pre-B or B-cell lymphomas after 6 weeks of age (10.Harris A.W. Pinkert C.A. Crawford M. Langdon W.Y. Brinster R.L. Adams J.M. J. Exp. 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Lippincott-Schwartz J. Ozato K. Mol. Cell. Biol. 2000; 20: 6537-6549Crossref PubMed Scopus (234) Google Scholar), which is closely related to Brd2, sharing its dual bromodomain and extraterminal (ET) domain structure (21.Florence B. Faller D.V. Front. Biosci. 2001; 6: D1008-D1018Crossref PubMed Google Scholar). BRD4 is rearranged in t (15.Mozer B.A. Dawid I.B. Proc. Natl. Acad. Sci. U. S. A. 1989; 86: 3738-3742Crossref PubMed Scopus (42) Google Scholar, 19.Horn P.J. Peterson C.L. Front. Biosci. 2001; 6: D1019-D1023Crossref PubMed Google Scholar) translocations associated with aggressive carcinomas of the respiratory tract and its fusion partners encode likely oncoproteins (23.French C.A. Miyoshi I. Kubonishi I. Grier H.E. Perez-Atayde A.R. Fletcher J.A. Cancer Res. 2003; 63: 304-307PubMed Google Scholar). Also, translocations that fuse the bromodomain and histone acetyltransferase (HAT) domain of CREB-binding protein (CBP) to MLL (24.Sobulo O.M. Borrow J. Tomek R. Reshmi S. Harden A. Schlegelberger B. Housman D. Doggett N.A. Rowley J.D. Zeleznik-Le N.J. Proc. Natl. Acad. Sci. U. S. A. 1997; 94: 8732-8737Crossref PubMed Scopus (297) Google Scholar, 25.Lavau C. Du C. Thirman M. Zeleznik-Le N. EMBO J. 2000; 19: 4655-4664Crossref PubMed Scopus (170) Google Scholar, 26.Liedman D. Zeleznik-Le N. Curr. Opin. Hematol. 2001; 8: 218-223Crossref PubMed Scopus (10) Google Scholar) or to the monocytic leukemia zinc finger protein (27.Borrow J. Stanton Jr., V.P. Andresen J.M. Nat. Genet. 1996; 14: 33-41Crossref PubMed Scopus (648) Google Scholar), or that fuse p300 to MLL, create oncoproteins (28.Ida K. Kitabayashi I. Taki T. Taniwaki M. Noro K. Yamamoto M. Ohki M. Hayashi Y. Blood. 1997; 90: 4699-4704Crossref PubMed Google Scholar) associated with acute leukemias. The bromodomain is required for full transforming activity in at least one of these cases (25.Lavau C. Du C. Thirman M. Zeleznik-Le N. EMBO J. 2000; 19: 4655-4664Crossref PubMed Scopus (170) Google Scholar). Therefore, inappropriate targeting of HATs to certain promoters can cause lymphoid malignancy. Our study was motivated by the genome-wide transcriptional profiling of human lymphomas that has revealed previously unsuspected subclasses of DLCL, the transcriptional "fingerprint" of which can be used to classify patients into the most appropriate therapeutic group (3.Shipp M.A. Ross K.N. Tamayo P. Weng A.P. Kutok J.L. Aguiar R.C. Gaasenbeek M. Angelo M. Reich M. Pinkus G.S. Ray T.S. Koval M.A. Last K.W. Norton A. Lister T.A. Mesirov J. Neuberg D.S. Lander E.S. Aster J.C. Golub T.R. Nat. Med. 2002; 8: 68-74Crossref PubMed Scopus (2039) Google Scholar). Some of these human profiles are correlated with the fingerprint of mitogenically activated B cells, and are associated with a more aggressive course and higher mortality rates (a five-year median survival rate of 16%), whereas others are correlated with the fingerprint of germinal center (GC) B cells and are associated with more indolent disease and a 5-year median survival rate of 76% (4.Godwin J.E. Fisher R.I. Clin. Lymphoma. 2001; 2: 155-163Abstract Full Text PDF PubMed Scopus (3) Google Scholar). As a result of the DLCL phenotype of Tg mice and the lack of studies suggesting a direct role for alterations in BRD2 expression in human lymphomagenesis or leukemogenesis, we chose to study the gene expression patterns of this malignancy in greater detail. An advantage of the relatively late onset of full blown malignant lymphomas in Tg mice is the ability to collect lymphoid tissue from mice at progressive stages of lymphomagenesis, from very early, "pre-malignant" splenic B cells through to aggressive, end-stage splenic lymphomas associated with peripheral leukemia and organ failure. We compared the genome-wide transcriptional signatures we obtained from malignant cells to normal resting B cells and mitogenically activated B cells from syngeneic mice. Based on our previous transcriptional profiling in this lymphoma model (6.Greenwald R.J. Tumang J.R. Sinha A. Currier N. Cardiff R.D. Rothstein T.L. Faller D.V. Denis G.V. Blood. 