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Cold Spring Harbor Laboratory Meetings tumor models mt4 pancreatic cell line
Tumor Models Mt4 Pancreatic Cell Line, supplied by Cold Spring Harbor Laboratory Meetings, 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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Article Title: TSG-6+ cancer-associated fibroblasts modulate myeloid cell responses and impair anti-tumor response to immune checkpoint therapy in pancreatic cancer.
Article Snippet: David A. Tuveson (Cold Spring Harbor Laboratory, NY). mT4 is an organoid cell line generated from mouse pancreata containing PDAC from the KrasLSL-G12D/+;Trp53LSL-R172H/+;Pdx1–Cre mouse model under C57BL/6 Fig. 2 | TSG-6 expression is induced in cancer setting. a UMAP plot of tumor and stromal compartment from 24 PDAC patients and 11 normal pancreas reanalyzed from ref. 27. bUMAP plots indicating distribution of all cells across the two groups (normal pancreas and tumor).

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Article Title: TSG-6+ cancer-associated fibroblasts modulate myeloid cell responses and impair anti-tumor response to immune checkpoint therapy in pancreatic cancer
Article Snippet: .. mT4 pancreatic cell line was a generous gift from Dr. David A. Tuveson (Cold Spring Harbor Laboratory, NY). mT4 is an organoid cell line generated from mouse pancreata containing PDAC from the Kras LSL-G12D/+ ;Trp53 LSL-R172H/+ ;Pdx1–Cre mouse model under C57BL/6 background . mT4-LS cells were generated and generously gifted by Dr. Michael Curran (The University of Texas MD Anderson Cancer Center, Houston, TX). ..



