scholarly journals Systematic and Cell Type-Specific Telomere Length Changes in Subsets of Lymphocytes

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Jue Lin ◽  
Joshua Cheon ◽  
Rashida Brown ◽  
Michael Coccia ◽  
Eli Puterman ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
B Cells ◽  
Telomere Length ◽  
Cell Types ◽  
Cell Type ◽  
Peripheral Blood Mononuclear ◽  
Potential Biomarker ◽  
Cell Type Specific ◽  
Length Changes

Telomeres, the protective DNA-protein complexes at the ends of linear chromosomes, are important for genome stability. Leukocyte or peripheral blood mononuclear cell (PBMC) telomere length is a potential biomarker for human aging that integrates genetic, environmental, and lifestyle factors and is associated with mortality and risks for major diseases. However, only a limited number of studies have examined longitudinal changes of telomere length and few have reported data on sorted circulating immune cells. We examined the average telomere length (TL) in CD4+, CD8+CD28+, and CD8+CD28− T cells, B cells, and PBMCs, cross-sectionally and longitudinally, in a cohort of premenopausal women. We report that TL changes over 18 months were correlated among these three T cell types within the same participant. Additionally, PBMC TL change was also correlated with those of all three T cell types, and B cells. The rate of shortening for B cells was significantly greater than for the three T cell types. CD8+CD28− cells, despite having the shortest TL, showed significantly more rapid attrition when compared to CD8+CD28+ T cells. These results suggest systematically coordinated, yet cell type-specific responses to factors and pathways contribute to telomere length regulation.

scholarly journals Th2 Cytokine Modulates Herpesvirus Reactivation in a Cell Type Specific Manner

2021 ◽  
Author(s):  
Guoxun Wang ◽  
Christina Zarek ◽  
Tyron Chang ◽  
Lili Tao ◽  
Alexandria Lowe ◽  
...  
Keyword(s):  
B Cells ◽  
Cell Types ◽  
The Body ◽  
Receptor Expression ◽  
Conditional Knockout ◽  
Interleukin 4 ◽  
Virus Reactivation ◽  
Cell Type ◽  
Murine Gammaherpesvirus ◽  
Cell Type Specific

Gammaherpesviruses, such as Epstein-Barr virus (EBV), Kaposi’s sarcoma associated virus (KSHV), and murine γ-herpesvirus 68 (MHV68), establish latent infection in B cells, macrophages, and non-lymphoid cells, and can induce both lymphoid and non-lymphoid cancers. Research on these viruses has relied heavily on immortalized B cell and endothelial cell lines. Therefore, we know very little about the cell type specific regulation of virus infection. We have previously shown that treatment of MHV68-infected macrophages with the cytokine interleukin-4 (IL-4) or challenge of MHV68-infected mice with an IL-4-inducing parasite leads to virus reactivation. However, we do not know if all latent reservoirs of the virus, including B cells, reactivate the virus in response to IL-4. Here we used an in vivo approach to address the question of whether all latently infected cell types reactivate MHV68 in response to a particular stimulus. We found that IL-4 receptor expression on macrophages was required for IL-4 to induce virus reactivation, but that it was dispensable on B cells. We further demonstrated that the transcription factor, STAT6, which is downstream of the IL-4 receptor and binds virus gene 50 N4/N5 promoter in macrophages, did not bind to the virus gene 50 N4/N5 promoter in B cells. These data suggest that stimuli that promote herpesvirus reactivation may only affect latent virus in particular cell types, but not in others. Importance Herpesviruses establish life-long quiescent infections in specific cells in the body, and only reactivate to produce infectious virus when precise signals induce them to do so. The signals that induce herpesvirus reactivation are often studied only in one particular cell type infected with the virus. However, herpesviruses establish latency in multiple cell types in their hosts. Using murine gammaherpesvirus-68 (MHV68) and conditional knockout mice, we examined the cell type specificity of a particular reactivation signal, interleukin-4 (IL-4). We found that IL-4 only induced herpesvirus reactivation from macrophages, but not from B cells. This work indicates that regulation of virus latency and reactivation is cell type specific. This has important implications for therapies aimed at either promoting or inhibiting reactivation for the control or elimination of chronic viral infections.

