anticd8 antibody Search Results


94
ATCC mg dose anti cd8
Mg Dose Anti Cd8, supplied by ATCC, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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90
Becton Dickinson fluorochrome-conjugated antibodies (abs) to cd4 and cd8
Fluorochrome Conjugated Antibodies (Abs) To Cd4 And Cd8, supplied by Becton Dickinson, 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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Dab Ihc Detection Kit, supplied by OptiView Technologies, 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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Becton Dickinson cd8-pecy5
Cd8 Pecy5, supplied by Becton Dickinson, 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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96
Proteintech anti cd8 alpha antibody
RC48-ADC therapy reshapes the tumor immune microenvironment in BCa. ( A ) Kaplan-Meier survival curves were generated for the anti-PD-1 cohort, stratifying patients based on ERBB2 expression levels. Kaplan-Meier plotter ( https://kmplot.com/analysis/ ) was used to generate survival curves and assess the efficacy of immunotherapy. (B) Boxplot illustrating the relationship between ERBB2 expression and immunotherapy efficacy in the Xiangya Immunotherapy Cohort. (C) The relationship between ERBB2 expression and immune scores in the TCGA-BLCA cohort. (D) Activity levels of the cancer immunity cycle across high and low ERBB2 expression groups. (E) Correlations between ERBB2 and various immune cell types <t>(CD8+T</t> cells, CD4+T cells, dendritic cells, and natural killer cells) analyzed using five independent algorithms (TIMER, CIBERSORT, CIBERSORT-ABS, MCP-COUNTER, and XCELL). (F) Correlations between ERBB2 and tumor-infiltrating immune cells (TIICs) (right) and the cancer immunity cycle (left). (G) Expression patterns of immune cell-related effector genes (including NK cells, Th1 cells, macrophages, CD8+T cells, and dendritic cells) in ADC-treated (n=7) and ADC-untreated (n=18) groups. (H) Cancer immunity cycle activity in the ADC-treated (n=7) and ADC-untreated (n=18) groups. *p<0.05; **p<0.01; ***p<0.001. (I) Correlations between ERBB2 and various immune cell types. *p<0.05; **p<0.01; ***p<0.001. (J) tSNE plot showing the distribution of immune cells in BCa samples from RC48- untreated and RC48-treated patients, with each dot representing a single cell and colors indicating different cell types. (K) Differences in the ratios of three CD8+T cell subgroups (exhausted CD8+T cells, cytotoxic CD8+T cells, and TRM CD8 cells) estimated using the STARTRAC-dist index in ADC-treated (n=4) and ADC-untreated (n=2) groups. +++, Ro/e>1; ++, 0.8<Ro/e≤1; +, 0.2≤Ro/e≤0.8; +/−, 0<Ro/e<0.2; −, Ro/e=0, where Ro/e denotes the ratio of observed to expected cell numbers. ADC, antibody-drug conjugate; BCa, bladder cancer; BLCA, bladder cancer; CR, Complete Response; PD, Progressive Disease; PR, Partial Response; SD, Stable Disease; TCGA, The Cancer Genome Atlas; t-SNE, t-distributed stochastic neighbor embedding.
Anti Cd8 Alpha Antibody, supplied by Proteintech, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Proteintech anti cd8 mouse 66868 1 ig proteintech ihc
RC48-ADC therapy reshapes the tumor immune microenvironment in BCa. ( A ) Kaplan-Meier survival curves were generated for the anti-PD-1 cohort, stratifying patients based on ERBB2 expression levels. Kaplan-Meier plotter ( https://kmplot.com/analysis/ ) was used to generate survival curves and assess the efficacy of immunotherapy. (B) Boxplot illustrating the relationship between ERBB2 expression and immunotherapy efficacy in the Xiangya Immunotherapy Cohort. (C) The relationship between ERBB2 expression and immune scores in the TCGA-BLCA cohort. (D) Activity levels of the cancer immunity cycle across high and low ERBB2 expression groups. (E) Correlations between ERBB2 and various immune cell types <t>(CD8+T</t> cells, CD4+T cells, dendritic cells, and natural killer cells) analyzed using five independent algorithms (TIMER, CIBERSORT, CIBERSORT-ABS, MCP-COUNTER, and XCELL). (F) Correlations between ERBB2 and tumor-infiltrating immune cells (TIICs) (right) and the cancer immunity cycle (left). (G) Expression patterns of immune cell-related effector genes (including NK cells, Th1 cells, macrophages, CD8+T cells, and dendritic cells) in ADC-treated (n=7) and ADC-untreated (n=18) groups. (H) Cancer immunity cycle activity in the ADC-treated (n=7) and ADC-untreated (n=18) groups. *p<0.05; **p<0.01; ***p<0.001. (I) Correlations between ERBB2 and various immune cell types. *p<0.05; **p<0.01; ***p<0.001. (J) tSNE plot showing the distribution of immune cells in BCa samples from RC48- untreated and RC48-treated patients, with each dot representing a single cell and colors indicating different cell types. (K) Differences in the ratios of three CD8+T cell subgroups (exhausted CD8+T cells, cytotoxic CD8+T cells, and TRM CD8 cells) estimated using the STARTRAC-dist index in ADC-treated (n=4) and ADC-untreated (n=2) groups. +++, Ro/e>1; ++, 0.8<Ro/e≤1; +, 0.2≤Ro/e≤0.8; +/−, 0<Ro/e<0.2; −, Ro/e=0, where Ro/e denotes the ratio of observed to expected cell numbers. ADC, antibody-drug conjugate; BCa, bladder cancer; BLCA, bladder cancer; CR, Complete Response; PD, Progressive Disease; PR, Partial Response; SD, Stable Disease; TCGA, The Cancer Genome Atlas; t-SNE, t-distributed stochastic neighbor embedding.
Anti Cd8 Mouse 66868 1 Ig Proteintech Ihc, supplied by Proteintech, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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99
Thermo Fisher anti-cd8 magnetic beads
