scholarly journals Evidence for Selective Transformation of Autoreactive Immature Plasma Cells in Mice Deficient in Fasl

2004 ◽  
Vol 200 (11) ◽  
pp. 1467-1478 ◽  
Author(s):  
Jian Qiao Zhang ◽  
Cheryl Okumura ◽  
Thomas McCarty ◽  
Min Sun Shin ◽  
Partha Mukhopadhyay ◽  
...  

Germline mutations in Fas and Fasl induce nonmalignant T cell hyperplasia and systemic autoimmunity and also greatly increase the risk of B cell neoplasms. B lymphomas occurring in Fasl mutant (gld) mice usually are immunoglobulin (Ig) isotype switched, secrete Ig, and are plasmacytoid in appearance but lack Myc translocations characteristic of other plasma cell (PC) neoplasms. Here, we explore the relationship between B cell autoreactivity and transformation and use gene expression profiling to further classify gld plasmacytoid lymphomas (PLs) and to identify genes of potential importance in transformation. We found that the majority of PLs derive from antigen-experienced autoreactive B cells producing antinuclear antibody or rheumatoid factor and exhibit the skewed Ig V gene repertoire and Ig gene rearrangement patterns associated with these specificities. Gene expression profiling revealed that both primary and transplanted PLs share a transcriptional profile that places them at an early stage in PC differentiation and distinguishes them from other B cell neoplasms. In addition, genes were identified whose altered expression might be relevant in lymphomagenesis. Our findings provide a strong case for targeted transformation of autoreactive B cells in gld mice and establish a valuable model for understanding the relationship between systemic autoimmunity and B cell neoplasia.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 2277-2277
Author(s):  
Daruka Mahadevan ◽  
Catherine Spier ◽  
Kimiko Della Croce ◽  
Susan Miller ◽  
Benjamin George ◽  
...  

Abstract Background: WHO classifies NHL into B (~85%) and T (~15%) cell subtypes. Of the T-cell NHL, peripheral T-cell NHL (PTCL, NOS) comprises ~6–10% with an inferior response and survival to chemotherapy compared to DLBCL. Gene Expression Profiling (GEP) of DLBCL has provided molecular signatures that define 3 subclasses with distinct survival rates. The current study analyzed transcript profiling in PTCL (NOS) and compared and contrasted it to GEP of DLBCL. Methods : Snap frozen samples of 5 patients with PTCL (NOS) and 4 patients with DLBCL were analyzed utilizing the HG-U133A 2.0 Affymetrix array (~18,400 transcripts, 22,000 probe sets) after isolating and purifying total RNA (Qiagen, RNAeasy). The control RNA samples were isolated from normal peripheral blood (PB) B-cell (AllCell, CA), normal PB T-cell (AllCell, CA) and normal lymph node (LN). Immunohisto-chemistry (IHC) confirmed tumor lineage and quantitative real time RT-PCR was performed on selected genes to validate the microarray study. The GEP data were processed and analyzed utilizing Affymetrix MAS 5.0 and GeneSpring 5.0 software. Our data were analyzed in the light of the published GEP of DLBCL (lymphochip and affymtrix) and the validated 10 prognostic genes (by IHC and real time RT-PCR). Results : Data are represented as “robust” increases or decreases of relative gene expression common to all 5 PTCL or 4 DLBCL patients respectively. The table shows the 5 most over-expressed genes in PTCL or DLBCL compared to normal T-cell (NT), B-cell (NB) and lymph node (LN). PTCL vs NT PTCL vs LN DLVCL vs NB DLBCL vs LN COL1A1 CHI3L1 CCL18 CCL18 CCL18 CCL18 VNN1 IGJ CXCL13 CCL5 UBD VNN1 IGFBP7 SH2D1A LYZ CD52 RARRES1 NKG7 CCL5 MAP4K1 Of the top 20 increases, 3 genes were common to PTCL and DLBCL when compared to normal T and B cells, while 11 were common when compared to normal LN. Comparison of genes common to normal B-cell and LN Vs DLBCL or PTCL and normal T-cell and LN Vs PTCL or DLBCL identified sets of genes that are commonly and differentially expressed in PTCL and/or DLBCL. The 4 DLBCL patients analyzed express 3 of 10 prognostic genes compared to normal B-cells and 7 of 10 prognostic genes compared to normal LN and fall into the non-germinal center subtype. Quantitative real time RT-PCR on 10 functionally distinct common over-expressed genes in the 5 PTCL (NOS) patients (Lumican, CCL18, CD14, CD54, CD106, CD163, α-PDGFR, HCK, ABCA1 and Tumor endothelial marker 6) validated the microarray data. Conclusions: GEP of PTCL (NOS) and DLBCL in combination with quantitative real time RT-PCR and IHC have identified a ‘molecular signature’ for PTCL and DLBCL based on a comparison to normal (B-cell, T-cell and LN) tissue. The categorization of the GEP based on the six hallmarks of cancer identifies a ‘tumor profile signature’ for PTCL and DLBCL and a number of novel targets for therapeutic intervention.


Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 266-266 ◽  
Author(s):  
Enrico Tiacci ◽  
Verena Brune ◽  
Susan Eckerle ◽  
Wolfram Klapper ◽  
Ines Pfeil ◽  
...  

Abstract Abstract 266 Background. Previous gene expression profiling studies on cHL have been performed on whole tissue sections (mainly reflecting the prominent reactive background in which the few HRS cells are embedded), or on cHL cell lines. However, cultured HRS cells do not likely reflect primary HRS cells in all aspects, being derived from end-stage patients and from sites (e.g. pleural effusions or bone marrow) which are not typically involved by cHL and where HRS cells lost their dependence on the inflammatory microenvironment of the lymph node. Methods. ∼1000–2000 neoplastic cells were laser-microdissected from hematoxylin/eosin-stained frozen sections of lymph nodes taken at disease onset from patients with cHL (n=16) or with various B-cell lymphomas (n=35), including primary mediastinal B-cell lymphoma (PMBL) and nodular lymphocyte-predominant Hodgkin lymphoma (nLPHL). After two rounds of in vitro linear amplification, mRNA was hybridized to Affymetrix HG-U133 Plus 2.0 chips. Expression profiles were likewise generated from sorted cHL cell lines and several normal mature B-cell populations. Results. Primary and cultured HRS cells, although sharing hallmark cHL signatures such as high NF-kB transcriptional activity and lost B-cell identity, showed considerable transcriptional divergence in chemokine/chemokine receptor activity, extracellular matrix remodeling and cell adhesion (all enriched in primary HRS cells), as well as in proliferation (enriched in cultured HRS cells). Unsupervised and supervised analyses indicated that microdissected HRS cells of cHL represent a transcriptionally unique lymphoma entity, overall closer to nLPHL than to PMBL but with differential behavior of the cHL histological subtypes, being HRS cells of the lymphocyte-rich and mixed-cellularity subtypes close to nLPHL cells while HRS cells of NS and LD exhibited greater similarity to PMBL cells. HRS cells downregulated a large number of genes involved in cell cycle checkpoints and in the maintenance of genomic integrity and chromosomal stability, while upregulating gene and gene signatures involved in various oncogenic signaling pathways and in cell phenotype reprogramming. Comparisons with normal B cells highlighted the lack of consistent transcriptional similarity of HRS cells to bulk germinal center (GC) B cells or plasma cells and, interestingly, a more pronounced resemblance to CD30+ GC B cells and CD30+ extrafollicular B cells, two previously uncharacterized subsets that are transcriptionally distinct from the other mature B-cell types. Conclusions. Gene expression profiling of primary HRS cells provided several new insights into the biology and pathogenesis of cHL, its relatedness to other lymphomas and normal B cells, and its enigmatic phenotype. Disclosures: No relevant conflicts of interest to declare.


Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 2938-2938
Author(s):  
Frank Dicker ◽  
Susanne Schnittger ◽  
Claudia Schoch ◽  
Alexander Kohlmann ◽  
Wei-Min Liu ◽  
...  

