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Bio X Cell invivoplus anti-mouse ctla-4
Invivoplus Anti Mouse Ctla 4, supplied by Bio X Cell, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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A. Survival of mice bearing TSA WT tumors, Ripk1null tumors, or Ripk1null tumors with ectopic expression of Ccl2 alone (left; n=10–20, 3 independent experiments) or Ccl2 and Cxcl1 (right; n=5–20, 2 independent experiments), treated with <t>anti-CTLA4.</t> B. UMAP of myeloid clusters from scRNA-seq of untreated TSA WT or Ripk1null tumors (n=2 for each). Each cluster is color-coded (left) and the density of cells in each cluster is shown (right). C. Frequency of cells in the myeloid clusters shown in (B). D. Expression of top 10 differentially expressed genes from each myeloid cluster. Select genes including genes from Mac_1 and Mac_4 clusters are highlighted in red and blue, respectively. E-F. Expression of Cxcl9 and Arg1 in myeloid cells (E) and flow cytometric analysis of ARG1+ F4/80+ macrophages (F) from WT or Ripk1null tumors. P-values for survival were determined by log-rank test. For comparison between two groups, a two-sided T-test or Wilcoxon test was used for parametric or non-parametric data, respectively.
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A. Survival of mice bearing TSA WT tumors, Ripk1null tumors, or Ripk1null tumors with ectopic expression of Ccl2 alone (left; n=10–20, 3 independent experiments) or Ccl2 and Cxcl1 (right; n=5–20, 2 independent experiments), treated with anti-CTLA4. B. UMAP of myeloid clusters from scRNA-seq of untreated TSA WT or Ripk1null tumors (n=2 for each). Each cluster is color-coded (left) and the density of cells in each cluster is shown (right). C. Frequency of cells in the myeloid clusters shown in (B). D. Expression of top 10 differentially expressed genes from each myeloid cluster. Select genes including genes from Mac_1 and Mac_4 clusters are highlighted in red and blue, respectively. E-F. Expression of Cxcl9 and Arg1 in myeloid cells (E) and flow cytometric analysis of ARG1+ F4/80+ macrophages (F) from WT or Ripk1null tumors. P-values for survival were determined by log-rank test. For comparison between two groups, a two-sided T-test or Wilcoxon test was used for parametric or non-parametric data, respectively.

Journal: Immunity

Article Title: The Interferon-Stimulated Gene RIPK1 Regulates Cancer Cell Intrinsic and Extrinsic Resistance to Immune Checkpoint Blockade

doi: 10.1016/j.immuni.2022.03.007

Figure Lengend Snippet: A. Survival of mice bearing TSA WT tumors, Ripk1null tumors, or Ripk1null tumors with ectopic expression of Ccl2 alone (left; n=10–20, 3 independent experiments) or Ccl2 and Cxcl1 (right; n=5–20, 2 independent experiments), treated with anti-CTLA4. B. UMAP of myeloid clusters from scRNA-seq of untreated TSA WT or Ripk1null tumors (n=2 for each). Each cluster is color-coded (left) and the density of cells in each cluster is shown (right). C. Frequency of cells in the myeloid clusters shown in (B). D. Expression of top 10 differentially expressed genes from each myeloid cluster. Select genes including genes from Mac_1 and Mac_4 clusters are highlighted in red and blue, respectively. E-F. Expression of Cxcl9 and Arg1 in myeloid cells (E) and flow cytometric analysis of ARG1+ F4/80+ macrophages (F) from WT or Ripk1null tumors. P-values for survival were determined by log-rank test. For comparison between two groups, a two-sided T-test or Wilcoxon test was used for parametric or non-parametric data, respectively.

Article Snippet: InVivoPlus Anti-Mouse CTLA-4 (CD152) Antibody, clone 9H10 , Bio X Cell , Cat#BE0131; RRID:AB_10950184.