RC48-ADC therapy reshapes the tumor immune microenvironment in BCa. ( A ) Kaplan-Meier survival curves were generated for the anti-PD-1 cohort, stratifying patients based on ERBB2 expression levels. Kaplan-Meier plotter ( https://kmplot.com/analysis/ ) was used to generate survival curves and assess the efficacy of immunotherapy. (B) Boxplot illustrating the relationship between ERBB2 expression and immunotherapy efficacy in the Xiangya Immunotherapy Cohort. (C) The relationship between ERBB2 expression and immune scores in the TCGA-BLCA cohort. (D) Activity levels of the cancer immunity cycle across high and low ERBB2 expression groups. (E) Correlations between ERBB2 and various immune cell types <t>(CD8+T</t> cells, CD4+T cells, dendritic cells, and natural killer cells) analyzed using five independent algorithms (TIMER, CIBERSORT, CIBERSORT-ABS, MCP-COUNTER, and XCELL). (F) Correlations between ERBB2 and tumor-infiltrating immune cells (TIICs) (right) and the cancer immunity cycle (left). (G) Expression patterns of immune cell-related effector genes (including NK cells, Th1 cells, macrophages, CD8+T cells, and dendritic cells) in ADC-treated (n=7) and ADC-untreated (n=18) groups. (H) Cancer immunity cycle activity in the ADC-treated (n=7) and ADC-untreated (n=18) groups. *p<0.05; **p<0.01; ***p<0.001. (I) Correlations between ERBB2 and various immune cell types. *p<0.05; **p<0.01; ***p<0.001. (J) tSNE plot showing the distribution of immune cells in BCa samples from RC48- untreated and RC48-treated patients, with each dot representing a single cell and colors indicating different cell types. (K) Differences in the ratios of three CD8+T cell subgroups (exhausted CD8+T cells, cytotoxic CD8+T cells, and TRM CD8 cells) estimated using the STARTRAC-dist index in ADC-treated (n=4) and ADC-untreated (n=2) groups. +++, Ro/e>1; ++, 0.8<Ro/e≤1; +, 0.2≤Ro/e≤0.8; +/−, 0<Ro/e<0.2; −, Ro/e=0, where Ro/e denotes the ratio of observed to expected cell numbers. ADC, antibody-drug conjugate; BCa, bladder cancer; BLCA, bladder cancer; CR, Complete Response; PD, Progressive Disease; PR, Partial Response; SD, Stable Disease; TCGA, The Cancer Genome Atlas; t-SNE, t-distributed stochastic neighbor embedding.
Anti Cd8 Magnetic Beads, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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95
ATCC anti cd8 2 43 monoclonal antibodies
RC48-ADC therapy reshapes the tumor immune microenvironment in BCa. ( A ) Kaplan-Meier survival curves were generated for the anti-PD-1 cohort, stratifying patients based on ERBB2 expression levels. Kaplan-Meier plotter ( https://kmplot.com/analysis/ ) was used to generate survival curves and assess the efficacy of immunotherapy. (B) Boxplot illustrating the relationship between ERBB2 expression and immunotherapy efficacy in the Xiangya Immunotherapy Cohort. (C) The relationship between ERBB2 expression and immune scores in the TCGA-BLCA cohort. (D) Activity levels of the cancer immunity cycle across high and low ERBB2 expression groups. (E) Correlations between ERBB2 and various immune cell types <t>(CD8+T</t> cells, CD4+T cells, dendritic cells, and natural killer cells) analyzed using five independent algorithms (TIMER, CIBERSORT, CIBERSORT-ABS, MCP-COUNTER, and XCELL). (F) Correlations between ERBB2 and tumor-infiltrating immune cells (TIICs) (right) and the cancer immunity cycle (left). (G) Expression patterns of immune cell-related effector genes (including NK cells, Th1 cells, macrophages, CD8+T cells, and dendritic cells) in ADC-treated (n=7) and ADC-untreated (n=18) groups. (H) Cancer immunity cycle activity in the ADC-treated (n=7) and ADC-untreated (n=18) groups. *p<0.05; **p<0.01; ***p<0.001. (I) Correlations between ERBB2 and various immune cell types. *p<0.05; **p<0.01; ***p<0.001. (J) tSNE plot showing the distribution of immune cells in BCa samples from RC48- untreated and RC48-treated patients, with each dot representing a single cell and colors indicating different cell types. (K) Differences in the ratios of three CD8+T cell subgroups (exhausted CD8+T cells, cytotoxic CD8+T cells, and TRM CD8 cells) estimated using the STARTRAC-dist index in ADC-treated (n=4) and ADC-untreated (n=2) groups. +++, Ro/e>1; ++, 0.8<Ro/e≤1; +, 0.2≤Ro/e≤0.8; +/−, 0<Ro/e<0.2; −, Ro/e=0, where Ro/e denotes the ratio of observed to expected cell numbers. ADC, antibody-drug conjugate; BCa, bladder cancer; BLCA, bladder cancer; CR, Complete Response; PD, Progressive Disease; PR, Partial Response; SD, Stable Disease; TCGA, The Cancer Genome Atlas; t-SNE, t-distributed stochastic neighbor embedding.
Anti Cd8 2 43 Monoclonal Antibodies, supplied by ATCC, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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ho2 2  (ATCC)
92
ATCC ho2 2
RC48-ADC therapy reshapes the tumor immune microenvironment in BCa. ( A ) Kaplan-Meier survival curves were generated for the anti-PD-1 cohort, stratifying patients based on ERBB2 expression levels. Kaplan-Meier plotter ( https://kmplot.com/analysis/ ) was used to generate survival curves and assess the efficacy of immunotherapy. (B) Boxplot illustrating the relationship between ERBB2 expression and immunotherapy efficacy in the Xiangya Immunotherapy Cohort. (C) The relationship between ERBB2 expression and immune scores in the TCGA-BLCA cohort. (D) Activity levels of the cancer immunity cycle across high and low ERBB2 expression groups. (E) Correlations between ERBB2 and various immune cell types <t>(CD8+T</t> cells, CD4+T cells, dendritic cells, and natural killer cells) analyzed using five independent algorithms (TIMER, CIBERSORT, CIBERSORT-ABS, MCP-COUNTER, and XCELL). (F) Correlations between ERBB2 and tumor-infiltrating immune cells (TIICs) (right) and the cancer immunity cycle (left). (G) Expression patterns of immune cell-related effector genes (including NK cells, Th1 cells, macrophages, CD8+T cells, and dendritic cells) in ADC-treated (n=7) and ADC-untreated (n=18) groups. (H) Cancer immunity cycle activity in the ADC-treated (n=7) and ADC-untreated (n=18) groups. *p<0.05; **p<0.01; ***p<0.001. (I) Correlations between ERBB2 and various immune cell types. *p<0.05; **p<0.01; ***p<0.001. (J) tSNE plot showing the distribution of immune cells in BCa samples from RC48- untreated and RC48-treated patients, with each dot representing a single cell and colors indicating different cell types. (K) Differences in the ratios of three CD8+T cell subgroups (exhausted CD8+T cells, cytotoxic CD8+T cells, and TRM CD8 cells) estimated using the STARTRAC-dist index in ADC-treated (n=4) and ADC-untreated (n=2) groups. +++, Ro/e>1; ++, 0.8<Ro/e≤1; +, 0.2≤Ro/e≤0.8; +/−, 0<Ro/e<0.2; −, Ro/e=0, where Ro/e denotes the ratio of observed to expected cell numbers. ADC, antibody-drug conjugate; BCa, bladder cancer; BLCA, bladder cancer; CR, Complete Response; PD, Progressive Disease; PR, Partial Response; SD, Stable Disease; TCGA, The Cancer Genome Atlas; t-SNE, t-distributed stochastic neighbor embedding.
Ho2 2, supplied by ATCC, used in various techniques. Bioz Stars score: 92/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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94
Abcam anti cd8