Abstract The lack of somatic mutations of the immunoglobulin variable heavy chain (IgVH) gene has been established as poor prognostic marker for chronic lymphocytic leukemia (CLL) patients at early stage disease. Expression of the non receptor tyrosine kinase zeta chain associated protein (ZAP-70) was proposed as a surrogate marker for an unmutated IgVH, however, up to 30% discordant samples have been reported depending on the respective study. B cell receptor (BCR) mediated signaling is enhanced by ZAP-70 expression in CLL cells in vitro and ZAP-70 expression also tends to decrease the time from diagnosis to treatment irrespective of the IgVH status. Therefore, we wanted to identify differentially expressed genes between the ZAP-70 positive and negative CLLs by gene expression profiling of peripheral blood mononuclear cells (PBMCs) using Affymetrix microarrays (HG-U133 Plus 2.0). ZAP-70 expression was analyzed by quantitative real time PCR of CD19 purified (purity > 99%) PBMCs (n=62) using a LightCycler instrument. Expression of ZAP-70 mRNA was normalized against the housekeeping gene ABL and a relative quantitation against Jurkat T cells as a calibrator was performed. Results are expressed as normalized ratio and a cut-off of 0.5 normalized ratio gave the best correlation to the IgVH status with 77% concordant samples between ZAP-70 expression and the IgVH status. The discordant samples consisted of 5 unmutated IgVHs in the ZAP-70 negative group and 9 mutated in the ZAP-70 positive group. In a second step PBMCs of the same samples were analyzed by gene expression profiling and differentially expressed genes were identified by t-test. Among the two best genes that could be used in a classification algorithm (SVM) to distinguish between the 2 subsets with 92% accuracy were ZAP-70 and B cell scaffold protein with ankyrin repeats (BANK1). The expression of BANK1 was increased 3–4-fold in the ZAP-70 negative compared to the ZAP-70 positive CLL subset (P = 0,001). In the literature, BANK1 has been identified in human BCR expressing B cells and seems to be B cell restricted. In B cells the scaffolding protein BANK1 enhances BCR-mediated Ca2+-signaling, a signaling pathway that is also enhanced by ZAP-70 expression in CLL B cells. Based on these data we show that increased BANK1 expression correlates with a ZAP-70 negative status in CLL B cells. The functional consequences of BANK1 expression in the ZAP-70 negative subset of CLL B cells, which are usually associated with a more favorable prognosis, still need to be established further.


Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 1352-1352
Author(s):  
Marit E. Hystad ◽  
Trond H. Bo ◽  
Edith Rian ◽  
June H. Myklebust ◽  
Einar Sivertsen ◽  
...  

Abstract B cells develop from hematopoietic stem cells (HSC) in the bone marrow (BM) through a number of distinct stages before they migrate to the periphery as naïve mature B lymphocytes. These developmental stages can be identified by expression of cell surface antigens and Ig gene rearrangement status. The aim of this study was to characterize the earliest steps of normal human B cell development by gene expression profiling. Immunomagnetic selection and subsequent fluorescence-activated cell sorting (FACS) were used to isolate five populations from adult human BM: CD34+CD38− (HSC), CD34+CD10+CD19− early lymphoid progenitor cells (ELP), CD34+CD10+CD19+IgM− progenitor B cells (pro-B), CD34−CD10+CD19+IgM− precursor B cells (pre-B) and CD34−CD10+CD19+IgM+ immature B cells (IM). Total RNA was extracted from the purified cell populations, amplified and hybridized to Lymphochip cDNA microarrays. Six independent experiments from different donors were performed for each cell population. Expression of the genes encoding the selection markers confirmed the validity of the approach. Interestingly, genes necessary for the V(D)J-recombination such as RAG-1, RAG-2, TdT and ADA showed higher gene expression in the ELP population than in the HSC. In contrast, the transcription factors E2A, EBF, and Pax-5, which are all essential for early B-cell development, were first turned on in pro-B cells, in accordance with the B-cell lineage commitment. The ELP did not express B, T or NK lineage markers, except for a higher expression level of CD2 in the ELP population than in the four other cell populations. Taken together, the expression pattern of CD2 and the V(D)J-recombination genes in the ELP population, indicate that these cells have developed a lymphocyte potential, but are not fully committed to B-lineage cells. Hierarchical cluster analysis of the 758 differentially expressed genes (differences in relative expression by a factor of two or more and with maximum10% FDR) revealed a pattern that clearly separated the five consecutive cell populations. Furthermore, we created expression signatures based on information from Gene Ontology (GO) http://source.stanford.edu/cgi-bin/source/sourceSearch. One of the clearest distinctions between the gene expressions of the five developmental populations involved genes associated with proliferation, and showed that the HSC and IM populations are relatively indolent while the pro-B and pre-B populations comprised high expression levels of nearly all the proliferation associated genes. Finally, we examined in further detail the transitions between HSC, ELP and pro B cells. We found 25 genes to be differently expressed in the ELP population in comparison to the HSC and pro-B populations, including IGJ, BCL2 and BLNK. To identify combinations of markers that could better discriminate the ELP population, we also performed a gene pair class separation test. This resulted in 68 gene pairs with score above 10 that were denoted very good discriminators. For several of the markers the differences in gene expression were verified at the protein level by five colour FACS analysis. Taken together, these results provide new insight into the molecular processes that take place in the early human B cell differentiation, and in particular provide new information regarding expression of genes in the ELP population.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 359-359
Author(s):  
Coraline Mlynarczyk ◽  
Matthew Teater ◽  
Juhee Pae ◽  
Theinmozhi Arulraj ◽  
Christopher R Chin ◽  
...  

