Journal: Molecular therapy : the journal of the American Society of Gene Therapy

Article Title: Oncolytic adenovirus in treating malignant ascites: A phase II trial and longitudinal single-cell study.

doi: 10.1016/j.ymthe.2024.04.029

Figure Lengend Snippet: Figure 4. Characteristics and dynamics of CD8+ and CD4+ T cell subsets during H101 treatment (A) Distinct cell subtypes of CD8+ T cells demonstrated by UMAP plot. (B) Cell proportion of each CD8+ T cell subtype. Black asterisks represent the statistical significantly increased proportion on day 7 compared with that at baseline. (C) Fraction of CD8_MKI67 cells in two response groups on days 0, 7, and 14. Wilcoxon test. *p < 0.05. (D) Representative double-color immunofluorescence staining of CD8+Ki67+ cells in MA samples (P04 [T-long patient] and P07 [T-short patient]) on days 0, 7, and 14, with

Article Snippet: For double-color immunofluorescence of CD8A and Ki67, mouse anti-human CD8a (CST, Cat#70306) and rabbit anti-human Ki67 (Abcam, Cat#15580), were applied.

Techniques: Staining

Journal: Cancers

Article Title: Alterations in Natural Killer Cells in Colorectal Cancer Patients with Stroma AReactive Invasion Front Areas (SARIFA).

doi: 10.3390/cancers15030994

Figure Lengend Snippet: Figure 2. Comparison of lymphocyte subsets between SARIFA-positive (red) and SARIFA-negative (blue) CRC patients: Main lymphocyte subsets (A), B cell subsets (B), T cell subsets (C), CD4+ T cell subsets (D), CD8+ T cell subsets (E). Small white lines indicate individual data points; large black lines show the overall subset average of SARIFA-positive and SARIFA-negative CRC patients, respectively. * p < 0.05, ** p < 0.01.

Article Snippet: Immunohistochemical staining with CD3 (2GV6 rabbit monoclonal antibody, 1:100, Roche Ventana Medical Systems, Tucson, AZ, USA) CD8 (144B mouse monoclonal antibody, ready to use, Cell Marque, Rocklin, CA, USA) antibodies was performed on 2 μm whole slide sections in an automated manner on a Ventana BenchMark ULTRA platform with an iVIEW DAB detection system (Roche, Mannheim, Germany), as has been described by our group previously [15].

Techniques: Comparison

Journal: NPJ Breast Cancer

Article Title: Targeting GD2 with naxitamab overcomes GD3 synthase-driven immune suppression in triple-negative breast cancer

doi: 10.1038/s41523-025-00843-7

Figure Lengend Snippet: A Analysis of GD3S ( ST8SIA1 ) mRNA expression in METABRIC and TCGA (pan cancer) BC patient datasets shows significant correlation with immune checkpoint inhibitors. In the METABRIC dataset, Pearson’s correlation coefficients indicate significant correlations of GD3S mRNA expression with CTLA-4 ( r = 0.4; P < 0.001), LAG3 ( r = 0.33; P < 0.001), PD1 ( r = 0.3; P < 0.001), CD25 ( r = 0.38; P < 0.001), and SIRPα ( r = 0.36; P < 0.001). Similarly, in the TCGA dataset, GD3S mRNA expression was significantly correlated with CTLA-4 ( r = 0.47; P < 0.001), LAG3 ( r = 0.33; P < 0.001), PD1 ( r = 0.38; P < 0.001), CD25 ( r = 0.45; P < 0.001), and SIRPα ( r = 0.56; P < 0.001). B Representative IHC images obtained by sequential multiplex immunofluorescence images (Lunaphore COMET) from FFPE samples of TNBC patients with high or low GD3S expression ( n = 20 total) were used to compare immune infiltration patterns, showing distinct fluorescence intensities for PANK, Ki67, CD163, CD86, CD56, CD8, CD4, FOXP3, and GD3S within tumor tissues. C H-scores for GD3S expression in BC patients categorized into high and low GD3S expression groups ( ****P < 0.0001). Immune cell counts using Visiopharm IHC image analysis software show differences in the expression of CD8, CD4, CD86, and CD56 between the high and low GD3S expression groups ( ****P < 0.0001; **P < 0.01). Scale bar in IHC images represents 55 µm with 20x magnification. Bar graphs display means ± standard deviations.

