Journal: bioRxiv

Article Title: CD47 as a potential biomarker for the early diagnosis of severe COVID-19

doi: 10.1101/2021.03.01.433404

Figure Lengend Snippet: SARS-CoV-2 infection is associated with increased CD47 levels. A) TF protein abundance in uninfected (control) and SARS-CoV-2-infected (virus) Caco-2 cells (data derived from . P-values were determined by two-sided Student’s t-test. B) CD47 and SARS-CoV-2 N protein levels and virus titres (genomic RNA determined by PCR) in SARS-CoV-2 strain FFM7 (MOI 1)-infected air-liquid interface cultures of primary human bronchial epithelial (HBE) cells and SARS-CoV-2 strain FFM7 (MOI 0.1)-infected Calu-3 cells. Uncropped blots are provided in Suppl. Figure 1. C) CD47 mRNA levels in post mortem samples from COVID-19 patients (data derived from ). P-values were determined by two-sided Student’s t-test.

Article Snippet: Detection occurred by using specific antibodies against CD47 (1:100 dilution, CD47 Antibody, anti-human, Biotin, REAfinityTM, # 130-101-343, Miltenyi Biotec), SARS-CoV-2 N (1:1000 dilution, SARS-CoV-2 Nucleocapsid Antibody, Rabbit MAb, #40143-R019, Sino Biological), and GAPDH (1:1000 dilution, Anti-G3PDH Human Polyclonal Antibody, #2275-PC-100, Trevigen).

Techniques: Infection, Quantitative Proteomics, Control, Virus, Derivative Assay

Journal: bioRxiv

Article Title: CD47 as a potential biomarker for the early diagnosis of severe COVID-19

doi: 10.1101/2021.03.01.433404

Figure Lengend Snippet: Results of the PubMed ( https://pubmed.ncbi.nlm.nih.gov ) literature search for “CD47 aging” (A) and “CD47 hypertension” (B). C) Overview figure of the data derived from the literature searches. Age-related increased CD47 levels may contribute to pathogenic conditions associated with severe COVID-19.

Article Snippet: Detection occurred by using specific antibodies against CD47 (1:100 dilution, CD47 Antibody, anti-human, Biotin, REAfinityTM, # 130-101-343, Miltenyi Biotec), SARS-CoV-2 N (1:1000 dilution, SARS-CoV-2 Nucleocapsid Antibody, Rabbit MAb, #40143-R019, Sino Biological), and GAPDH (1:1000 dilution, Anti-G3PDH Human Polyclonal Antibody, #2275-PC-100, Trevigen).

Techniques: Derivative Assay

Journal: bioRxiv

Article Title: CD47 as a potential biomarker for the early diagnosis of severe COVID-19

doi: 10.1101/2021.03.01.433404

Figure Lengend Snippet: Results of the PubMed ( https://pubmed.ncbi.nlm.nih.gov ) literature search for “CD47 diabetes” (A). B) Overview figure of the data derived from the literature search. Hyperglycaemia- and diabetes-induced increased CD47 levels may contribute to immune escape of SARS-CoV-2-infected cells.

Article Snippet: Detection occurred by using specific antibodies against CD47 (1:100 dilution, CD47 Antibody, anti-human, Biotin, REAfinityTM, # 130-101-343, Miltenyi Biotec), SARS-CoV-2 N (1:1000 dilution, SARS-CoV-2 Nucleocapsid Antibody, Rabbit MAb, #40143-R019, Sino Biological), and GAPDH (1:1000 dilution, Anti-G3PDH Human Polyclonal Antibody, #2275-PC-100, Trevigen).

