scholarly journals Distinctive growth requirements and gene expression patterns distinguish progenitor B cells from pre-B cells.

1993 ◽  
Vol 177 (4) ◽  
pp. 915-923 ◽  
Author(s):  
E A Faust ◽  
D C Saffran ◽  
D Toksoz ◽  
D A Williams ◽  
O N Witte
Keyword(s):  
Gene Expression ◽  
Bone Marrow ◽  
B Cells ◽  
Expression Patterns ◽  
Porous Membrane ◽  
Terminal Deoxynucleotidyl Transferase ◽  
Gene Expression Patterns ◽  
Murine Bone Marrow ◽  
Interleukin 7 ◽  
Rag 1

Long-term bone marrow cultures have been useful in determining gene expression patterns in pre-B cells and in the identification of cytokines such as interleukin 7 (IL-7). We have developed a culture system to selectively grow populations of B lineage restricted progenitors (pro-B cells) from murine bone marrow. Pro-B cells do not grow in response to IL-7, Steel locus factor (SLF), or a combination of the two. c-kit, the SLF receptor, and the IL-7 receptor are both expressed by pro-B cells, indicating that the lack of response is not simply due to the absence of receptors. Furthermore, SLF is not necessary for the growth of pro-B cells since they could be expanded on a stromal line derived from Steel mice that produces no SLF. IL-7 responsiveness in pre-B cells is associated with an increase in n-myc expression and is correlated with immunoglobulin (Ig) gene rearrangements. Although members of the ets family of transcription factors and the Pim-1 kinase are expressed by pro-B cells, n-myc is not expressed. Pro-B cells maintain Ig genes in the germline configuration, which is correlated with a low level of recombination activating genes 1 and 2 (Rag-1 and 2) mRNA expression, but high expression of sterile mu and terminal deoxynucleotidyl transferase. Pro-B cells are unable to grow separated from the stromal layer by a porous membrane, indicating that stromal contact is required for growth. These results suggest that pro-B cells are dependent on alternative growth signals derived from bone marrow stroma and can be distinguished from pre-B cells by specific patterns of gene expression.

Defining The Role Of Microrna-146a In B Cell Lymphomagenesis

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3805-3805
Author(s):  
Jorge Contreras ◽  
Jayanth Kumar Palanichamy ◽  
Tiffany Tran ◽  
Dinesh S. Rao
Keyword(s):  
Gene Expression ◽  
B Cells ◽  
B Cell ◽  
Conflicts Of Interest ◽  
Cell Lymphoma ◽  
Expression Patterns ◽  
Significant Proportion ◽  
B Cell Lymphoma ◽  
Gene Expression Patterns