Article Snippet: We also purchased the following antibodies: pan-Cytokeratin (Proteintech, cat. #26411-1-AP, rabbit host) along with GD3S (Proteintech, cat. #24918-1-AP, rabbit host), CD45 (Fortislife, clone BL-178-1267, cat. #A700-012, rabbit host), Ki67 (Bethyl, clone BLR021E, cat. #A700-021CF, rabbit host), CD3 (Fortislife, clone BL-298-5012, cat. #A700-016F, rabbit host), CD8 (Fortislife, clone c8/144B, cat. #A500-012A, mouse host), CD4 (Bethyl, clone BL-155-1C11, cat. #A700-015, rabbit host), FOXP3 (Bethyl, clone BLR034F, cat. #A700-034, rabbit host), CD68 (Fortislife, cat. #A500-018ACF, mouse host), CD163 (Invitrogen, clone I0D6, cat. #MA5-11458, mouse host), CD86 (CST, clone E2G8P, cat. #76755SF, rabbit host), CD56 (Fortislife, clone BLR152J, cat. #A700-152, rabbit host) and human IgG1 Kappa antibody (hIgG, cat. #0151K-14, SouthernBiotech).

Techniques: Expressing, Multiplex Assay, Immunofluorescence, Fluorescence, Software

Journal: Cancers

Article Title: Association of Enterotoxigenic Bacteroides fragilis with Immune Modulation in Colorectal Cancer Liver Metastasis

doi: 10.3390/cancers17172733

Figure Lengend Snippet: Immunohistochemistry of CD8 + , CD4 + , CD20 + , FOXP3 + , CD163 + , and CD68 + cells in colorectal cancer liver metastasis tissues. Scale bar = 50 μm.

Article Snippet: Immune-cell infiltration was then assessed using mouse monoclonal antibodies against CD8 (1:3; clone C8/144B; cat. 413201; Nichirei, Tokyo, Japan), CD4 (1:2; clone 4B12; cat. 413951; Nichirei), CD20 (1:800; clone L26; cat. NCL-L-CD20-L26; Leica Biosystems), FOXP3 (1:100; clone 236A/E7; cat. ab20034; Abcam), CD163 (1:1200; clone 10D6; cat. CD163-L-CE; Leica Biosystems), and CD68 (1:1000; clone KP-1; cat. M0814; Dako, Glostrup, Denmark).

Techniques: Immunohistochemistry

Journal: Cancers

Article Title: Association of Enterotoxigenic Bacteroides fragilis with Immune Modulation in Colorectal Cancer Liver Metastasis

doi: 10.3390/cancers17172733

Figure Lengend Snippet: Violin plots showing the density of different types of immune cells according to the ETBF-DNA level. Violin plots display the densities of six immune-cell populations (CD4 + , CD8 + , CD20 + , FOXP3 + , CD163 + , and CD68 + ) in three ETBF-DNA categories (very low, low, and high). The X -axis indicates the ETBF-DNA level in colorectal cancer liver metastases, and the Y -axis shows the corresponding immune-cell density. The Jonckheere–Terpstra test was used to determine p values for trend between ETBF-DNA levels (as an ordinal variable) and the density of tumor-infiltrating immune cells. * indicates p < 0.05. ETBF, enterotoxigenic Bacteroides fragilis .