Abstract Somatic missense mutations of BTG1 are exclusive to germinal center (GC)-derived B cell lymphomas (~12% of DLBCLs) and are most prevalent in ABC-DLBCL (p=0.0184 vs GCB-DLBCL), particularly in the MCD/cluster 5 subtype, which features extranodal dissemination and unfavorable outcome. However, the relevance, mechanism of action and biological contribution of BTG1 mutations have not been studied. Using a rigorous genomic covariate analysis, we identified BTG1 mutations as a top genetic driver in DLBCL. Furthermore, molecular dynamics simulations indicated that BTG1 recurrent mutations, including the most frequent Q36H, disrupted the protein structure, with likely deleterious functional consequences. To investigate the effect of BTG1 mutation in GC B cells, we generated a conditional Btg1Q36H knock in mouse crossed to the B cell specific Cd19Cre line. Surprisingly, there was no apparent phenotype in GC B cells or other B cell populations. However, placing Btg1 Q36H and WT GC B cells in competition within the same mouse through adoptive transfer revealed a dramatic competitive advantage of Btg1 Q36H cells, virtually taking over the GC reaction. To gain further insight into this striking fitness advantage, we performed RNAseq in Btg1 Q36H GCs, which showed marked enrichment for genes induced in positively selected GC B cells, including MYC targets and biosynthetic pathways. The same genes were also enriched in BTG1 mutant DLBCL patients in 2 independent cohorts. Furthermore, Btg1 Q36H GC B cells displayed greater RNA content and cell size, reflecting increased fitness. Positive selection normally triggers a brief Myc pulse in GC B cells. We therefore crossed our Btg1Q36H mice to the MycGFPprotein fusion reporter and observed higher proportion of Myc GFP+ cells in Btg1 Q36H GCs. For mechanistic studies, we generated isogenic BTG1 Q36H or BTG1 WT human DLBCL cell lines. BTG1 Q36H cells exhibited enrichment for the same positively selected GC B and MYC target genes, as well as greater RNA content and cell size. BTG1 family members were suggested to interact with RNA. Performing RNA-immunoprecipitation, we discovered that ~800 transcripts associated with BTG1 WT, but not BTG1 Q36H. Notably, these corresponded to the same positively selected GC B and MYC target genes, including MYC itself. BTG1 was shown to regulate mRNA stability in other cell types. However, BTG1 Q36H did not alter MYC mRNA stability and instead facilitated MYC protein synthesis, thus disrupting a novel GC context-specific checkpoint mechanism, whereby BTG1 normally attenuates spurious MYC translation to tightly restrict fitness potential. In GC B cells, Myc induction coincides with S phase entry, but G2/M progression requires re-entry into the proliferative dark zone. To characterize GC dynamics in vivo, we performed targeted single cell RNAseq in competing Btg1 Q36H and WT GC B cells and noted earlier and higher proportion of positively selected Btg1 Q36H GC B cells having committed to G2/M and the proliferative program. We confirmed faster S phase completion in competing Btg1 Q36H GC B cells by in vivo EdU/BrdU labelling and greater re-entry into the proliferative dark zone by in vivo antigen delivery to synchronize GC B cells at the time of positive selection. Given that MCD-DLBCLs express high levels of BCL2, we crossed our Btg1Q36H mice to the VavP-Bcl2 model. As compared to VavP-Bcl2, VavP-Bcl2+Btg1 Q36H mice displayed shorter survival (p=0.0005), earlier onset of lymphoma, dysplastic B cell infiltration into non lymphoid organs and they contained highly mutated, selected and clonal tumor B cells. Moribund VavP-Bcl2+Btg1 Q36H mice uniquely featured sheets of large, immunoblastic lymphoma cells, characteristic of ABC-DLBCLs. Most notably, examining ABC-DLBCLs from 5 independent cohorts showed inferior clinical outcome for BTG1 mutant patients (p=0.0011) and independent association of BTG1 mutation with inferior overall survival by multivariable Cox regression (p=0.0190). Collectively, we find that BTG1 mutations mediate lymphomagenesis through an entirely novel mechanism of action that recapitulates the embryonic MYC-dependent "super-competitive" phenotype originally described in Drosophila imaginal disc cells. In the GC, "super-competition" is provided by BTG1 mutation via a subtle acceleration of MYC induction and GC dynamics, conferring dramatic fitness and the potential to transform into aggressive lymphomas. Disclosures Hoehn: Prellis Biologics: Consultancy. Elemento: Janssen: Research Funding; Freenome: Consultancy, Other: Current equity holder in a privately-held company; Volastra Therapeutics: Consultancy, Other: Current equity holder, Research Funding; Owkin: Consultancy, Other: Current equity holder; Champions Oncology: Consultancy; One Three Biotech: Consultancy, Other: Current equity holder; Eli Lilly: Research Funding; AstraZeneca: Research Funding; Johnson and Johnson: Research Funding. Scott: NanoString Technologies: Patents & Royalties: Patent describing measuring the proliferation signature in MCL using gene expression profiling.; BC Cancer: Patents & Royalties: Patent describing assigning DLBCL COO by gene expression profiling--licensed to NanoString Technologies. Patent describing measuring the proliferation signature in MCL using gene expression profiling. ; AstraZeneca: Consultancy; Abbvie: Consultancy; Celgene: Consultancy; Incyte: Consultancy; Janssen: Consultancy, Research Funding; Rich/Genentech: Research Funding. Melnick: Constellation: Consultancy; Epizyme: Consultancy; Daiichi Sankyo: Research Funding; Sanofi: Research Funding; Janssen Pharmaceuticals: Research Funding; KDAC Pharma: Membership on an entity's Board of Directors or advisory committees.