Techniques: Expressing, Comparison

A. Flow cytometric analysis of anti-CSF1R (aCSF1R) mediated depletion of F4/80+ macrophages (left) and ARG1+F4/80+ macrophages (right). B. Survival of mice bearing WT or Ripk1null TSA tumors treated with anti-CSF1R, anti-PD1 (aPD1), or both (n=5–10, 1 independent experiment). C. Schema for analyzing enrichment of genes from mouse myeloid clusters (see Figure 4B) in myeloid cells from human melanomas. Shown are UMAPs of myeloid clusters from human melanoma (bottom left), enrichment for differentially expressed genes from mouse myeloid clusters in each human myeloid cluster (top right), and the median expression of genes from mouse Mac_4 cluster overlaid on the human myeloid cluster UMAP (bottom right). D. Density plot of myeloid clusters from human melanoma from patients treated with anti-PD1 +/− anti-CTLA4. Plots are stratified by ICB response (columns) and pre- and post-ICB biopsies (rows). For presentation purposes, densities for each condition are overlaid on UMAP from (C) (cyan dots). E. Multivariable random forest model for probability of response for melanoma patients treated with anti-PD1 +/− anti-CTLA4. Shown are the variable importance scores, which represents the increase in classification error rate when the variable is perturbed, for each myeloid and T/NK clusters. The classification error rate for the model is 21%. For comparison between two groups, a two-sided T-test or Wilcoxon test was used for parametric or non-parametric data, respectively.

Journal: Immunity

Article Title: The Interferon-Stimulated Gene RIPK1 Regulates Cancer Cell Intrinsic and Extrinsic Resistance to Immune Checkpoint Blockade

doi: 10.1016/j.immuni.2022.03.007

Figure Lengend Snippet: A. Flow cytometric analysis of anti-CSF1R (aCSF1R) mediated depletion of F4/80+ macrophages (left) and ARG1+F4/80+ macrophages (right). B. Survival of mice bearing WT or Ripk1null TSA tumors treated with anti-CSF1R, anti-PD1 (aPD1), or both (n=5–10, 1 independent experiment). C. Schema for analyzing enrichment of genes from mouse myeloid clusters (see Figure 4B) in myeloid cells from human melanomas. Shown are UMAPs of myeloid clusters from human melanoma (bottom left), enrichment for differentially expressed genes from mouse myeloid clusters in each human myeloid cluster (top right), and the median expression of genes from mouse Mac_4 cluster overlaid on the human myeloid cluster UMAP (bottom right). D. Density plot of myeloid clusters from human melanoma from patients treated with anti-PD1 +/− anti-CTLA4. Plots are stratified by ICB response (columns) and pre- and post-ICB biopsies (rows). For presentation purposes, densities for each condition are overlaid on UMAP from (C) (cyan dots). E. Multivariable random forest model for probability of response for melanoma patients treated with anti-PD1 +/− anti-CTLA4. Shown are the variable importance scores, which represents the increase in classification error rate when the variable is perturbed, for each myeloid and T/NK clusters. The classification error rate for the model is 21%. For comparison between two groups, a two-sided T-test or Wilcoxon test was used for parametric or non-parametric data, respectively.

Article Snippet: InVivoPlus Anti-Mouse CTLA-4 (CD152) Antibody, clone 9H10 , Bio X Cell , Cat#BE0131; RRID:AB_10950184.

Techniques: Expressing, Comparison

KEY RESOURCES TABLE

Journal: Immunity

Article Title: The Interferon-Stimulated Gene RIPK1 Regulates Cancer Cell Intrinsic and Extrinsic Resistance to Immune Checkpoint Blockade

doi: 10.1016/j.immuni.2022.03.007

Figure Lengend Snippet: KEY RESOURCES TABLE

Article Snippet: InVivoPlus Anti-Mouse CTLA-4 (CD152) Antibody, clone 9H10 , Bio X Cell , Cat#BE0131; RRID:AB_10950184.

Techniques: Control, Virus, Recombinant, Protease Inhibitor, Membrane, Lysis, Transfection, Luciferase, Cell Viability Assay, Mutagenesis, Staining, Sequencing, RNA Sequencing Assay, Derivative Assay, Expressing, CRISPR, Plasmid Preparation, Retroviral, Scaffolding, Software

