Shannon Turley's research while affiliated with Centre d'Immunologie de Marseille-Luminy and other places

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Publications (18)


486 Combined PD-L1/TGFβ blockade allows expansion and differentiation of stem cell-like CD8 T cells in immune excluded tumors
  • Conference Paper
  • Full-text available

October 2023

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35 Reads

Journal for ImmunoTherapy of Cancer

Journal for ImmunoTherapy of Cancer

Katherine Williams

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Yagai Yang

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[...]

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Soren Muller

Background TGFβ signaling is associated with non-response to immune checkpoint blockade in patients with advanced metastatic cancers, particularly in patients with the immune excluded phenotype. While previous work demonstrates that converting tumors from excluded to inflamed phenotypes requires attenuation of PD-L1 and TGFβ signaling, the underlying cellular mechanisms remain largely unclear. Methods We performed single-cell RNA-seq (n=5 animals per treatment) on myeloid, stromal, tumor, and T cells, as well as TCR-seq (n=7 animals per treatment) on T cells from anti-PD-L1 and anti-TGFβ antibody-treated mice bearing subcutaneous EMT6 tumors on day 7 after initiation of treatment. We performed flow cytometry to characterize and quantify T cell subtypes from treated tumors (n>=10 animals per treatment). Furthermore, we measured T cell motility (n=8 animals per treatment) in a dorsal skinfold chamber from IFNγ-YFP reporter mice bearing EMT6-mApple tumor cells with anti-gp120 as control or anti-PD-L1 and anti-TFGβ combination treatment. To determine the impact of IFNγ response on the effect of combination treatment, we tracked tumor growth in mice with anti-IFNγ treated EMT6 tumors (n=10 per treatment) or with IFNGR1 KO EMT6 tumors (n=10 per group). Results We show that TGFβ and PD-L1 restrain intratumoral stem cell-like CD8 T cell (TSCL) expansion and maintain progenitor-exhausted and dysfunctional CD8 T cells. Upon combined TGFβ/PD-L1 blockade, TSCL expand and can differentiate into IFNγhi CD8 T effector cells that show enhanced motility and accumulate in the tumor microenvironment. Ensuing IFNγ signaling transforms myeloid, stromal, and tumor niches to yield a broadly immune-supportive ecosystem. Blocking IFNγ either through knockout of IFNGR1 in tumor cells or blocking IFNγ abolishes the effect of anti-PD-L1/TGFβ combination therapy. Conclusions Our data suggest that TGFβ works with PD-L1 to prevent TSCL expansion and replacement of exhausted CD8 T cells, thereby maintaining the T cell compartment in a dysfunctional state. Ethics Approval All animal activities in the research studies here presented were conducted under protocols approved by the Genentech Institutional Animal Care and Use Committee (IACUC).

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1434 TGFβ-dependent LRRC15 + myofibroblasts dictate the tumor fibroblast setpoint to promote cancer immunotherapy resistance