2004 ◽  
Vol 199 (1) ◽  
pp. 59-68 ◽  
Author(s):  
Katia Basso ◽  
Arcangelo Liso ◽  
Enrico Tiacci ◽  
Roberta Benedetti ◽  
Alessandro Pulsoni ◽  
...  

Hairy cell leukemia (HCL) is a chronic B cell malignancy characterized by the diffuse infiltration of bone marrow and spleen by cells displaying a typical “hairy” morphology. However, the nature of the HCL phenotype and its relationship to normal B cells and to other lymphoma subtypes remains unclear. Using gene expression profiling, we show here that HCL displays a homogeneous pattern of gene expression, which is clearly distinct from that of other B cell non-Hodgkin lymphomas. Comparison with the gene expression profiles of purified normal B cell subpopulations, including germinal center (GC), pre-GC (naive), and post-GC (memory) B cells, shows that HCL cells are more related to memory cells, suggesting a derivation from this B cell population. Notably, when compared with memory cells, HCL cells displayed a remarkable conservation in proliferation, apoptosis, and DNA metabolism programs, whereas they appeared significantly altered in the expression of genes controlling cell adhesion and response to chemokines. Finally, these analyses have identified several genes that are specifically expressed in HCL and whose expression was confirmed at the protein level by immunocytochemical analysis of primary HCL cases. These results have biological implications relevant to the pathogenesis of this malignancy as well as clinical implications for its diagnosis and therapy.


Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 2375-2375
Author(s):  
Nicolas Blin ◽  
Celine Bossard ◽  
Jean-Luc Harousseau ◽  
Catherine Charbonnel ◽  
Wilfried Gouraud ◽  
...  