2004; 103: 1475-1484Crossref PubMed Scopus (90) Google Scholar), we hypothesized that we would identify several patterns of differential gene expression, with one group representing a "proliferation signature," similar to mitogenically activated normal B cells, another group representing a "cancer signature," comprising genes specific to lymphomagenesis and malignancy. We used Affymetrix arrays that detect the expression of 22,500 murine transcripts and found over 3,000 that are differentially expressed between resting B cells and aggressive Tg lymphomas. Examination of the expression of these genes in earlier stage lymphomas and activated B cells resulted in the identification of clusters of co-expressed genes, and reveals a number of genes that are specifically altered by lymphomagenesis, and not B cell activation, which may be important in human DLCL lymphomagenesis. Mice−Animals were handled humanely in accordance with Institutional Animal Care and Use Committee (IACUC), state and Federal regulatory requirements; the Boston University Medical Campus IACUC reviewed and authorized this study. Tg mice developed lymphomas over the course of the experiment and exhibited clinical signs, including failure to nest, hunched posture, loss of appetite, sleepiness, inactivity, and ruffled fur (6.Greenwald R.J. Tumang J.R. Sinha A. Currier N. Cardiff R.D. Rothstein T.L. Faller D.V. Denis G.V. Blood. 2004; 103: 1475-1484Crossref PubMed Scopus (90) Google Scholar). Flow Cytometry−For analysis of splenocytes from normal or lymphoma mice, single cell suspensions of spleen were dispersed with a 70-μm nylon cell strainer (BD Falcon) in HBSS and stained in PBS supplemented with 0.1% bovine serum albumin. For surface cytofluorimetric analyses, FITC-coupled antibody against the pan B cell marker B220 and PE-coupled antibodies against mouse CD5, IgM, and IgD were from eBioscience (San Diego, CA). Antibodies against CD25, CD69, B7-1, B7-2, and rat isotype controls were from BD Pharmingen. Cell staining was performed in the presence of Fc receptor blocking antibody (clone 2.4G2, eBioscience), and cells were detected by flow cytometry with a FACSCalibur system (Becton Dickinson, San Jose, CA). Signals were analyzed with Cell Quest software. Viability (>99%) was determined by trypan blue. Cells were stained with B220-FITC antibodies and compared with PE-coupled antibodies for other antigens (6.Greenwald R.J. Tumang J.R. Sinha A. Currier N. Cardiff R.D. Rothstein T.L. Faller D.V. Denis G.V. Blood. 2004; 103: 1475-1484Crossref PubMed Scopus (90) Google Scholar). B Cell Activation in Vitro−Spleens were isolated and, after erythrocyte lysis, B cells were purified with anti-CD43 negative selection using magnetic beads (Miltenyi Biotec, Auburn, CA) in PBS supplemented with 2 mm EDTA and 0.5% bovine serum albumin as previously described (6.Greenwald R.J. Tumang J.R. Sinha A. Currier N. Cardiff R.D. Rothstein T.L. Faller D.V. Denis G.V. Blood. 