October 2023

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16 Reads

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1 Citation

Journal for ImmunoTherapy of Cancer

Journal for ImmunoTherapy of Cancer

Background Single cell transcriptomics has led to the generation of large-scale atlases to understand cellular heterogeneity across both healthy and diseased tissues at the highest resolution. Such atlases have allowed for in silico inferences of fibroblast ontogeny and function, but without in vivo substantiation are limited in their utility to inspire novel fibroblast-directed therapies to improve disease outcome. In cancer, single cell studies identified the emergence of a myofibroblast population, in both mice and humans, uniquely marked by a highly restricted leucine rich repeat containing protein, LRRC15. This cancer-associated myofibroblast population expresses a multitude of extracellular matrix (ECM) associated and immunosuppressive genes. Clinically, high expression of an LRRC15⁺ CAF gene signature in bulk RNAseq data from cancer patients correlated with lack of response to anti-programmed death ligand-1 (aPDL1) checkpoint blockade therapy. It remains unclear if LRRC15⁺ CAFs are the cause of this lack of response, or if they represent a read-out of tumor-intrinsic features driving the association. Also missing are in vivo substantiation of the cellular and molecular signals driving LRRC15⁺ myofibroblast development and the direct impact LRRC15⁺ CAFs have on anti-tumor immunity. Methods To address these gaps, we paired newly developed preclinical genetic tools in murine tumor models of pancreatic cancer with a large clinical dataset of human stromal cell-sorted expression data from 159 cancer patients across 13 tumor types to understand LRRC15⁺ CAF development and function. Results In mouse models of pancreatic cancer, we provide in vivo genetic evidence that TGFβR2 signaling in healthy Dermatopontin (DPT)⁺ universal fibroblasts is essential for development of tumor-associated LRRC15⁺ myofibroblasts. Analysis of tumors from 159 patients across 13 indications revealed a conserved axis from universal fibroblasts to LRRC15⁺ myofibroblasts. This axis is the predominant driver of fibroblast lineage diversity in human cancers. Using newly developed Lrrc15-Diphtheria toxin receptor knock-in mice to selectively deplete LRRC15⁺ CAFs, we show loss of this population markedly reduced total tumor fibroblast content and recalibrated the CAF composition towards universal fibroblasts. This, in turn, relieved direct suppression of tumor-infiltrating CD8⁺ T cells to enhance their effector function and significantly augmented tumor regression in response to anti-PDL1 immune checkpoint blockade. Conclusions Collectively, these findings demonstrate that TGFβ-dependent LRRC15⁺ CAFs dictate the tumor-fibroblast setpoint to promote tumor growth, directly suppress CD8⁺ T cell functionality, and limit responsiveness to checkpoint blockade.¹ Development of treatments that restore the homeostatic fibroblast setpoint by diminishing pro-disease LRRC15⁺ myofibroblasts may improve patient survival and response to immunotherapy. Reference • Krishnamurty AT, Shyer JA, Thai M, Gandham V, Buechler MB, Yang YA, Pradhan RN, Wang AW, Sanchez PL, Qu Y, Breart B, Chalouni C, Dunlap D, Ziai J, Elstrott J, Zacharias N, Mao W, Rowntree RK, Sadowsky J, Lewis GD, Pillow TH, Nabet BY, Banchereau R, Tam L, Caothien R, Bacarro N, Roose-Girma M, Modrusan Z, Mariathasan S, Muller S*, Turley SJ*. LRRC15⁺ myofibroblasts dictate the stromal setpoint to suppress tumor immunity. Nature, 2022; 611 :148–154


Lung-innervating neurons expressing Tmc3 can induce broncho-constriction and dilation with direct consequences for the respiratory cycle

August 2023

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32 Reads

Sensory neurons of the vagal ganglia (VG) innervate lungs and play a critical role in maintaining airway homeostasis. However, the specific VG neurons that innervate lungs, and the mechanisms by which these neurons sense and respond to airway insults, are not well understood. Here, we identify a subpopulation of lung-innervating VG neurons defined by their expression of Tmc3 . Single cell transcriptomics illuminated several subpopulations of Tmc3+ sensory neurons, revealing distinct Piezo2 - and Trpv1 -expressing subclusters. Furthermore, Tmc3 deficiency in VG neurons leads to global and subcluster specific transcriptional changes related to metabolic and ion channel function. Importantly, we show that broncho-constriction and dilation can be modulated through inhibition or activation of Tmc3+ VG neurons resulting in a decrease or increase of end-expiratory lung volume, respectively. Together, our data show that Tmc3 is a marker of lung-innervating neurons and may play a pivotal role in maintaining fundamental inspiratory and expiratory processes. Significance Harnessing the neuronal mechanisms that regulate lung function offers potential alternatives to existing corticosteroid treatment regimens for respiratory illness associated with acute bronchoconstriction including asthma, COPD, and emphysema. Our findings define Transmembrane channel-like 3 , Tmc3 , as a marker of lung-innervating sensory neurons, identify distinct subpopulations of Tmc3 + neurons with unique transcriptional profiles, and show that activation or inhibition of these neurons has a significant impact on airway function. Our work highlights potential avenues of novel targeted intervention in respiratory conditions driven by dysfunctional neuronal reflexes.