Abstract Diffuse large B cell lymphoma (DLBCL) is one of the most common Non-Hodgkin lymphomas among adults. It is a heterogeneous disease characterized by multiple mutations and translocations. Gene expression profiling studies have revealed several characteristic gene expression patterns, with two main patterns emerging, namely Germinal Center(GC) type, and Activated B Cell (ABC) type. ABC-type DLBCL shows gene expression patterns that resemble activated B-cells, with increased expression of anti-apoptotic, and pro-proliferative genes. Critically, upregulation of the NF-κB the pathway is a hallmark of ABC-type DLBCL and has been shown to be necessary for survival, and is caused by several different mutations at different levels within the pathway. Recent work has revealed the critical importance of a new class of small RNA molecules, namely microRNAs, in gene regulation. Of these, microRNA-146a (miR-146a) was discovered as an NF-κB induced microRNA that plays a role as a negative feedback regulator of this pathway by targeting adaptor proteins. To further characterize miR-146a, mice deficient for this miRNA were created, and were found to develop lymphadenopathy, splenomegaly, and myeloid proliferation. As expected, immune cells in these mice have an upregulated NF-κB pathway and many of the phenotypes can be ameliorated by inhibition of the NF-κB pathway. Importantly, a significant proportion of the animals develop B-cell lymphoma at older ages. In this study, we examined the role of miR-146a in the development of malignancy in B-cells. To accelerate the role of miR-146a in tumor formation we overlaid the miR-146a deficient allele onto the Eμ-Myc like mouse model. Eμ-Myc mice develop tumors on average by 14weeks of age. The transgenic status of animals was verified by genotyping, RNA and protein expression analyses. miR-146a sufficient and deficient animals on the Eμ-Myc background were followed for tumor latency by peripheral blood analysis and careful physical examination. Based on approved humane criteria for animal discomfort, animals were sacrificed and hematopoietic tissue was harvested for analysis. Mice deficient for miR-146a had a statistically reduced survival in comparison with miR-146a sufficient animals with a p-value of .0098 (Kaplan Meir survival analysis). Complete Blood Count of animals at time of death revealed an increase leukemia presentation in the miR-146a deficient background. FACS analysis of tumor tissue from both groups revealed an increase in the number of IgM positive tumors in the miR-146a-deficient background indicating skewing towards more mature B cell neoplasms when miR-146a is lacking. Lineage analysis of tumors verified them to be of B cell origin although a subset of miR-146a sufficient tumors had higher numbers of infiltrating myeloid cells compared to deficient animals. Furthermore, histologic analysis of hematopoietic organs showed that while infiltration remained similar in kidneys and liver, more spleens in the miR-146a deficient background tended to be less involved. Our extensive histopathologic and immunophenotypic analyses indicate that miR-146a deficiency drives a more aggressive malignant phenotype in the B-cell lineage. In keeping with this, our profiling studies of human DLBCL suggest that a subset of DLBCL show decreased expression of miR-146a. We are currently examining the status of NF-κB in the murine tumors and using high throughput sequencing approaches to delineate gene expression differences between miR-146a sufficient and deficient tumors. We anticipate the discovery of novel gene targets of miR-146a and expect that these studies will lead to improved diagnostic and therapeutic options for patients of B-cell malignancies. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Immunoglobulin recombinase gene activity is modulated reciprocally by interleukin 7 and CD19 in B cell progenitors.

1995 ◽  
Vol 182 (4) ◽  
pp. 973-982 ◽  
Author(s):  
L G Billips ◽  
C A Nuñez ◽  
F E Bertrand ◽  
A K Stankovic ◽  
G L Gartland ◽  
...  
Keyword(s):  
Bone Marrow ◽  
B Cell ◽  
Terminal Deoxynucleotidyl Transferase ◽  
Immunoglobulin Gene ◽  
B Cell Differentiation ◽  
Interleukin 7 ◽  
Cross Linkage ◽  
Recombinase Gene ◽  
Rag 1 ◽  
B Lineage

Bone marrow stromal cells promote B cell development involving recombinase gene-directed rearrangement of the immunoglobulin genes. We observed that the stromal cell-derived cytokine interleukin 7 (IL-7) enhances the expression of CD19 molecules on progenitor B-lineage cells in human bone marrow samples and downregulates the expression of terminal deoxynucleotidyl transferase (TdT) and the recombinase-activating genes RAG-1 and RAG-2. Initiation of the TdT downregulation on the first day of treatment, CD19 upregulation during the second day, and RAG-1 and RAG-2 downmodulation during the third day implied a cascade of IL-7 effects. While CD19 ligation by divalent antibodies had no direct effect on TdT or RAG gene expression, CD19 cross-linkage complete blocked the IL-7 downregulation of RAG expression without affecting the earlier TdT response. These results suggest that signals generated through CD19 and the IL-7 receptor could modulate immunoglobulin gene rearrangement and repertoire diversification during the early stages of B cell differentiation.

scholarly journals Human bone marrow-derived mesenchymal stem cell gene expression patterns vary with culture conditions

2013 ◽  
Vol 48 (2) ◽  
pp. 107 ◽  
Author(s):  
Myoung Woo Lee ◽  
Dae Seong Kim ◽  
Keon Hee Yoo ◽  
Hye Ryung Kim ◽  
In Keun Jang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bone Marrow ◽  
Stem Cell ◽  
Mesenchymal Stem Cell ◽  
Expression Patterns ◽  
Culture Conditions ◽  
Gene Expression Patterns ◽  
Cell Gene Expression ◽  
Cell Gene ◽  
Stem Cell Gene