scholarly journals High Dimensional Tissue-Based Spatial Analysis of the Tumor Microenvironment of Follicular Lymphoma Reveals Unique Immune Niches inside Malignant Follicles

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 17-18
Author(s):  
Jose C Villasboas ◽  
Patrizia Mondello ◽  
Angelo Fama ◽  
Melissa C. Larson ◽  
Andrew L. Feldman ◽  
...  
Keyword(s):  
T Cells ◽  
Spatial Distribution ◽  
T Cell ◽  
B Cells ◽  
Research Funding ◽  
Memory T Cells ◽  
Cell Types ◽  
T Cell Subsets ◽  
Cell Contact ◽  
Private Company

Background The importance of the immune system in modulating the trajectory of lymphoma outcomes has been increasingly recognized. We recently showed that CD4+ cells are associated with clinical outcomes in a prospective cohort of almost 500 patients with follicular lymphoma (FL). Specifically, we showed that the absence of CD4+ cells inside follicles was independently associated with increased risk of early clinical failure. These data suggest that the composition, as well as the spatial distribution of immune cells within the tumor microenvironment (TME), play an important role in FL. To further define the architecture of the TME in FL we analyzed a FL tumor section using the Co-Detection by Indexing (CODEX) multiplex immunofluorescence system. Methods An 8-micron section from a formalin-fixed paraffin-embedded block containing a lymph node specimen from a patient with FL was stained with a cocktail of 15 CODEX antibodies. Five regions of interest (ROIs) were imaged using a 20X air objective. Images underwent single-cell segmentation using a Unet neural network, trained on manually segmented cells (Fig 1A). Cell type assignment was done after scaling marker expression and clustering using Phenograph. Each ROI was manually masked to indicate areas inside follicles (IF) and outside follicles (OF). Relative and absolute frequencies of cell types were calculated for each region. Cellular contacts were measured as number and types of cell-cell contacts within two cellular diameters. To identify proximity communities, we clustered cells based on number and type of neighboring masks using Phenograph. The number of cell types and cellular communities were calculated inside and outside follicles after adjustment for total IF and OF areas. The significance of cell contact was measured using a random permutation test. Results We identified 13 unique cell subsets (11 immune, 1 endothelial, 1 unclassified) in the TME of our FL section (Fig. 1A). The unique phenotype of each subset was confirmed using a dimensionality reduction tool (t-SNE). The global composition of the TME varied minimally across ROIs and consisted primarily of B cells, T cells, and macrophages subsets - in decreasing order of frequency. Higher spatial heterogeneity across ROIs was observed in the frequency of T cell subsets in comparison to B cells subsets. Inspecting the spatial distribution of T cell subsets (Fig. 1B), we observed that cytotoxic T cells were primarily located in OF areas, whereas CD4+ T cells were found in both IF and OF areas. Notably, the majority of CD4+ T cells inside the follicles expressed CD45RO (memory phenotype), while most of the CD4+ T cells outside the follicles did not. Statistical analysis of the spatial distribution of CD4+ memory T cell subsets confirmed a significant increase in their frequency inside follicles compared to outside (20.4% vs 11.2%, p < 0.001; Fig. 1D). Cell-cell contact analysis (Fig 1C) showed increased homotypic contact for all cell types. We also found a higher frequency of heterotypic contact between Ki-67+CD4+ memory T cells and Ki-67+ B cells. Pairwise analysis showed these findings were statistically significant, indicating these cells are organized in niches rather than randomly distributed across image. Analysis of cellular communities (Fig. 1C) identified 13 niches, named according to the most frequent type of cell-cell contact. All CD4+ memory T cell subsets were found to belong to the same neighborhood (CD4 Memory community). Analysis of the spatial distribution of this community confirmed that these niches were more frequently located inside follicles rather than outside (26.3±4% vs 0.004%, p < 0.001, Fig. 1D). Conclusions Analysis of the TME using CODEX provides insights on the complex composition and unique architecture of this FL case. Cells were organized in a pattern characterized by (1) high degree of homotypic contact and (2) increased heterotypic interaction between activated B cells and activated CD4+ memory T cells. Spatial analysis of both individual cell subsets and cellular neighborhoods demonstrate a statistically significant increase in CD4+ memory T cells inside malignant follicles. This emerging knowledge about the specific immune-architecture of FL adds mechanistic details to our initial observation around the prognostic value of the TME in this disease. These data support future studies using modulation of the TME as a therapeutic target in FL. Figure 1 Disclosures Galkin: BostonGene: Current Employment, Patents & Royalties. Svekolkin:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Postovalova:BostonGene: Current Employment, Current equity holder in private company. Bagaev:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Ovcharov:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Varlamova:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Novak:Celgene/BMS: Research Funding. Witzig:AbbVie: Consultancy; MorphSys: Consultancy; Incyte: Consultancy; Acerta: Research Funding; Karyopharm Therapeutics: Research Funding; Immune Design: Research Funding; Spectrum: Consultancy; Celgene: Consultancy, Research Funding. Nowakowski:Nanostrings: Research Funding; Seattle Genetics: Consultancy; Curis: Consultancy; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other; Kymera: Consultancy; Denovo: Consultancy; Kite: Consultancy; Celgene/BMS: Consultancy, Research Funding; Roche: Consultancy, Research Funding; MorphoSys: Consultancy, Research Funding. Cerhan:BMS/Celgene: Research Funding; NanoString: Research Funding. Ansell:Trillium: Research Funding; Takeda: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Bristol Myers Squibb: Research Funding; AI Therapeutics: Research Funding; ADC Therapeutics: Research Funding.