RC48-ADC therapy reshapes the tumor immune microenvironment in BCa. ( A ) Kaplan-Meier survival curves were generated for the anti-PD-1 cohort, stratifying patients based on ERBB2 expression levels. Kaplan-Meier plotter ( https://kmplot.com/analysis/ ) was used to generate survival curves and assess the efficacy of immunotherapy. (B) Boxplot illustrating the relationship between ERBB2 expression and immunotherapy efficacy in the Xiangya Immunotherapy Cohort. (C) The relationship between ERBB2 expression and immune scores in the TCGA-BLCA cohort. (D) Activity levels of the cancer immunity cycle across high and low ERBB2 expression groups. (E) Correlations between ERBB2 and various immune cell types <t>(CD8+T</t> cells, CD4+T cells, dendritic cells, and natural killer cells) analyzed using five independent algorithms (TIMER, CIBERSORT, CIBERSORT-ABS, MCP-COUNTER, and XCELL). (F) Correlations between ERBB2 and tumor-infiltrating immune cells (TIICs) (right) and the cancer immunity cycle (left). (G) Expression patterns of immune cell-related effector genes (including NK cells, Th1 cells, macrophages, CD8+T cells, and dendritic cells) in ADC-treated (n=7) and ADC-untreated (n=18) groups. (H) Cancer immunity cycle activity in the ADC-treated (n=7) and ADC-untreated (n=18) groups. *p<0.05; **p<0.01; ***p<0.001. (I) Correlations between ERBB2 and various immune cell types. *p<0.05; **p<0.01; ***p<0.001. (J) tSNE plot showing the distribution of immune cells in BCa samples from RC48- untreated and RC48-treated patients, with each dot representing a single cell and colors indicating different cell types. (K) Differences in the ratios of three CD8+T cell subgroups (exhausted CD8+T cells, cytotoxic CD8+T cells, and TRM CD8 cells) estimated using the STARTRAC-dist index in ADC-treated (n=4) and ADC-untreated (n=2) groups. +++, Ro/e>1; ++, 0.8<Ro/e≤1; +, 0.2≤Ro/e≤0.8; +/−, 0<Ro/e<0.2; −, Ro/e=0, where Ro/e denotes the ratio of observed to expected cell numbers. ADC, antibody-drug conjugate; BCa, bladder cancer; BLCA, bladder cancer; CR, Complete Response; PD, Progressive Disease; PR, Partial Response; SD, Stable Disease; TCGA, The Cancer Genome Atlas; t-SNE, t-distributed stochastic neighbor embedding.
Anti Cd8, supplied by Abcam, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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90
ImmunoTools cd4-fitc-(immunotools) antibody
RC48-ADC therapy reshapes the tumor immune microenvironment in BCa. ( A ) Kaplan-Meier survival curves were generated for the anti-PD-1 cohort, stratifying patients based on ERBB2 expression levels. Kaplan-Meier plotter ( https://kmplot.com/analysis/ ) was used to generate survival curves and assess the efficacy of immunotherapy. (B) Boxplot illustrating the relationship between ERBB2 expression and immunotherapy efficacy in the Xiangya Immunotherapy Cohort. (C) The relationship between ERBB2 expression and immune scores in the TCGA-BLCA cohort. (D) Activity levels of the cancer immunity cycle across high and low ERBB2 expression groups. (E) Correlations between ERBB2 and various immune cell types <t>(CD8+T</t> cells, CD4+T cells, dendritic cells, and natural killer cells) analyzed using five independent algorithms (TIMER, CIBERSORT, CIBERSORT-ABS, MCP-COUNTER, and XCELL). (F) Correlations between ERBB2 and tumor-infiltrating immune cells (TIICs) (right) and the cancer immunity cycle (left). (G) Expression patterns of immune cell-related effector genes (including NK cells, Th1 cells, macrophages, CD8+T cells, and dendritic cells) in ADC-treated (n=7) and ADC-untreated (n=18) groups. (H) Cancer immunity cycle activity in the ADC-treated (n=7) and ADC-untreated (n=18) groups. *p<0.05; **p<0.01; ***p<0.001. (I) Correlations between ERBB2 and various immune cell types. *p<0.05; **p<0.01; ***p<0.001. (J) tSNE plot showing the distribution of immune cells in BCa samples from RC48- untreated and RC48-treated patients, with each dot representing a single cell and colors indicating different cell types. (K) Differences in the ratios of three CD8+T cell subgroups (exhausted CD8+T cells, cytotoxic CD8+T cells, and TRM CD8 cells) estimated using the STARTRAC-dist index in ADC-treated (n=4) and ADC-untreated (n=2) groups. +++, Ro/e>1; ++, 0.8<Ro/e≤1; +, 0.2≤Ro/e≤0.8; +/−, 0<Ro/e<0.2; −, Ro/e=0, where Ro/e denotes the ratio of observed to expected cell numbers. ADC, antibody-drug conjugate; BCa, bladder cancer; BLCA, bladder cancer; CR, Complete Response; PD, Progressive Disease; PR, Partial Response; SD, Stable Disease; TCGA, The Cancer Genome Atlas; t-SNE, t-distributed stochastic neighbor embedding.
Cd4 Fitc (Immunotools) Antibody, supplied by ImmunoTools, 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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86
Servicebio Inc recombinant anti cd8 alpha antibody
Non-canonical neo-antigens presented by MHC class I effectively activate <t>CD8</t> + T cells and suppress tumor growth in a mouse model (A) Workflow for identification and validation of neo-epitopes in a mouse model. (B) Schematic of peptide challenge assay. (C and D) Spot-forming units (SFU; IFN-γ spots per 1 × 10 5 cells) for neo-epitopes derived from intronic (C) and intergenic (D) regions at 14 days post immunization. PBS served as the negative control. (E) Schematic of the in vivo anti-tumor experiment. All ELISpot-confirmed neo-antigens were combined into a multi-epitope vaccine. (F) Tumor volume changes following subcutaneous MC38 cell injection. (G) Tumor-volume changes after antibody-mediated blockade of CD8 + T cells, CD4 + T cells, NK cells, or macrophages. (H) Immunostaining of tumor sections showing CD8 + T, CD4 + T, and regulatory T (Treg) cell infiltration across treatment groups (PBS, control vaccine “CtrlVax and neo-antigen vaccine “Vax”). Scale bar: 40 μm. (I) UMAP projection of single-cell transcriptomic data, annotating tumor-infiltrating lymphocyte (TIL) subpopulations: cytotoxic CD8 + T cells, exhausted CD8 + T cells, exhausted CD4 + T cells, naive CD4 + T cells, proliferating CD4 + T cells, Tregs, NK cells, and B cells. (J) Dot plot of marker gene expression across TIL subsets. Dot size. fraction of cells expressing the gene; dot color. mean normalized expression. (K) Proportion of CD3 + T cells among total tumor-infiltrating immune cells in treatment groups (PBS, CtrlVax, and Vax). (L) Relative distribution of CD4 + T cell subpopulations across treatment groups (PBS, CtrlVax, and Vax) shown as pie charts. Error bars represent mean ± SEM; ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001.
Recombinant Anti Cd8 Alpha Antibody, supplied by Servicebio Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