A. Gene set enrichment analysis (GSEA) of anti-PD1-based therapy resistance genes in untreated Res 499 melanoma cells vs. B16 parental cells (top left), Res 499 vs. Res 499 IFNGR + IFNAR deficient (bottom left), Res 499 IFNGR + IFNAR deficient vs. Res 499 IFNAR deficient (top right), or Res 499 IFNGR + IFNAR deficient vs Res 499 IFNGR deficient (bottom right). Cancer cells were sorted from in vivo tumors. Heatmaps for resistance genes most impacted by IFNGR or IFNAR deficiency are shown (leading edge genes) with blue indicating decreased expression. B. Protein expression of RIPK1 in TSA breast cancer cells treated with 100 ng/ml recombinant murine IFNG at indicated timepoints. C-D. Survival analysis of mice bearing Res 499 tumors (n=5–10, 1 independent experiment) (C) or B16 tumors (n=15–20, 3 independent experiments) (D) with gRNA control (WT) or RIPK1 CRISPR-mediated deletion (Ripk1null) and treated with or without anti-CTLA4 (aC4) +/− anti-PDL1 (aP1). E. Tumor growth curves of mice with control or Ripk1null TSA breast cancer tumors treated with or without anti-CTLA4 (aCTLA4) or anti-PD1 (aPD1) (n=5–10, 1 independent experiment). P-values indicate interaction between treatment and genotype (i.e., effect of treatment is influenced by genotype). F. Survival analysis of mice with WT or Ripk1null TSA tumors treated with or without anti-CTLA4 (n=15–30, 3 independent experiments). G-H. RIPK1 protein expression (G) and tumor growth curves (H) of empty vector expressing WT or Ripk1null TSA cells, or Ripk1null cells with ectopic WT Ripk1. Mice were treated with or without anti-CTLA4 (n=5–10, representative of 3 independent experiments). I. Association between RIPK1 copy number alterations (CNA) and mRNA expression (left) or progression-free survival (right) from pan-cancer TCGA patients (n=10,713). P-values for survival were determined by log-rank test. Mixed effect model was used for tumor growth analysis. For comparison between two groups, a two-sided Wilcoxon test was used for non-parametric data, and for multiple groups a Kruskal-Wallis test is used.

Journal: Immunity

Article Title: The Interferon-Stimulated Gene RIPK1 Regulates Cancer Cell Intrinsic and Extrinsic Resistance to Immune Checkpoint Blockade

doi: 10.1016/j.immuni.2022.03.007

Figure Lengend Snippet: A. Gene set enrichment analysis (GSEA) of anti-PD1-based therapy resistance genes in untreated Res 499 melanoma cells vs. B16 parental cells (top left), Res 499 vs. Res 499 IFNGR + IFNAR deficient (bottom left), Res 499 IFNGR + IFNAR deficient vs. Res 499 IFNAR deficient (top right), or Res 499 IFNGR + IFNAR deficient vs Res 499 IFNGR deficient (bottom right). Cancer cells were sorted from in vivo tumors. Heatmaps for resistance genes most impacted by IFNGR or IFNAR deficiency are shown (leading edge genes) with blue indicating decreased expression. B. Protein expression of RIPK1 in TSA breast cancer cells treated with 100 ng/ml recombinant murine IFNG at indicated timepoints. C-D. Survival analysis of mice bearing Res 499 tumors (n=5–10, 1 independent experiment) (C) or B16 tumors (n=15–20, 3 independent experiments) (D) with gRNA control (WT) or RIPK1 CRISPR-mediated deletion (Ripk1null) and treated with or without anti-CTLA4 (aC4) +/− anti-PDL1 (aP1). E. Tumor growth curves of mice with control or Ripk1null TSA breast cancer tumors treated with or without anti-CTLA4 (aCTLA4) or anti-PD1 (aPD1) (n=5–10, 1 independent experiment). P-values indicate interaction between treatment and genotype (i.e., effect of treatment is influenced by genotype). F. Survival analysis of mice with WT or Ripk1null TSA tumors treated with or without anti-CTLA4 (n=15–30, 3 independent experiments). G-H. RIPK1 protein expression (G) and tumor growth curves (H) of empty vector expressing WT or Ripk1null TSA cells, or Ripk1null cells with ectopic WT Ripk1. Mice were treated with or without anti-CTLA4 (n=5–10, representative of 3 independent experiments). I. Association between RIPK1 copy number alterations (CNA) and mRNA expression (left) or progression-free survival (right) from pan-cancer TCGA patients (n=10,713). P-values for survival were determined by log-rank test. Mixed effect model was used for tumor growth analysis. For comparison between two groups, a two-sided Wilcoxon test was used for non-parametric data, and for multiple groups a Kruskal-Wallis test is used.