Meta-Transcriptome of Bone Marrow Stem Cells Demonstrates Platform and Lab Dependant Variability in Gene Expression and Reveals a Novel Set of Enriched Genes.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 4189-4189
Author(s):  
Davendra Sohal ◽  
Andrew Yeatts ◽  
Joanna Opalinska ◽  
Li Zhou ◽  
Perry Pahanish ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Bone Marrow ◽  
Expression Patterns ◽  
Bone Marrow Stem Cells ◽  
Human Bone ◽  
Human Bone Marrow ◽  
Gene Expression Patterns ◽  
Expression Studies ◽  
Gene Expression Studies

Abstract While microarray analysis of global gene expression yields enormous amounts of data, there are concerns about standardization and validity of findings. Consequently, we wanted to determine the variability in gene expression studies of human bone marrow in the literature and study the factors that account for these differences. We also wanted to determine if certain genes were consistently and differentially enriched in human bone marrow stem cells. A total of 64 individual datasets were collected from gene expression omnimbus (GEO) database for our analysis (2001–2006). Most of the datasets had been used as controls in studies of hematological malignancies. 13 datasets were hybridized to the Affymetrix U95 chip, 38 analyzed by the Affymetrix human U133A chip and 13 by the U133 plus 2.0 platform. RNA for these studies was derived from purified normal CD34+ cells in 48 cases and from unsorted normal bone marrow mononuclear cells in 16 cases. To merge data from different platforms, we converted individual probe Sequence_ids to RefSeq gene IDs and analyzed them by SAS (SAS Institute, Cary, NC) and Arrayassist software package (Stratagene©). A total of 23686 unique gene IDs were obtained for analysis after the data were normalized, and a KNN algorithm was used to fill the gaps in the data. Our results reveal that there is marked variability in gene expression patterns in this cohort. The data sets clustered together primarily on the basis of the laboratory that performed the assays. (Hierarchical clustering based on average Euclidean distances). Clustering was further defined by the type of chip/platform used for the analysis. Interestingly, the similarity between CD34+ sorted and ununsorted whole BM samples was greater than interplatform similarity between the same phenotypes of cells examined. Notwithstanding the variability in gene expression, there were a novel set of genes that were differentially enriched in all 64 samples. These genes included transcription factors (Kruppel like factor 6), translational proteins (eukaryotic translation initiation factor 4A, isoform 1, ribosomal proteins) and other proteins not previously implicated in hematopoeisis (guanine nucleotide binding protein (GNAS), Calnexin, HLA associated proteins, dUTP pryophosphatase etc.) Mouse homologues of several of these proteins were found to be overexpressed in a previous well respected study of mouse hematopoeitic stem cells (Ramalho-Santos et al, Science2002;298(5593)). To further validate these findings, we performed gene expression array analysis on primary bone marrow cells using a completely different platform (Nimblegen 37K arrays) and demonstrated enrichment of majority of these genes. Thus, we provide a blueprint for conducting similar meta-analysis across various microarray platforms and our findings disclose tremendous platform and lab dependant differences in microarray gene expression patterns. In spite of this variability, data mining of discrete datasets can be a useful tool for gene discovery. Finally, we are in the process of constructing a publicly searchable database of normal human bone marrow gene expression which may serve as a source of controls for gene expression studies of hematopoeitic malignancies by various investigators.

Molecular Basis of Proliferation/Survival and Migration of CLL in Peripheral Blood, Bone Marrow and Lymph Nodes

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 546-546
Author(s):  
Amit K Mittal ◽  
Javeed Iqbal ◽  
Tara Marie Nordgren ◽  
Margaret Moragues ◽  
R. Gregory Bociek ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bone Marrow ◽  
B Cell ◽  
Chemokine Receptors ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Bcr Signaling ◽  
And Migration