2004; 103: 1475-1484Crossref PubMed Scopus (90) Google Scholar). B cells were cultured at 37 °C, 5% CO2 and 100% humidity in Na2HCO3-buffered RPMI1640 medium, supplemented with 10% heat-inactivated fetal bovine serum (Whittaker Bioproducts, Walkersville, MD), 50 μm 2-mercaptoethanol, glutamine, penicillin, and streptomycin, stimulated for 48 h with 10 μg/ml each of goat anti-mouse IgM F(ab′)2 antibody, μ chain-specific (Jackson ImmunoResearch, West Grove, PA), rat anti-mouse CD40 (BD Pharmingen, San Diego, CA) and 10 ng/ml murine recombinant interleukin-4 (eBioscience). Cell surface markers for B cell activation were measured with flow cytometry as above. Microarray Analysis−RNA was isolated from purified B cells as above, extracted with acid phenol and precipitated from 2-propyl alcohol, quantified, examined by nucleic acid electrophoresis for purity and integrity, labeled and hybridized in accordance with standard Affymetrix protocols to Murine Genome 430A Arrays (Affymetrix, Santa Clara, CA). These arrays contained representative sequences for ∼22,500 transcripts that were identified from the UniGene data base (Build 107, June 2002). Whole genome expression profiles were generated for 26 samples. Probe hybridization intensities were linearly scaled to a mean probe hybridization intensity of 500 units for each array using Microarray Suite 5.0 (MAS 5.0) software (Affymetrix, Santa Clara, CA). The signal intensities from the twenty-two probes in each probeset were then used to determine an overall expression level for each transcript and a measure of sequence-specific hybridization. These data and the probe level data have been submitted to the NCBI Gene Expression Omnibus (29.Barrett T. Suzek T.O. Troup D.B. Wilhite S.E. Ngau W.-C. Ledoux P. Rudnev D. Lash A.E. Fujibuchi W. Edgar R. Nucleic Acids Res. 2005; 33: D562-D566Crossref PubMed Scopus (862) Google Scholar) under accession number GSE6136. To eliminate expression measurements of genes that are not expressed in B cells, we identified 5,561 probesets among the 22,690 tested that failed to exhibit significant sequence-specific hybridization in any of the twenty-six samples using the detection calls generated by MAS 5. The hybridization intensities of the remaining 17,129 probesets were log10 transformed and used in subsequent analyses. For some analyses, hybridization intensities were further Z-Score normalized such that each probeset had a mean intensity of 0 with a standard deviation of 1. Principal component analysis (PCA) was performed with these normalized data in DecisionSite for Functional Genomics (Spotfire, Somerville, MA). Student's t-tests were performed using Excel (Microsoft, Redmond, WA). A false discovery rate (FDR) for each t test p value was calculated (30.Benjamini Y. Hochberg Y. J. Roy. Statist. Soc. Ser. B. 1995; 57: 289-300Google Scholar), and the smallest p value that gave an FDR > 0.05 (p =∼0.01) was used as the threshold p value for evidence of significant differential expression. Hierarchical clustering was performed with normalized data and Ward's method (31.Ward Jr., J.H. J. Am. Stat. Assoc. 1963; 38: 236-244Crossref Scopus (13432) Google Scholar) in DecisionSite. Fold changes for each probeset are expressed as log2 relative to the average hybridization intensity across all samples. Comparison with Human Lymphoma Datasets−Mouse probesets for transcripts orthologous to human genes known to be involved in lymphomagenesis were identified in a multi-step procedure (see supplemental Methods). We used the Monti et al. dataset (32.Monti S. Savage K.J. Kutok J.L. Feuerhake F. Kurtin P. Mihm M. Wu B. Pasqualucci L. Neuberg D. Aguiar R.C. Dal Cin P. Ladd C. Pinkus G.S. Salles G. Harris N.L. Dalla-Favera R. Habermann T.M. Aster J.C. Golub T.R. Shipp M.A. Blood. 