RC48-ADC therapy reshapes the tumor immune microenvironment in BCa. ( A ) Kaplan-Meier survival curves were generated for the anti-PD-1 cohort, stratifying patients based on ERBB2 expression levels. Kaplan-Meier plotter ( https://kmplot.com/analysis/ ) was used to generate survival curves and assess the efficacy of immunotherapy. (B) Boxplot illustrating the relationship between ERBB2 expression and immunotherapy efficacy in the Xiangya Immunotherapy Cohort. (C) The relationship between ERBB2 expression and immune scores in the TCGA-BLCA cohort. (D) Activity levels of the cancer immunity cycle across high and low ERBB2 expression groups. (E) Correlations between ERBB2 and various immune cell types (CD8+T cells, CD4+T cells, dendritic cells, and natural killer cells) analyzed using five independent algorithms (TIMER, CIBERSORT, CIBERSORT-ABS, MCP-COUNTER, and XCELL). (F) Correlations between ERBB2 and tumor-infiltrating immune cells (TIICs) (right) and the cancer immunity cycle (left). (G) Expression patterns of immune cell-related effector genes (including NK cells, Th1 cells, macrophages, CD8+T cells, and dendritic cells) in ADC-treated (n=7) and ADC-untreated (n=18) groups. (H) Cancer immunity cycle activity in the ADC-treated (n=7) and ADC-untreated (n=18) groups. *p<0.05; **p<0.01; ***p<0.001. (I) Correlations between ERBB2 and various immune cell types. *p<0.05; **p<0.01; ***p<0.001. (J) tSNE plot showing the distribution of immune cells in BCa samples from RC48- untreated and RC48-treated patients, with each dot representing a single cell and colors indicating different cell types. (K) Differences in the ratios of three CD8+T cell subgroups (exhausted CD8+T cells, cytotoxic CD8+T cells, and TRM CD8 cells) estimated using the STARTRAC-dist index in ADC-treated (n=4) and ADC-untreated (n=2) groups. +++, Ro/e>1; ++, 0.8<Ro/e≤1; +, 0.2≤Ro/e≤0.8; +/−, 0<Ro/e<0.2; −, Ro/e=0, where Ro/e denotes the ratio of observed to expected cell numbers. ADC, antibody-drug conjugate; BCa, bladder cancer; BLCA, bladder cancer; CR, Complete Response; PD, Progressive Disease; PR, Partial Response; SD, Stable Disease; TCGA, The Cancer Genome Atlas; t-SNE, t-distributed stochastic neighbor embedding.