Abstract B-cell chronic lymphocytic leukemia (CLL) is a heterogenous and incurable B-cell malignancy. CLL cells migrate and accumulate in different sites including the peripheral blood (PB), bone marrow (BM) and lymph nodes (LN) in vivo, but undergo apoptosis in vitro. Therefore, we hypothesized that CLL cells at these sites are different and receive different microenvironmental signals that regulate their proliferation/survival and migration. Most reports on the microenvironmental influence on CLL cells have used in vitro models consisting of stromal and CLL cells. However, in this study, to better understand the influence of site-specific microenvironments in vivo, gene expression patterns of CLL cells obtained from PB, BM and LN were investigated. CLL cells were isolated from patients’ PB (PB-CLL, n= 20), BM (BM-CLL, n=14) and LN (LN-CLL, n=15) and used to determine the gene expression patterns by microarray analysis. In addition, we also included PB-CLL cases from our previous study (n=40) to further validate the findings of this study. Significant Analyses of Microarray (SAM) revealed differential expression of more than 500 genes among these three sites. To understand the potential roles of these differentially-expressed genes and their association with relevant functional pathways in CLL, Gene Set Enrichment Analysis (GSEA) was performed. The validation of pathway specific genes was further confirmed by quantitative real time PCR. Among the pathways identified, the most active pathways associated with the migration and proliferation/survival of CLL cells, namely chemokine-signaling, BCR signaling, BAFF/APRIL-signaling, and NFκB-signaling pathways, were selected for further analyses. We hypothesized that chemokines and their receptors mediate the migration of CLL cells between PB and LN or BM, and that molecules of the BCR, BAFF/APRIL and NFκB pathways regulate proliferation/survival. To determine the role of chemokines and their receptors in CLL cell migration, we studied the expression of 52 chemokine/chemokine receptors and found that PB-CLL cells significantly (p<0.005) overexpressed CXCR4 and CCR7 compared to BM-CLL and LN-CLL cells. The ligands CCL21 and CXCL13 were significantly overexpressed (p<0.005 and p<0.01 respectively) in LN-CLL. These results indicate that PB-CLL cells express distinct chemokine receptors which may lead them to home to BM or LN and receive stimuli to form proliferation centers. Based on GSEA analysis, the stimuli for proliferation/survival for CLL cells in the LN and BM are provided by Syk and Btk (BCR signaling), BAFF and TRAF2 (BAFF/APRIL signaling), and several targets of the NFκB pathways. Syk and Btk were significantly overexpressed in LN-CLL (p<0.05) and PB-CLL (p<0.005) compared to BM-CLL, with the highest expression in LN-CLL, suggesting chronic activation of CLL cells in lymph node. Similarly, BAFF and TRAF2 were significantly overexpressed (p<0.03) in LN-CLL compared to PB-CLL and BM-CLL. Furthermore, the NFκB pathway, which is important for the proliferation and survival, also showed distinct association in different CLL-cell compartments. The RELA, NFκB1, NFκB2, TNFAIP3 and NFκB regulators such as NFκBIA, NFκBIE were also significantly (p<0.01) overexpressed in PB-CLL and BM-CLL compared to LN-CLL with highest expression in BM-CLL. Whereas few NFκB associated genes such as NFκB1L1 and RelB were significantly (p<0.02) expressed in LN-CLL cells. Thus, differentially-expressed NFkB genes among PB-CLL, BM-CLL and LN-CLL cells indicate that these different CLL cells utilize different NFκB molecules for proliferation/survival. Together, our results show that CLL cells from different in vivo microenvironments such as PB, BM and LN exhibit differential gene expression patterns, and many of the genes are involved in regulation of migration and proliferation/survival. Furthermore, LN-CLL cells expressing chemokine ligands, BCR, BAFF and NFκB signaling molecules attract other cells including more CLL cells to form an optimal microenvironment which provide prosurvival and proliferative signals to CLL cells.

scholarly journals Genetic Subtypes of Human Pediatric ALLs Show Gene Expression Differences That Parallel Those Observed in Mouse B1 and B2 Progenitors, Suggesting Divergent Developmental Origins

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1741-1741
Author(s):  
Scott C. Kogan ◽  
Huimin Geng ◽  
Ritu Roy ◽  
Encarnacion Montecino-Rodriguez ◽  
Coline M Gaillard ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cells ◽  
B Cell ◽  
Conflicts Of Interest ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Gene Expression Patterns ◽  
Developmental Origins ◽  
Rna Seq ◽  
Pediatric All

