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Image Search Results
Journal: Molecular & cellular proteomics : MCP
Article Title: Quantitative Proteomics of Tissue-Infiltrating T Cells From CRC Patients Identified Lipocalin-2 Induces T-Cell Apoptosis and Promotes Tumor Cell Proliferation by Iron Efflux.
doi: 10.1016/j.mcpro.2023.100691
Figure Lengend Snippet: FIG. 1. Validation of the purity of sorted T cells and DEPs screening from CRC patient proteome data. The purity of sorted (A) CD4+ T cells and (B) CD8+ T cells was confirmed using flow cytometry. DEPs from (C) CD4+ T cells and (D) CD8+ T cells were visualized using volcano plots, with significantly upregulated proteins (fold change >1.50, p < 0.05) in red and downregulated proteins (fold change <0.67, p < 0.05) in blue. E, known immunotherapy targets, clinical diagnostic markers, and (F) potential diagnostic markers among these DEPs. Statistical analysis was performed using a paired t test of tumor samples to normal samples. *p < 0.05, **p < 0.01. CRC, differentially expressed protein; DEP, differentially expressed protein.
Article Snippet: Single cells were resuspended with sorting buffer and incubated with magnetic microbeads conjugated to monoclonal antihuman CD4 or
Techniques: Biomarker Discovery, Cytometry, Diagnostic Assay
Journal: Cell reports
Article Title: CD4 + T cells drive an inflammatory, TNF-α/IFN-rich tumor microenvironment responsive to chemotherapy.
doi: 10.1016/j.celrep.2022.111874
Figure Lengend Snippet: Figure 3. CD4+ T cells are required for the development of an inflammatory, cyclophosphamide-sensitive tumor (A) Experimental design. CD4+ T cells were depleted prior to inoculation with AB1-HA, with depletion maintained until experimental endpoint. (B and C) Survival plots of mice bearing AB1-HA (B) or CT26 (C) depleted of CD4+ or CD8+ T cells and treated with cyclophosphamide (n = 10 for AB1-HA and n = 5 for CT26). (D) Significantly enriched gene sets in CD4-depleted (aCD4) or control (phosphate-buffered saline [PBS]) tumors as determined by GSEA (FDR < 0.05). A positive NES indicates the gene set is upregulated in CD4-depleted tumors, and a negative NES indicates the gene set is downregulated in CD4-depleted tumors. EMT, epithelial mesenchymal transition. (E) Gene Ontology terms downregulated in the absence of CD4+ T cells. (F) Unsupervised hierarchical clustering of control or CD4-depleted tumors based on the ‘‘CY responder’’ signature. Counts per million were log2 transformed and z scaled. (G and H) Mean fluorescent intensity (MFI) of IFNg (G) and TNF-a (H) expression on CD8+ T cells and non-T cells (CD45+CD3) from CD4-depleted or control tumors. (I and J) MFI of TNF-a (I) and IFNg (J) expression on non-T cells (CD45+CD3) from CD4-depleted or control tumors. (n = 5). Survival analysis using log rank test. Flow cytometry shown as mean ± SD, and Mann-Whitney U test corrected for multiple comparisons was performed. LogR, *p < 0.05, **p < 0.01, ***p < 0.001.