Journal: Journal for Immunotherapy of Cancer

Article Title: Overcoming immunotherapy resistance in bladder cancer with a novel antibody-drug conjugate RC48

doi: 10.1136/jitc-2025-011881

Figure Lengend Snippet: RC48-ADC therapy reshapes the tumor immune microenvironment in BCa. ( A ) Kaplan-Meier survival curves were generated for the anti-PD-1 cohort, stratifying patients based on ERBB2 expression levels. Kaplan-Meier plotter ( https://kmplot.com/analysis/ ) was used to generate survival curves and assess the efficacy of immunotherapy. (B) Boxplot illustrating the relationship between ERBB2 expression and immunotherapy efficacy in the Xiangya Immunotherapy Cohort. (C) The relationship between ERBB2 expression and immune scores in the TCGA-BLCA cohort. (D) Activity levels of the cancer immunity cycle across high and low ERBB2 expression groups. (E) Correlations between ERBB2 and various immune cell types (CD8+T cells, CD4+T cells, dendritic cells, and natural killer cells) analyzed using five independent algorithms (TIMER, CIBERSORT, CIBERSORT-ABS, MCP-COUNTER, and XCELL). (F) Correlations between ERBB2 and tumor-infiltrating immune cells (TIICs) (right) and the cancer immunity cycle (left). (G) Expression patterns of immune cell-related effector genes (including NK cells, Th1 cells, macrophages, CD8+T cells, and dendritic cells) in ADC-treated (n=7) and ADC-untreated (n=18) groups. (H) Cancer immunity cycle activity in the ADC-treated (n=7) and ADC-untreated (n=18) groups. *p<0.05; **p<0.01; ***p<0.001. (I) Correlations between ERBB2 and various immune cell types. *p<0.05; **p<0.01; ***p<0.001. (J) tSNE plot showing the distribution of immune cells in BCa samples from RC48- untreated and RC48-treated patients, with each dot representing a single cell and colors indicating different cell types. (K) Differences in the ratios of three CD8+T cell subgroups (exhausted CD8+T cells, cytotoxic CD8+T cells, and TRM CD8 cells) estimated using the STARTRAC-dist index in ADC-treated (n=4) and ADC-untreated (n=2) groups. +++, Ro/e>1; ++, 0.8

Article Snippet: The primary antibodies included: Anti-PD-L1 antibody ( EPR19759 ), abcam, ab213524; anti-PD-L1 antibody ( EPR20529 ), abcam, ab213480; anti-CD8 alpha antibody ( EPR21769 ), abcam, ab217344; anti-CD8 alpha antibody (CAL66), abcam, ab237709; Granzyme B Polyclonal antibody, Proteintech, 13588-1-AP; TAZ Rabbit Polyclonal Antibody, Proteintech, 23306-1-AP.

Techniques: Generated, Expressing, Activity Assay

RC48-ADC inhibits tumor PD-L1 expression, increases CD8+T cell infiltration and activity. ( A ) h-HER2-MB49 mouse bladder cancer cells overexpressing h-HER2 were injected into mice on day 0, and RC48-ADC was administered at either a high dose (HD, 10 mg/kg) or low dose (LD, 5 mg/kg) based on the indicated schedule. (B) Tumor volumes were measured at various time points, with data shown as mean±SD. (C) Representative tumor images from different RC48-ADC dose groups at the final time point in the h-HER2-MB49 tumor-bearing mouse model. (D) Tumor weights were measured on day 15 following RC48-ADC treatment. (E) Representative flow cytometry profiles showing CD8 (CTL marker) detection in h-HER2-MB49 tumors from different treatment groups. (F) Quantification of CD8+/CD3+ cells in tumors from various treatment groups (n=7 per group). (G) Representative flow cytometry profiles displaying GZMB and IFNγ, markers of T cell activity, in h-HER2-MB49 tumor tissues across different treatment groups. (H, I) Quantification of CD8+GZMB+/IFNγ+ CTL percentages in tumor tissues from different treatment groups (n=7 per group). (J) Representative flow cytometry profiles of PD-L1 detection in h-HER2-MB49 tumor tissues from the various treatment groups. (K) Quantification of PD-L1+CD45 cells in tumors from different treatment groups (n=7 mice per group). (L) Representative images of immunohistochemistry staining for CD8 and PD-L1 in h-HER2-MB49 tumors. (M) Representative immunofluorescence staining images showing CD8 and PD-L1 in h-HER2-MB49 tumors. (N, O) Quantification of CD8+ and PD-L1+cell percentages in tumors from different treatment groups (n=7 per group). (P) Representative images of immunofluorescence staining for CD8, GZMB, and PD-L1 in tumor specimens before and after RC48-ADC treatment. (Q) Quantification of CD8+, GZMB+, and PD-L1+cells in tumors RC48-ADC treated or untreated. (n=13 per group). Data are presented as mean±SD, *p<0.05, **p<0.01, ***p<0.001. ADC, antibody-drug conjugate.