2005; 105: 1851-1861Crossref PubMed Scopus (676) Google Scholar) to determine the expression of human genes orthologous to mouse genes that are differentially expressed during Tg lymphomagenesis in a collection of human clinical lymphoma samples. We first processed the dataset to remove probesets with sequence-specific hybridization in less than 9 of the 176 human lymphoma samples (<5% of samples) and log10-transformed the remaining hybridization intensities. The resulting dataset was then searched with NetAffx (33.Liu G. Loraine A.E. Shigeta R. Cline M. Cheng J. Valmeekam V. Sun S. Kulp D. Siani-Rose M.A. Nucleic Acids Res. 2003; 31: 82-86Crossref PubMed Scopus (419) Google Scholar) to identify probesets that detect expression of transcripts orthologous to various mouse genes of interest. Analyses of variance were used to identify genes that vary between the three DLCL lymphoma classes identified by Monti et al. (32.Monti S. Savage K.J. Kutok J.L. Feuerhake F. Kurtin P. Mihm M. Wu B. Pasqualucci L. Neuberg D. Aguiar R.C. Dal Cin P. Ladd C. Pinkus G.S. Salles G. Harris N.L. Dalla-Favera R. Habermann T.M. Aster J.C. Golub T.R. Shipp M.A. Blood. 2005; 105: 1851-1861Crossref PubMed Scopus (676) Google Scholar) and were performed in PartekPro (Partek). Pearson correlation between gene expression and patient survival time was performed using the cor.test function in the stats package of R 2.2.1.3. 3R Development Core Team (2005) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3–900051-07-0. We characterized B cell lymphomas as they occurred sporadically in breeding lines of Tg mice over 2 years. We performed phenotypic analyses of splenic pathology, using flow cytometry and immunohistochemistry, and classified each tumor according to its stage of advancement, and confirmed our previously published histopathology of spleen (6.Greenwald R.J. Tumang J.R. Sinha A. Currier N. Cardiff R.D. Rothstein T.L. Faller D.V. Denis G.V. Blood. 2004; 103: 1475-1484Crossref PubMed Scopus (90) Google Scholar). After we had assembled a well characterized tumor bank, we performed microarray analysis of RNA extracted from purified B cells of tumors or controls. Microarray analysis generated a dataset to compare cell types and draw conclusions about molecular characteristics of the tumors. Splenocytes were isolated from normal mice and mice with advanced lymphoma, then subjected to flow cytometry analysis. Forward versus side scatter profiles show a shift to larger cell size in lymphoma (Fig. 1A, FSC). Immunophenotype was consistent with a B-1 cell identity (Fig. 1A, CD5, sIgM), as previously reported (6.Greenwald R.J. Tumang J.R. Sinha A. Currier N. Cardiff R.D. Rothstein T.L. Faller D.V. Denis G.V. Blood. 2004; 103: 1475-1484Crossref PubMed Scopus (90) Google Scholar). B cell surface markers also show that the lymphoma cells were activated (Fig. 1A, panels B7-1 and B7-2). B cell surface markers defined two in vitro control conditions for interpretation of transcriptional signatures, independent of the microarray measurements themselves: "resting" cells from spleens of normal, non-Tg female (6–8 weeks) mice, mitogenically unstimulated (Fig. 1B, open histograms) or stimulated to become "activated" (closed histograms). Activated cells showed increased CD25, CD69, B7-1, and B7-2 expression, and decreased IgM and IgD (Fig. 1B), as expected (6.Greenwald R.J. Tumang J.R. Sinha A. Currier N. Cardiff R.D. Rothstein T.L. Faller D.V. Denis G.V. Blood. 2004; 103: 1475-1484Crossref PubMed Scopus (90) Google Scholar). We later used total RNA from these B cells to define the transcriptional signatures "resting" and "activated," against which we compared the signatures of B cell lymphomas by microarray analysis, described below. Pathology Groups−As expected in intermediate stages of splenic lymphoid malignancy, B cell Ig genes no longer showed polyclonal phenotypes, but an oligoclonal phenotype emerged, which was replaced by a monoclonal phenotype in many advanced cases (6.Greenwald R.J. Tumang J.R. Sinha A. Currier N. Cardiff R.D. Rothstein T.L. Faller D.V. Denis G.V. Blood. 