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Cold Spring Harbor Laboratory Meetings tumor models mt4 pancreatic cell line
Tumor Models Mt4 Pancreatic Cell Line, supplied by Cold Spring Harbor Laboratory Meetings, 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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Cold Spring Harbor Laboratory Meetings mt4 pancreatic cell line
a Schematic representation of the scRNAseq experimental design created with BioRender.com, released under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International license. 3 tumors in each group were pooled for internal control. b Representative Uniform Manifold Approximation Projection (UMAP) plot of sorted intratumoral CD45-negative cells. Each dot represents a cell. c UMAP plots indicating expression of genes depicting B16F10 tumor cells ( Pmel , Mlana ), <t>mT4</t> tumor cells ( Krt18 , Krt19 ) and fibroblasts ( Col1a1 , Dcn ). d UMAP plots highlighting differences in fibroblast abundance between mT4 and B16F10 tumors (red circle). e UMAP plot depicting tnfaip6 (gene encoding TNF Stimulating Gene-6 (TSG-6)) expression in B16F10 and mT4 tumors (red circle). f Box-and-whisker plot representing TNFAIP6 RNA expression in TCGA datasets of melanoma (skcm, skin cutaneous melanoma) ( n = 480 patients) and <t>pancreatic</t> patient tumors (paad, pancreatic adenocarcinoma) ( n = 186 patients). Each dot represents a patient. Statistical significance was calculated using Student’s t test (two-tailed) and p value for the comparison has been indicated in the figure. Data are presented as mean values ± SD. The center of the plot represents mean of the group and the whiskers represent minimum- maximum values.
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Analysis of the naïve tumor microenvironment of <t>MT4</t> pancreatic and NDL breast cancer models reveals distinct TMEs and immunological signatures . A-D) Hematoxylin and eosin staining before (A-B) and after (C-D) ablation in MT4 (A, C) and NDL (B, D) models. A) MT4 pancreatic ductal adenocarcinoma has decreased cellularity compared to B) NDL mammary adenocarcinoma, which is comparatively well vascularized (white arrows) with scattered leucocytes (black dots). E-K) Results of single-cell RNA sequencing, including Uniform Manifold Approximation and Projection (UMAP) plots for the MT4 (E) and NDL (F) tumors. B cells (dark pink) were CD19 + , CD79 + and Ly6d + . T cells were CD3e + , with CD8 + (dark blue) and CD4 + (light blue) T cell subsets defined by CD8a and CD4, respectively. NK cells (lavender) were Klrb1b + and Klrb1c + (NK1.1 + ). Eosinophils (yellow) were Siglec-F + . Neutrophils (light orange) were Ly6g + . Monocytes (light pink) were Ly6c + , Ccr2 + , Mrc1 + , and Ccl9 + . Macrophages (green) were Itgam + and Adgre1 + . Dendritic cells (purple) were Itgax + , H2-Ab1 + , Fcgr1 + , Ly6g - , Siglecf - , Klrb1c - . Granulocytes (turquoise) were Tmem189 + , Sap30 + , and Idha + . G) Quantitative summary of immune cells within each tumor model. The MT4 model has a smaller faction of CD8 + T cells, macrophages and NK cells compared to the NDL model. H-K) Gene expression distribution and levels across UMAP cell clusters in the MT4 (H, J) and NDL (I, K) models. In the MT4 model, overall cellular Myd88 expression levels are higher, and CD40 expression is higher in dendritic cell (DC) clusters compared to the NDL model. The MT4 model also has a greater fraction of both CD4 + and CD8 + T cells expressing PD-1, CD8 + T cells expressing CTLA4, and DCs expressing CD40. Scale bars represent 300 µm.
Metastatic Pancreatic Cancer Cell Line Mt4, supplied by Cold Spring Harbor Laboratory Meetings, 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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Analysis of the naïve tumor microenvironment of <t>MT4</t> pancreatic and NDL breast cancer models reveals distinct TMEs and immunological signatures . A-D) Hematoxylin and eosin staining before (A-B) and after (C-D) ablation in MT4 (A, C) and NDL (B, D) models. A) MT4 pancreatic ductal adenocarcinoma has decreased cellularity compared to B) NDL mammary adenocarcinoma, which is comparatively well vascularized (white arrows) with scattered leucocytes (black dots). E-K) Results of single-cell RNA sequencing, including Uniform Manifold Approximation and Projection (UMAP) plots for the MT4 (E) and NDL (F) tumors. B cells (dark pink) were CD19 + , CD79 + and Ly6d + . T cells were CD3e + , with CD8 + (dark blue) and CD4 + (light blue) T cell subsets defined by CD8a and CD4, respectively. NK cells (lavender) were Klrb1b + and Klrb1c + (NK1.1 + ). Eosinophils (yellow) were Siglec-F + . Neutrophils (light orange) were Ly6g + . Monocytes (light pink) were Ly6c + , Ccr2 + , Mrc1 + , and Ccl9 + . Macrophages (green) were Itgam + and Adgre1 + . Dendritic cells (purple) were Itgax + , H2-Ab1 + , Fcgr1 + , Ly6g - , Siglecf - , Klrb1c - . Granulocytes (turquoise) were Tmem189 + , Sap30 + , and Idha + . G) Quantitative summary of immune cells within each tumor model. The MT4 model has a smaller faction of CD8 + T cells, macrophages and NK cells compared to the NDL model. H-K) Gene expression distribution and levels across UMAP cell clusters in the MT4 (H, J) and NDL (I, K) models. In the MT4 model, overall cellular Myd88 expression levels are higher, and CD40 expression is higher in dendritic cell (DC) clusters compared to the NDL model. The MT4 model also has a greater fraction of both CD4 + and CD8 + T cells expressing PD-1, CD8 + T cells expressing CTLA4, and DCs expressing CD40. Scale bars represent 300 µm.
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In vitro release of IFN-α (A), IFN-β (B) in NDL and 4T1 murine mammary carcinoma, <t>mT4</t> murine <t>pancreatic</t> cancer, MC-38 murine colon cancer cells, B16 murine melanoma, and HMGB 1 in NDL cell culture 24 h post treatment, respectively. Cells were preincubated for 5 min (type I IFN) or 1 min (HMGB 1) at 42°C prior to addition of media only (42°C) or a solution of 5 µg/mL Dox in media (Free Dox+42°C) at 42°C for another 5 min. * p < 0.05, ** p< 0.01, *** p< 0.001, **** p< 0.0001.
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a Schematic representation of the scRNAseq experimental design created with BioRender.com, released under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International license. 3 tumors in each group were pooled for internal control. b Representative Uniform Manifold Approximation Projection (UMAP) plot of sorted intratumoral CD45-negative cells. Each dot represents a cell. c UMAP plots indicating expression of genes depicting B16F10 tumor cells ( Pmel , Mlana ), mT4 tumor cells ( Krt18 , Krt19 ) and fibroblasts ( Col1a1 , Dcn ). d UMAP plots highlighting differences in fibroblast abundance between mT4 and B16F10 tumors (red circle). e UMAP plot depicting tnfaip6 (gene encoding TNF Stimulating Gene-6 (TSG-6)) expression in B16F10 and mT4 tumors (red circle). f Box-and-whisker plot representing TNFAIP6 RNA expression in TCGA datasets of melanoma (skcm, skin cutaneous melanoma) ( n = 480 patients) and pancreatic patient tumors (paad, pancreatic adenocarcinoma) ( n = 186 patients). Each dot represents a patient. Statistical significance was calculated using Student’s t test (two-tailed) and p value for the comparison has been indicated in the figure. Data are presented as mean values ± SD. The center of the plot represents mean of the group and the whiskers represent minimum- maximum values.

Journal: Nature Communications

Article Title: TSG-6+ cancer-associated fibroblasts modulate myeloid cell responses and impair anti-tumor response to immune checkpoint therapy in pancreatic cancer

doi: 10.1038/s41467-024-49189-x

Figure Lengend Snippet: a Schematic representation of the scRNAseq experimental design created with BioRender.com, released under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International license. 3 tumors in each group were pooled for internal control. b Representative Uniform Manifold Approximation Projection (UMAP) plot of sorted intratumoral CD45-negative cells. Each dot represents a cell. c UMAP plots indicating expression of genes depicting B16F10 tumor cells ( Pmel , Mlana ), mT4 tumor cells ( Krt18 , Krt19 ) and fibroblasts ( Col1a1 , Dcn ). d UMAP plots highlighting differences in fibroblast abundance between mT4 and B16F10 tumors (red circle). e UMAP plot depicting tnfaip6 (gene encoding TNF Stimulating Gene-6 (TSG-6)) expression in B16F10 and mT4 tumors (red circle). f Box-and-whisker plot representing TNFAIP6 RNA expression in TCGA datasets of melanoma (skcm, skin cutaneous melanoma) ( n = 480 patients) and pancreatic patient tumors (paad, pancreatic adenocarcinoma) ( n = 186 patients). Each dot represents a patient. Statistical significance was calculated using Student’s t test (two-tailed) and p value for the comparison has been indicated in the figure. Data are presented as mean values ± SD. The center of the plot represents mean of the group and the whiskers represent minimum- maximum values.