Journal: Journal for Immunotherapy of Cancer

Article Title: Overcoming immunotherapy resistance in bladder cancer with a novel antibody-drug conjugate RC48

doi: 10.1136/jitc-2025-011881

Figure Lengend Snippet: RC48-ADC inhibits tumor PD-L1 expression, increases CD8+T cell infiltration and activity. ( A ) h-HER2-MB49 mouse bladder cancer cells overexpressing h-HER2 were injected into mice on day 0, and RC48-ADC was administered at either a high dose (HD, 10 mg/kg) or low dose (LD, 5 mg/kg) based on the indicated schedule. (B) Tumor volumes were measured at various time points, with data shown as mean±SD. (C) Representative tumor images from different RC48-ADC dose groups at the final time point in the h-HER2-MB49 tumor-bearing mouse model. (D) Tumor weights were measured on day 15 following RC48-ADC treatment. (E) Representative flow cytometry profiles showing CD8 (CTL marker) detection in h-HER2-MB49 tumors from different treatment groups. (F) Quantification of CD8+/CD3+ cells in tumors from various treatment groups (n=7 per group). (G) Representative flow cytometry profiles displaying GZMB and IFNγ, markers of T cell activity, in h-HER2-MB49 tumor tissues across different treatment groups. (H, I) Quantification of CD8+GZMB+/IFNγ+ CTL percentages in tumor tissues from different treatment groups (n=7 per group). (J) Representative flow cytometry profiles of PD-L1 detection in h-HER2-MB49 tumor tissues from the various treatment groups. (K) Quantification of PD-L1+CD45 cells in tumors from different treatment groups (n=7 mice per group). (L) Representative images of immunohistochemistry staining for CD8 and PD-L1 in h-HER2-MB49 tumors. (M) Representative immunofluorescence staining images showing CD8 and PD-L1 in h-HER2-MB49 tumors. (N, O) Quantification of CD8+ and PD-L1+cell percentages in tumors from different treatment groups (n=7 per group). (P) Representative images of immunofluorescence staining for CD8, GZMB, and PD-L1 in tumor specimens before and after RC48-ADC treatment. (Q) Quantification of CD8+, GZMB+, and PD-L1+cells in tumors RC48-ADC treated or untreated. (n=13 per group). Data are presented as mean±SD, *p<0.05, **p<0.01, ***p<0.001. ADC, antibody-drug conjugate.

Article Snippet: The primary antibodies included: Anti-PD-L1 antibody ( EPR19759 ), abcam, ab213524; anti-PD-L1 antibody ( EPR20529 ), abcam, ab213480; anti-CD8 alpha antibody ( EPR21769 ), abcam, ab217344; anti-CD8 alpha antibody (CAL66), abcam, ab237709; Granzyme B Polyclonal antibody, Proteintech, 13588-1-AP; TAZ Rabbit Polyclonal Antibody, Proteintech, 23306-1-AP.

Techniques: Expressing, Activity Assay, Injection, Flow Cytometry, Marker, Immunohistochemistry, Staining, Immunofluorescence

RC48-ADC promotes the recruitment and activation of CD8+T cells by inducing the release of chemokines from tumors. ( A) h-HER2-MB49 cells were injected into mice on day 0, and treatment with RC48-ADC (10 mg/kg) and CD8α (100 µg/mouse) was administered based on the indicated schedule. (B) Tumor volume was measured at various time points. Data are presented as mean±SD. (C) Mice were sacrificed on day 15 following RC48-ADC or CD8α treatment, and tumor weights were measured. (D) Representative images of tumors at the final time point after RC48-ADC or CD8α treatment in the h-HER2-MB49 tumor-bearing mouse model. (E) Peripheral blood T cells were extracted and purified for T cell-mediated cytotoxicity assay and Chemotaxis assay. (F) Flow cytometry analysis showing the purification of CD8+T cells for chemotaxis experiments. (G, H) T24 cells were co-incubated with activated T cells for 48 hours, either with or without RC48-ADC (5 µmol), and then stained using crystal violet. The numbers represent the normalized cancer cell survival rates after T cell killing. The ratio of T cells to tumor cells was maintained at 3:1. (I) Bar graph showing the quantitative analysis of cancer cell survival rates from ( E ). (J, K) Flow cytometry analysis showing differences in CD8+T cell activity among various co-culture groups in the T24 or 5637 cell lines. (L-M) Chemotaxis assay demonstrating the different chemotaxis abilities of CTLs in the control versus RC48-ADC-treated group. (N) Bar graph showing the mRNA levels of four chemokines as determined by qRT-PCR after RC48-ADC treatment. (O) Bar graph showing normalized protein secretion concentrations of the four chemokines after RC48-ADC treatment. (P, Q) Use three different neutralizing antibodies to block the chemokines and assess the number of CD8+T cells in T24 and 5637. Data are presented as mean±SD, *p<0.05, **p<0.01, ***p<0.001. ADC, antibody-drug conjugate. FSC, Forward Scatter; SSC, Side Scatter; PBS, phosphate buffered saline.