Abstract The presence in mice of progenitors that can give rise selectively to B-1 or B-2 B-cells raised the possibility that B-lymphoid neoplasms may have varied developmental origins. Prior work demonstrated that murine B-1 and B-2 progenitors of mice can both be transformed by the BCR-ABL1 oncogene and that leukemias derived from B-1 progenitors initiated more quickly than leukemias derived from B-2 progenitors (J Immunol. 2014;192:5171-8). We have recently profiled the gene expression patterns of murine B-1 and B-2 progenitors using RNA-seq and have applied the observed divergences in gene expression pattern to investigate whether varied human pediatric B-cell acute lymphoblastic leukemias (B-ALLs) might arise from human B-cell progenitors with characteristics paralleling either mouse B-1 or B-2 progenitors. Underlying these analyses is the concept that pediatric ALLs might arise from progenitors present during development that may not persist into adulthood. In order to assess our hypothesis that human pediatric B-ALLs have common features with either mouse B-1 progenitors or mouse B-2 progenitors, we examined whether gene expression differences observed in the mouse cells could be used to segregate human pediatric ALLs into B-1 progenitor-like or B-2 progenitor-like subsets. We used two different computational approaches to compare gene expression of mouse B-1 and B-2 progenitors to 126 human pediatric B-ALLs (St Jude ALLs: GSE26281, JCI 2013 123:3099-3111). In the first approach, we identified 327 genes that varied between mouse B-1 and B-2 progenitors derived from mice of varied ages (embryonic day 15, post-natal day 1, post-natal day 2, week 9 and week 11 animals). We were able to map 207 of these genes onto probes for human orthologs in the St Jude ALL gene expression microarray dataset. When multiple probes for a gene were present in the human array, the most variable probe was selected for analysis. The human ALLs were analyzed by unsupervised hierarchical clustering using these 207 genes. Of interest, when examining the first bifurcation of the unsupervised clustering diagram, ETV6-RUNX1 leukemias clustered in the same fork as the TCF3-PBX1 leukemias, whereas Hyperdiploid B-ALLs clustered in the same fork as most of the MLL leukemias. Further analysis identified 58 genes that could be used to score the human leukemias as B-1 progenitor-like and B-2 progenitor-like with a Z-score. Examination of the resulting scores showed that TCF3-PBX1 and ETV6-RUNX1 leukemias scored as the most similar to mouse B-1 progenitors, whereas hyperdiploid and MLL ALLs appeared predominantly B-2 like. In our second analytical approach, we identified 574 genes that showed at least a 2 fold difference and a p-value <0.001 in gene expression between the B-1 and B-2 progenitor subsets derived from embryonic day 15 and post-natal day 2 animals and could also be mapped onto the St. Jude ALL microarray data. From these 574 genes, we removed genes that were expressed at very low levels (at least one RNA-seq read count of 0), and selected genes previously identified as being expressed in B-cells by ImmGen (J Immunol. 2011 186:3047-57). This allowed us to identify 76 genes with increased expression in mouse B-1 progenitors and 77 genes with increased expression in mouse B-2 progenitors. Then we applied those 153 mouse B1- or B2-progenitor gene signatures in examining the expression in human ALLs using a Baysian predictor. Interestingly, this algorithm also classified human TCF3-PBX1 and ETV6-RUNX1 leukemias as B-1 progenitor-like and Hyperdiploid and MLL leukemias as B-2 progenitor-like. Using the same approach, we examined two additional human pediatric ALL datasets (COG P9906 ALLS: GSE28460, Blood 2010 116: 4874-4884 & COALL/DCOG ALLS: GSE13351, Lancet Oncol. 2009 10(2): 125-134). These added analyses supported our conclusion that different genetic sub-types of human pediatric ALL have gene expression patterns that parallel features of mouse B-1 or B-2 progenitors. Additional studies are underway to further assess whether human ALLs may be derived from B-1 like or B-2 like progenitors and to examine whether there may be a biological basis to use differences in cell of origin to inform future therapy. This work was supported by R21-CA173028 from the National Cancer Institute. Disclosures No relevant conflicts of interest to declare.

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