Article Snippet: mT4 pancreatic cell line was a generous gift from Dr. David A. Tuveson (Cold Spring Harbor Laboratory, NY). mT4 is an organoid cell line generated from mouse pancreata containing PDAC from the Kras LSL-G12D/+ ;Trp53 LSL-R172H/+ ;Pdx1–Cre mouse model under C57BL/6 background . mT4-LS cells were generated and generously gifted by Dr. Michael Curran (The University of Texas MD Anderson Cancer Center, Houston, TX).

Techniques: Control, Expressing, Whisker Assay, RNA Expression, Two Tailed Test, Comparison

a Schematic representation of the scRNAseq experimental design created with BioRender.com, released under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International license. b Representative landscape in B16F10 and mT4 tumors. Three tumors in each group were pooled for internal control. All major immune cell subsets were identified. c Cluster frequency plot of each immune subset in B16F10 and mT4 tumors. The T cells are depicted in shades of green, B cells in purple, NK cells in gray, macrophages and monocytes in red, neutrophil in orange, and dendritic cells in blue. d Violin plot representing expression of marker genes used for characterization of immune subsets identified in ( b ). e UMAP plots depicting total macrophages in B16F10 tumors (red) and mT4 (blue) to highlight minimal overlap between subsets. Each dot represents a cell. f Distribution of the macrophages across the B16F10 and mT4 tumors depicted in ( e ). g Heatmap of functional markers for the individual macrophage subsets providing phenotypic information. Expression levels are scaled between minimum and maximum expression for each gene across all clusters. h GSEA results depicting differential pathways between mT4 and B16F10 macrophages.

Journal: Nature Communications

Article Title: TSG-6+ cancer-associated fibroblasts modulate myeloid cell responses and impair anti-tumor response to immune checkpoint therapy in pancreatic cancer

doi: 10.1038/s41467-024-49189-x

Figure Lengend Snippet: a Schematic representation of the scRNAseq experimental design created with BioRender.com, released under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International license. b Representative landscape in B16F10 and mT4 tumors. Three tumors in each group were pooled for internal control. All major immune cell subsets were identified. c Cluster frequency plot of each immune subset in B16F10 and mT4 tumors. The T cells are depicted in shades of green, B cells in purple, NK cells in gray, macrophages and monocytes in red, neutrophil in orange, and dendritic cells in blue. d Violin plot representing expression of marker genes used for characterization of immune subsets identified in ( b ). e UMAP plots depicting total macrophages in B16F10 tumors (red) and mT4 (blue) to highlight minimal overlap between subsets. Each dot represents a cell. f Distribution of the macrophages across the B16F10 and mT4 tumors depicted in ( e ). g Heatmap of functional markers for the individual macrophage subsets providing phenotypic information. Expression levels are scaled between minimum and maximum expression for each gene across all clusters. h GSEA results depicting differential pathways between mT4 and B16F10 macrophages.

Article Snippet: mT4 pancreatic cell line was a generous gift from Dr. David A. Tuveson (Cold Spring Harbor Laboratory, NY). mT4 is an organoid cell line generated from mouse pancreata containing PDAC from the Kras LSL-G12D/+ ;Trp53 LSL-R172H/+ ;Pdx1–Cre mouse model under C57BL/6 background . mT4-LS cells were generated and generously gifted by Dr. Michael Curran (The University of Texas MD Anderson Cancer Center, Houston, TX).

Techniques: Control, Expressing, Marker, Functional Assay

a Expression of Cd44 across macrophages present in B16F10 and mT4 tumors. b Violin plot quantifying Cd44 expression in macrophages present in B16F10 and mT4 tumors. c Representative multi-immunofluorescence (mIF) image highlighting co-localization of CD68+ CD44+ CD163+ myeloid cells with TSG-6 (white arrow) in human pancreatic tissue FFPE samples. d Quantification of the mIF images using infiltration analysis technique. Red borders indicate TSG-6+ cells and areas from red to green indicate the increasing distance from the TSG-6+ cells (green being furthest). Percentage of CD68+ CD44+ cells that were at a distance of 0–20 μm (closest) from TSG6+ cells were quantified, and bar plotted ( n = 14 pancreatic tissues; patient characteristics provided in Supplementary Table ). e Quantification of number of CD68+ CD44+ cells that were at a distance of 0–20 μm (closest) from TSG-6+ SMA+ versus TSG-6+ SMA- cells ( n = 10 pancreatic tissues; patient characteristics provided in Supplementary Table ). Each symbol represents a patient. Statistical significance was calculated using Student’s t test (two-tailed). Data are presented as mean values ± SD and p values for each comparison has been indicated in the figure. Source data are provided as a file.