1450 TGFβ dependent LRRC15 + myofibroblasts dictate the tumor fibroblast setpoint to promote cancer immunotherapy resistance

November 2022

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9 Reads

Journal for ImmunoTherapy of Cancer

Journal for ImmunoTherapy of Cancer

Background Single cell transcriptomics has led to the generation of large-scale atlases to understand cellular heterogeneity across both healthy and diseased tissues at the highest resolution. Such atlases have allowed for in silico inferences of fibroblast ontogeny and function, but without in vivo substantiation are limited in their utility to inspire novel fibroblast-directed therapies to improve disease outcome. In cancer, single cell studies identified the emergence of a myofibroblast population, in both mice and humans, uniquely marked by a highly restricted leucine rich repeat containing protein, LRRC15. This cancer-associated myofibroblast population expresses a multitude of extracellular matrix (ECM) associated and immunosuppressive genes. Clinically, high expression of an LRRC15⁺ CAF gene signature in bulk RNAseq data from cancer patients correlated with lack of response to anti-programmed death ligand-1 (aPDL1) checkpoint blockade therapy. It remains unclear if LRRC15⁺ CAFs are the cause of this lack of response, or if they represent a read-out of tumor-intrinsic features driving the association. Also missing are in vivo substantiation of the cellular and molecular signals driving LRRC15⁺ myofibroblast development and the direct impact LRRC15⁺ CAFs have on anti-tumor immunity. Methods To address these gaps, we paired newly developed preclinical genetic tools in murine tumor models of pancreatic cancer with a large clinical dataset of human stromal cell-sorted expression data from 159 cancer patients across 13 tumor types to understand LRRC15⁺ CAF development and function. Results In mouse models of pancreatic cancer, we provide in vivo genetic evidence that TGFβR2 signaling in healthy Dermatopontin (DPT)⁺ universal fibroblasts is essential for development of tumor-associated LRRC15⁺ myofibroblasts. Analysis of tumors from 159 patients across 13 indications revealed a conserved axis from universal fibroblasts to LRRC15⁺ myofibroblasts. This axis is the predominant driver of fibroblast lineage diversity in human cancers. Using newly developed Lrrc15-Diphtheria toxin receptor knock-in mice to selectively deplete LRRC15⁺ CAFs, we show loss of this population markedly reduced total tumor fibroblast content and recalibrated the CAF composition towards universal fibroblasts. This, in turn, relieved direct suppression of tumor-infiltrating CD8⁺ T cells to enhance their effector function and significantly augmented tumor regression in response to anti-PDL1 immune checkpoint blockade. Conclusions Collectively, these findings demonstrate that TGFβ-dependent LRRC15⁺ CAFs dictate the tumor-fibroblast setpoint to promote tumor growth, directly suppress CD8⁺ T cell functionality, and limit responsiveness to checkpoint blockade. Development of treatments that restore the homeostatic fibroblast setpoint by diminishing pro-disease LRRC15⁺ myofibroblasts may improve patient survival and response to immunotherapy.