Structure and functions of T-cell immunoglobulin-domain and mucin- domain protein 3 in cancer

2021 ◽  
Vol 28 ◽  
Author(s):  
Xinjie Lu
Keyword(s):  
T Cells ◽  
T Cell ◽  
Cancer Immunotherapy ◽  
Intracellular Signaling ◽  
Checkpoint Inhibitors ◽  
Cell Types ◽  
Structural Features ◽  
Type I ◽  
Potential Biomarker ◽  
Tim Proteins

Background: T-cell immunoglobulin (Ig)-domain and mucin-domain (TIM) proteins represent a family of receptors expressed on T-cells that play essential cellular immunity roles. The TIM proteins span across the membrane belonging to type I transmembrane proteins. The N terminus contains an Ig-like V-type domain and a Ser/Thr-rich mucin stalk as a co-inhibitory receptor. The C-terminal tail oriented toward the cytosol predominantly mediates intracellular signaling. Methods: This review discusses the structural features and functions of TIM-3, specifically on its role in mediating immune responses in different cell types, and the rationale for TIM-3-targeted cancer immunotherapy. Results: TIM-3 has gained significant importance to be a potential biomarker in cancer immunotherapy. It has been shown that blockade with checkpoint inhibitors promotes anti-tumor immunity and inhibits tumor growth in several preclinical tumor models. Conclusion: TIM-3 is an immune regulating molecule expressed on several cell types, including IFNγ-producing T-cells, FoxP3+ Treg cells, and innate immune cells. The roles of TIM-3 in immunosuppression support its merit as a target for cancer immunotherapy.

A single-cell map for the transcriptomic signatures of peripheral blood mononuclear cells in end-stage renal disease

2019 ◽  
Author(s):  
Ting Luo ◽  
Fengping Zheng ◽  
Kang Wang ◽  
Yong Xu ◽  
Huixuan Xu ◽  
...  
Keyword(s):  
Single Cell ◽  
End Stage Renal Disease ◽  
Mononuclear Cells ◽  
Cell Types ◽  
Cell Type ◽  
Peripheral Blood Mononuclear ◽  
Blood Mononuclear Cells ◽  
Cell Type Specific ◽  
Stage Renal Disease ◽  
End Stage