Journal: Nature Communications

Article Title: TSG-6+ cancer-associated fibroblasts modulate myeloid cell responses and impair anti-tumor response to immune checkpoint therapy in pancreatic cancer

doi: 10.1038/s41467-024-49189-x

Figure Lengend Snippet: a Expression of Cd44 across macrophages present in B16F10 and mT4 tumors. b Violin plot quantifying Cd44 expression in macrophages present in B16F10 and mT4 tumors. c Representative multi-immunofluorescence (mIF) image highlighting co-localization of CD68+ CD44+ CD163+ myeloid cells with TSG-6 (white arrow) in human pancreatic tissue FFPE samples. d Quantification of the mIF images using infiltration analysis technique. Red borders indicate TSG-6+ cells and areas from red to green indicate the increasing distance from the TSG-6+ cells (green being furthest). Percentage of CD68+ CD44+ cells that were at a distance of 0–20 μm (closest) from TSG6+ cells were quantified, and bar plotted ( n = 14 pancreatic tissues; patient characteristics provided in Supplementary Table ). e Quantification of number of CD68+ CD44+ cells that were at a distance of 0–20 μm (closest) from TSG-6+ SMA+ versus TSG-6+ SMA- cells ( n = 10 pancreatic tissues; patient characteristics provided in Supplementary Table ). Each symbol represents a patient. Statistical significance was calculated using Student’s t test (two-tailed). Data are presented as mean values ± SD and p values for each comparison has been indicated in the figure. Source data are provided as a file.

Article Snippet: mT4 pancreatic cell line was a generous gift from Dr. David A. Tuveson (Cold Spring Harbor Laboratory, NY). mT4 is an organoid cell line generated from mouse pancreata containing PDAC from the Kras LSL-G12D/+ ;Trp53 LSL-R172H/+ ;Pdx1–Cre mouse model under C57BL/6 background . mT4-LS cells were generated and generously gifted by Dr. Michael Curran (The University of Texas MD Anderson Cancer Center, Houston, TX).

Techniques: Expressing, Immunofluorescence, Two Tailed Test, Comparison

Analysis of the naïve tumor microenvironment of MT4 pancreatic and NDL breast cancer models reveals distinct TMEs and immunological signatures . A-D) Hematoxylin and eosin staining before (A-B) and after (C-D) ablation in MT4 (A, C) and NDL (B, D) models. A) MT4 pancreatic ductal adenocarcinoma has decreased cellularity compared to B) NDL mammary adenocarcinoma, which is comparatively well vascularized (white arrows) with scattered leucocytes (black dots). E-K) Results of single-cell RNA sequencing, including Uniform Manifold Approximation and Projection (UMAP) plots for the MT4 (E) and NDL (F) tumors. B cells (dark pink) were CD19 + , CD79 + and Ly6d + . T cells were CD3e + , with CD8 + (dark blue) and CD4 + (light blue) T cell subsets defined by CD8a and CD4, respectively. NK cells (lavender) were Klrb1b + and Klrb1c + (NK1.1 + ). Eosinophils (yellow) were Siglec-F + . Neutrophils (light orange) were Ly6g + . Monocytes (light pink) were Ly6c + , Ccr2 + , Mrc1 + , and Ccl9 + . Macrophages (green) were Itgam + and Adgre1 + . Dendritic cells (purple) were Itgax + , H2-Ab1 + , Fcgr1 + , Ly6g - , Siglecf - , Klrb1c - . Granulocytes (turquoise) were Tmem189 + , Sap30 + , and Idha + . G) Quantitative summary of immune cells within each tumor model. The MT4 model has a smaller faction of CD8 + T cells, macrophages and NK cells compared to the NDL model. H-K) Gene expression distribution and levels across UMAP cell clusters in the MT4 (H, J) and NDL (I, K) models. In the MT4 model, overall cellular Myd88 expression levels are higher, and CD40 expression is higher in dendritic cell (DC) clusters compared to the NDL model. The MT4 model also has a greater fraction of both CD4 + and CD8 + T cells expressing PD-1, CD8 + T cells expressing CTLA4, and DCs expressing CD40. Scale bars represent 300 µm.

Journal: Theranostics

Article Title: Multiomic analysis for optimization of combined focal and immunotherapy protocols in murine pancreatic cancer

doi: 10.7150/thno.73218

Figure Lengend Snippet: Analysis of the naïve tumor microenvironment of MT4 pancreatic and NDL breast cancer models reveals distinct TMEs and immunological signatures . A-D) Hematoxylin and eosin staining before (A-B) and after (C-D) ablation in MT4 (A, C) and NDL (B, D) models. A) MT4 pancreatic ductal adenocarcinoma has decreased cellularity compared to B) NDL mammary adenocarcinoma, which is comparatively well vascularized (white arrows) with scattered leucocytes (black dots). E-K) Results of single-cell RNA sequencing, including Uniform Manifold Approximation and Projection (UMAP) plots for the MT4 (E) and NDL (F) tumors. B cells (dark pink) were CD19 + , CD79 + and Ly6d + . T cells were CD3e + , with CD8 + (dark blue) and CD4 + (light blue) T cell subsets defined by CD8a and CD4, respectively. NK cells (lavender) were Klrb1b + and Klrb1c + (NK1.1 + ). Eosinophils (yellow) were Siglec-F + . Neutrophils (light orange) were Ly6g + . Monocytes (light pink) were Ly6c + , Ccr2 + , Mrc1 + , and Ccl9 + . Macrophages (green) were Itgam + and Adgre1 + . Dendritic cells (purple) were Itgax + , H2-Ab1 + , Fcgr1 + , Ly6g - , Siglecf - , Klrb1c - . Granulocytes (turquoise) were Tmem189 + , Sap30 + , and Idha + . G) Quantitative summary of immune cells within each tumor model. The MT4 model has a smaller faction of CD8 + T cells, macrophages and NK cells compared to the NDL model. H-K) Gene expression distribution and levels across UMAP cell clusters in the MT4 (H, J) and NDL (I, K) models. In the MT4 model, overall cellular Myd88 expression levels are higher, and CD40 expression is higher in dendritic cell (DC) clusters compared to the NDL model. The MT4 model also has a greater fraction of both CD4 + and CD8 + T cells expressing PD-1, CD8 + T cells expressing CTLA4, and DCs expressing CD40. Scale bars represent 300 µm.