Determination of miRNA abundance thresholds
a, qPCR standard curve generated for 10 different miRNAs using synthetic RNA mimics. Plotted are copies of synthetic mature miRNA species input into qPCR reaction against the corresponding Ct value. Horizontal grey dashed line marks a Ct value of 28. b, Representative scatterplot of Ct values for two PC macrophage replicates against each other. c, Schematic diagram of the in vivo miRNA sensor assay. Lineage negative cells were isolated from CD45.1⁺ C57BL/6 mice, transduced with lentiviral-based sensors for miR-24-3p or miR-652-3p, or a control vector, and transplanted in to lethally irradiated CD45.2⁺ mice. After 8 weeks, cells from the spleen and peritoneal cavity were collected, stained for immune cell markers, and NGFR, and analyzed by flow cytometry. d, Representative flow plots showing logarithmic fluorescence intensities for NGFR and GFP from mice that received a sensor for the indicated microRNA. Values are the percent of NGFR⁺ GFP⁺ cells in the total population. Accompanying integer values for each plot represent MFI of GFP of all NGFR⁺ cells within the plot. e, Correlation between miRNA sensor suppression and miRNA expression in 7 cell types from the 11-cell set. Percent suppression was calculated as one minus the target miRNA GFP/NGFR median fluorescence intensity divided by the average of the same ratio for all 3 non-targeting control replicates in a given cell type. Error bars represent the standard error of the mean (miR-24-3p n = 2 mice; miR-652-3p n = 4 mice). f, Cumulative percent of total linear abundance within a given cell type compared to the number of miRNAs added in decreasing order of expression.
Source data
MiRNA abundance patterns in T cells and after perturbation
a, Pearson correlation of the 11-cell immune subset and lymph node stroma cells based on miRNA expression signatures. Expression data was filtered on miRNAs that are high-abundance (>32 AU) in at least one cell type. Only correlations between samples >0.7 are plotted. b,Htr2c read counts in ImmGen cis-Atlas samples. c, Percent linear abundance of the 15 most highly expressed miRNA and miRNA families in T cell subsets and DP thymocytes cells. Bars are shaded by Z-score value of the miRNA family across populations. d, miRNAs changing consistently in 3 or more perturbation conditions not highlighted in Fig. 2d. (limma two-sided unadjusted p<0.05, log2 FC > 1, and expression >4AU in perturbed or >32AU in steady-state population; n = 2 for all activated and stimulated populations except: NK.Sp = 5, NKT = 5, B1ab = 5).
Source data
Characterization of miRNA associate cis-elements
a, Table displaying the number of pre-miRNAs (having an expressed mature isoform) with promoter annotations after aggregation, broken down by TargetScan V7 conservation category. b, The number of annotation sources from compiled studies annotating a particular OCR as a promoter region. c, Table displaying the alignment of cell types from externally downloaded datasets with ImmGen miRNA and ATAC-seq populations for integrative analysis. † = BM monocyte miRNA profile only used for H3K27ac signal to miRNA expression correlation. ‡ = NK cells were not part of 22 overlapping cell types used for miRNA to ATAC-seq correlations. d, Distance from significantly correlated OCRs to an annotated miRNA promoter/TSS. e, Percent of correlated OCRs within the same TAD as the promoter for the same miRNA according to TAD definitions in 4 listed cell types from Johanson et al. f, Frequency of miRNAs with different numbers of significantly correlated OCRs. g, Unaligned additional datasets incorporated in promoter and enhancer analyses. h, log10 ATAC-seq signal compared with log10 H3K27ac signal at associated distal elements across the 6 fully aligned populations in c. i, Fraction of associated DEs in either direction of effect above or below high-abundance miRNAs in the 6 fully aligned populations meeting various molecular criteria of active enhancer elements. Bars from left to right represent the number of accessible putative DEs of total possible for expressed miRNAs, the number of accessible putative DEs marked with H3K4me1 or H3K27ac, and the number of accessible putative DEs marked with H3K27ac and with nascent RNA transcripts detected.
Source data
Histone mark and nascent RNA visualization at select miRNA loci
a,b, IGV plot of layered available molecular information at miR-142 (a) and miR-21a (b) loci in splenic B cells and RAW 264.7 macrophages. Correlated DEs from Fig. 3a and regions selected for luciferase reporter assays displayed in Fig. 3b are labeled. Lanes are normalized individually. Promoter regions are shaded in gray for all panels. c, Representative read pile-up tracks of ATAC-seq signal, all normalized to same scale, showing differential cis-element accessibility at the miR-223 locus in select cells. Peak highlighted in gray is the pri-miR-223 promoter region and peaks highlighted in light blue are correlated elements with miR-223 expression from analysis in Fig. 3a. d, H3K27ac and H3K4me1 read pile-ups in aligned histone mark populations at the miR-223 locus. Tracks are normalized by histone mark. e, IGV plots of histone mark and nascent RNA signatures at associated distal elements in CD4⁺ T cells at the miR-146a locus. e1 corresponds to the enhancer site targeted by flanking sgRNAs in Fig. 3d. Lanes are normalized individually.
Source data
Histone marks and nascent RNA support promoter additivity
a, Fraction of mature miRNAs (includes duplicated) with a given number of promoter regions, colored by TargetScan conservation categories. b, miRNA log2 expression compared to its number of ‘active’ promoter regions across the genome using the 6 aligned populations with chromatin mark, nascent RNA, accessibility, and miRNA expression measurements. Active promoters are defined as accessible by ATAC-seq, presence of H3K4me3, and a nascent transcript detected initiating from the promoter region and spanning the miRNA. (n = 6 populations) (c) Aligned dataset read pile-ups and de novo nascent transcript calls at the miR-29a/b-1 locus in BMDMs and MEFs illustrating multiple promoter use. All tracks are normalized independently. d, Number of active promoters for each expressed miRNA across the 6 aligned populations with or without histone mark and nascent RNA criteria.
Source data