Abstract Background Immune aberrations in end-stage renal disease (ESRD) are characterized by systemic inflammation and immune deficiency. The mechanistic understanding of this phenomenon remains limited. Methods We generated 12 981 and 9578 single-cell transcriptomes of peripheral blood mononuclear cells (PBMCs) that were pooled from 10 healthy volunteers and 10 patients with ESRD by single-cell RNA sequencing. Unsupervised clustering and annotation analyses were performed to cluster and identify cell types. The analysis of hallmark pathway and regulon activity was performed in the main cell types. Results We identified 14 leukocytic clusters that corresponded to six known PBMC types. The comparison of cells from ESRD patients and healthy individuals revealed multiple changes in biological processes. We noticed an ESRD-related increase in inflammation response, complement cascade and cellular metabolism, as well as a strong decrease in activity related to cell cycle progression in relevant cell types in ESRD. Furthermore, a list of cell type-specific candidate transcription factors (TFs) driving the ESRD-associated transcriptome changes was identified. Conclusions We generated a distinctive, high-resolution map of ESRD-derived PBMCs. These results revealed cell type-specific ESRD-associated pathways and TFs. Notably, the pooled sample analysis limits the generalization of our results. The generation of larger single-cell datasets will complement the current map and drive advances in therapies that manipulate immune cell function in ESRD.

scholarly journals Cell type–specific actions of Bcl11b in early T-lineage and group 2 innate lymphoid cells

2019 ◽  
Vol 217 (1) ◽  
Author(s):  
Hiroyuki Hosokawa ◽  
Maile Romero-Wolf ◽  
Qi Yang ◽  
Yasutaka Motomura ◽  
Ditsa Levanon ◽  
...  
Keyword(s):  
T Cells ◽  
Target Genes ◽  
Cell Types ◽  
Innate Lymphoid Cells ◽  
Lymphoid Cells ◽  
Cell Type ◽  
Distal Enhancer ◽  
Distinct Cell Type ◽  
Cell Type Specific ◽  
Group 2

The zinc finger transcription factor, Bcl11b, is expressed in T cells and group 2 innate lymphoid cells (ILC2s) among hematopoietic cells. In early T-lineage cells, Bcl11b directly binds and represses the gene encoding the E protein antagonist, Id2, preventing pro-T cells from adopting innate-like fates. In contrast, ILC2s co-express both Bcl11b and Id2. To address this contradiction, we have directly compared Bcl11b action mechanisms in pro-T cells and ILC2s. We found that Bcl11b binding to regions across the genome shows distinct cell type–specific motif preferences. Bcl11b occupies functionally different sites in lineage-specific patterns and controls totally different sets of target genes in these cell types. In addition, Bcl11b bears cell type–specific post-translational modifications and organizes different cell type–specific protein complexes. However, both cell types use the same distal enhancer region to control timing of Bcl11b activation. Therefore, although pro-T cells and ILC2s both need Bcl11b for optimal development and function, Bcl11b works substantially differently in these two cell types.

Longitudinal Analysis Reveals Telomere Length Maintenance In CLL B-Cells But Marked Erosion In CLL Patient T-Cells

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 1617-1617
Author(s):  
Ceri Jones ◽  
Thet Lin ◽  
Guy Pratt ◽  
Chris Fegan ◽  
Duncan Baird ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
B Cells ◽  
Telomere Length ◽  
Erosion Rate ◽  
B Lymphocyte ◽  
Cell Populations ◽  
Aggressive Disease ◽  
Telomere Dynamics