Article Snippet: Immune-cell infiltration was then assessed using mouse monoclonal antibodies against CD8 (1:3; clone C8/144B; cat. 413201; Nichirei, Tokyo, Japan), CD4 (1:2; clone 4B12; cat. 413951; Nichirei), CD20 (1:800; clone L26; cat. NCL-L-CD20-L26; Leica Biosystems), FOXP3 (1:100; clone 236A/E7; cat. ab20034; Abcam), CD163 (1:1200; clone 10D6; cat. CD163-L-CE; Leica Biosystems), and CD68 (1:1000; clone KP-1; cat. M0814; Dako, Glostrup, Denmark).

Techniques:

Journal: Nature immunology

Article Title: Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry

doi: 10.1038/s41590-019-0378-1

Figure Lengend Snippet: High-dimensional transcriptomic scRNA-seq clustering reveals distinct cell type subpopulations. a . 18 clusters across 5,265 cells from all cell types on a tSNE visualization. b . Cluster abundances across donors. c . Fibroblasts: three types of THY1 + sublining fibroblasts (SC-F1, SC-F2, and SC-F3) and CD55 + lining fibroblasts (SC-F4). d . Monocytes: two activated cell states of IL1B + pro-inflammatory (SC-M1) and IFN-activated (SC-M4) monocytes. e . T cells: CD4 + subsets: SC-T1, SC-T2, SC-T3, and CD8 + subsets: SC-T4, SC-T5, and SC-T6. f . B cells: HLA + (SC-B1, SC-B2, and SC-B3) and plasmablasts (SC-B4). The cluster colors in c-f are consistent with ( a ).

Article Snippet: Primary antibodies to detect IFNg + T cells include goat anti-CD3 epsilon (clone M-20, Santa Cruz Biotechnology), mouse anti-human CD8 (clone 144B, GeneTex), and rabbit anti-human IFNg (Biorbyt, orb214082).

Techniques:

Journal: Nature immunology

Article Title: Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry

doi: 10.1038/s41590-019-0378-1

Figure Lengend Snippet: Connection between cell populations determined by mass cytometry and scRNA-seq clusters and disease associations. Bold mass cytometry clusters are significantly enriched in leukocyte-rich RA (one-sided Benjamini-Hochberg FDR q value < 0.05). Two significant digits are given to the one-sided F-tests conducted on nested models with MASC. 95% confidence interval (CI) for the odds ratio (OR) is given for each mass cytometry cluster. Where possible, we have identified the most similar scRNA-seq clusters for each cluster found by mass cytometry. The mass cytometry analysis is performed on downsampled datasets of 25,161 fibroblasts from 23 patients, 15,298 monocytes from 26 patients, 19,985 T cells from 26 patients, and 8,179 B cells from 23 patients.

Article Snippet: Primary antibodies to detect IFNg + T cells include goat anti-CD3 epsilon (clone M-20, Santa Cruz Biotechnology), mouse anti-human CD8 (clone 144B, GeneTex), and rabbit anti-human IFNg (Biorbyt, orb214082).