Techniques: Derivative Assay, Infection

Journal: Nature

Article Title: CD47 blocking antibodies restore phagocytosis and prevent atherosclerosis

doi: 10.1038/nature18935

Figure Lengend Snippet: ( a ). Cytoscape network visualization of the genes which are significantly correlated with CD47 expression in both human and murine atherosclerotic plaque reveals a high number of TNF-α-related factors (indicated in blue), including ligands, receptors, and downstream signaling factors. ( b ). PANTHER pathway analysis of those genes which were (a) significantly associated with CD47 expression in mouse and human vascular tissue and (b) have been previously associated with atherosclerosis through the STAGE study , identifies “ inflammation mediated by chemokine and cytokine signaling pathway ” as the most over-abundant pathway associated with CD47 expression in vascular tissue. ( c ). Using the Hybrid Mouse Diversity Panel (HMDP), which correlates aortic gene expression with Luminex cytokine array data of plasma samples from over 100 inbred strains of mice, we found that vascular CD47 expression is positively correlated with three inflammatory cytokines in vivo, including TNF-α, IL-2 and CXCL1. Correlation data shown for CD47 and TNF-α. ( d ). Co-expression studies confirm that TNF-α and CD47 expression are positively correlated in human carotid endarterectomy samples from the BiKE validation study. The Pearson correlation coefficient was determined assuming a Gaussian distribution and P values were determined using a two-tailed test. ( e ). Experiments with primarily cultured mouse aortic SMCs indicate that TNF-α reproducibly induces CD47 mRNA upregulation, while a number of other classical pro-atherosclerotic stimuli have no significant effect. Notably, CXCL1, IL4, TGFβ and IL-2 fail to induce CD47 expression in vitro, as assessed by ANOVA. ( f ). Additional studies suggest that the effect of TNF-α on CD47 expression persists in the presence of oxidized LDL, as occurs in the atherosclerotic plaque. ( g ). Western blotting confirms that TNF-α induces CD47 expression in vascular cells at the protein level. For gel source data, see . ( h ). Immunocytochemistry studies of HCASMCs confirm that CD47 expression is induced on the cell surface of TNF-α treated cells. TNF-α effect is assessed by co-staining for HMGB1, and antibody specificity is confirmed with isotype control and recombinant CD47 peptide quenching assays. ( i ). Multiple assays (including FACS, Taqman and immunocytochemistry studies) reveal that CD47 expression is downregulated on vascular SMCs during programmed cell death, as has previously been observed with inflammatory cells. ( j ). Confirmatory assays in cultured human coronary artery SMC reveal that TNF-α induces changes similar to those observed in murine cells , including an induction of CD47 under physiological conditions and a blunting of its expected downregulation during apoptosis. ( k ). TNF-α’s capacity to impair CD47 downregulation during programmed cell death is also observed in mouse SMCs simultaneously exposed to pro-apoptotic stimuli and oxidized LDL. ( l ). No correlation between CD47 and other candidate cytokines was observed in the BiKE biobank, further supporting a specific relationship between CD47 and TNF-α. ( m ). Representative FACS-based apoptosis panels from cells exposed to the conditions used in confirm that TNF-α suppresses efferocytosis despite increasing programmed cell death. Comparisons made by two-tailed t tests, unless otherwise specified. *** = P < 0.001, * = P < 0.05. Error bars represent the SEM.

Article Snippet: In some experiments, membranes loaded with protein were incubated with anti-CD47 Ab that had been preabsorbed with CD47 peptide (R&D systems, 1866-CD, 1:5 dilution) for 16 hours, to determine the specificity of the primary Ab.

Techniques: Expressing, Gene Expression, Luminex, Clinical Proteomics, In Vivo, Biomarker Discovery, Two Tailed Test, Cell Culture, In Vitro, Western Blot, Immunocytochemistry, Staining, Control, Recombinant

Journal: Nature

Article Title: CD47 blocking antibodies restore phagocytosis and prevent atherosclerosis