Abstract Telomere length (TL) is a prognostic factor in Chronic Lymphocytic Leukemia (CLL) with short TL being a predictor of time to first treatment, progression-free survival and overall survival. However, little is known about telomere dynamics through the course of the disease. Most studies conducted on CLL patients have measured TL in unselected peripheral blood mononuclear cell populations, often at a single time point. In this context, longitudinal analysis of TL is problematic as patients who undergo disease progression and/or treatment may have a significantly altered proportion of CLL cells in their peripheral blood compared to T-cells. In order to ensure that we specifically analyzed the TL of the tumor cells, we used fluorescence-activated cell sorting (FACS) to sort populations of CD19+CD5+ CLL B-cells and CD3+T-cells from samples taken from individual patients at different time points throughout their disease (n=30). We then performed high-resolution single telomere length analysis (STELA) on these sorted subsets of cells and analyzed their telomere dynamics over time (median follow up 69 months). We found a signifcant difference in the CLL B-cell TL (p=0.05) with a mean erosion rate of -52base pairs/year. TL change in the 18/30 patients who remained untreated at all time points was -51bp/year. In the 6/30 patients who received treatment following their initial TL measurements the mean TL change was -40bp/year. Finally, for 11/30 patients samples were only available in the post treatment setting, for these patients the TL change was lower at -29bp/year. The difference in TL erosion between these different groups was not statistically significant. These data shows that the TL erosion in CLL B-cells is modest and similar to that of an age-matched population (Steenstrup et al 2013). Furthermore, CLL B-cells showed no reduction in TL standard deviation signifying the maintenance of intraclonal diversity (p=0.78). In contrast to the modest changes in TL observed in the CLL B-cells, TL change in the T-cell populations were much more pronounced with mean change of -119bp/year (p=0.02). Furthermore, there was a trend towards increased erosion in the treated patient group when compared with the untreated group (-230bp/year vs -85bp/year, p=0.14) suggesting that therapy may have an impact on the composition of T-cell populations in treated CLL patients. In keeping with this notion, the T-cells derived from CLL patients showed a significant reduction in TL standard deviation (P=0.02), implying that the T-cell repertoire is significantly altered during the course of the disease. In conclusion, this study of TL in ex vivo CLL B-cell samples shows TL erosion during long-term follow-up that is comparable to that seen in non-leukemic leukocyte and lymphocyte samples (Lansdorp et al 1999). In keeping with a recent study, we showed that the erosion rate correlated with starting TL, with the longest telomeres showing the largest erosion and the shortest telomeres showing elongation (Rosenquist et al 2013). This implies that the radical telomere shortening observed in some CLL patients is an early disease event which is in keeping with our previous data demonstrating that a proportion of stage A patients possess very short dysfunctional telomeres (Lin et al 2010). Given that short TL is associated with an inferior clinical outcome, our data indicates that part of the explanation for the clinical heterogeneity seen in CLL may be telomere dependent whereby if the mutagenic event occurs in a B lymphocyte which already has shorter TL then a more aggressive disease occurs whereas if it occurs in a B lymphocyte with longer TL then the outcome is less aggressive disease. Finally, T-cells in CLL patients show markedly more TL erosion corroborating previous studies suggesting there is extensive and abnormal T-cell proliferation in CLL. Whether the CLL cells themselves are driving T-cell TL erosion is at present unknown. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Single-Cell RNA-Seq Reveals AML Cellular Hierarchies Relevant to Clinical Outcomes and Immunity

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 542-542
Author(s):  
Peter Van Galen ◽  
Volker Hovestadt ◽  
Marc Wadsworth II ◽  
Travis Hughes ◽  
Gabriel Kenneth Griffin ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
T Cell Activation ◽  
Cell Activation ◽  
Cell Types ◽  
Healthy Controls ◽  
Cell Type ◽  
Healthy Donors ◽  
Type Composition