Article Snippet: REAGENT or RESOURCE SOURCE IDENTIFIER Antibodies FITC anti-mouse CD45 BD Biosciences Cat:553080 RRID:AB_394610 BV510 anti-mouse CD3 BD Biosciences Cat:563024 RRID:AB_2737959 APC anti-mouse CD4 BD Biosciences Cat:553051 RRID:AB_398528 PE-Cy7 anti-mouse CD8 BD Biosciences Cat:552877 RRID:AB_394506 PerCP-Cy5.5 anti-mouse Foxp3 BD Biosciences Cat:563902 RRID:AB_2630318 APC-Cy7 anti-mouse CD19 BD Biosciences Cat:557655 RRID:AB_396770 BUV395 anti-mouse CD45 BD Biosciences Cat:564279 RRID:AB_2651134 BV510 anti-mouse Ly6C Biolegend Cat:128033 RRID:AB_2562351 Ev605 anti-mouse CD11c Biolegend Cat:117333 RRID:AB_11204262 BV711 anti-mouse CD117 Biolegend Cat:105835 RRID:AB_2565956 APC anti-mouse CD11b Miltenyi Biotec Cat:130-109-364 RRID:AB_2654646 AF700 anti-mouse Ly6G Biolegend Cat:127621 RRID:AB_10640452 APC-ef780 anti-mouse MHCII eBiosciences Cat:47-5321-80 RRID:AB_1548792 BUV395 anti-mouse CD3 BD Biosciences Cat:740268 RRID:AB_2687927 BV786 anti-mouse CD4 BD Biosciences Cat:563331 RRID:AB_2738140 BV480 anti-mouse CD8 BD Biosciences Cat:566096 RRID:AB_2739500 BV421 anti-mouse CD25 Biolegend Cat:102043 RRID:AB_2562611 AF647 anti-mouse Foxp3 Biolegend Cat:320013 RRID:AB_11179223 PE-Cy7 anti-mouse ICOS Biolegend Cat:313519 RRID:AB_10641839 PE anti-mouse Ki67 BD Biosciences Cat:556027 RRID:AB_2266296 BV711 anti-mouse CD335 Biolegend Cat:137621 RRID:AB_2563289 APCVio7770 anti-mouse B220 Miltenyi Biotec Cat:130-110-849 RRID:AB_2658286 PE-Cy7 anti-mouse IFNy BD Biosciences Cat:557649 RRID:AB_396766 APC-Cy7 anti-mouse TNFa BD Biosciences Cat:560658 RRID:AB_1727577 Zombie UV live dead Biolegend Cat: 423107 Anti-mouse CD4 BioXCell Cat:
Techniques: Control, Saline, Transformation Assay, Expressing, Flow Cytometry, MANN-WHITNEY
Journal: Cell reports
Article Title: CD4 + T cells drive an inflammatory, TNF-α/IFN-rich tumor microenvironment responsive to chemotherapy.
doi: 10.1016/j.celrep.2022.111874
Figure Lengend Snippet: Figure 5. Targeted modulation of the tumor immune microenvironment using IFNg/poly(I:C)/TNF-a sensitizes tumors to cyclophosphamide chemotherapy in a CD4+-dependent manner (A) Upstream regulators, ranked by Z score, predicted to induce the gene expression profile of cyclophosphamide-responsive tumors. Red are positive regu- lators, and blue are negative regulators. (B) Experimental design for local pre-treatment of tumors. (C–G) Proportion of CD45+ (C), CD8+ (D), Non-Tregs (E), Tregs (F), and NK cells (G) within the tumors of control (PBS) and IFNg/poly(I:C)/TNF-a (PTX)-treated mice (n = 5). (H and I) Survival of AB1-HA (H) and CT26 (I) tumor-bearing mice pre-treated with the triple combination of IFNg/poly(I:C)/TNF-a prior to cyclophosphamide treatment (n = 10). (J) Tumor growth (mean ± SEM) of mice treated with dexamethasone in combination with cyclophosphamide (n = 10, n = 5 for dexamethasone [DEX]). (K) Survival of mice treated with anti-IFNg or anti-IFNAR alone or in combination with cyclophosphamide (n = 5). (L) Survival of mice pre-treated with IFNg/poly(I:C)/TNF-a followed by 5-FU (n = 5). Survival analysis using log rank test. Comparison between groups determined using Student’s t test. Differences in mean tumor growth over time were deter- mined using a mixed model ANOVA. *p < 0.05, **p < 0.01, ***p < 0.001.