Article Snippet: The murine MT4 (Kras +/LSL-G12D ; Trp53 +/LSL-R172H ; Pdx1-Cre) metastatic pancreatic cancer cell line was obtained from Dr. David Tuveson (Cold Spring Harbor Laboratory Cancer Center, Cold Spring Harbor, NY).

Techniques: Staining, RNA Sequencing, Gene Expression, Expressing

Ablation or agonist CD40 (aCD40) treatment combined with aPD-1 has reduced, but immune-targeted, effects on gene expression in MT4 pancreatic tumors as compared with highly-differentiated NDL breast tumors. Two-component treatment protocols of aPD-1 + ablation (n=4, treated tumor, (A-aPD-1-T)) or aCD40 + aPD-1 (n=3 or 4, aCD40-aPD-1) were delivered as a one-time treatment to MT4 (B-E) or NDL (F-I) tumor-bearing mice and compared with a no treatment cohort (n=4). A) Protocol and processing methodology. B-E) Changes in gene expression and ontologies in the MT4 model after (B, D) aPD-1 combined with ablation (A-aPD-1-T) or (C, E) aPD-1 combined with aCD40 (aCD40-aPD-1) treatment. Gene ontologies increased by A-PD-1-T: leukocyte migration and chemotaxis; by aCD40-aPD-1: leukocyte and receptor activation. In the NDL model, aPD-1 was combined with (F, H) ablation or (G, I) aCD40. In the NDL model, gene ontologies increased by A-PD-1-T: wound healing; by aCD40-aPD-1: leukocyte migration, cell adhesion and chemotaxis. Differential expression based on comparison to no treatment control is displayed for an adjusted p value < 0.05 and a fold change > 2, and the changes were subsequently used for gene ontology analysis.

Journal: Theranostics

Article Title: Multiomic analysis for optimization of combined focal and immunotherapy protocols in murine pancreatic cancer

doi: 10.7150/thno.73218

Figure Lengend Snippet: Ablation or agonist CD40 (aCD40) treatment combined with aPD-1 has reduced, but immune-targeted, effects on gene expression in MT4 pancreatic tumors as compared with highly-differentiated NDL breast tumors. Two-component treatment protocols of aPD-1 + ablation (n=4, treated tumor, (A-aPD-1-T)) or aCD40 + aPD-1 (n=3 or 4, aCD40-aPD-1) were delivered as a one-time treatment to MT4 (B-E) or NDL (F-I) tumor-bearing mice and compared with a no treatment cohort (n=4). A) Protocol and processing methodology. B-E) Changes in gene expression and ontologies in the MT4 model after (B, D) aPD-1 combined with ablation (A-aPD-1-T) or (C, E) aPD-1 combined with aCD40 (aCD40-aPD-1) treatment. Gene ontologies increased by A-PD-1-T: leukocyte migration and chemotaxis; by aCD40-aPD-1: leukocyte and receptor activation. In the NDL model, aPD-1 was combined with (F, H) ablation or (G, I) aCD40. In the NDL model, gene ontologies increased by A-PD-1-T: wound healing; by aCD40-aPD-1: leukocyte migration, cell adhesion and chemotaxis. Differential expression based on comparison to no treatment control is displayed for an adjusted p value < 0.05 and a fold change > 2, and the changes were subsequently used for gene ontology analysis.

Article Snippet: The murine MT4 (Kras +/LSL-G12D ; Trp53 +/LSL-R172H ; Pdx1-Cre) metastatic pancreatic cancer cell line was obtained from Dr. David Tuveson (Cold Spring Harbor Laboratory Cancer Center, Cold Spring Harbor, NY).

Techniques: Gene Expression, Migration, Chemotaxis Assay, Activation Assay, Quantitative Proteomics, Comparison, Control

Comparing digital cytometry results for two-component treatment with aCD40 + aPD-1 or ablation + aPD-1 in the MT4 pancreatic and NDL breast cancer models. aCD40 + aPD-1 increases leukocytes and activated dendritic cell numbers. Digital cytometry was applied to bulk RNA sequencing data acquired in the MT4 and NDL models under the protocol in Figure A. A-C) MT4 model. D-F) NDL model. A, D) CIBERSORTx absolute score. B, E) Fold change from the no treatment control (NTC) cohort, plotted between ablation + aPD-1 in the directly-ablated tumor (A-aPD-1-T) and aCD40 + aPD-1 (aCD40-aPD-1). C, F) Fold change from the NTC cohort, plotted between ablation + aPD-1 in the distant tumor (A-aPD-1-C) and aCD40 + aPD-1 (aCD40-aPD-1). Note that log ratios are based on CIBERSORTx absolute scores. RNAseq experiments were performed with n = 4 replicates with a negative binomial test and Bonferroni correction for p values. Expression of genes in the grey region of E-F was zero in the NTC. Abbreviations: Mast cells (MCs), Polymorphonuclear leukocytes (PMN).