Abstract Gene expression profiling has provided new insights into the understanding of mature B cell neoplasms by relating each one to its normal counterpart, so that they can be to some extent classified according to the corresponding normal B-cell stage. Thus, diffuse large B cell (DLBCL) and follicular lymphoma (FL) have been related to a germinal center precursor whereas mantle cell lymphoma (MCL) or marginal zone lymphoma (MZL) are more likely to derive from naïve and memory B cell, respectively. However, little is still known about the physiopathology of B-cell lymphomas and particularly the deregulated pathways involved in their oncogenesis. To further investigate that point, we performed laser capture microdissection (LCM) of the three anatomic lymphoid compartments (i.e germinal center, mantle zone and marginal zone) taken from nine normal spleens and lymph nodes and magnetic cell separation of the four normal B cell subpopulations (i.e naïve B cells, centroblasts, centrocytes and memory B cells) purified from twelve normal tonsils for gene expression profiling by cDNA microarray. These molecular profiles have been compared to those of the four most frequent mature B cell neoplasms in adult (i.e DLBCL, FL, MZL and MCL), each one isolated from five previously untreated patients. Unsupervised analysis by hierarchical clustering of the normal anatomic and cellular populations could discriminate the germinal from the extra-germinal populations by genes involved in cell proliferation (e.g. E2F5, CCNB2, BUB1B and AURKB), DNA repair (e.g. PCNA and EXO1), cytokine secretion (e.g. IL8, IL10RB, IL4R and TGFBI) and apoptosis (e.g. CASP8, CASP10, BCL2 and FAS). Supervised analysis of the comparison between each B-cell lymphoma and its anatomic and cellular physiologic equivalent identified molecular deregulations concerning several genes’families characterizing the different histologic subtypes. Genes associated with cellular adhesion and ubiquitin cycle were significantly up-regulated in MCL (FCGBP, ITGAE, USP7, VCAM1) and MZL (CTGF, CDH1, ITGAE) whereas germinal center derived lymphomas (i.e. DLBCL and FL) mainly showed up-regulation of genes involved in cell proliferation (TNFRSF17, SEPT8) and immune response (FCER1G, XBP1, IL1RN). Few deregulated genes were common to the four subtypes, principally associated with cell proliferation (CYR61, GPNMB), cytosqueleton organization (EPB41L3) and carbohydrates metabolism (GNPDA1), suggesting potential similar oncogenic pathways. Those preliminary results are compatible with both subtype-specific and overall mechanisms of lympomagenesis and should be verified in a wider range of samples to confirm the oncogenic events involved in this heterogeneous disease.


Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 355-355 ◽  
Author(s):  
Karin Tarte ◽  
Céline Pangault ◽  
John de Vos ◽  
Philippe Ruminy ◽  
Fabienne Sauvee ◽  
...  