doi: 10.1038/nature18935

Figure Lengend Snippet: In vivo serological data and additional in silico and bioinformatic data ( a ). Complete serological studies (including blood count, liver function studies, basic metabolic panel, and fasting glucose) from the 4 week apoE −/− -AngII atherosclerosis model indicate that anti-CD47 Ab induces a significant reduction in hemoglobin and compensatory reticulocytosis, consistent with prior reports 4 , 7 . The erythrophagocytosis of senescent RBCs appears to be self-limited, and no anemia was observed in the chronic atherosclerosis model or the reduced dose model (P = 0.54 and 0.57, respectively). No significant difference in any other serum marker is observed except for an increase in serum creatinine, which does not deviate outside of the reference range. Metabolic parameters and leukocyte differential data from the 12 week chronic atherosclerosis model are displayed at the bottom of the table. ( b ). Additional Upstream Regulator Analysis (URA) bioinformatic analyses of the Cytoscape data displayed in Extended Data Figure 7a performed within the Ingenuity Pathway Analysis (IPA) software identifies a number of TNF-α related factors (indicated in red) which are predicted to mediate transcriptional regulatory roles in the gene network shown in that panel. P-values were determined from Fisher’s Exact Test by comparing overlap of co-expressed genes with known upstream regulators from the Ingenuity Knowledge Base. ( c ). Several additional DAVID -based bioinformatics analyses including ( KEGG , SMART , PANTHER and GO analyses) confirm the association between CD47 and inflammatory signaling related to the TNF-α pathway (indicated in red). Blue panels indicate the –logp10 value for each identified factor. ( d ). Transcription factor binding site prediction algorithms identify several putative NFKB family binding sites within the CD47 promoter, as displayed in Extended Data Figure 8a . ( d ). List of primers used in this study.

Article Snippet: In some experiments, membranes loaded with protein were incubated with anti-CD47 Ab that had been preabsorbed with CD47 peptide (R&D systems, 1866-CD, 1:5 dilution) for 16 hours, to determine the specificity of the primary Ab.

Techniques: In Vivo, In Silico, Marker, Software, Binding Assay

Journal: bioRxiv

Article Title: EV trace : tracing extracellular vesicles-associated proteins in recipient cells using stable isotope labeling

doi: 10.1101/2025.11.23.690082

Figure Lengend Snippet: ( A ) Distribution of the amount of clusters (indicative of EVs) per size range (nm, depicting the diameter of the clusters) detected using the different staining panels (black circle, Integrin-β1+WGA; blue square, Integrin-β1+GFRP78; red triangle, CD47+GRP78). ( B ) Representative images of individual EVs that were enriched in either one (left, right) or two (middle) of the indicated markers: WGA (green), integrin-β1 (magenta), GRP78 (cyan), CD47 (yellow). Each horizontal row represents one of the three staining panels. White scale bars indicate 200 nm. ( C ) The percentage of EVs (of all clusters detected in each staining panel as in A) that are single or double positive for indicated markers. Bars are colored to indicate markers: light grey, WGA; blue horizontal stripes, integrin-β1; dark grey, GRP78; red vertical stripes, CD47. ( D ) Graphical summary of the detected PCa EV subpopulations and in which cell types these markers were traced (see ). Colors indicating the proteins are similar as in C. A and C show mean±SEM of 3 fields of view. WGA, Wheat Germ Agglutinin

Article Snippet: Unconjugated integrin-β1 antibody (clone P5D2, Santa Cruz Biotechnology, Dallas, TX, USA), CD47 antibody (clone B6.H12, InVivo MAb), or mouse IgG1 isotype control (clone P3.6.2.8.1, eBioscience, Invitrogen) were labeled with mouse IgG1 targeting nanobodies (VHH-AlexaFluor568, VHH-AlexaFluor647, Proteintech, Rosemont, IL, USA).

Techniques: Staining

Journal: Oncoimmunology

Article Title: Bendamustine with total body irradiation conditioning yields tolerant T-cells while preserving T-cell-dependent graft-versus-leukemia