Article Snippet: InVivoPlus Anti-Mouse CTLA-4 (CD152) Antibody, clone 9H10 , Bio X Cell , Cat#BE0131; RRID:AB_10950184.

Techniques: In Vivo, Expressing, Recombinant, Control, CRISPR, Plasmid Preparation, Comparison

A-B. Survival of mice bearing B16 WT or Ripk1null tumors and depleted of either CD8 T cells (n=5–10, representative of 2 independent experiments) (A) or NK cells (n=5–15, 2 independent experiments) (B) and treated with or without anti-CTLA4 (aC4). Depletion was performed using an anti-CD8 (aCD8) or anti-NK1.1 (aNK) antibody. C. Survival of WT or Prf1−/− mice bearing Ripk1null B16 tumors and treated with or without anti-CTLA4 (n= 15, 2 independent experiments). D. UMAP of lymphocytes and cancer cells from scRNA-seq of untreated TSA WT or Ripk1null tumors (n=2 for each) (right). Expression of Ripk1 in cancer cells and in the indicated T and NK cell subsets is shown in the heatmap. Black box represents p<0.05 for comparison between WT and Ripk1null groups. E-F. Expression of a cell death metagene or Tradd (E) or of the indicated TNF superfamily receptor or ligand (F) in cancer or immune cells. Median expression in each cell population is shown in the heatmap (left), while per cell expression is overlaid on the UMAP from (D) but faceted by Ripk1 genotype and cell type (right). The cell death metagene is the average scaled expression of genes in the Hallmark apoptosis gene set. For the heatmap, cell types of interest for each comparison are highlighted in bold, and black boxes represent values with p<0.05 for comparison between WT and Ripk1null groups. Scale shows relative expression. G-H. Expression of the indicated proteins (G) and in vitro TNF dose response for normalized viability after treatment with TNF plus 1 ug/ml of cycloheximide for 24 hours (H) for WT B16 cells and B16 cells genetically deleted for Ripk1 (Ripk1null), Casp8 (Casp8null), and Ripk1 and Casp8 (Ripk1null/Casp8null). Data for WT and single Ripk1 deletion groups shown in (H) are from Fig. 2G and presented here to facilitate comparison. I. Survival of mice bearing B16 tumors with the indicated genotypes treated with or without antiCTLA4 (n=15–25, 3 independent experiments). P values for survival analysis were determined by log-rank test. For dose response, a non-linear model was fitted and significance determined by comparison to a reduced model using ANOVA.

Journal: Immunity

Article Title: The Interferon-Stimulated Gene RIPK1 Regulates Cancer Cell Intrinsic and Extrinsic Resistance to Immune Checkpoint Blockade

doi: 10.1016/j.immuni.2022.03.007

Figure Lengend Snippet: A-B. Survival of mice bearing B16 WT or Ripk1null tumors and depleted of either CD8 T cells (n=5–10, representative of 2 independent experiments) (A) or NK cells (n=5–15, 2 independent experiments) (B) and treated with or without anti-CTLA4 (aC4). Depletion was performed using an anti-CD8 (aCD8) or anti-NK1.1 (aNK) antibody. C. Survival of WT or Prf1−/− mice bearing Ripk1null B16 tumors and treated with or without anti-CTLA4 (n= 15, 2 independent experiments). D. UMAP of lymphocytes and cancer cells from scRNA-seq of untreated TSA WT or Ripk1null tumors (n=2 for each) (right). Expression of Ripk1 in cancer cells and in the indicated T and NK cell subsets is shown in the heatmap. Black box represents p<0.05 for comparison between WT and Ripk1null groups. E-F. Expression of a cell death metagene or Tradd (E) or of the indicated TNF superfamily receptor or ligand (F) in cancer or immune cells. Median expression in each cell population is shown in the heatmap (left), while per cell expression is overlaid on the UMAP from (D) but faceted by Ripk1 genotype and cell type (right). The cell death metagene is the average scaled expression of genes in the Hallmark apoptosis gene set. For the heatmap, cell types of interest for each comparison are highlighted in bold, and black boxes represent values with p<0.05 for comparison between WT and Ripk1null groups. Scale shows relative expression. G-H. Expression of the indicated proteins (G) and in vitro TNF dose response for normalized viability after treatment with TNF plus 1 ug/ml of cycloheximide for 24 hours (H) for WT B16 cells and B16 cells genetically deleted for Ripk1 (Ripk1null), Casp8 (Casp8null), and Ripk1 and Casp8 (Ripk1null/Casp8null). Data for WT and single Ripk1 deletion groups shown in (H) are from Fig. 2G and presented here to facilitate comparison. I. Survival of mice bearing B16 tumors with the indicated genotypes treated with or without antiCTLA4 (n=15–25, 3 independent experiments). P values for survival analysis were determined by log-rank test. For dose response, a non-linear model was fitted and significance determined by comparison to a reduced model using ANOVA.