Journal: Journal for Immunotherapy of Cancer

Article Title: Overcoming immunotherapy resistance in bladder cancer with a novel antibody-drug conjugate RC48

doi: 10.1136/jitc-2025-011881

Figure Lengend Snippet: RC48-ADC promotes the recruitment and activation of CD8+T cells by inducing the release of chemokines from tumors. ( A) h-HER2-MB49 cells were injected into mice on day 0, and treatment with RC48-ADC (10 mg/kg) and CD8α (100 µg/mouse) was administered based on the indicated schedule. (B) Tumor volume was measured at various time points. Data are presented as mean±SD. (C) Mice were sacrificed on day 15 following RC48-ADC or CD8α treatment, and tumor weights were measured. (D) Representative images of tumors at the final time point after RC48-ADC or CD8α treatment in the h-HER2-MB49 tumor-bearing mouse model. (E) Peripheral blood T cells were extracted and purified for T cell-mediated cytotoxicity assay and Chemotaxis assay. (F) Flow cytometry analysis showing the purification of CD8+T cells for chemotaxis experiments. (G, H) T24 cells were co-incubated with activated T cells for 48 hours, either with or without RC48-ADC (5 µmol), and then stained using crystal violet. The numbers represent the normalized cancer cell survival rates after T cell killing. The ratio of T cells to tumor cells was maintained at 3:1. (I) Bar graph showing the quantitative analysis of cancer cell survival rates from ( E ). (J, K) Flow cytometry analysis showing differences in CD8+T cell activity among various co-culture groups in the T24 or 5637 cell lines. (L-M) Chemotaxis assay demonstrating the different chemotaxis abilities of CTLs in the control versus RC48-ADC-treated group. (N) Bar graph showing the mRNA levels of four chemokines as determined by qRT-PCR after RC48-ADC treatment. (O) Bar graph showing normalized protein secretion concentrations of the four chemokines after RC48-ADC treatment. (P, Q) Use three different neutralizing antibodies to block the chemokines and assess the number of CD8+T cells in T24 and 5637. Data are presented as mean±SD, *p<0.05, **p<0.01, ***p<0.001. ADC, antibody-drug conjugate. FSC, Forward Scatter; SSC, Side Scatter; PBS, phosphate buffered saline.

Article Snippet: The primary antibodies included: Anti-PD-L1 antibody ( EPR19759 ), abcam, ab213524; anti-PD-L1 antibody ( EPR20529 ), abcam, ab213480; anti-CD8 alpha antibody ( EPR21769 ), abcam, ab217344; anti-CD8 alpha antibody (CAL66), abcam, ab237709; Granzyme B Polyclonal antibody, Proteintech, 13588-1-AP; TAZ Rabbit Polyclonal Antibody, Proteintech, 23306-1-AP.

Techniques: Activation Assay, Injection, Purification, Cytotoxicity Assay, Chemotaxis Assay, Flow Cytometry, Incubation, Staining, Activity Assay, Co-Culture Assay, Control, Quantitative RT-PCR, Blocking Assay, Saline

The combination of RC48-ADC and CTLA-4/PD-1 mAb has a synergistic effect in treating BCa in immunocompetent mice. ( A ) h-HER2-MB49 cells were injected into mice on day 0, and treatment with RC48-ADC (10 mg/kg) and 100 µg/mouse of PD-1 or CTLA-4 mAb was administered as indicated. (B) Tumor volume was measured at various time points. (C) Mice were sacrificed on day 15 after treatment with RC48-ADC, PD-1, or CTLA-4 mAb, and tumor weight was measured. (D) Representative tumor images at the end of the experiment after RC48-ADC, PD-1, or CTLA-4 mAb treatment in the h-HER2-MB49 tumor-bearing mouse model. (E) Immunofluorescence staining of CD8 and PD-L1 in h-HER2-MB49 tumors, showing significant differences between treatment groups. (F) Representative flow cytometry profiles detecting CD8 (CTL marker), GZMB, and IFNγ, markers of T cell activity, in h-HER2-MB49 tumors from different treatment groups. (G, H) Quantification of CD8+GZMB+/IFNγ+ CTLs and CD8+/CD3+cell percentages in tumor masses from the different treatment groups (n=5 mice per group). Data are presented as mean±SD, *p<0.05, **p<0.01, ***p<0.001. ADC, antibody-drug conjugate; BCa, bladder cancer. PBS, phosphate buffered saline.

Journal: Journal for Immunotherapy of Cancer

Article Title: Overcoming immunotherapy resistance in bladder cancer with a novel antibody-drug conjugate RC48

doi: 10.1136/jitc-2025-011881

Figure Lengend Snippet: The combination of RC48-ADC and CTLA-4/PD-1 mAb has a synergistic effect in treating BCa in immunocompetent mice. ( A ) h-HER2-MB49 cells were injected into mice on day 0, and treatment with RC48-ADC (10 mg/kg) and 100 µg/mouse of PD-1 or CTLA-4 mAb was administered as indicated. (B) Tumor volume was measured at various time points. (C) Mice were sacrificed on day 15 after treatment with RC48-ADC, PD-1, or CTLA-4 mAb, and tumor weight was measured. (D) Representative tumor images at the end of the experiment after RC48-ADC, PD-1, or CTLA-4 mAb treatment in the h-HER2-MB49 tumor-bearing mouse model. (E) Immunofluorescence staining of CD8 and PD-L1 in h-HER2-MB49 tumors, showing significant differences between treatment groups. (F) Representative flow cytometry profiles detecting CD8 (CTL marker), GZMB, and IFNγ, markers of T cell activity, in h-HER2-MB49 tumors from different treatment groups. (G, H) Quantification of CD8+GZMB+/IFNγ+ CTLs and CD8+/CD3+cell percentages in tumor masses from the different treatment groups (n=5 mice per group). Data are presented as mean±SD, *p<0.05, **p<0.01, ***p<0.001. ADC, antibody-drug conjugate; BCa, bladder cancer. PBS, phosphate buffered saline.