doi: 10.1080/2162402X.2020.1758011

Figure Lengend Snippet: BEN-TBI does not result in appreciable donor T-cell phenotypic differences post-transplant when compared to CY-TBI. (a–c) BALB/c recipient mice received 40 mg/kg BEN iv or 200 mg/kg CY ip on day −2, 400 cGy TBI on day −1, and 10 7 TCD-BM from naïve C57BL/6 mice with 3 × 10 6 CellTrace Violet-stained tT from naïve BoyJ mice on day 0. Blood and spleen were collected on day +3. (a) % donor T-cells (CD45.1+) was determined by flow cytometry. Using CBCs determined by HemaVet analysis, absolute number of donor T-cells was calculated. (b) After gating on CD45.1+ cells (representing donor T-cells), CellTrace Violet dilution was analyzed using ModFit software to determine proliferation index. Representative CellTrace Violet dilution is shown. (c) Within the CD45.1+ gate, cells were stratified by CellTrace high (non- proliferative) and CellTrace low (proliferative) and CD25 and CD47 expression were analyzed by flow cytometry. Pooled data from 2 experiments with line at mean are shown, n = 6–7 mice/group. * p < .05 , ** p < .01 . (d-g) BALB/c recipient mice received 40 mg/kg BEN iv or 200 mg/kg CY ip on day −2, 400 cGy TBI on day −1, and 10 7 BM with 3 × 10 6 SC from naïve C57BL/6 mice on day 0. Peripheral blood was collected on days +7, +14, +21, +35, and +70 and stained for CD8, CD4, Tbet, GATA3, RORγt, CD134, CD278, PD-1, TIM3, CTLA-4, and CD272. CBCs were determined and used to calculate absolute cell numbers. Average absolute numbers of cells per μL of blood are shown with SEM. Representative flow plots from day +7 with fluorescence minus one (FMO) controls are shown (e). (d) Pooled data from 4 experiments are shown, n = 19 mice/group. (e-g) Pooled data from 2 experiments are shown, n = 10 mice/group. ** p < .01.

Article Snippet: Antibodies used were anti-mouse H2kb PerCP-eFluor710 (clone AF6-88.5.5.3; 46–5958), CD8α PE-Cy7 (53–6.7; 25–0081), CD4 APC (RM4-5; 50-148-54), FoxP3 APC (FJK-16s; 17–5773), CD45.1 APC (A20; 17–0453), GATA3 PE-Cy7 (TWAJ; 25–9966), CD134 PE-Cy7 (OX-86; 25–1341), FoxP3 PE (150D/E4; 12–4774), CD69 PE-Cy5 (H1.2F3; 15–0691), RORγt APC (AFKJS-9; 17–6988), IFN gamma PE (XMG1.2, 12–7311) (Thermo Fisher Scientific), CD45.1 PE-CF594 (A20; 562452), CD3ε PE-CF594 (145–2 C11; 562286), CD44 BB515 (IM7; 565941), CD44 BV510 (IM7; 563114) (BD Biosciences), CD47 PE-Vio770 (REA170; 130-102-383), TIM-3 VioBright FITC (REA602; 130-109-449), TIM-3 PE (REA602; 130-118-563), CD278 VioGreen (REA192; 130-100-739), CD272 PE (REA224; 130-102-689), CD4 APC-Vio770 (GK1.5; 130-102-786), CD4 VioGreen (GK1.5; 130-102-444) (Miltenyi Biotec), Tbet PE-Dazzle594 (4B10; 644828), CTLA-4 PE-Dazzle594 (UC10-4B9; 106318), CD8α Brilliant Violet 421 (53–6.7; 100738), CCR7 PE-Cy5 (4B12; 120114), PD-1 APC (29F.1A12; 135210), CD25 AlexaFluor700 (PC61; 102024), and TNF-α Brilliant Violet 510 (MP6-XT22, 506339) (Biolegend).

Techniques: Staining, Flow Cytometry, Software, Expressing, Fluorescence

Journal: Nature

Article Title: CD47 blocking antibodies restore phagocytosis and prevent atherosclerosis