Article Snippet: InVivoPlus Anti-Mouse CTLA-4 (CD152) Antibody, clone 9H10 , Bio X Cell , Cat#BE0131; RRID:AB_10950184.

Techniques: Expressing, Comparison, In Vitro

KEY RESOURCES TABLE

Journal: Immunity

Article Title: The Interferon-Stimulated Gene RIPK1 Regulates Cancer Cell Intrinsic and Extrinsic Resistance to Immune Checkpoint Blockade

doi: 10.1016/j.immuni.2022.03.007

Figure Lengend Snippet: KEY RESOURCES TABLE

Article Snippet: InVivoPlus Anti-Mouse CTLA-4 (CD152) Antibody, clone 9H10 , Bio X Cell , Cat#BE0131; RRID:AB_10950184.

Techniques: Control, Virus, Recombinant, Protease Inhibitor, Membrane, Lysis, Transfection, Luciferase, Cell Viability Assay, Mutagenesis, Staining, Sequencing, RNA Sequencing Assay, Derivative Assay, Expressing, CRISPR, Plasmid Preparation, Retroviral, Scaffolding, Software

KEY RESOURCES TABLE

Journal: Immunity

Article Title: The Interferon-Stimulated Gene RIPK1 Regulates Cancer Cell Intrinsic and Extrinsic Resistance to Immune Checkpoint Blockade

doi: 10.1016/j.immuni.2022.03.007

Figure Lengend Snippet: KEY RESOURCES TABLE

Article Snippet: InVivoPlus Anti-Mouse CTLA-4 (CD152) Antibody, clone 9H10 , Bio X Cell , Cat#BE0131; RRID:AB_10950184.

Techniques: Control, Virus, Recombinant, Protease Inhibitor, Membrane, Lysis, Transfection, Luciferase, Cell Viability Assay, Mutagenesis, Staining, Sequencing, RNA Sequencing Assay, Derivative Assay, Expressing, CRISPR, Plasmid Preparation, Retroviral, Scaffolding, Software

KEY RESOURCES TABLE

Journal: Immunity

Article Title: The Interferon-Stimulated Gene RIPK1 Regulates Cancer Cell Intrinsic and Extrinsic Resistance to Immune Checkpoint Blockade

doi: 10.1016/j.immuni.2022.03.007

Figure Lengend Snippet: KEY RESOURCES TABLE

Article Snippet: InVivoPlus Anti-Mouse CTLA-4 (CD152) Antibody, clone 9H10 , Bio X Cell , Cat#BE0131; RRID:AB_10950184.

Techniques: Control, Virus, Recombinant, Protease Inhibitor, Membrane, Lysis, Transfection, Luciferase, Cell Viability Assay, Mutagenesis, Staining, Sequencing, RNA Sequencing Assay, Derivative Assay, Expressing, CRISPR, Plasmid Preparation, Retroviral, Scaffolding, Software

Journal: Cell

Article Title: Therapeutic potential of co-signaling receptor modulation in hepatitis B

doi: 10.1016/j.cell.2024.05.038

Figure Lengend Snippet:

Article Snippet: InVivoPlus anti-mouse CTLA-4 (CD152) , Bio X Cell , Cat# BE0131; RRID: AB_10950184.

Techniques: Purification, Virus, Recombinant, Staining, Saline, Fluorsave, Sequencing, DNA Labeling, Cell Isolation, Sample Prep, Reverse Transcription, Software, Microscopy