Article Snippet: The primary antibodies included: Anti-PD-L1 antibody ( EPR19759 ), abcam, ab213524; anti-PD-L1 antibody ( EPR20529 ), abcam, ab213480; anti-CD8 alpha antibody ( EPR21769 ), abcam, ab217344; anti-CD8 alpha antibody (CAL66), abcam, ab237709; Granzyme B Polyclonal antibody, Proteintech, 13588-1-AP; TAZ Rabbit Polyclonal Antibody, Proteintech, 23306-1-AP.

Techniques: Injection, Immunofluorescence, Staining, Flow Cytometry, Marker, Activity Assay, Saline

Non-canonical neo-antigens presented by MHC class I effectively activate CD8 + T cells and suppress tumor growth in a mouse model (A) Workflow for identification and validation of neo-epitopes in a mouse model. (B) Schematic of peptide challenge assay. (C and D) Spot-forming units (SFU; IFN-γ spots per 1 × 10 5 cells) for neo-epitopes derived from intronic (C) and intergenic (D) regions at 14 days post immunization. PBS served as the negative control. (E) Schematic of the in vivo anti-tumor experiment. All ELISpot-confirmed neo-antigens were combined into a multi-epitope vaccine. (F) Tumor volume changes following subcutaneous MC38 cell injection. (G) Tumor-volume changes after antibody-mediated blockade of CD8 + T cells, CD4 + T cells, NK cells, or macrophages. (H) Immunostaining of tumor sections showing CD8 + T, CD4 + T, and regulatory T (Treg) cell infiltration across treatment groups (PBS, control vaccine “CtrlVax and neo-antigen vaccine “Vax”). Scale bar: 40 μm. (I) UMAP projection of single-cell transcriptomic data, annotating tumor-infiltrating lymphocyte (TIL) subpopulations: cytotoxic CD8 + T cells, exhausted CD8 + T cells, exhausted CD4 + T cells, naive CD4 + T cells, proliferating CD4 + T cells, Tregs, NK cells, and B cells. (J) Dot plot of marker gene expression across TIL subsets. Dot size. fraction of cells expressing the gene; dot color. mean normalized expression. (K) Proportion of CD3 + T cells among total tumor-infiltrating immune cells in treatment groups (PBS, CtrlVax, and Vax). (L) Relative distribution of CD4 + T cell subpopulations across treatment groups (PBS, CtrlVax, and Vax) shown as pie charts. Error bars represent mean ± SEM; ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001.

Journal: Cell Genomics

Article Title: Predominant mutated non-canonical tumor-specific antigens identified by proteogenomics demonstrate immunogenicity and tumor suppression in CRC

doi: 10.1016/j.xgen.2025.101062

Figure Lengend Snippet: Non-canonical neo-antigens presented by MHC class I effectively activate CD8 + T cells and suppress tumor growth in a mouse model (A) Workflow for identification and validation of neo-epitopes in a mouse model. (B) Schematic of peptide challenge assay. (C and D) Spot-forming units (SFU; IFN-γ spots per 1 × 10 5 cells) for neo-epitopes derived from intronic (C) and intergenic (D) regions at 14 days post immunization. PBS served as the negative control. (E) Schematic of the in vivo anti-tumor experiment. All ELISpot-confirmed neo-antigens were combined into a multi-epitope vaccine. (F) Tumor volume changes following subcutaneous MC38 cell injection. (G) Tumor-volume changes after antibody-mediated blockade of CD8 + T cells, CD4 + T cells, NK cells, or macrophages. (H) Immunostaining of tumor sections showing CD8 + T, CD4 + T, and regulatory T (Treg) cell infiltration across treatment groups (PBS, control vaccine “CtrlVax and neo-antigen vaccine “Vax”). Scale bar: 40 μm. (I) UMAP projection of single-cell transcriptomic data, annotating tumor-infiltrating lymphocyte (TIL) subpopulations: cytotoxic CD8 + T cells, exhausted CD8 + T cells, exhausted CD4 + T cells, naive CD4 + T cells, proliferating CD4 + T cells, Tregs, NK cells, and B cells. (J) Dot plot of marker gene expression across TIL subsets. Dot size. fraction of cells expressing the gene; dot color. mean normalized expression. (K) Proportion of CD3 + T cells among total tumor-infiltrating immune cells in treatment groups (PBS, CtrlVax, and Vax). (L) Relative distribution of CD4 + T cell subpopulations across treatment groups (PBS, CtrlVax, and Vax) shown as pie charts. Error bars represent mean ± SEM; ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001.

Article Snippet: Recombinant Anti-CD8 alpha antibody (Rabbit mAb) , Servicebio , Cat# GB15068;RRID: AB_3246431.

Techniques: Biomarker Discovery, Derivative Assay, Negative Control, In Vivo, Enzyme-linked Immunospot, Injection, Immunostaining, Control, Single Cell, Marker, Gene Expression, Expressing