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A microRNA expression and regulatory element activity atlas of the mouse immune system

July 2021

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513 Reads

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22 Citations

Nature Immunology

To better define the control of immune system regulation, we generated an atlas of microRNA (miRNA) expression from 63 mouse immune cell populations and connected these signatures with assay for transposase-accessible chromatin using sequencing (ATAC–seq), chromatin immunoprecipitation followed by sequencing (ChIP–seq) and nascent RNA profiles to establish a map of miRNA promoter and enhancer usage in immune cells. miRNA complexity was relatively low, with >90% of the miRNA compartment of each population comprising <75 miRNAs; however, each cell type had a unique miRNA signature. Integration of miRNA expression with chromatin accessibility revealed putative regulatory elements for differentially expressed miRNAs, including miR-21a, miR-146a and miR-223. The integrated maps suggest that many miRNAs utilize multiple promoters to reach high abundance and identified dominant and divergent miRNA regulatory elements between lineages and during development that may be used by clustered miRNAs, such as miR-99a/let-7c/miR-125b, to achieve distinct expression. These studies, with web-accessible data, help delineate the cis-regulatory elements controlling miRNA signatures of the immune system. Brown and colleagues generated an atlas of miRNA expression profiles from primary mouse immune cell populations and connected these signatures with ATAC–seq, ChIP–seq and nascent RNA profiles to establish a map of miRNA promoter and enhancer usage in immune cells.



Gut CD4+ T cell phenotypes are a continuum molded by microbes, not by TH archetypes

September 2019

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66 Reads

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7 Citations

CD4 effector lymphocytes (T ) are traditionally classified by the cytokines they produce. To determine the states that T cells actually adopt in frontline tissues in vivo, we applied single-cell transcriptome and chromatin analyses to colonic T cells in germ-free or conventional mice or in mice after challenge with a range of phenotypically biasing microbes. Unexpected subsets were marked by the expression of the interferon (IFN) signature or myeloid-specific transcripts, but transcriptome or chromatin structure could not resolve discrete clusters fitting classic helper T cell (T ) subsets. At baseline or at different times of infection, transcripts encoding cytokines or proteins commonly used as T markers were distributed in a polarized continuum, which was functionally validated. Clones derived from single progenitors gave rise to both IFN-γ- and interleukin (IL)-17-producing cells. Most of the transcriptional variance was tied to the infecting agent, independent of the cytokines produced, and chromatin variance primarily reflected activities of activator protein (AP)-1 and IFN-regulatory factor (IRF) transcription factor (TF) families, not the canonical subset master regulators T-bet, GATA3 or RORγ. + eff eff eff H H



Identification of a new cell therapy candidate reveals immunological specialization and robust therapeutic efficacy against high-mortality sepsis (P4212)

May 2013

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1 Read

The Journal of Immunology

Sepsis is an aggressive inflammatory syndrome, killing 7.3 million people per year. In mouse and human systems, we have identified highly differentiated, immune-specialized myofibroblasts called Fibroblastic Reticular Cells (FRCs) as a new cell therapy candidate for sepsis. One injection of ex-vivo expanded allogeneic FRCs significantly reduced mortality when administered at therapeutic timepoints. When administered 4 hrs after cecal ligation and puncture (CLP) in mice, FRCs prevented peritonitis progressing to blood sepsis, reducing deaths by 50%, while mesenchymal stromal cells (MSCs) were ineffective. FRCs also reduced lung pathology and lowered systemic concentrations of pathogenic cytokines. Rarely for putative sepsis therapies, we found that when FRCs were administered very late, as mice approached euthanasia endpoints (16 hrs), survival was still extremely robust: 44% of FRC-treated mice survived compared to 9% of controls. Production of the prominent vasodilator and immunosuppressant NOS2 was a primary molecular mechanism. Human FRCs showed strong similarities to mouse FRCs and exhibited desirable traits for a cell therapy candidate, including low variance between unrelated donors. Importantly, human FRCs constitutively secrete high levels of soluble cytokine decoy receptors against major mediators of sepsis. Together these data describe a novel anti-inflammatory cell type and provide robust pre-clinical evidence for therapeutic efficacy in multiple models of sepsis.