Journal: Theranostics

Article Title: Multiomic analysis for optimization of combined focal and immunotherapy protocols in murine pancreatic cancer

doi: 10.7150/thno.73218

Figure Lengend Snippet: Comparing digital cytometry results for two-component treatment with aCD40 + aPD-1 or ablation + aPD-1 in the MT4 pancreatic and NDL breast cancer models. aCD40 + aPD-1 increases leukocytes and activated dendritic cell numbers. Digital cytometry was applied to bulk RNA sequencing data acquired in the MT4 and NDL models under the protocol in Figure A. A-C) MT4 model. D-F) NDL model. A, D) CIBERSORTx absolute score. B, E) Fold change from the no treatment control (NTC) cohort, plotted between ablation + aPD-1 in the directly-ablated tumor (A-aPD-1-T) and aCD40 + aPD-1 (aCD40-aPD-1). C, F) Fold change from the NTC cohort, plotted between ablation + aPD-1 in the distant tumor (A-aPD-1-C) and aCD40 + aPD-1 (aCD40-aPD-1). Note that log ratios are based on CIBERSORTx absolute scores. RNAseq experiments were performed with n = 4 replicates with a negative binomial test and Bonferroni correction for p values. Expression of genes in the grey region of E-F was zero in the NTC. Abbreviations: Mast cells (MCs), Polymorphonuclear leukocytes (PMN).

Article Snippet: The murine MT4 (Kras +/LSL-G12D ; Trp53 +/LSL-R172H ; Pdx1-Cre) metastatic pancreatic cancer cell line was obtained from Dr. David Tuveson (Cold Spring Harbor Laboratory Cancer Center, Cold Spring Harbor, NY).

Techniques: Cytometry, RNA Sequencing, Control, Expressing

Applying spectral cytometry to phenotype individual immune cells following treatment combinations of aCD40 and checkpoint inhibitors in the MT4 tumor model revealed mobilized monocytes and increased T-cell and NK-cell effector phenotypes. MT4 tumor-bearing mice were treated based on the protocol in Figure A, comparing a one-time injection of aCD40 to an injection of aCD40 combined with the checkpoint inhibitors aPD-1 and aCTLA-4 (denoted CP4), or aPD-1 and aCTLA-4 alone, using spectral cytometry at 72 hrs. A) Master pseudocolor UMAP and its annotated version (750,000 total events) for the no treatment control (NTC) (n = 5 tumors) (n = 5 tumors), aCD40 (n = 4 tumors), and CP4 treatments (n = 3 tumors) (250,000 events for each treatment evenly distributed among tumor replicates). Combinations of markers used to label each subset are described in the caption for A. B) NTC MT4 scRNA-seq plot annotated using a similar number of the same parameters as used in spectral cytometry. C) Pseudocolor UMAP subplots (NTC and CP4 separately) and Ly6C overlay (NTC and CP4 combined), each derived from the master UMAP (250,000 events for each treatment subplot, 500,000 for Ly6C overlay). The colorbar represents Ly6C expression, where red is high and blue is low to zero.D) Major immune subsets as a percentage of non-granulocyte leukocytes (live, CD45 + Siglec-F - Ly6G - ) or lineage- leukocytes (live, CD45 + Siglec-F - Ly6G - CD64 - ). E) Representative pseudocolor dot plots of monocyte populations in response to NTC, aPD-1 + aCTLA-4, aCD40, and CP4 treatment (22,831 events each) with Ly6C - BV605 median fluorescence intensity of each subset. The two monocyte populations were distinguished by I-A/I-E presence (inflammatory monocytes were I-A/I-E - and differentiating monocytes were I-A/I-E + ) F) T cells (39,220 events each) and G) NK cells (7,971 events each) with respective subsets as a percentage of total T cells or NK cells. The two monocyte populations were differentiated by I-A/I-E presence (inflammatory monocytes were I-A/I-E - and differentiating monocytes were I-A/I-E + ). Data in D, E, F, and G are presented as mean ± SD. Statistical analyses were performed using one-way ANOVA with Tukey's multiple comparisons test. ns = non-significant, * = p < 0.05, ** = p < 0.01, *** = p < 0.001, **** = p < 0.0001.

Journal: Theranostics

Article Title: Multiomic analysis for optimization of combined focal and immunotherapy protocols in murine pancreatic cancer