Techniques: Mass Cytometry

Journal: Nature immunology

Article Title: Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry

doi: 10.1038/s41590-019-0378-1

Figure Lengend Snippet: Synovial T cells display heterogeneous CD4 and CD8 T cell subpopulations in RA synovium. a . scRNA-seq analysis identified three CD4 + subsets: CCR7 + (SC-T1), T reg cells (SC-T2), and Tph and Tfh (SC-T3); and three CD8 + subsets: GZMK + (SC-T4), CTLs (SC-T5), and GZMK + GZMB + (SC-T6). Differential expression analysis on leukocyte-rich RA ( n = 18) comparing with OA ( n = 13) on sorted T cell bulk RNA-seq samples revealed that CXCL13 is most significantly enriched in leukocyte-rich RA compared to OA. Effect sizes with 95% CI are given. b . Disease association of scRNA-seq clusters by aggregating top markers (AUC>0.7) by comparing leukocyte-rich RA ( n = 18) with OA ( n = 13) using bulk RNA-seq. Tph and Tfh cells (SC-T4) are upregulated (two-sided Student’s t-test p=0.01, t-value=2.73, df =29.00) in leukocyte-rich RA. Error bars indicate mean and 95% CI. c . Pathway analysis based on immunologic gene set enrichment indicates the potential enriched T cell states pathways. Two-sided Kolmogorov-Smirnov test with 10 5 times permutation was performed; Benjamini-Hochberg was used to control the FDR of multiple tests. The brief description of the standard names from up to bottom are: Genes up-regulated in CD4 high cells from thymus: Treg versus T conv (GSE42021); Genes up-regulated in comparison of effector CD8 T cells versus memory CD8 T cells (GOLDRATH); Genes down-regulated in comparison of effector memory T cells versus central memory T cells from peripheral blood mononuclear cells (PBMC) (GSE11057); Genes up-regulated in comparison of effective memory CD4 T cells versus Th1 cells (GSE3982); Genes up-regulated in comparison of T follicular helper (Tfh) cells versus Th17 cells (GSE11924). d . Detection of CD3 + CD8 + IFNγ + (white arrow) in inflamed RA synovium by multicolor immunofluorescent staining with antibodies CD3 (green), CD8 (red), IFNγ (white), and counterstained with DAPI (blue). The experiment was repeated > 5 times with staining of 6 independent leukocyte-rich RA samples with similar results. Image was acquired at 200 magnification. Scale bar is 50 μm. e-f . Identified subpopulations from T cells ( n = 19,985) and disease status from 6 leukocyte-rich RA, 9 leukocyte-poor RA, and 11 OA by mass cytometry. g-h . Distinct patterns of protein markers by tSNE and heatmap that define these clusters. i . Integration of identified mass cytometry clusters with bulk RNA-seq using CCA reveals bulk genes that are associated with CD4 + PD-1 + ICOS + and CD8 + PD-1 − HLA-DR + by mass cytometry. j . Integration of mass cytometry clusters with scRNA-seq clusters on the top markers (AUC>0.7) for each scRNA-seq cluster in the top 10 canonical variates. Z-score based on permutation test reveals that CD4 + PD-1 + ICOS + and CD8 + PD-1 + HLA-DR + by mass cytometry are highly associated with Tph and Tfh (SC-T3) by scRNA-seq; CD8 + PD-1 − HLA-DR + T cells by mass cytometry are highly associated with CD8 + T cells (SC-T4, SC-T5, and SC-T6).

Article Snippet: Primary antibodies to detect IFNg + T cells include goat anti-CD3 epsilon (clone M-20, Santa Cruz Biotechnology), mouse anti-human CD8 (clone 144B, GeneTex), and rabbit anti-human IFNg (Biorbyt, orb214082).

Techniques: Quantitative Proteomics, RNA Sequencing, Control, Comparison, Staining, Mass Cytometry

Journal: Journal of Clinical Investigation

Article Title: Distinct histopathological phenotypes of severe alcoholic hepatitis suggest different mechanisms driving liver injury and failure

doi: 10.1172/jci157780

Figure Lengend Snippet: Figure 1. IHC staining analyses of inflammatory cells in the liver of SAH patients. (A and B) Liver tissues from SAH patients (n = 10) were subjected to sequential multiplex immunofluorescence staining of α-SMA, HepPar1, MPO, CD8, CD4, CD20, and IBA1. (A) Typical starry image of immunofluorescent staining from 1 SAH patient with a large number of inflammatory cells surrounding hepatocytes. (B) Two different patterns of representative images from SAH55 and SAH1 patients. (C) Liver tissues from healthy controls (HC) (n = 5) and SAH patients (n = 40) were subjected to IHC staining for MPO, CD8, and CD4. The number of MPO+, CD8+, CD4+ cells in the parenchymal area (SAH-P) and fibrotic area (SAH-F) were quantified. From 5 to 7 parenchymal or fibrotic areas were randomly selected for quantitation, and average numbers of cells are shown. For the graph, each dot represents one patient. (D and E) Analyses of SAH data from C show negative correlation between P-Neu and F-CD8+ T cells or F-CD4+ T cells and positive correlation between F-CD8+ T cells and F-CD4+ T cells. P values are indicated. Data are represented as mean ± SEM. ***P < 0.001. Statistical significance was assessed using 1-way ANOVA followed by Tukey’s post hoc test for multiple groups (C) and Pearson’s correlation analysis (E).