doi: 10.1038/nature18935

Figure Lengend Snippet: ( a ). Cytoscape network visualization of the genes which are significantly correlated with CD47 expression in both human and murine atherosclerotic plaque reveals a high number of TNF-α-related factors (indicated in blue), including ligands, receptors, and downstream signaling factors. ( b ). PANTHER pathway analysis of those genes which were (a) significantly associated with CD47 expression in mouse and human vascular tissue and (b) have been previously associated with atherosclerosis through the STAGE study , identifies “ inflammation mediated by chemokine and cytokine signaling pathway ” as the most over-abundant pathway associated with CD47 expression in vascular tissue. ( c ). Using the Hybrid Mouse Diversity Panel (HMDP), which correlates aortic gene expression with Luminex cytokine array data of plasma samples from over 100 inbred strains of mice, we found that vascular CD47 expression is positively correlated with three inflammatory cytokines in vivo, including TNF-α, IL-2 and CXCL1. Correlation data shown for CD47 and TNF-α. ( d ). Co-expression studies confirm that TNF-α and CD47 expression are positively correlated in human carotid endarterectomy samples from the BiKE validation study. The Pearson correlation coefficient was determined assuming a Gaussian distribution and P values were determined using a two-tailed test. ( e ). Experiments with primarily cultured mouse aortic SMCs indicate that TNF-α reproducibly induces CD47 mRNA upregulation, while a number of other classical pro-atherosclerotic stimuli have no significant effect. Notably, CXCL1, IL4, TGFβ and IL-2 fail to induce CD47 expression in vitro, as assessed by ANOVA. ( f ). Additional studies suggest that the effect of TNF-α on CD47 expression persists in the presence of oxidized LDL, as occurs in the atherosclerotic plaque. ( g ). Western blotting confirms that TNF-α induces CD47 expression in vascular cells at the protein level. For gel source data, see . ( h ). Immunocytochemistry studies of HCASMCs confirm that CD47 expression is induced on the cell surface of TNF-α treated cells. TNF-α effect is assessed by co-staining for HMGB1, and antibody specificity is confirmed with isotype control and recombinant CD47 peptide quenching assays. ( i ). Multiple assays (including FACS, Taqman and immunocytochemistry studies) reveal that CD47 expression is downregulated on vascular SMCs during programmed cell death, as has previously been observed with inflammatory cells. ( j ). Confirmatory assays in cultured human coronary artery SMC reveal that TNF-α induces changes similar to those observed in murine cells , including an induction of CD47 under physiological conditions and a blunting of its expected downregulation during apoptosis. ( k ). TNF-α’s capacity to impair CD47 downregulation during programmed cell death is also observed in mouse SMCs simultaneously exposed to pro-apoptotic stimuli and oxidized LDL. ( l ). No correlation between CD47 and other candidate cytokines was observed in the BiKE biobank, further supporting a specific relationship between CD47 and TNF-α. ( m ). Representative FACS-based apoptosis panels from cells exposed to the conditions used in confirm that TNF-α suppresses efferocytosis despite increasing programmed cell death. Comparisons made by two-tailed t tests, unless otherwise specified. *** = P < 0.001, * = P < 0.05. Error bars represent the SEM.

Article Snippet: Antibody specificity was confirmed using isotype control and by preincubating the anti-CD47 Ab with recombinant CD47 antigen (R&D Systems) in a 1:5 ratio for 16h at 4°C before application.

Techniques: Expressing, Gene Expression, Luminex, Clinical Proteomics, In Vivo, Biomarker Discovery, Two Tailed Test, Cell Culture, In Vitro, Western Blot, Immunocytochemistry, Staining, Control, Recombinant

Journal: Nature

Article Title: CD47 blocking antibodies restore phagocytosis and prevent atherosclerosis

doi: 10.1038/nature18935

Figure Lengend Snippet: In vivo serological data and additional in silico and bioinformatic data ( a ). Complete serological studies (including blood count, liver function studies, basic metabolic panel, and fasting glucose) from the 4 week apoE −/− -AngII atherosclerosis model indicate that anti-CD47 Ab induces a significant reduction in hemoglobin and compensatory reticulocytosis, consistent with prior reports 4 , 7 . The erythrophagocytosis of senescent RBCs appears to be self-limited, and no anemia was observed in the chronic atherosclerosis model or the reduced dose model (P = 0.54 and 0.57, respectively). No significant difference in any other serum marker is observed except for an increase in serum creatinine, which does not deviate outside of the reference range. Metabolic parameters and leukocyte differential data from the 12 week chronic atherosclerosis model are displayed at the bottom of the table. ( b ). Additional Upstream Regulator Analysis (URA) bioinformatic analyses of the Cytoscape data displayed in Extended Data Figure 7a performed within the Ingenuity Pathway Analysis (IPA) software identifies a number of TNF-α related factors (indicated in red) which are predicted to mediate transcriptional regulatory roles in the gene network shown in that panel. P-values were determined from Fisher’s Exact Test by comparing overlap of co-expressed genes with known upstream regulators from the Ingenuity Knowledge Base. ( c ). Several additional DAVID -based bioinformatics analyses including ( KEGG , SMART , PANTHER and GO analyses) confirm the association between CD47 and inflammatory signaling related to the TNF-α pathway (indicated in red). Blue panels indicate the –logp10 value for each identified factor. ( d ). Transcription factor binding site prediction algorithms identify several putative NFKB family binding sites within the CD47 promoter, as displayed in Extended Data Figure 8a . ( d ). List of primers used in this study.