doi: 10.7150/thno.73218

Figure Lengend Snippet: Applying spectral cytometry to phenotype individual immune cells following treatment combinations of aCD40 and checkpoint inhibitors in the MT4 tumor model revealed mobilized monocytes and increased T-cell and NK-cell effector phenotypes. MT4 tumor-bearing mice were treated based on the protocol in Figure A, comparing a one-time injection of aCD40 to an injection of aCD40 combined with the checkpoint inhibitors aPD-1 and aCTLA-4 (denoted CP4), or aPD-1 and aCTLA-4 alone, using spectral cytometry at 72 hrs. A) Master pseudocolor UMAP and its annotated version (750,000 total events) for the no treatment control (NTC) (n = 5 tumors) (n = 5 tumors), aCD40 (n = 4 tumors), and CP4 treatments (n = 3 tumors) (250,000 events for each treatment evenly distributed among tumor replicates). Combinations of markers used to label each subset are described in the caption for A. B) NTC MT4 scRNA-seq plot annotated using a similar number of the same parameters as used in spectral cytometry. C) Pseudocolor UMAP subplots (NTC and CP4 separately) and Ly6C overlay (NTC and CP4 combined), each derived from the master UMAP (250,000 events for each treatment subplot, 500,000 for Ly6C overlay). The colorbar represents Ly6C expression, where red is high and blue is low to zero.D) Major immune subsets as a percentage of non-granulocyte leukocytes (live, CD45 + Siglec-F - Ly6G - ) or lineage- leukocytes (live, CD45 + Siglec-F - Ly6G - CD64 - ). E) Representative pseudocolor dot plots of monocyte populations in response to NTC, aPD-1 + aCTLA-4, aCD40, and CP4 treatment (22,831 events each) with Ly6C - BV605 median fluorescence intensity of each subset. The two monocyte populations were distinguished by I-A/I-E presence (inflammatory monocytes were I-A/I-E - and differentiating monocytes were I-A/I-E + ) F) T cells (39,220 events each) and G) NK cells (7,971 events each) with respective subsets as a percentage of total T cells or NK cells. The two monocyte populations were differentiated by I-A/I-E presence (inflammatory monocytes were I-A/I-E - and differentiating monocytes were I-A/I-E + ). Data in D, E, F, and G are presented as mean ± SD. Statistical analyses were performed using one-way ANOVA with Tukey's multiple comparisons test. ns = non-significant, * = p < 0.05, ** = p < 0.01, *** = p < 0.001, **** = p < 0.0001.

Article Snippet: The murine MT4 (Kras +/LSL-G12D ; Trp53 +/LSL-R172H ; Pdx1-Cre) metastatic pancreatic cancer cell line was obtained from Dr. David Tuveson (Cold Spring Harbor Laboratory Cancer Center, Cold Spring Harbor, NY).

Techniques: Cytometry, Injection, Control, Derivative Assay, Expressing, Fluorescence

Journal: Theranostics

Article Title: Multiomic analysis for optimization of combined focal and immunotherapy protocols in murine pancreatic cancer

doi: 10.7150/thno.73218

Figure Lengend Snippet: Summary results for spectral cytometry studies in the MT4 tumor model.

Article Snippet: The murine MT4 (Kras +/LSL-G12D ; Trp53 +/LSL-R172H ; Pdx1-Cre) metastatic pancreatic cancer cell line was obtained from Dr. David Tuveson (Cold Spring Harbor Laboratory Cancer Center, Cold Spring Harbor, NY).

Techniques: Cytometry

Digital cytometry analysis in the MT4 model demonstrates the enhanced immune activation resulting from a four-component treatment combining ablation with CP4 (aCD40 + aPD-1 + aCTLA-4). A) Treatment protocol. Mice were treated with two doses of checkpoint inhibition priming prior to an application of checkpoint inhibitors with aCD40 and ablation each added in a subset of mice (n=4 each group) and compared to no treatment control (NTC) mice (n=4). Bulk RNA sequencing was performed 72 hrs after ablation. B-E) Volcano plots showing gene expression response to treatment combinations. B) Ablation + aPD-1 in the distant tumor (A-aPD-1-C) altered expression of 50 genes. C) CP4 altered expression of 285 genes. D-E) Ablation + CP4 resulted in D) 1379 differentially expressed genes in the treated (A-CP4-T) tumor and E) 475 differentially expressed genes in the distant (A-CP4-C) tumor. F) Ablation + CP4 upregulated genes in key immune pathways such as the adaptive immune (GO:0002819), innate immune (GO:0045088) and toll-like receptor (TLR) (GO:0002224) pathways and downregulated the Kras cancer gene in both the treated and contralateral tumors to a greater degree than systemic CP4 treatment alone. G-J) Digital cytometry was applied to bulk RNA sequencing data. Fold change from the NTC is plotted between ablation + CP4 in the ablated tumor (A-CP4-T) versus G) CP4, H) ablation + CP4 in the distant tumor (A-CP4-C), I) ablation-only in the treated tumor (A-T), and J) ablation-only in the distant tumor (A-C). Ablation + CP4 stimulated immune cell changes in both the treated and distant tumor sites, increasing CD4 + T cells and dendritic cell and NK-cell activation.

Journal: Theranostics

Article Title: Multiomic analysis for optimization of combined focal and immunotherapy protocols in murine pancreatic cancer

doi: 10.7150/thno.73218

Figure Lengend Snippet: Digital cytometry analysis in the MT4 model demonstrates the enhanced immune activation resulting from a four-component treatment combining ablation with CP4 (aCD40 + aPD-1 + aCTLA-4). A) Treatment protocol. Mice were treated with two doses of checkpoint inhibition priming prior to an application of checkpoint inhibitors with aCD40 and ablation each added in a subset of mice (n=4 each group) and compared to no treatment control (NTC) mice (n=4). Bulk RNA sequencing was performed 72 hrs after ablation. B-E) Volcano plots showing gene expression response to treatment combinations. B) Ablation + aPD-1 in the distant tumor (A-aPD-1-C) altered expression of 50 genes. C) CP4 altered expression of 285 genes. D-E) Ablation + CP4 resulted in D) 1379 differentially expressed genes in the treated (A-CP4-T) tumor and E) 475 differentially expressed genes in the distant (A-CP4-C) tumor. F) Ablation + CP4 upregulated genes in key immune pathways such as the adaptive immune (GO:0002819), innate immune (GO:0045088) and toll-like receptor (TLR) (GO:0002224) pathways and downregulated the Kras cancer gene in both the treated and contralateral tumors to a greater degree than systemic CP4 treatment alone. G-J) Digital cytometry was applied to bulk RNA sequencing data. Fold change from the NTC is plotted between ablation + CP4 in the ablated tumor (A-CP4-T) versus G) CP4, H) ablation + CP4 in the distant tumor (A-CP4-C), I) ablation-only in the treated tumor (A-T), and J) ablation-only in the distant tumor (A-C). Ablation + CP4 stimulated immune cell changes in both the treated and distant tumor sites, increasing CD4 + T cells and dendritic cell and NK-cell activation.