Abstract Genetic and functional studies have demonstrated that FL cells retain the major features of normal germinal center (GC)-derived B cells, in particular the dependency on an active crosstalk with their specialized microenvironment. In agreement, microarray analyses have recently revealed that FL patient outcome is primarily predicted by molecular characteristics of tumor-infiltrating immune cells instead of tumor cells. However, our knowledge of the crucial interactions between malignant and non-malignant cells in FL remains limited by the use of whole biopsy specimen to perform gene expression profiling (GEP). We thus conducted GEP on both CD19pos B cells and CD19negCD22neg non-B cells purified from lymph nodes of 17 patients with de novo FL & 4 normal donors (CD20pos >94.5%, median=98.2%) and 9 de novo FL patients & 5 normal donors (CD20pos<6.7%, median=0.5%), respectively. Biotinylated cRNA were amplified according to the small sample labelling protocol and hybridized onto HGU133 Plus 2.0 arrays (Affymetrix). Raw data were normalized using GC-RMA methodology (ArrayAssist, Stratagene) and finally, based on a CV>80, 10870 probesets were selected for further analyses. Unsupervised hierarchical clustering (Eisen’s software) allowed the correct classification of the 35 samples into the 4 groups: FL B-cell, Normal B-cells, FL non-B cells, and Normal non-B cells. Supervised analyzes were done using asymptotic non-parametric Mann-Whitney U-test (fold change ≥2, P<0.01) and confirmed by permutation analysis (500 permutations, false discovery rate <5%) using SAM software. We first established the list of the 841 probesets that were differentially expressed between FL and normal B-cells containing, 355 probesets overexpressed in malignant B cells including genes involved in GC B-cell biology (BCL6, MTA3, ID2, CD80, SDC4) and oncogenes as well (BCL2, AURK2) and conversely, 486 probesets downregulated in malignant B cells involving several interferon-stimulated genes for example. We then looked for the FL-specific microenvironment signature and pointed out the 1206 probesets that were differentially expressed between FL and normal non-B cells. Interestingly, all these genes were upregulated in the lymphoma context. Among them, we identified a striking follicular helper T-cell (TFH) signature (CXCR5, ICOS, CXCL13, CD200, PDCD1, SH2D1A) and an activated T-cell signature (IFNG, FASLG, GZMA, ZAP70, CD247). Notably, the TFH and activated T-cell signatures were not merely a surrogate for the number of T cells since many standard T-cell genes (i.e. CD2, CD4, CD7, LEF1, CD8A) were not induced in the FL microenvironment. Finally, in order to draw an overview of the FL-specific synapse between B and non-B cell compartments, we isolated a group of 2323 probesets that were differentially expressed between both compartments in FL and not in normal context. Using Ingenuity Pathway Analysis software we then identified among them FL-specific functional networks, including an IL-4- & an IL-15-centered pathway. Altogether, these data shed new light on our understanding of FL biology and could be a source of new therapeutics targeting the interplay between B cells and their microenvironment.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3013-3013
Author(s):  
Ruth M de Tute ◽  
Sharon Barrans ◽  
Andy C. Rawstron ◽  
Peter W.M. Johnson ◽  
Andrew J Davies ◽  
...  

Abstract Clonal B-cell populations with either a CLL or a non-CLL phenotype are a common finding in normal individuals but uncertainty remains about how this relates to the development of clinically significant disease. The aim of this study was to investigate the frequency of peripheral blood clonal B-cell populations and B-cell subset abnormalities in newly presenting DLBCL patients and to determine whether the incidence of these abnormalities differed between the GCB and ABC subtypes, which are regarded as having distinct pathogenesis. The study was carried out using peripheral blood samples collected from patients entered in the UK-REMoDL-B trial. This trial is testing the hypothesis that the ABC subtype of DLBCL responds preferentially to R-CHOP- Bortezomib. Gene expression profiling is performed on the diagnostic tissue biopsy (FFPE) using the Illumina WG-DASL assay prior to randomisation classified as GCB, ABC or unclassified (UN). The availability of GEP data allows meaningful comparison with the phenotype of clonal populations detected by flow cytometry. Peripheral blood taken prior to first treatment was analysed using multi-colour flow cytometry. Following red cell lysis with ammonium chloride, samples were incubated with a panel of antibodies comprising of a CD19 and CD20 backbone, with Kappa, Lambda, CD5, CD45, CD49d, LAIR-1, CXCR5, CD31, CD95, CD38 and CD10, supplemented in some cases by CD81, CD79b, and CD43. A minimum of 500,000 events were acquired on a FacsCanto II flow cytometer (Becton Dickinson). B-cells were enumerated and any monoclonal populations identified were classified as CLL, germinal centre (GC), non-GC or not otherwise specified (NOS) where the phenotype was indeterminate. 358 samples were eligible for inclusion from patients with an average age of 62.2years (range 22.9-86.1). Abnormalities were detected in 52% of cases (B-lymphopenia ((<0.06 x 109/l) 33%, B-lymphocytosis (>1 x 109/l) 2.8%, CLL clone 3.6%, GC clone 9.8%, non-GC clone 9.8%, clonal population NOS 2.2%). Gene expression profiling results were available for 278 individuals; 51% GCB, 32% ABC and 17% unclassified. The relationship between peripheral blood B-cell findings and the GEP determined phenotype of the tumour is shown in the table:TableB-lymphopeniaCLL CloneMonoclonal GC typeMonoclonalNon-GC typeMonoclonal NOSNormalB-cellGCB n=14241/142 (29%)5/142 (3.5%)21/142 (15%)8/142 (5.6%)2/142 (1%)72/142 (51%)ABC n=8927/89 (30%)2/89 (2%)2/89 (2%)12/89 (13.5%)2/89 (2%)49/89 (55%)Unclassified n=4726/47 (55%)0/50 (0%)2/47 (4%)6/47 (12%)6/47 (5%)14/47 (30%) In patients where clonal populations were detected in the peripheral blood there was striking concordance between the phenotype of the clone and the GEP of the underlying tumour. Presence of a GC-population by flow was highly predictive of GCB GEP (84% GC–type populations detected were in GCB cases). The number of discordant cases and the number of CLL clones detected approximate to the numbers that would be expected in a normal population of a similar age. It is, therefore, likely that in most cases circulating tumour cells or a closely related precursor clone are being detected. The similarity between the results of the ABC and unclassified GEP groups suggest that these are biologically related. An unexpected finding in this study was the high incidence of B-lymphopenia at a level that might be expected to be associated with increased risk of infection. This may reflect suppression of normal B-cells by the neoplastic clone or be a marker of underlying immune dysfunction that may predispose to the development of the tumour. Immuosuppression has a role in the pathogenesis of DLBCL in the elderly and this study suggests that this may also be a factor in the wider patient population. These results may have implications for prognostic assessment and may offer opportunities for early diagnosis and possibly response assessment in some patients. The impact on outcome will be assessed in the course of the trial. Disclosures: Jack: Roche /Genentech: Research Funding.


Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 3353-3353
Author(s):  
Cassandra L. Jacobs ◽  
Anand S. Lagoo ◽  
Raj C Dash ◽  
Adekunle Raji ◽  
Andrew M Evens ◽  
...  

Abstract Background: Burkitt lymphoma (BL) is a highly aggressive lymphoma that can be cured in up to 80% of patients when treated with intensive multi-agent chemotherapy. The distinction between BL and diffuse large B-cell lymphoma (DLBCL) is critical because there are important differences in their clinical management. However, the distinction can be difficult because of an overlap between DLBCL and BL in morphology, immunophenotype and cytogenetics. Previous work has shown that gene expression profiling can distinguish these entities with a high degree of certainty. Our previous work has demonstrated that microRNAs play a direct role in regulating key transcription factors in normal and malignant B cells. We investigated whether microRNA expression could be used to reliably distinguish BL from DLBCL. Methods: Biopsy samples were collected from 104 patients with a diagnosis of either sporadic BL (N=25) or DLBCL (N=79). All cases were reviewed for pathology diagnosis and profiled for microRNA expression using microarrays. Using the 30 most highly differentially expressed microRNAs with the highest t-statistic, we applied singular value decomposition to identify the 10 most predictive microRNAs. Using those 10 microRNAs, we constructed a Bayesian predictor to distinguish BL from DLBCL. The predictor performance was tested using leave-one-out cross-validation. We further applied gene expression profiling to 52 cases of DLBCL to identify the molecular subsets of DLBCL: activated B cell type and germinal center B cell type DLBCL. We constructed a Bayesian predictor to distinguish these molecular subsets based upon their gene expression. A separate predictor was created from the microRNA profiles of these DLBCL subsets and tested using leave-one-out cross-validation. In order to understand the effects of lineage-specific microRNAs in B cell lymphomas, we applied FACS-sorting to isolate mature B cell subsets including naïve B cells, germinal center B cells, plasma cells and memory cells. We compared the microRNAs involved in germinal center differentiation to those expressed highly in Burkitt lymphoma. Results: The predictor constructed based on microRNA expression was 90% accurate in distinguishing Burkitt lymphoma from DLBCL, using pathology diagnosis as the standard. The microRNA-based predictor was also over 90% accurate in the distinction of the molecular subsets of DLBCL, compared to the gold standard of gene expression-profiling. Further, we found that the Burkitt lymphoma cases consistently expressed microRNAs related to normal germinal center B cell differentiation, suggesting that they also maintain expression of B cell stage-specific microRNAs. Conclusion: This study demonstrates that the microRNA expression profiles can be used to accurately distinguish Burkitt lymphoma from DLBCL. The ability of the predictor to identify the molecular subsets of patients with DLBCL and those with BL suggests that it will be useful in the diagnosis and management of patients with Burkitt lymphoma. Further, the patterns of microRNA expression and their target genes suggests a role for microRNAs in the pathophysiology of these tumors.


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