2004; 103: 1475-1484Crossref PubMed Scopus (90) Google Scholar). The features of histopathology, Ig gene clonality, and surface markers allowed us to define five pathology groups for microarray analysis (Table 1). Group 1 (P1) comprised normal resting B cells from asymptomatic Tg or non-Tg mice (6–8 weeks) without a premalignant phenotype. These samples were tentatively grouped together in P1, because histology, FACS, and Ig analysis indicated that there were no detectable differences between asymptomatic Tg and non-Tg B cells. This supposition was later borne out with genome-wide transcriptome analysis, wherein PCA, shown below, confirmed that asymptomatic Tg B cells had a very similar signature to non-Tg B cells. Group 2 (P2) comprised normal activated B cells from asymptomatic non-Tg mice. Group 3 (P3) comprised B cells of Tg mice that showed early clinical signs and spleen enlargement of 1.25–2.0 times normal weight, premalignant expansion of peritoneal B cells and B cell hyperplasia by flow cytometry and histology (Fig. 1 and Ref. 6.Greenwald R.J. Tumang J.R. Sinha A. Currier N. Cardiff R.D. Rothstein T.L. Faller D.V. Denis G.V. Blood. 2004; 103: 1475-1484Crossref PubMed Scopus (90) Google Scholar). About 90% of the samples in P3 showed oligoclonal Ig genes. Group 4 (P4) comprised Tg mice with more severe clinical signs and pathology, including severe splenomegaly (2.0–10.0+ times normal weight), B cell lymphoma and disruption of splenic architecture (6.Greenwald R.J. Tumang J.R. Sinha A. Currier N. Cardiff R.D. Rothstein T.L. Faller D.V. Denis G.V. Blood. 2004; 103: 1475-1484Crossref PubMed Scopus (90) Google Scholar) as well lymphadenopathy and B cell infiltration of bone marrow. B cells of P4 and P5 were frequently monoclonal for Ig genes. Group 5 (P5) included Tg mice with end-stage pathologies and always showed additional leukemic infiltrates in liver, lung, and kidney. Heart and brain were the only organs that did not show infiltrates, the appearance of which infiltrates coincided with peripheral B cell leukemia and severe anemia (Results not shown).TABLE 1Summary of pathology groups Based on clinical presentation, pathology, and flow cytometry, we grouped 26 samples into five major classes. P1, normal resting B cells; P2, normal activated B cells; P3, marginal cases; P4, transitional cases; P5, aggressive cases (aggressive 8, 9, 19, 20, 21, 22, 23; transitional 13, 14, 15, 16, 17; marginal 5, 6, 7, 10, 11, 12; activated 2, 25, 26; resting 1, 3, 4, 18, 24).GroupnDescriptionSplenomegalyOther pathologyFACSIg gene clonalityP15RestingNoneNoneNormal restingPolyclonalP23ActivatedNoneNoneNormal activatedPolyclonalP36Marginal+/–+/–AbnormalOligoclonalP45Transitional++MixedOligoclonalP57Aggressive++++++B-1 clonesMonoclonal Open table in a new tab Ig Gene Sequences Discarded−To gain insight into the molecular mechanisms associated with lymphomagenesis in Tg mice, we compared the genome-wide gene expression patterns of the P1–P5 categories of B cells from Table 1. As we have previously reported for this Tg B cell lymphoma (6.Greenwald R.J. Tumang J.R. Sinha A. Currier N. Cardiff R.D. Rothstein T.L. Faller D.V. Denis G.V. Blood. 2004; 103: 1475-1484Crossref PubMed Scopus (90) Google Scholar), the majority of gene expression changes reflected a decrease in mouse immune cell markers, particularly Igκ light chain sequences. Many of these markers were decreased between 50- and 100-fold, which we interpreted to be a hallmark of the emergence of clonality in the B cell lymphomas. Given this reason for differential expression of Ig genes, we removed probesets for detecting the expression of these genes from the dataset. Principal Component Analysis−First, we sought to understand the general similarities and differences in gene expression between P1 and P5 by PCA of expression of all genes in the filtered dataset (Fig. 2A). The most important observation was that aggre
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