Article Snippet: The following antibodies were used: HepPar1 (catalog M7158, Dako), CD8a (catalog NBP2-34318-0.1 mg, Novus), CD4 (catalog ab133616, Abcam), MPO (catalog ab208670, Abcam), CD20 (catalog PA5-16701, Thermo Fisher), IBA1 (catalog MABN92, EMD Millipore), and α-SMA (catalog M085129-2, Agilent).

Techniques: Immunohistochemistry, Multiplex Assay, Immunofluorescence, Staining, Quantitation Assay

Journal: Journal of Clinical Investigation

Article Title: Distinct histopathological phenotypes of severe alcoholic hepatitis suggest different mechanisms driving liver injury and failure

doi: 10.1172/jci157780

Figure Lengend Snippet: Figure 2. Hepatic neutrophil and CD8+ T cell infiltration are associated with liver injury in patients with SAH. (A) Upper panel: correlation analysis between the numbers of P-Neu per field and MELD score, serum ALT, or AST level; lower panel: correlation analysis between the numbers of F-CD8+ T cells per field and MELD score, serum ALT, or ALT level. (B–E) SAH patients were dichotomized into Neulo and Neuhi groups (using the average quantity at 50 cells/field of intrahepatic neutrophils in our study cohort as the cutoff) or into CD8lo and CD8hi groups. MELD score, serum AST, and ALT levels were compared between groups. For panels B and D, all SAH patients were used for the comparison. For panels C and E, only SAH patients with abnormal ALT (>40 U/L) levels were used for the comparison. Data are represented as mean ± SEM. *P < 0.05. Statistical significance was assessed using Pearson’s correlation analysis (A) and 2-tailed Student’s t test for comparing 2 groups (B–E).

Article Snippet: The following antibodies were used: HepPar1 (catalog M7158, Dako), CD8a (catalog NBP2-34318-0.1 mg, Novus), CD4 (catalog ab133616, Abcam), MPO (catalog ab208670, Abcam), CD20 (catalog PA5-16701, Thermo Fisher), IBA1 (catalog MABN92, EMD Millipore), and α-SMA (catalog M085129-2, Agilent).

Techniques: Comparison

Journal: Journal of Clinical Investigation

Article Title: Distinct histopathological phenotypes of severe alcoholic hepatitis suggest different mechanisms driving liver injury and failure

doi: 10.1172/jci157780

Figure Lengend Snippet: Figure 4. Hepatic neutrophil infiltration negatively correlates with fibrosis progression in patients with SAH, cirrhosis, and alcoholic steatohepatitis. (A and B) Liver tissues from SAH patients (n = 33) were subjected to Sirius red staining. Representative images from NeuhiCD8lo and NeuloCD8hi groups are shown (A). Scale bars: 500 μm. (B) Fibrosis scores were evaluated by the Ishak system, and SAH patients were divided into 2 groups based on fibrosis scores and hepatic neutrophils. CD8+ T cell numbers were compared between the 2 groups. (C) Liver tissues from healthy control (n = 6) and alcoholic cirrhosis (ALC) patients (n = 32) were subjected to IHC staining of MPO, CD8, and MPO+; CD8+ cells in the parenchymal area (ALC-P) and fibrotic area (ALC-F) were quantified. (D) Liver tissues from healthy controls (n = 6) and alcoholic steatohepatitis patients (n = 12) were subjected to IHC staining of MPO+ and CD8+ cells. Representative images (top) and quantification are shown (bottom). Red arrows indi- cate MPO+ staining, and blue arrows indicate CD8+ staining. Scale bars: 100 μm. Data are represented as mean ± SEM. *P < 0.05; ***P < 0.001. Statistical significance was assessed using 2-tailed Student’s t test for comparing 2 groups (B and D) and 1-way ANOVA followed by Tukey’s post hoc test for multiple groups (C).