Article Snippet: Antibody specificity was confirmed using isotype control and by preincubating the anti-CD47 Ab with recombinant CD47 antigen (R&D Systems) in a 1:5 ratio for 16h at 4°C before application.

Techniques: In Vivo, In Silico, Marker, Software, Binding Assay

Journal: Nature communications

Article Title: Airway epithelial CD47 plays a critical role in inducing influenza virus-mediated bacterial super-infection.

doi: 10.1038/s41467-024-47963-5

Figure Lengend Snippet: Fig. 1 | Influenza virus induces CD47 expression on the apical surface of ciliated cells in an NF-κB-dependent manner. HBECs were infected with (+ IAV) or without (Mock) influenza A virus. a Immunoblot analysis of junction protein ZO-1 and surface protein CD47 at 1 day post-infection (dpi). Normalized CD47 and ZO-1 protein levels are presented as bar graphs (Mock, n = 4; + IAV, n = 4). b Repre- sentative whole-mount images of ZO-1 (white) and CD47 (red) at 1 dpi. The area where ZO-1 disconnection occurred are presented as bar graphs (Mock, n = 6; + IAV, n = 6). c Quantitative PCR (qPCR) analysis of ZO-1 and CD47 mRNAs at 1 and 3 dpi [Mock, n = 3; + IAV (1 dpi), n = 3; + IAV (3 dpi), n = 3]. d HBECs were treated with or without 10 μM NF-κB inhibitor caffeic acid phenethyl ester (CAPE) for 1 h

Article Snippet: His-tagged human CD47 protein (250ng) (CD7-H5227; Acro biosystems) and 1 × 102 colony-forming units (CFUs) of bacteria were mixed, and the mixtures were isolated using DynabeadsTM His-Tag Isolation & Pulldown kit (10103D; Invitrogen) according to the manufacturer’s instructions.

Techniques: Virus, Expressing, Infection, Western Blot, Real-time Polymerase Chain Reaction

Journal: Nature communications

Article Title: Airway epithelial CD47 plays a critical role in inducing influenza virus-mediated bacterial super-infection.

doi: 10.1038/s41467-024-47963-5

Figure Lengend Snippet: Fig. 2 | Knock-down or neutralization of CD47 protects HBECs from viral–bacterial co-infection. For CD47 knock-down, HBECs were transfected with scrambled shRNA (sc-shRNA) or shRNA targeting CD47 (CD47 shRNA) using a len- tiviral delivery system. For CD47 neutralization, HBECs were treated with either IgG1 (MOPC-21) or α-hCD47 (B6H12.2) antibodies. a Gene expression of CD47 was analyzed using qRT-PCR (normalized by GAPDH mRNA) (sc-shRNA, n = 4; CD47 shRNA, n = 4). b Protein expression of CD47 was analyzed using immunoblotting (sc-shRNA, n = 5; CD47 shRNA, n = 5). c Paracellular FITC-dextran permeability was measured in Mock (n = 16), Virus only (IAV, n = 16), Bacteria only (S. aureus, n = 16), sc-shRNA + Super-infection (n = 12), CD47 shRNA + Super-infection (n = 6), IgG1 +

Article Snippet: His-tagged human CD47 protein (250ng) (CD7-H5227; Acro biosystems) and 1 × 102 colony-forming units (CFUs) of bacteria were mixed, and the mixtures were isolated using DynabeadsTM His-Tag Isolation & Pulldown kit (10103D; Invitrogen) according to the manufacturer’s instructions.

Techniques: Knockdown, Neutralization, Infection, Transfection, shRNA, Gene Expression, Quantitative RT-PCR, Expressing, Western Blot, Permeability, Virus, Bacteria