Figure 1. Analysis of macrophage diversity (a) Relative distance between different types of macrophages and DCs was assessed using principal component analysis. (b) Correlation matrix of macrophages and dendritic cells based on all genes probes. (c) Examples of the relatively greater diversity between macrophage populations than DCs were plotted. The number of probes increased by a minimum of 2-fold for each population is indicated. (d) Hierarchical clustering of macrophages and dendritic cells based on the top 15% most variable genes.
Figure 2. Unique gene expression profiles of macrophages from different organs (a) Scatter plots depict in distinct colors the mRNA transcripts that are ≥ 2-fold increased (left) or decreased (right) in one macrophage population compared to the remaining three populations. (b) Heat map and gene lists reveal mRNA transcripts uniquely expressed by single macrophage populations by ≥ 5 fold. (c) Transcription factor mRNA transcripts increased in only one of the four macrophage populations by ≥ 2 fold. (d) Specific cell surface markers for each macrophage populations, identified from the gene expression profiling data were validated by flow cytometry. Macrophages reacting with the antibodies tested matched the pattern of gene expression observed in (b). Shaded blue line shows isotype control and red line specific antibody.
Figure 3. Identification of gene modules enriched for macrophage-related gene signatures and their predicted regulators (a) The overlap size of ImmGen modules of co-expressed genes with all macrophageassociated genes signatures (Table 1 and 2) is depicted graphically as a heat map. Only modules significantly enriched for at least one signature are shown. Stars mark significant overlap size by hypergeometric test (Methods). (b) Simplified hematopoietic tree showing mean expression of genes in module 161 (red-high expression; blue-low expression). Listed are genes that constitute module 161 (top) and the predicted positive regulators of the module (bottom). (c) A bar graph listing the positive regulators (activators) predicted by the Ontogenet algorithm to regulate two or more modules listed in a. The frequency that each factor was associated with the 14 modules is depicted. (d). Physical and regulatory interactions between the 18 most frequently represented regulators across the 14 macrophage-associated modules were interrogated using Ingenuity analysis tools. The scheme uses arrows to depict links where there are established physical interactions, or known pathways of co-activation or inhibition.
Figure 4: Expression of genes of the macrophage core signature by other populations of mononuclear phagocytes.(a) Heat map of 39 genes (right margin) with higher expression in spleen, brain, peritoneal and lung macrophages than in classical or migratory DCs (left); middle, tissue-derived mononuclear phagocytes not included in the generation of this list of genes; right, blood monocytes and plasmacytoid DCs; 161a, genes from module 161 included here; 161b, genes from module 161 that did not meet the criteria for inclusion (Table 1). SLN, skin lymph node; MLN, mesenteric lymph node; Thio, thioglycollate-elicited. (b) Frequency of signal intensity for the 39 genes in a at least twofold higher in various populations (horizontal axis) than in the DC population with the highest expression (filled bars; open bars indicate extension up to 100%). (c) Relationships among various mononuclear phagocytes based on their expression of the 39 genes in a. Lang, langerin; LC, Langerhans cell. Data are pooled from three or more experiments.
Figure 5. Examination of macrophage core transcripts at the protein level in multiple tissues
Gene-expression profiles and transcriptional regulatory pathways that underlie the identity and diversity of mouse tissue macrophages

September 2012

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1,341 Reads

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1,745 Citations

Nature Immunology

We assessed gene expression in tissue macrophages from various mouse organs. The diversity in gene expression among different populations of macrophages was considerable. Only a few hundred mRNA transcripts were selectively expressed by macrophages rather than dendritic cells, and many of these were not present in all macrophages. Nonetheless, well-characterized surface markers, including MerTK and FcγR1 (CD64), along with a cluster of previously unidentified transcripts, were distinctly and universally associated with mature tissue macrophages. TCEF3, C/EBP-α, Bach1 and CREG-1 were among the transcriptional regulators predicted to regulate these core macrophage-associated genes. The mRNA encoding other transcription factors, such as Gata6, was associated with single macrophage populations. We further identified how these transcripts and the proteins they encode facilitated distinguishing macrophages from dendritic cells.