Abstract Acute myeloid leukemia (AML) is a heterogeneous disease with functionally diverse cells. While primitive leukemia cells are thought to be responsible for clonal expansion, other cell types may play roles in immune evasion and paracrine signaling. To analyze the complex AML ecosystem, we developed a technology for high throughput single-cell RNA-sequencing (scRNA-seq) combined with single-cell genotyping to capture mutations in cancer driver genes. We used this technology to parse normal and malignant hematopoietic systems. We profiled 38,410 cells from bone marrow (BM) aspirates from five healthy donors and 16 AML patients that span different WHO subtypes and cytogenetic abnormalities. Within the normal donors, we identified 15 diverse hematopoietic cell types demarcated by established markers such as CD34 (HSC/Progenitors), CD14 (monocytes) and CD3 (T-cells), confirming expected differentiation trajectories. To systematically distinguish between malignant and normal cell types within tumors, we developed a machine learning classifier that integrated scRNA-seq and single-cell genotyping data. Malignant cells were classified into six types: HSC-like, progenitor-like, granulocyte macrophage progenitor (GMP)-like, promonocyte-like, monocyte-like and dendritic-like cells. Each cell type was represented by at least 1,000 cells and identified in at least ten patients. To assess the significance of these six malignant cell types, we estimated their abundance in an independent cohort of 179 AMLs that were analyzed by bulk RNA-seq (TCGA). We found that the cell type composition of a tumor closely correlates to its underlying genetic lesions. For example, RUNX1-RUNX1T1 translocations are associated with GMP-like cells and TP53 mutations with undifferentiated cells (P < 0.001). NPM1+FLT3-ITD mutated tumors are enriched for more primitive cells compared to NPM1+FLT3-TKD mutants, which may relate to the worse outcomes of patients with FLT3-ITD mutations. The correspondence between genetic lesions and tumor cell type composition can guide strategies for genotype-specific therapies that target appropriate cellular states. Further investigation of primitive cells showed that gene expression programs associated with stemness (e.g. EGR1, MSI2) are mutually exclusive with myeloid priming (e.g. MPO, ELANE) in primitive cells of healthy donors. In contrast, these programs are often co-expressed within the same individual AML cells. When we applied our single cell-derived gene signatures to the TCGA dataset, stratification of these bulk expression profiles showed that patients with HSC-like progenitors had significantly poorer outcomes than patients with GMP-like progenitors (P < 0.0001). Aberrant co-expression of stemness and myeloid programs may underlie simultaneous self-renewal and proliferation, and expression of myeloid priming factors may provide a therapeutic window to target primitive AML cells while sparing normal HSCs. Examination of T-cells in our single-cell dataset showed that AML patients have fewer CD8+ cytotoxic T-lymphocytes within the CD3+ T-cell compartment compared to healthy controls, which was validated by immunohistochemistry on BM core biopsies (69% in healthy controls vs. 54% in AML, P < 0.05). We observed increased CD25+FOXP3+ T-regulatory cells in AML patients (1.2% in healthy controls vs. 3.6% in AML, P < 0.001), indicating an immunosuppressive tumor environment. To investigate mechanisms of immunosuppression, we used a T-cell activation bioassay that reports Nuclear Factor of Activated T-cells (NFAT). We compared the immunosuppressive function of different AML cell types, and found that CD14+ monocyte-like cells most effectively inhibit T-cell activation (P < 0.0001). The malignant status of these differentiated AML cells was confirmed by genotyping, and they express multiple factors associated with immunosuppression and T-cell engagement, including TIM-3 (HAVCR2), HVEM (TNFRSF14), CD155 (PVR) and HLA-DR. These results suggest that AMLs can differentiate into monocyte-like cells that suppress T-cell activation. In conclusion, we use novel technologies to parse heterogeneous cell states within the AML ecosystem. Our findings nominate strategies for precision therapies targeting AML progenitors or immunosuppressive functions of their differentiated progeny. Disclosures Pozdnyakova: Promedior, Inc.: Consultancy. Lane:N-of-one: Consultancy; Stemline Therapeutics: Research Funding.

Significantly Shorter Telomeres in T-Cells of ZAP-70+/CD38+ Patients with Chronic Lymphocytic Leukemia (CLL): An Important Role of T-Cells in This Subgroup of CLL?.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 1120-1120
Author(s):  
Alexander Roeth ◽  
Dirk de Beer ◽  
Holger Nueckel ◽  
Ludger Sellmann ◽  
Ulrich Duehrsen ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
B Cells ◽  
Chronic Lymphocytic Leukemia ◽  
Telomere Length ◽  
Memory T Cells ◽  
Lymphocytic Leukemia ◽  
Healthy Individuals ◽  
Cell Numbers