Article Snippet: The murine MT4 (Kras +/LSL-G12D ; Trp53 +/LSL-R172H ; Pdx1-Cre) metastatic pancreatic cancer cell line was obtained from Dr. David Tuveson (Cold Spring Harbor Laboratory Cancer Center, Cold Spring Harbor, NY).

Techniques: Cytometry, Activation Assay, Inhibition, Control, RNA Sequencing, Gene Expression, Expressing

Combination of ablation with CP4 in the MT4 tumor model generates a systemic anti-tumor effect. Tumor growth from the protocols shown in Figure A (n=4 for treatments and n=3 for the no treatment control (NTC) cohort). A) Survival for NTC, Ablation alone, Ablation + aPD-1, Ablation + aCTLA-4, Ablation + aCD40, CP4 alone, Ablation + CP4 cohorts. B-G) Tumor growth for B) NTC, C) CP4, D) Ablation in the treated tumor, E) Ablation in the distant tumor, F-G) Ablation + CP4 in the treated (F) and distant (G) tumor. Tumor volume plots are provided in . H) Cox-hazard analysis comparing cells to survival outlined the importance of activated dendritic cells. I) Pearson correlation analysis indicated high correlations between 1) survival and dendritic cell (DC) activation, 2) NK cells and CD4 + T cells and 3) plasma cells (PCs) and dendritic cell activation.

Journal: Theranostics

Article Title: Multiomic analysis for optimization of combined focal and immunotherapy protocols in murine pancreatic cancer

doi: 10.7150/thno.73218

Figure Lengend Snippet: Combination of ablation with CP4 in the MT4 tumor model generates a systemic anti-tumor effect. Tumor growth from the protocols shown in Figure A (n=4 for treatments and n=3 for the no treatment control (NTC) cohort). A) Survival for NTC, Ablation alone, Ablation + aPD-1, Ablation + aCTLA-4, Ablation + aCD40, CP4 alone, Ablation + CP4 cohorts. B-G) Tumor growth for B) NTC, C) CP4, D) Ablation in the treated tumor, E) Ablation in the distant tumor, F-G) Ablation + CP4 in the treated (F) and distant (G) tumor. Tumor volume plots are provided in . H) Cox-hazard analysis comparing cells to survival outlined the importance of activated dendritic cells. I) Pearson correlation analysis indicated high correlations between 1) survival and dendritic cell (DC) activation, 2) NK cells and CD4 + T cells and 3) plasma cells (PCs) and dendritic cell activation.

Article Snippet: The murine MT4 (Kras +/LSL-G12D ; Trp53 +/LSL-R172H ; Pdx1-Cre) metastatic pancreatic cancer cell line was obtained from Dr. David Tuveson (Cold Spring Harbor Laboratory Cancer Center, Cold Spring Harbor, NY).

Techniques: Control, Activation Assay, Clinical Proteomics

In vitro release of IFN-α (A), IFN-β (B) in NDL and 4T1 murine mammary carcinoma, mT4 murine pancreatic cancer, MC-38 murine colon cancer cells, B16 murine melanoma, and HMGB 1 in NDL cell culture 24 h post treatment, respectively. Cells were preincubated for 5 min (type I IFN) or 1 min (HMGB 1) at 42°C prior to addition of media only (42°C) or a solution of 5 µg/mL Dox in media (Free Dox+42°C) at 42°C for another 5 min. * p < 0.05, ** p< 0.01, *** p< 0.001, **** p< 0.0001.

Journal: Journal of controlled release : official journal of the Controlled Release Society

Article Title: Combining activatable nanodelivery with immunotherapy in a murine breast cancer model

doi: 10.1016/j.jconrel.2019.04.008

Figure Lengend Snippet: In vitro release of IFN-α (A), IFN-β (B) in NDL and 4T1 murine mammary carcinoma, mT4 murine pancreatic cancer, MC-38 murine colon cancer cells, B16 murine melanoma, and HMGB 1 in NDL cell culture 24 h post treatment, respectively. Cells were preincubated for 5 min (type I IFN) or 1 min (HMGB 1) at 42°C prior to addition of media only (42°C) or a solution of 5 µg/mL Dox in media (Free Dox+42°C) at 42°C for another 5 min. * p < 0.05, ** p< 0.01, *** p< 0.001, **** p< 0.0001.

Article Snippet: The mT4 syngeneic mouse KPC pancreatic cancer cell line was isolated from KPC tumors derived from KPC-B6 background mice (Kras +/LSL-G12D ; p53 +/LSL-R172H ; PDX-Cre) and was a generous gift from Dr. David Tuveson (Cold Spring Harbor Laboratory, Cold Spring Harbor, NY).

Techniques: In Vitro, Cell Culture