Article Snippet: REAGENT or RESOURCE SOURCE IDENTIFIER Antibodies FITC anti-mouse CD45 BD Biosciences Cat:553080 RRID:AB_394610 BV510 anti-mouse CD3 BD Biosciences Cat:563024 RRID:AB_2737959 APC anti-mouse CD4 BD Biosciences Cat:553051 RRID:AB_398528 PE-Cy7 anti-mouse CD8 BD Biosciences Cat:552877 RRID:AB_394506 PerCP-Cy5.5 anti-mouse Foxp3 BD Biosciences Cat:563902 RRID:AB_2630318 APC-Cy7 anti-mouse CD19 BD Biosciences Cat:557655 RRID:AB_396770 BUV395 anti-mouse CD45 BD Biosciences Cat:564279 RRID:AB_2651134 BV510 anti-mouse Ly6C Biolegend Cat:128033 RRID:AB_2562351 Ev605 anti-mouse CD11c Biolegend Cat:117333 RRID:AB_11204262 BV711 anti-mouse CD117 Biolegend Cat:105835 RRID:AB_2565956 APC anti-mouse CD11b Miltenyi Biotec Cat:130-109-364 RRID:AB_2654646 AF700 anti-mouse Ly6G Biolegend Cat:127621 RRID:AB_10640452 APC-ef780 anti-mouse MHCII eBiosciences Cat:47-5321-80 RRID:AB_1548792 BUV395 anti-mouse CD3 BD Biosciences Cat:740268 RRID:AB_2687927 BV786 anti-mouse CD4 BD Biosciences Cat:563331 RRID:AB_2738140 BV480 anti-mouse CD8 BD Biosciences Cat:566096 RRID:AB_2739500 BV421 anti-mouse CD25 Biolegend Cat:102043 RRID:AB_2562611 AF647 anti-mouse Foxp3 Biolegend Cat:320013 RRID:AB_11179223 PE-Cy7 anti-mouse ICOS Biolegend Cat:313519 RRID:AB_10641839 PE anti-mouse Ki67 BD Biosciences Cat:556027 RRID:AB_2266296 BV711 anti-mouse CD335 Biolegend Cat:137621 RRID:AB_2563289 APCVio7770 anti-mouse B220 Miltenyi Biotec Cat:130-110-849 RRID:AB_2658286 PE-Cy7 anti-mouse IFNy BD Biosciences Cat:557649 RRID:AB_396766 APC-Cy7 anti-mouse TNFa BD Biosciences Cat:560658 RRID:AB_1727577 Zombie UV live dead Biolegend Cat: 423107 Anti-mouse CD4 BioXCell Cat:
Techniques: Gene Expression, Control, Comparison
Journal: Frontiers in Oncology
Article Title: Metagenomic Analyses Reveal Distinct Gut Microbiota Signature for Predicting the Neoadjuvant Chemotherapy Responsiveness in Breast Cancer Patients
doi: 10.3389/fonc.2022.865121
Figure Lengend Snippet: Comparison of clinical indices and pathological data between NAC non-effectual group and NAC effectual group.
Article Snippet: For the detection of peripheral blood T lymphocyte subsets, the following antibodies were used:
Techniques: Comparison, Expressing
Journal: Frontiers in Oncology
Article Title: Metagenomic Analyses Reveal Distinct Gut Microbiota Signature for Predicting the Neoadjuvant Chemotherapy Responsiveness in Breast Cancer Patients
doi: 10.3389/fonc.2022.865121
Figure Lengend Snippet: An overview of the microbiota–T lymphocyte (TILs) interactions that modulate neoadjuvant chemotherapy (NAC) efficacy. NAC treatment induces changes in the gut microbiota diversity, causing inflammation and damage to the mucosal barrier of cancer patients, permitting pathogenic bacteria to cross the intestinal barrier and enter lymphoid organs. Then the intestinal microbiota may mediate the induction of TILs such as CD3 + , CD4 + , and CD8 + cells in patients undergoing NAC. When the tight junctions between epithelial cells are broken and the intestinal permeability reduces, pathogenic bacteria interact with immune cells, regulating the response rate of the NAC treatment.
Article Snippet: For the detection of peripheral blood T lymphocyte subsets, the following antibodies were used:
Techniques: Bacteria, Permeability