Citations (7)


... Interestingly, several other ECM-related genes, such as TNC (Tenascin-C), SPP1 (Secreted phosphoprotein 1), LRRC15 (Leucine Rich Repeat Containing 15) and IBSP (Integrin binding sialoprotein), and integrins such as ITGA11 (Integrin subunit alpha 11) were also significantly upregulated (Fig. 7B, Table S1). LRRC15 is a membrane protein known to be involved in ECM binding and as a marker for cancer associated myofibroblasts in lung, breast and other tumors [72][73][74] . Our data revealed a very significant upregulation of LRRC15 in the presence of TGF-β1, compared to cells cultured in serum free conditions. ...

Reference:

Investigating transcriptional differences in mechanotransductive and ECM related genes in cultured primary corneal keratocytes, fibroblasts and myofibroblasts
1434 TGFβ-dependent LRRC15 + myofibroblasts dictate the tumor fibroblast setpoint to promote cancer immunotherapy resistance
Journal for ImmunoTherapy of Cancer

Journal for ImmunoTherapy of Cancer

... The stroma provides distinct cues to attract and organize immune cells at different stages of response in LNs and spleen. These interactions are coordinated through the types of signals presented 85,86 , as well as the locations 87-89 and timing 90 . Stromal cells, such as fibroblastic reticular cells, blood endothelial cells and lymphatic endothelial cells, can all present antigens to T cells 91,92 . ...

Transcriptional profiling of steady-state and inflamed lymph node stroma reveals potential hematopoietic-stromal cross-talk pathways and suggests an active role for stroma during ongoing immune responses. (176.22)
  • Citing Article
  • May 2012

The Journal of Immunology

... Yes (Astarita, 2014;Acton et al., 2012;Pinner and Turley, 2011) Yes (Astarita, 2014;Acton et al., 2012;Pinner and Turley, 2011) Yes (Astarita, 2014;Acton et al., 2012;Pinner and Turley, 2011) Yes (Astarita, 2014;Acton et al., 2012;Pinner and Turley, 2011) DOCK8 ...

Podoplanin-rich stromal networks induce dendritic cell motility via activation of CLEC-2 (102.21)
  • Citing Article
  • April 2011

The Journal of Immunology

... All six members share the same seed sequence ACAUUC -pairing to the seed match GAAUGU in the mRNA -but differ in length and sequence at the 3' end. In developing T cells, miR-181a-1 and miR-181b-1 are among the most prominently expressed miRNAs [18][19][20] . Deletion of the Mirc14 locus encoding miR-181a/b-1 results in a profound defect in the development of unconventional T cells, including invariant Natural Killer T (iNKT) cells, Mucosal-Associated Invariant T (MAIT) cells, and regulatory T (Treg) cells [21][22][23][24] . ...

A microRNA expression and regulatory element activity atlas of the mouse immune system

Nature Immunology

... The downregulation of canonical cDC1 and cDC2 gene transcripts observed in the identified DC3 cluster aligns with the decreased expression of these genes during dendritic cell maturation 46 . This maturation process involves specialized antigen presentation programs and is associated with an inflammatory gene profile, as documented in previous studies 56,57 . Our findings suggest that mregDCs, also known as CCR7+LAMP3+ cells 42 , represent a distinct molecular state preferentially with cDC1s profile in cervical LN. ...

Deciphering the transcriptional network of the dendritic cell lineage

Nature Immunology

... Therefore, interventions to reduce cardiac cell death have been investigated in pre-clinical and clinical studies [23]. Previous studies demonstrated that decreased mortality and improved ventricular function are associated with a reduction in apoptotic cell death [24]. ...

Gene-expression profiles and transcriptional regulatory pathways that underlie the identity and diversity of mouse tissue macrophages

Nature Immunology