Abstract BACKGROUND: In contrast to other B-cell neoplasias, chronic lymphocytic leukemia (CLL) is not only characterized by a clonal expansion of specific B-cells, but also by an increase in non-leukemic T-cells, most likely involved in sustaining the growth of the leukemic B-cell clone. Based on ZAP-70, CD38 and the IgVH mutation status, two prognostic groups of CLL patients can be identified. Our aim was to characterize the replicative histories of the B- and T-cells in the two groups of CLL patients compared to healthy individuals. PATIENTS and METHODS: Blood samples from 73 patients with CLL (ZAP-70−/CD38−: n = 29, ZAP-70+/CD38+: n = 30, ZAP-70/CD38 discordant: n = 14) were analyzed. The quantity and characteristics of the lymphocyte subsets was assessed by a cell counter and by immunophenotypic analysis. The replicative histories of naive and memory T-cells as well as B-cells was determined by measurements of telomere length in peripheral blood leukocytes of CLL patients and healthy individuals by automated multicolor flow-FISH. RESULTS: As expected, the average telomere length of the clonal B-cells was short. The telomere length was, however, significantly shorter for the ZAP-70+/CD38+ patient samples (2.46 ± 1.08 kb) than for the ZAP-70−/CD38− patient samples (5.06 ± 1.76 kb, p < 6.7 x 10−9). Interestingly, also the naive and memory T-cells from ZAP-70+/CD38+ CLL patients exhibited significantly shorter average telomere lengths (mean ± std: 4.85 ± 1.58 kb; 4.39 ± 1.09 kb) than T-cells from ZAP-70−/CD38− CLL patients (6.64 ± 1.72 kb, p < 2.2 x 10−4; 6.22 ± 1.5 kb, p < 7.4 x 10−6). These results are in line with the observed higher absolute T-cell numbers in the ZAP-70+/CD38+ CLL patients compared to ZAP-70−/CD38− CLL patients. Moreover, the average telomere loss in relation to time from primary diagnosis to sample date was higher for naive T-cells than memory T-cells in ZAP-70+/CD38+ patients (7.8 vs. 5.8 bp/month). When we compared the telomere length to age-related percentiles calculated from over 400 healthy individuals aged 0–102 years practically all telomere length values of the naive and memory T-cells from the ZAP-70+/CD38+ CLL patients fell below the 50th percentile, whereas the values of naive and memory T-cells from the ZAP-70−/CD38− CLL patients were within the normal distribution. CONCLUSIONS: We can confirm significantly shorter telomere length values for the B-cells of the ZAP-70+/CD38+ CLL patients. In addition, we can also demonstrate significantly shorter telomeres in T-cells of ZAP-70+/CD38+ CLL patients, which are below the 50th percentile compared to controls, and a higher telomere loss over time for naive T-cells of ZAP-70+/CD38+ CLL patients. As telomere length shortens approximately 50 to 100 bp per cell division the observed decrease in telomere length of the T-cells in ZAP-70+/CD38+ CLL patients equals to approximately 18 to 36 population doublings. This is by far more than expected by the slightly higher T-cell numbers in the peripheral blood. Our observations imply an extensive expansion of the T-cell compartment in ZAP-70+/CD38+ CLL patients and suggest an important role of T-cells in this subgroup of CLL patients.

Single Cell Network Profiling (SCNP) of IFN-α Signaling Pathways In Peripheral Blood Mononuclear Cells From Healthy Donors: Implications for Disease Characterization, Treatment Selection, and Drug Discovery

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 4867-4867
Author(s):  
Diane Longo ◽  
Erik Evensen ◽  
Wendy J. Fantl ◽  
Zoltan Pos ◽  
Francesco Marincola ◽  
...  
Keyword(s):  
T Cells ◽  
B Cells ◽  
Signaling Pathways ◽  
Intracellular Signaling ◽  
Mononuclear Cells ◽  
Cell Types ◽  
Employment Equity ◽  
Peripheral Blood Mononuclear ◽  
Healthy Donors ◽  
Equity Ownership

Abstract Abstract 4867 Background: The antiviral and antitumor effects of IFN-α, have been exploited for the treatment of viral infections such as hepatitis C (HCV) as well as for various malignancies, such as hairy cell leukemia and melanoma. However, widespread use of IFN-α for these and other indications is severely hampered by significant side effects which can have a major impact on patient quality of life. Thus, a greater understanding of intracellular signaling pathways regulated by IFN-α may guide in the selection of patients whose disease will have an optimal response with tolerable side effects to this cytokine. Specifically, the Signal Transducer and Activation of Transcription (Stat) transcription factors are known to play a critical role in transducing IFN-α mediated signals. Single cell network profiling (SCNP) is a multiparameter flow-cytometry based approach that can be used to simultaneously measure extracellular surface makers and intracellular signaling proteins in individual cells in response to externally added modulators. Here, we use SCNP to interrogate IFN-α signaling pathways in multiple cell subsets within peripheral blood mononuclear cells (PBMCs) from healthy donors. Objectives: This study was designed to apply SCNP to generate a map of IFN-α-mediated signaling responses, with emphasis on Stat proteins, in PBMCs from healthy donors. The data provides a reference for future studies using PBMCs from patient samples in which IFN-α-mediated signaling is aberrantly regulated. Methods: IFN-α-mediated signaling responses were measured by SCNP in PBMC samples from 12 healthy donors. PBMCs were processed for flow cytometry by fixation and permeabilization followed by incubation with fluorochrome-conjugated antibodies that recognize extracellular lineage markers and intracellular signaling molecules. The levels of several phospho-proteins (p-Stat1, p-Stat3, p-Stat4, p-Stat5, p-Stat6, and p-p38) were measured in multiple cell populations (CD14+ monocytes, CD20+ B cells, CD4+ CD3+ T cells, and CD4- CD3+ T cells) at 15 minutes, 1, 2 and 4 hours post IFN-α exposure. Results: The data revealed distinct phospho-protein activation patterns in different cell subsets within PBMCs in response to IFN-α exposure. For example, activation of p-Stat4 was detected in T cell subsets (both CD4+ and CD4- T cells), but not in monocytes or B cells. Such cell-type specific activation patterns likely play a key role in mediating specific functions within different cell types in response to IFN-α. Differences in the kinetics of activation by IFN-α for different phospho-proteins were also observed. The peak response for activation of p-Stat1, p-Stat3, and p-Stat5 was at 15 minutes in most of the cell types interrogated in this study, whereas for the activation of p-Stat4, p-Stat6, and p-p38 it was at 1 hr in the majority of cell types tested. The relationships between phospho-protein readouts in each cell subset were determined by calculating the Pearson correlation coefficients. For example, the activation of p-Stat1 and p-Stat5 at 15 minutes was positively correlated in both B cells and T cells. Conclusions: In this study, we have measured the activation of intracellular signaling proteins with emphasis on Stat transcription factors in PBMC subsets from healthy donors. We have analyzed the relationships between the activation states of phospho-proteins in the IFN-α signaling network. Characterization of IFN-α signaling pathways in samples from healthy donors has provided a network map that can be used as a reference for identifying alterations in IFN-α signaling that are the consequence of disease and/or therapeutic intervention. Future studies using SCNP to characterize IFN-α signaling pathways in PBMCs from patients with diseases such as viral infections or cancer may enable the optimization of IFN-α dosing and the identification of patient stratification biomarkers as well as the discovery of novel therapeutic agents. Disclosures: Longo: Nodality: Employment, Equity Ownership. Evensen: Nodality: Employment, Equity Ownership. Fantl: Nodality: Equity Ownership. Cesano: Nodality Inc.: Employment, Equity Ownership.

scholarly journals Cell-Type-Specific Activation and Repression of PU.1 by a Complex of Discrete, Functionally Specialized cis-Regulatory Elements

2010 ◽  
Vol 30 (20) ◽  
pp. 4922-4939 ◽  
Author(s):  
Mark A. Zarnegar ◽  
Jing Chen ◽  
Ellen V. Rothenberg
Keyword(s):  
T Cells ◽  
T Cell ◽  
Regulatory Element ◽  
Cell Lineage ◽  
Myeloid Cell ◽  
Regulatory Elements ◽  
Cell Type ◽  
Enhancer Activity ◽  
Cell Type Specific

ABSTRACT The transcription factor PU.1 is critical for multiple hematopoietic lineages, but different leukocyte types require strictly distinct patterns of PU.1 regulation. PU.1 is required early for T-cell lineage development but then must be repressed by a stage-specific mechanism correlated with commitment. Other lineages require steady, low expression or upregulation. Until now, only the promoter plus a distal upstream regulatory element (URE) could be invoked to explain nearly all Sfpi1 (PU.1) activation and repression, including bifunctional effects of Runx1. However, the URE is dispensable for most Sfpi1 downregulation in early T cells, and we show that it retains enhancer activity in immature T-lineage cells even where endogenous Sfpi1 is repressed. We now present evidence for another complex of conserved noncoding elements that mediate discrete, cell-type-specific regulatory features of Sfpi1, including a myeloid cell-specific activating element and a separate, pro-T-cell-specific silencer element. These elements yield opposite, cell-type-specific responses to Runx1. T-cell-specific repression requires Runx1 acting through multiple nonconsensus sites in the silencer core. These newly characterized sites recruit Runx1 binding in early T cells in vivo and define a functionally specific scaffold for dose-dependent, Runx-mediated repression.

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