Article Snippet: The following antibodies were used: HepPar1 (catalog M7158, Dako), CD8a (catalog NBP2-34318-0.1 mg, Novus), CD4 (catalog ab133616, Abcam), MPO (catalog ab208670, Abcam), CD20 (catalog PA5-16701, Thermo Fisher), IBA1 (catalog MABN92, EMD Millipore), and α-SMA (catalog M085129-2, Agilent).

Techniques: Staining, Control, Immunohistochemistry

Journal: Journal of Clinical Investigation

Article Title: Distinct histopathological phenotypes of severe alcoholic hepatitis suggest different mechanisms driving liver injury and failure

doi: 10.1172/jci157780

Figure Lengend Snippet: Figure 6. Hepatic NCF1 expression is upregulated and positively correlated with neutrophil-related genes in patients and mice with alcoholic steatohep- atitis. (A) Liver tissues from alcoholic steatohepatitis patients were subjected to immunofluorescence staining of MPO and NCF1. Representative images are shown. Scale bar: 23 μm. (B) Correlation analyses were performed between NCF1 and neutrophil-related genes based on RNA-Seq data (n = 12). Values in x and y axes represent relative transcripts per million (TPM). (C and D) Liver tissues from ethanol- (n = 3) and pair-fed (n = 3) mice were subjected to microarray analyses. Heatmap analyses of neutrophil-related genes (C) and CD8+ T cell–related genes (D). Microarray data were pulled from our previous paper (50); GEO database number is GSE67546. Statistical significance was assessed using Pearson’s correlation analysis (B).

Article Snippet: The following antibodies were used: HepPar1 (catalog M7158, Dako), CD8a (catalog NBP2-34318-0.1 mg, Novus), CD4 (catalog ab133616, Abcam), MPO (catalog ab208670, Abcam), CD20 (catalog PA5-16701, Thermo Fisher), IBA1 (catalog MABN92, EMD Millipore), and α-SMA (catalog M085129-2, Agilent).

Techniques: Expressing, Immunofluorescence, Staining, RNA Sequencing, Microarray

Journal: Journal of Clinical Investigation

Article Title: Distinct histopathological phenotypes of severe alcoholic hepatitis suggest different mechanisms driving liver injury and failure

doi: 10.1172/jci157780

Figure Lengend Snippet: Figure 11. Model depicting distinct histopathological phenotypes in SAH patients based on liver immune phenotyping and the role of neutrophilic NCF1-dependent ROS in AH pathogenesis. SAH exists as 2 distinct histopathological pheno- types, NeuhiCD8lo and NeuloCD8hi, suggesting different pathogenesis leading to liver injury and/or failure among these patients. Patients with high hepatic neutrophils but low CD8+ T cells are younger and have higher MELD scores and ALT levels, but have less fibrosis compared with those with NeuloCD8hi. Among those with Neuhi, neutrophilic NCF1-depen- dent ROS promotes AH progression through the NCF1/SIRT1/AMPK axis on lipid metabolism and NCF1/p38 MAPK/miR-223 on alcohol-induced inflammation and fibrosis.

Article Snippet: The following antibodies were used: HepPar1 (catalog M7158, Dako), CD8a (catalog NBP2-34318-0.1 mg, Novus), CD4 (catalog ab133616, Abcam), MPO (catalog ab208670, Abcam), CD20 (catalog PA5-16701, Thermo Fisher), IBA1 (catalog MABN92, EMD Millipore), and α-SMA (catalog M085129-2, Agilent).

Techniques: