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P Erk1 2, supplied by Cell Signaling Technology 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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( A ) UMAP plot of ∼18,000 cochlear cells from P28 mice organized into 19 cell-type clusters. Abbreviations: Inner Hair Cells (IHCs), Outer Hair Cells (OHCs), Hemoglobin-positive cells (HB+), Inner Sulcus/ Outer Sulcus (IS/OS), Reissner’s Membrane (RM), Spiral Ganglion Neurons (SGNs), Tympanic Boarder Cells (TBCs). ( B ) Feature plots showing the expression of Braf, Map2k1 (MEK1), Map2k2 (MEK2), Mapk3 <t>(ERK1),</t> Mapk1 (ERK2), Ksr1, and Ksr2 genes for the same cells in (A). ( C ) Violin plots showing median gene expression from (B) across cell-type clusters.

Anti P Erk1 2, supplied by Cell Signaling Technology 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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1) Product Images from "KSR1 knockout mouse model demonstrates MAPK pathway’s key role in cisplatin- and noise-induced hearing loss"

Article Title: KSR1 knockout mouse model demonstrates MAPK pathway’s key role in cisplatin- and noise-induced hearing loss

Journal: bioRxiv

doi: 10.1101/2023.11.08.566316

Figure Legend Snippet: ( A ) UMAP plot of ∼18,000 cochlear cells from P28 mice organized into 19 cell-type clusters. Abbreviations: Inner Hair Cells (IHCs), Outer Hair Cells (OHCs), Hemoglobin-positive cells (HB+), Inner Sulcus/ Outer Sulcus (IS/OS), Reissner’s Membrane (RM), Spiral Ganglion Neurons (SGNs), Tympanic Boarder Cells (TBCs). ( B ) Feature plots showing the expression of Braf, Map2k1 (MEK1), Map2k2 (MEK2), Mapk3 (ERK1), Mapk1 (ERK2), Ksr1, and Ksr2 genes for the same cells in (A). ( C ) Violin plots showing median gene expression from (B) across cell-type clusters.

Techniques Used: Membrane, Expressing

Cisplatin or noise exposure leads to phosphorylation and activation of BRAF at S445. KSR1, a scaffolding protein which binds MEK and ERK in the cytoplasm, then dimerizes with activated BRAF on the plasma membrane to colocalize all three kinases. BRAF then phosphorylates and activates MEK1/2 at S217/221, and MEK phosphorylates and activates ERK1/2 at T202/Y204 which leads to permanent hearing loss. In the present study, we demonstrate disruption of the MAPK pathway, by inhibition of BRAF with dabrafenib or genetic KO of KSR1, significantly reduces hearing loss caused by cisplatin or noise exposure

Figure Legend Snippet: Cisplatin or noise exposure leads to phosphorylation and activation of BRAF at S445. KSR1, a scaffolding protein which binds MEK and ERK in the cytoplasm, then dimerizes with activated BRAF on the plasma membrane to colocalize all three kinases. BRAF then phosphorylates and activates MEK1/2 at S217/221, and MEK phosphorylates and activates ERK1/2 at T202/Y204 which leads to permanent hearing loss. In the present study, we demonstrate disruption of the MAPK pathway, by inhibition of BRAF with dabrafenib or genetic KO of KSR1, significantly reduces hearing loss caused by cisplatin or noise exposure

Techniques Used: Activation Assay, Scaffolding, Membrane, Disruption, Inhibition

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Cell Signaling Technology Inc phosphorylated p erk1 2
Phosphorylated P Erk1 2, supplied by Cell Signaling Technology 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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Anti P Erk1 2, supplied by Cell Signaling Technology 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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Anti-inflammatory mechanism of CeO 2 @RSV evaluated by transcriptome. A Volcano plots showing the genes regulated by treatment with CeO 2 @RSV. B Clustered heatmap of representative inflammation-related genes (fold change ≥ 2.0 and p < 0.05). C Bar plot of biological processes of differentially expressed genes between the M1 and CeO 2 @RSV groups. D KEGG pathway enrichment analysis of the differentially expressed genes between the M1 and CeO 2 @RSV groups. E The protein expression of STAT3/p-STAT3, <t>NF-κB/p-NF-κB,</t> <t>Erk1/2/p-Erk1/2,</t> and MAPK/p-MAPK was detected by western blotting. n = 3, * P < 0.05, ** P < 0.01, *** P < 0.001 vs. the M1 group

P Erk1 2, supplied by Cell Signaling Technology 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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1) Product Images from "Nanocomposites based on nanoceria regulate the immune microenvironment for the treatment of polycystic ovary syndrome"

Article Title: Nanocomposites based on nanoceria regulate the immune microenvironment for the treatment of polycystic ovary syndrome

Journal: Journal of Nanobiotechnology

doi: 10.1186/s12951-023-02182-w

Figure Legend Snippet: Anti-inflammatory mechanism of CeO 2 @RSV evaluated by transcriptome. A Volcano plots showing the genes regulated by treatment with CeO 2 @RSV. B Clustered heatmap of representative inflammation-related genes (fold change ≥ 2.0 and p < 0.05). C Bar plot of biological processes of differentially expressed genes between the M1 and CeO 2 @RSV groups. D KEGG pathway enrichment analysis of the differentially expressed genes between the M1 and CeO 2 @RSV groups. E The protein expression of STAT3/p-STAT3, NF-κB/p-NF-κB, Erk1/2/p-Erk1/2, and MAPK/p-MAPK was detected by western blotting. n = 3, * P < 0.05, ** P < 0.01, *** P < 0.001 vs. the M1 group

Techniques Used: Expressing, Western Blot

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sEH deficiency inhibited CSE-induced activation of the IRE1α/JNK/AP-1 pathway in BEAS-2B cells. ( A-G ) Western blotting evaluating the effect of si-sEH on the protein expression of GRP78, IRE1α, p-IRE1α, JNK, p-JNK, p38, <t>p-p38,</t> <t>ERK1/2,</t> p-ERK1/2 and AP-1 in BEAS-2B cells after stimulation with CSE. ( H-J ) Immunofluorescence was used to determine the p-IRE1α, p-JNK and AP-1expression in each group. Data represent the mean ± SD. * P < 0.05, *** P < 0.001

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1) Product Images from "Soluble epoxide hydrolase deficiency attenuates airway inflammation in COPD via IRE1α/JNK/AP-1 signaling pathway"

Article Title: Soluble epoxide hydrolase deficiency attenuates airway inflammation in COPD via IRE1α/JNK/AP-1 signaling pathway

Journal: Journal of Inflammation (London, England)

doi: 10.1186/s12950-023-00361-y

Figure Legend Snippet: sEH deficiency inhibited CSE-induced activation of the IRE1α/JNK/AP-1 pathway in BEAS-2B cells. ( A-G ) Western blotting evaluating the effect of si-sEH on the protein expression of GRP78, IRE1α, p-IRE1α, JNK, p-JNK, p38, p-p38, ERK1/2, p-ERK1/2 and AP-1 in BEAS-2B cells after stimulation with CSE. ( H-J ) Immunofluorescence was used to determine the p-IRE1α, p-JNK and AP-1expression in each group. Data represent the mean ± SD. * P < 0.05, *** P < 0.001

Techniques Used: Activation Assay, Western Blot, Expressing, Immunofluorescence

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A. Representative IHC images of C-MYC, P53, PTEN and <t>phospho-ERK1/2</t> staining performed on liver sections from genetically-distinct HCC-bearing and control mice. Scale bars = 100 µm. B. T2-weighted MRI scans illustrating the penetrance of HCC induction, the tumor latency and growth in the genetically-distinct HCC models. Tumors were monitored weekly/bi-weekly one-week post-HDTVi. Red lines indicate the regions of interest used to calculate the tumor volumes (see Methods ) presented in . C. Kaplan–Meier survival curves of HCC-bearing mice HDTV injected with Nras G12D / Pten KO (n=15; median survival of 62 days shown in ), and pT3- Nras G12V / Pten KO oncogenic drivers (n=8; median survival of 230 days). D. Representative IHC images of Arginase-1 performed on liver sections from genetically-distinct end-stage HCC-bearing mice. E. Barplot depicting the histopathology scoring of Arginase-1 expression assessed in genetically-distinct, end-stage HCC (presented in ( D ); n=3 for all HCC models). F. Barplot depicting AFP quantification performed in the sera of control and genetically-distinct HCC-bearing mice at intermediate stage; (n=3 for all HCC models). G. Barplot showing Afp gene expression in control and genetically-distinct end-stage HCC from the bulk RNA-seq; (n=3 for all HCC models). H. Barplot depicting ALT activity in the sera of control and genetically-distinct HCC- bearing mice; ( Myc OE / Trp53 KO intermediate [Int] n = 5 and end [End]-stage n = 4, Myc OE / Pten KO Int n= 3 and End n = 4, Nras G12D / Pten KO Int n= 7 and End n = 4, Nras G12V / Pten KO Int n= 6 and End n = 8 (see Methods for intermediate and end-stage definition). I. Representative images of H&E and Oil Red staining performed on sectioned livers collected from end-stage pT3-Nras G12V / Pten KO tumor-bearing mice. Scale bars = 100 µm. J. Barplot depicting the differentiation status of genetically-distinct end-stage HCC tumors according to the 2019 WHO classification histopathology grading guidelines (see Methods ); (n=3 for all HCC models). K. Heatmap of unsupervised hierarchical clustering depicting the Pearson correlation calculated from the normalized Transcripts per Million (TPMs) of the genetically-distinct HCC tumors and control (n=3 for all HCC models). Squares represents Nras G12V /Pten KO and circles represents pT3- Nras G12V /Pten KO . L. Heatmap of unsupervised hierarchical clustering depicting the geneset enrichment of the MAPK, PI3K and MYC signaling pathways in Nras G12D / Pten KO (shown in ) and pT3- Nras G12V / Pten KO HCCs compared to control. The color scale represents the significance of the enrichment in –log10(FDR). FDR False Discovery Rate. Graphs show the mean ± SEM ( E-H, J ). Statistical significance was determined by one-way ANOVA with Tukey’s multiple comparison test ( E, J ), differential expression analyses ( G ) and unpaired Student’s t -test in ( F, H ). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

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1) Product Images from "Cancer cell genetics shaping of the tumor microenvironment reveals myeloid cell-centric exploitable vulnerabilities in hepatocellular carcinoma"

Article Title: Cancer cell genetics shaping of the tumor microenvironment reveals myeloid cell-centric exploitable vulnerabilities in hepatocellular carcinoma

Journal: bioRxiv

doi: 10.1101/2023.10.29.564350

A. Representative IHC images of C-MYC, P53, PTEN and phospho-ERK1/2 staining performed on liver sections from genetically-distinct HCC-bearing and control mice. Scale bars = 100 µm. B. T2-weighted MRI scans illustrating the penetrance of HCC induction, the tumor latency and growth in the genetically-distinct HCC models. Tumors were monitored weekly/bi-weekly one-week post-HDTVi. Red lines indicate the regions of interest used to calculate the tumor volumes (see Methods ) presented in . C. Kaplan–Meier survival curves of HCC-bearing mice HDTV injected with Nras G12D / Pten KO (n=15; median survival of 62 days shown in ), and pT3- Nras G12V / Pten KO oncogenic drivers (n=8; median survival of 230 days). D. Representative IHC images of Arginase-1 performed on liver sections from genetically-distinct end-stage HCC-bearing mice. E. Barplot depicting the histopathology scoring of Arginase-1 expression assessed in genetically-distinct, end-stage HCC (presented in ( D ); n=3 for all HCC models). F. Barplot depicting AFP quantification performed in the sera of control and genetically-distinct HCC-bearing mice at intermediate stage; (n=3 for all HCC models). G. Barplot showing Afp gene expression in control and genetically-distinct end-stage HCC from the bulk RNA-seq; (n=3 for all HCC models). H. Barplot depicting ALT activity in the sera of control and genetically-distinct HCC- bearing mice; ( Myc OE / Trp53 KO intermediate [Int] n = 5 and end [End]-stage n = 4, Myc OE / Pten KO Int n= 3 and End n = 4, Nras G12D / Pten KO Int n= 7 and End n = 4, Nras G12V / Pten KO Int n= 6 and End n = 8 (see Methods for intermediate and end-stage definition). I. Representative images of H&E and Oil Red staining performed on sectioned livers collected from end-stage pT3-Nras G12V / Pten KO tumor-bearing mice. Scale bars = 100 µm. J. Barplot depicting the differentiation status of genetically-distinct end-stage HCC tumors according to the 2019 WHO classification histopathology grading guidelines (see Methods ); (n=3 for all HCC models). K. Heatmap of unsupervised hierarchical clustering depicting the Pearson correlation calculated from the normalized Transcripts per Million (TPMs) of the genetically-distinct HCC tumors and control (n=3 for all HCC models). Squares represents Nras G12V /Pten KO and circles represents pT3- Nras G12V /Pten KO . L. Heatmap of unsupervised hierarchical clustering depicting the geneset enrichment of the MAPK, PI3K and MYC signaling pathways in Nras G12D / Pten KO (shown in ) and pT3- Nras G12V / Pten KO HCCs compared to control. The color scale represents the significance of the enrichment in –log10(FDR). FDR False Discovery Rate. Graphs show the mean ± SEM ( E-H, J ). Statistical significance was determined by one-way ANOVA with Tukey’s multiple comparison test ( E, J ), differential expression analyses ( G ) and unpaired Student’s t -test in ( F, H ). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

Figure Legend Snippet: A. Representative IHC images of C-MYC, P53, PTEN and phospho-ERK1/2 staining performed on liver sections from genetically-distinct HCC-bearing and control mice. Scale bars = 100 µm. B. T2-weighted MRI scans illustrating the penetrance of HCC induction, the tumor latency and growth in the genetically-distinct HCC models. Tumors were monitored weekly/bi-weekly one-week post-HDTVi. Red lines indicate the regions of interest used to calculate the tumor volumes (see Methods ) presented in . C. Kaplan–Meier survival curves of HCC-bearing mice HDTV injected with Nras G12D / Pten KO (n=15; median survival of 62 days shown in ), and pT3- Nras G12V / Pten KO oncogenic drivers (n=8; median survival of 230 days). D. Representative IHC images of Arginase-1 performed on liver sections from genetically-distinct end-stage HCC-bearing mice. E. Barplot depicting the histopathology scoring of Arginase-1 expression assessed in genetically-distinct, end-stage HCC (presented in ( D ); n=3 for all HCC models). F. Barplot depicting AFP quantification performed in the sera of control and genetically-distinct HCC-bearing mice at intermediate stage; (n=3 for all HCC models). G. Barplot showing Afp gene expression in control and genetically-distinct end-stage HCC from the bulk RNA-seq; (n=3 for all HCC models). H. Barplot depicting ALT activity in the sera of control and genetically-distinct HCC- bearing mice; ( Myc OE / Trp53 KO intermediate [Int] n = 5 and end [End]-stage n = 4, Myc OE / Pten KO Int n= 3 and End n = 4, Nras G12D / Pten KO Int n= 7 and End n = 4, Nras G12V / Pten KO Int n= 6 and End n = 8 (see Methods for intermediate and end-stage definition). I. Representative images of H&E and Oil Red staining performed on sectioned livers collected from end-stage pT3-Nras G12V / Pten KO tumor-bearing mice. Scale bars = 100 µm. J. Barplot depicting the differentiation status of genetically-distinct end-stage HCC tumors according to the 2019 WHO classification histopathology grading guidelines (see Methods ); (n=3 for all HCC models). K. Heatmap of unsupervised hierarchical clustering depicting the Pearson correlation calculated from the normalized Transcripts per Million (TPMs) of the genetically-distinct HCC tumors and control (n=3 for all HCC models). Squares represents Nras G12V /Pten KO and circles represents pT3- Nras G12V /Pten KO . L. Heatmap of unsupervised hierarchical clustering depicting the geneset enrichment of the MAPK, PI3K and MYC signaling pathways in Nras G12D / Pten KO (shown in ) and pT3- Nras G12V / Pten KO HCCs compared to control. The color scale represents the significance of the enrichment in –log10(FDR). FDR False Discovery Rate. Graphs show the mean ± SEM ( E-H, J ). Statistical significance was determined by one-way ANOVA with Tukey’s multiple comparison test ( E, J ), differential expression analyses ( G ) and unpaired Student’s t -test in ( F, H ). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

Techniques Used: Staining, Injection, Histopathology, Expressing, RNA Sequencing Assay, Activity Assay, Comparison

A. Venn diagram of the differentially expressed genes (DEG) between genetically-distinct HCC and control livers as determined in RNA-seq analyses (see Supplementary Table 1 ). B. Scatterplots depicting the correlation in global gene expression between TCGA- LIHC patients and each of the genetically-distinct HCC tumors. TCGA-LIHC patients were divided according to their TCGA classification . C. Boxplots depicting the enrichment of the MYC, MAPK and PI3K/mTOR signaling pathways in patients segregated according to their high/low correlation with each of the genetically-distinct HCC bulk tumor transcriptional signatures from (sample size n=93 for each set of patients). D. Violin plots depicting the tumor mutational burden (TMB) of genetically-distinct HCC compared to human LIHC (n= 723), as determined by whole exome sequencing analyses of bulk tumors (n=3 per genotype) (see Supplementary Table 3 ). E. Donut charts of the variant type distribution of mutations of genetically-distinct HCC (n=3 per genotype) compared to TCGA-LIHC (n= 371). SNP: single nucleotide polymorphism. MNP: multiple nucleotide polymorphism. F. Kaplan-Meier curves displaying the overall survival and recurrence-free survival of HCC patients (from the Wu et al . dataset ) segregated according to p-ERK1/2 and c- MYC positive or negative staining in cancer cells (see Supplementary Table 4 for median OS and RFS time). Statistical significance was determined by unpaired Student’s T-test in ( C ), unpaired Wilcoxon test in ( D ), and log-rank test in ( F ). *p < 0.01, **p < 0.01, ****p < 0.0001; n.s. non-significant.

Figure Legend Snippet: A. Venn diagram of the differentially expressed genes (DEG) between genetically-distinct HCC and control livers as determined in RNA-seq analyses (see Supplementary Table 1 ). B. Scatterplots depicting the correlation in global gene expression between TCGA- LIHC patients and each of the genetically-distinct HCC tumors. TCGA-LIHC patients were divided according to their TCGA classification . C. Boxplots depicting the enrichment of the MYC, MAPK and PI3K/mTOR signaling pathways in patients segregated according to their high/low correlation with each of the genetically-distinct HCC bulk tumor transcriptional signatures from (sample size n=93 for each set of patients). D. Violin plots depicting the tumor mutational burden (TMB) of genetically-distinct HCC compared to human LIHC (n= 723), as determined by whole exome sequencing analyses of bulk tumors (n=3 per genotype) (see Supplementary Table 3 ). E. Donut charts of the variant type distribution of mutations of genetically-distinct HCC (n=3 per genotype) compared to TCGA-LIHC (n= 371). SNP: single nucleotide polymorphism. MNP: multiple nucleotide polymorphism. F. Kaplan-Meier curves displaying the overall survival and recurrence-free survival of HCC patients (from the Wu et al . dataset ) segregated according to p-ERK1/2 and c- MYC positive or negative staining in cancer cells (see Supplementary Table 4 for median OS and RFS time). Statistical significance was determined by unpaired Student’s T-test in ( C ), unpaired Wilcoxon test in ( D ), and log-rank test in ( F ). *p < 0.01, **p < 0.01, ****p < 0.0001; n.s. non-significant.

Techniques Used: RNA Sequencing Assay, Expressing, Sequencing, Variant Assay, Negative Staining

A. Heatmap of unsupervised hierarchical clustering depicting the global gene expression level as TPMs of genetically-distinct HCCs. Top annotations represent the classification of HCC mouse models’ transcriptomic profiles based on the human molecular HCC subtypes. B. Heatmap of unsupervised hierarchical clustering depicting the link between the MAPK, PI3K and MYC signaling pathway enrichment and patients correlating to genetically-distinct HCC-derived transcriptional signatures across TCGA: Liver Hepatocellular Cancer (LIHC) patients ( Supplementary Table 2 ). C. Kaplan-Meier survival curves displaying TCGA: LIHC patients segregated according to their high/low correlation with the transcriptional signatures of each genetically-distinct HCC relative to control. Lines at survival probability=0.5 depict median survival (see Methods for sample size and Supplementary Table 2 ). D. Representative IHC image for p-ERK1/2 and MYC performed on human HCC TMA sections. Pie charts depict the percentage of patients positive for p-ERK1/2 and Myc. Scale bars = 100 µm. Statistical significance was determined by unpaired Student’s t-test ( A ) and log-rank test ( C ). *p < 0.01, ****p < 0.0001; n.s. non-significant. TPMs Transcripts per Million.

Figure Legend Snippet: A. Heatmap of unsupervised hierarchical clustering depicting the global gene expression level as TPMs of genetically-distinct HCCs. Top annotations represent the classification of HCC mouse models’ transcriptomic profiles based on the human molecular HCC subtypes. B. Heatmap of unsupervised hierarchical clustering depicting the link between the MAPK, PI3K and MYC signaling pathway enrichment and patients correlating to genetically-distinct HCC-derived transcriptional signatures across TCGA: Liver Hepatocellular Cancer (LIHC) patients ( Supplementary Table 2 ). C. Kaplan-Meier survival curves displaying TCGA: LIHC patients segregated according to their high/low correlation with the transcriptional signatures of each genetically-distinct HCC relative to control. Lines at survival probability=0.5 depict median survival (see Methods for sample size and Supplementary Table 2 ). D. Representative IHC image for p-ERK1/2 and MYC performed on human HCC TMA sections. Pie charts depict the percentage of patients positive for p-ERK1/2 and Myc. Scale bars = 100 µm. Statistical significance was determined by unpaired Student’s t-test ( A ) and log-rank test ( C ). *p < 0.01, ****p < 0.0001; n.s. non-significant. TPMs Transcripts per Million.

Techniques Used: Expressing, Derivative Assay

A. Quantification of the content of myeloid (CD45 + CD11b + ) and lymphoid (CD45 + CD11b - ) cells relative to total CD45 + leukocytes in tumors collected from end-stage genetically-distinct HCC-bearing mice and age-matched control livers (4 weeks and 15 weeks following HDTVi of empty vectors; Control-4-weeks n=5, Myc OE / Trp53 KO n=6, Myc OE / Pten KO n=5, Control-15-weeks n=6, Nras G12D / Pten KO n=7 and Nras G12V / Pten KO n=4). B. Quantification of circulating myeloid cells (CD45 + CD11b + ) in the blood relative to total CD45 + leukocytes at the indicated timepoints for each of the genetically-distinct HCC murine models (Control n=10, Myc OE / Trp53 KO n=20, Myc OE / Pten KO n=19, Nras G12D / Pten KO n=32, Nras G12V / Pten KO n=18). Arrows indicate timepoints when detectable tumors were visible by MRI. C. Genetically-distinct HCC tumors were processed for flow cytometry at intermediate and end-stages (see Methods ) to assess the content and activation profiles of the indicated immune cell populations. Lymphoid cells: CD8 + T cells (CD45 + CD11b - NK1.1 - CD19 - CD3 + CD8 + CD4 - ), CD4 + T cells (CD45 + CD11b - NK1.1 - CD19 - CD3 + CD8 - CD4 + ); myeloid cells: DCs (CD45 + F4/80 - CD11c high MHCII high ) neutrophils (CD45 + CD11b + Ly6C int Ly6G + ), Ly6C high monocytes (CD45 + CD11b + Ly6C high Ly6G - ), Ly6C low monocytes (CD45 + CD11b + Ly6C low Ly6G - ), monocyte-derived macrophages (MDMs; CD45 + CD11b + Ly6C low Ly6G - F4-80 int CD11b high ). Graphs depicting the percentage of the aforementioned populations relative to total CD45 + leukocytes in control and genetically-distinct HCCs at intermediate and end-stage (Control-4-weeks n=5; Myc OE / Trp53 KO intermediate n=4 and end-stage n=5; Myc OE / Pten KO intermediate n=5 and end-stage n=5, Control-15-weeks n=5, Nras G12D / Pten KO intermediate n=7 and end-stage n=7; and Nras G12V / Pten KO intermediate n=4 and end-stage n=5) (see Supplementary Data 1 and 2 for gating strategy). D. Dotplots depicting the quantification of CD11B, CD15, CD204 and S100A9 positive cells by immunohistochemistry in paraffin-embedded HCC patient samples from the Wu et al. dataset segregated according to p-ERK1/2 (positive n=99, negative n=369) and c-MYC (positive n=78, negative n=389) positive staining in cancer cells (see Methods ). E. Heatmap of unsupervised hierarchical clustering depicting the transcriptome of CD45 + cells isolated from genetically-distinct HCC (mean of n=3-5 per model) and their classification according to the human HCC immune subtypes clustering . F. Heatmap of unsupervised hierarchical clustering depicting the ssGSEA enrichment scores per HCC model using immune-related pathways presented in the Biocarta database (see Supplementary Table 6 ). The color scale represents the z-score normalized enrichment per pathway (row) between HCC models. Graphs show mean + ( A, B ) or ± ( C ) SEM. Statistical significance was determined by unpaired Student’s t -test ( A-E ). Significance was determined within the myeloid content ( A). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

Figure Legend Snippet: A. Quantification of the content of myeloid (CD45 + CD11b + ) and lymphoid (CD45 + CD11b - ) cells relative to total CD45 + leukocytes in tumors collected from end-stage genetically-distinct HCC-bearing mice and age-matched control livers (4 weeks and 15 weeks following HDTVi of empty vectors; Control-4-weeks n=5, Myc OE / Trp53 KO n=6, Myc OE / Pten KO n=5, Control-15-weeks n=6, Nras G12D / Pten KO n=7 and Nras G12V / Pten KO n=4). B. Quantification of circulating myeloid cells (CD45 + CD11b + ) in the blood relative to total CD45 + leukocytes at the indicated timepoints for each of the genetically-distinct HCC murine models (Control n=10, Myc OE / Trp53 KO n=20, Myc OE / Pten KO n=19, Nras G12D / Pten KO n=32, Nras G12V / Pten KO n=18). Arrows indicate timepoints when detectable tumors were visible by MRI. C. Genetically-distinct HCC tumors were processed for flow cytometry at intermediate and end-stages (see Methods ) to assess the content and activation profiles of the indicated immune cell populations. Lymphoid cells: CD8 + T cells (CD45 + CD11b - NK1.1 - CD19 - CD3 + CD8 + CD4 - ), CD4 + T cells (CD45 + CD11b - NK1.1 - CD19 - CD3 + CD8 - CD4 + ); myeloid cells: DCs (CD45 + F4/80 - CD11c high MHCII high ) neutrophils (CD45 + CD11b + Ly6C int Ly6G + ), Ly6C high monocytes (CD45 + CD11b + Ly6C high Ly6G - ), Ly6C low monocytes (CD45 + CD11b + Ly6C low Ly6G - ), monocyte-derived macrophages (MDMs; CD45 + CD11b + Ly6C low Ly6G - F4-80 int CD11b high ). Graphs depicting the percentage of the aforementioned populations relative to total CD45 + leukocytes in control and genetically-distinct HCCs at intermediate and end-stage (Control-4-weeks n=5; Myc OE / Trp53 KO intermediate n=4 and end-stage n=5; Myc OE / Pten KO intermediate n=5 and end-stage n=5, Control-15-weeks n=5, Nras G12D / Pten KO intermediate n=7 and end-stage n=7; and Nras G12V / Pten KO intermediate n=4 and end-stage n=5) (see Supplementary Data 1 and 2 for gating strategy). D. Dotplots depicting the quantification of CD11B, CD15, CD204 and S100A9 positive cells by immunohistochemistry in paraffin-embedded HCC patient samples from the Wu et al. dataset segregated according to p-ERK1/2 (positive n=99, negative n=369) and c-MYC (positive n=78, negative n=389) positive staining in cancer cells (see Methods ). E. Heatmap of unsupervised hierarchical clustering depicting the transcriptome of CD45 + cells isolated from genetically-distinct HCC (mean of n=3-5 per model) and their classification according to the human HCC immune subtypes clustering . F. Heatmap of unsupervised hierarchical clustering depicting the ssGSEA enrichment scores per HCC model using immune-related pathways presented in the Biocarta database (see Supplementary Table 6 ). The color scale represents the z-score normalized enrichment per pathway (row) between HCC models. Graphs show mean + ( A, B ) or ± ( C ) SEM. Statistical significance was determined by unpaired Student’s t -test ( A-E ). Significance was determined within the myeloid content ( A). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

Techniques Used: Flow Cytometry, Activation Assay, Derivative Assay, Immunohistochemistry, Staining, Isolation

A. Quantification of the longitudinal content of neutrophils, Ly6C high monocytes and Ly6C low monocytes (from the parental CD45 + CD11b + cells) in blood collected at the indicated time points post-HDTVi (Control n=10, Myc OE / Trp53 KO n=20, Myc OE / Pten KO n=19, Nras G12D / Pten KO n=32, and Nras G12V / Pten KO n=18). Arrows indicate the time points when detectable tumors were visible by MRI. B. Heatmap depicting the median percentage of the different immune cell populations in end-stage HCC (presented in ) expressing the indicated phenotypic markers. Statistical significance tested against aged-matched control livers. C. Representative CD3 IHC staining performed in liver sections from genetically-distinct HCC-bearing mice. Black lines indicate the tumor borders. Scale bars= 100 μm D. Barplots depicting the TAM content as percentages of F4/80 high CD11b low tissue-resident Kupffer cells (KCs) and F4/80 int CD11b high infiltrating MDMs (from the parental CD45 + cells). (Control n=7, Myc OE / Trp53 KO n= 6, Myc OE / Pten KO n= 5, Nras G12D / Pten KO n= 4, Nras G12V / Pten KO n= 4, pT3 - Nras G12V / Pten KO n = 4). E. PCA plot depicting the CD45 + immune cell transcriptome of control livers and genetically-distinct HCCs at intermediate and end-stages following RNA-seq analyses (Control n=5, Myc OE / Trp53 KO n= 3, Myc OE / Pten KO n= 3, Nras G12D / Pten KO intermediate n= 3 and end-stage n=3, Nras G12V / Pten KO intermediate n= 2 and end-stage n=5, see Supplementary Table 5 ). F. Heatmap of unsupervised hierarchical clustering depicting 60 genes with the highest variation between samples in the CD45 + immune cell transcriptome of control and genetically-distinct HCC models at intermediate and end-stages (presented in ( E )). G. Barplots depicting the myeloid responsive score (MRS) in HCC patients from the Wu et al. dataset segregated according to p-ERK1/2 (top) and Myc (bottom) expressing cancer cells (see Methods for quantification). H. Barplots depicting the significant geneset enrichment for specific immune genesets (see Methods ) in the transcriptome of CD45 + cells isolated from end-stage genetically-distinct HCC and compared to the rest of the HCC models (vs rest). Vertical line at - log10(FDR)=1 is used as threshold for significance. I. Network plots depicting enrichment analyses of the protein-protein interactions from the interferon response genes identified in the Myc OE HCC models (presented in ( H )). Node size represents the -log10 (FDR). J. Barplots depicting caspase 1 activity in control and end-stage tumors from genetically-distinct HCCs. Results are shown as relative fold change compared to control. (Control n=4, Myc OE / Trp53 KO n= 5, Myc OE / Pten KO n= 5, Nras G12D / Pten KO n= 5, Nras G12V / Pten KO n= 5). Graphs show mean + SEM ( A , D and J ). Statistical significance was determined by two-sided unpaired Student’s t -test analysis in ( A, D, J), χ ² test in ( G ) and one-way ANOVA with Tukey’s multiple comparison test ( B ). Significance was determined for the KC content ( D ). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

Figure Legend Snippet: A. Quantification of the longitudinal content of neutrophils, Ly6C high monocytes and Ly6C low monocytes (from the parental CD45 + CD11b + cells) in blood collected at the indicated time points post-HDTVi (Control n=10, Myc OE / Trp53 KO n=20, Myc OE / Pten KO n=19, Nras G12D / Pten KO n=32, and Nras G12V / Pten KO n=18). Arrows indicate the time points when detectable tumors were visible by MRI. B. Heatmap depicting the median percentage of the different immune cell populations in end-stage HCC (presented in ) expressing the indicated phenotypic markers. Statistical significance tested against aged-matched control livers. C. Representative CD3 IHC staining performed in liver sections from genetically-distinct HCC-bearing mice. Black lines indicate the tumor borders. Scale bars= 100 μm D. Barplots depicting the TAM content as percentages of F4/80 high CD11b low tissue-resident Kupffer cells (KCs) and F4/80 int CD11b high infiltrating MDMs (from the parental CD45 + cells). (Control n=7, Myc OE / Trp53 KO n= 6, Myc OE / Pten KO n= 5, Nras G12D / Pten KO n= 4, Nras G12V / Pten KO n= 4, pT3 - Nras G12V / Pten KO n = 4). E. PCA plot depicting the CD45 + immune cell transcriptome of control livers and genetically-distinct HCCs at intermediate and end-stages following RNA-seq analyses (Control n=5, Myc OE / Trp53 KO n= 3, Myc OE / Pten KO n= 3, Nras G12D / Pten KO intermediate n= 3 and end-stage n=3, Nras G12V / Pten KO intermediate n= 2 and end-stage n=5, see Supplementary Table 5 ). F. Heatmap of unsupervised hierarchical clustering depicting 60 genes with the highest variation between samples in the CD45 + immune cell transcriptome of control and genetically-distinct HCC models at intermediate and end-stages (presented in ( E )). G. Barplots depicting the myeloid responsive score (MRS) in HCC patients from the Wu et al. dataset segregated according to p-ERK1/2 (top) and Myc (bottom) expressing cancer cells (see Methods for quantification). H. Barplots depicting the significant geneset enrichment for specific immune genesets (see Methods ) in the transcriptome of CD45 + cells isolated from end-stage genetically-distinct HCC and compared to the rest of the HCC models (vs rest). Vertical line at - log10(FDR)=1 is used as threshold for significance. I. Network plots depicting enrichment analyses of the protein-protein interactions from the interferon response genes identified in the Myc OE HCC models (presented in ( H )). Node size represents the -log10 (FDR). J. Barplots depicting caspase 1 activity in control and end-stage tumors from genetically-distinct HCCs. Results are shown as relative fold change compared to control. (Control n=4, Myc OE / Trp53 KO n= 5, Myc OE / Pten KO n= 5, Nras G12D / Pten KO n= 5, Nras G12V / Pten KO n= 5). Graphs show mean + SEM ( A , D and J ). Statistical significance was determined by two-sided unpaired Student’s t -test analysis in ( A, D, J), χ ² test in ( G ) and one-way ANOVA with Tukey’s multiple comparison test ( B ). Significance was determined for the KC content ( D ). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

Techniques Used: Expressing, Immunohistochemistry, RNA Sequencing Assay, Isolation, Activity Assay, Comparison

A. Barplot depicting the expression levels (signal intensity) of RAS/MAPK-associated phospho-proteins in Nras G12D / Pten KO and Nras G12V / Pten KO HCC cell lysates. B. Barplot depicting GM-CSF protein levels quantified in Nras G12D / Pten KO cancer cell conditioned media after 24h of treatment with Trametinib (MEK1/2 inhibitor; n=4-5), Temuterkib (ERK1/2 inhibitor; n=3) and Vx-11e (ERK2 inhibitor; n= 4-6) at the indicated drug concentrations. C. Barplots depicting the GM-CSF protein level quantified in the supernatant of scramble (sh Scr , n=9), sh Erk2 (n=4) and sh Erk1 (n=4) Nras G12D / Pten KO HCC cell lines. D. Venn diagram depicting the overlap of DEG between Nras G12D / Pten KO and Nras G12V / Pten KO cells treated or not with Vx-11e ( Supplementary Table 9A, E-F ). E. Diagram depicting the gene expression pattern (y-axis) across conditions (x-axis) that follow Csf2 regulation ( D ; 1270 overlapping DEG). “+” indicates the up-regulated genes and “-“ indicates the down-regulated genes. F. Motif enrichment analysis in promoters from the 373 genes ( E ), identifying SP1 as a top candidate ( Supplementary Table 9G-H ). G. Barplots depicting the GM-CSF protein levels quantified in the supernatant of sh Scr (n=9) and sh Sp1 (n=3) Nras G12D / Pten KO HCC cell lines. H. Scatterplot depicting the correlation between the enrichment of ERK signaling pathway (y-axis) and GM-CSF signature (x-axis) for each TCGA cancer type. Correlation analyses were performed on the median pathway enrichment score of all patients per cancer type. Graph shows mean ± SEM ( B-C , G ). Statistical significance was determined by Student t-test ( B-C, G), binomial test ( F ) and test for association between paired samples, using one of Pearson’s product moment correlation coefficient ( H). *p < 0.05; **p<0.01, *** p < 0.001, **** p < 0.0001.

Figure Legend Snippet: A. Barplot depicting the expression levels (signal intensity) of RAS/MAPK-associated phospho-proteins in Nras G12D / Pten KO and Nras G12V / Pten KO HCC cell lysates. B. Barplot depicting GM-CSF protein levels quantified in Nras G12D / Pten KO cancer cell conditioned media after 24h of treatment with Trametinib (MEK1/2 inhibitor; n=4-5), Temuterkib (ERK1/2 inhibitor; n=3) and Vx-11e (ERK2 inhibitor; n= 4-6) at the indicated drug concentrations. C. Barplots depicting the GM-CSF protein level quantified in the supernatant of scramble (sh Scr , n=9), sh Erk2 (n=4) and sh Erk1 (n=4) Nras G12D / Pten KO HCC cell lines. D. Venn diagram depicting the overlap of DEG between Nras G12D / Pten KO and Nras G12V / Pten KO cells treated or not with Vx-11e ( Supplementary Table 9A, E-F ). E. Diagram depicting the gene expression pattern (y-axis) across conditions (x-axis) that follow Csf2 regulation ( D ; 1270 overlapping DEG). “+” indicates the up-regulated genes and “-“ indicates the down-regulated genes. F. Motif enrichment analysis in promoters from the 373 genes ( E ), identifying SP1 as a top candidate ( Supplementary Table 9G-H ). G. Barplots depicting the GM-CSF protein levels quantified in the supernatant of sh Scr (n=9) and sh Sp1 (n=3) Nras G12D / Pten KO HCC cell lines. H. Scatterplot depicting the correlation between the enrichment of ERK signaling pathway (y-axis) and GM-CSF signature (x-axis) for each TCGA cancer type. Correlation analyses were performed on the median pathway enrichment score of all patients per cancer type. Graph shows mean ± SEM ( B-C , G ). Statistical significance was determined by Student t-test ( B-C, G), binomial test ( F ) and test for association between paired samples, using one of Pearson’s product moment correlation coefficient ( H). *p < 0.05; **p<0.01, *** p < 0.001, **** p < 0.0001.

Techniques Used: Expressing

A. Representative western blots assessing the expression of the indicated proteins in Nras G12D / Pten KO and Nras G12V / Pten KO HCC cell lines. B. Barplots depicting the expression levels of phosphorylated and total ERK1/ERK2 proteins relative to vinculin (presented in A , n=4 per cell line). C. Representative western blots assessing the expression of the indicated proteins in Nras G12D / Pten KO HCC cell lines after 24h of treatment with SP600125 (JNK inhibitor), MK2066 (AKT inhibitor), AZD8055 (mTOR inhibitor), Trametinib (MEK1/2 inhibitor), Temuterkib (ERK1/2 inhibitor) and VX-11e (ERK2 inhibitor) at the indicated concentrations. D. Barplots depicting the GM-CSF protein levels quantified in Nras G12D / Pten KO HCC cell line conditioned media after 24h of treatment with SP600125 (JNK inhibitor; n=4), MK2066 (AKT inhibitor; n=4) and AZD8055 (m-TOR inhibitor; n=4) at the indicated drug concentrations. E. Growth curves showing the proliferation of Nras G12D / Pten KO cancer cells treated with Trametinib (MEK1/2 inhibitor), Temuterkib (ERK1/2 inhibitor), Vx-11e (ERK2 inhibitor) SP600125 (JNK inhibitor), MK2066 (AKT inhibitor) and AZD8055 (mTOR inhibitor) at the indicated concentrations (n=3 independent experiments). Growth rate is relative to the 0h timepoint. F. Representative western blots assessing the expression of the indicated proteins in Nras G12D / Pten KO HCC cell line expressing either a non-targeting control shRNA (sh Scr ), an shRNA directed against Erk1 (sh Erk1 ), or Erk2 (sh Erk2 ). G. Growth curves showing the proliferation of sh Scr , sh Erk1 and s hErk2 Nras G12D / Pten KO cancer cell lines (n=3 independent experiments). Growth rate is relative to the 0h timepoint. H. PCA plot depicting the transcriptome of genetically-distinct HCC cell lines ( Nras G12D / Pten KO , Nras G12V / Pten KO ) treated with Vx-11e and control (each sample n=3), following RNA-seq analyses (see Supplementary Table 9 ). I-J. Gene expression analysis of Sp1 ( I ) and Csf2 ( J ) performed in sh Scr (n=-3) or sh Sp1 (n=3) Nras G12D / Pten KO cells. Ubc was used as a house keeping gene. All samples are relative to one sh Scr sample. Graph shows mean ± SEM ( B, D, E, G, I-J ). Statistical significance was determined by Student t-test ( B, I-J). * p < 0.05, ** p < 0.01; n.s. non-significant.

Figure Legend Snippet: A. Representative western blots assessing the expression of the indicated proteins in Nras G12D / Pten KO and Nras G12V / Pten KO HCC cell lines. B. Barplots depicting the expression levels of phosphorylated and total ERK1/ERK2 proteins relative to vinculin (presented in A , n=4 per cell line). C. Representative western blots assessing the expression of the indicated proteins in Nras G12D / Pten KO HCC cell lines after 24h of treatment with SP600125 (JNK inhibitor), MK2066 (AKT inhibitor), AZD8055 (mTOR inhibitor), Trametinib (MEK1/2 inhibitor), Temuterkib (ERK1/2 inhibitor) and VX-11e (ERK2 inhibitor) at the indicated concentrations. D. Barplots depicting the GM-CSF protein levels quantified in Nras G12D / Pten KO HCC cell line conditioned media after 24h of treatment with SP600125 (JNK inhibitor; n=4), MK2066 (AKT inhibitor; n=4) and AZD8055 (m-TOR inhibitor; n=4) at the indicated drug concentrations. E. Growth curves showing the proliferation of Nras G12D / Pten KO cancer cells treated with Trametinib (MEK1/2 inhibitor), Temuterkib (ERK1/2 inhibitor), Vx-11e (ERK2 inhibitor) SP600125 (JNK inhibitor), MK2066 (AKT inhibitor) and AZD8055 (mTOR inhibitor) at the indicated concentrations (n=3 independent experiments). Growth rate is relative to the 0h timepoint. F. Representative western blots assessing the expression of the indicated proteins in Nras G12D / Pten KO HCC cell line expressing either a non-targeting control shRNA (sh Scr ), an shRNA directed against Erk1 (sh Erk1 ), or Erk2 (sh Erk2 ). G. Growth curves showing the proliferation of sh Scr , sh Erk1 and s hErk2 Nras G12D / Pten KO cancer cell lines (n=3 independent experiments). Growth rate is relative to the 0h timepoint. H. PCA plot depicting the transcriptome of genetically-distinct HCC cell lines ( Nras G12D / Pten KO , Nras G12V / Pten KO ) treated with Vx-11e and control (each sample n=3), following RNA-seq analyses (see Supplementary Table 9 ). I-J. Gene expression analysis of Sp1 ( I ) and Csf2 ( J ) performed in sh Scr (n=-3) or sh Sp1 (n=3) Nras G12D / Pten KO cells. Ubc was used as a house keeping gene. All samples are relative to one sh Scr sample. Graph shows mean ± SEM ( B, D, E, G, I-J ). Statistical significance was determined by Student t-test ( B, I-J). * p < 0.05, ** p < 0.01; n.s. non-significant.

Techniques Used: Western Blot, Expressing, shRNA, RNA Sequencing Assay

A. Representative IHC images of H&E and Masson Trichrome staining performed on liver sections from HDTVi- and LOI-induced Nras G12D / Pten KO HCC-bearing mice at end-stage. B. Barplot depicting the quantification of intratumoral GM-CSF levels present in end-stage HDTVi- (n=7) and LOI-induced (n=4) Nras G12D / Pten KO HCC. C. Quantification of the content of myeloid (CD45 + CD11b + ) and lymphoid (CD45 + CD11b - ) cells relative to total CD45 + leukocytes in tumors collected from end-stage HDTVi- (n=7) and LOI-induced (n=5) Nras G12D / Pten KO HCC. HDTVi-induced end-stage Nras G12D / Pten KO HCC-bearing mice shown in are included in this graph. D. Barplots depicting the percentage of intratumoral Ly6C high monocytes, neutrophils and Ly6C low subsets relative to total CD45 + leukocytes in end-stage HDTVi- (n=7) and LOI-induced (n=3) Nras G12D / Pten KO HCC. E-F. Barplot depicting the relative mRNA expression of Ccl6 ( E ) and Ccl17 ( F ) genes in end-stage LOI-induced Nras G12D / Pten KO HCC post-preclinical trial treatment with a- IgG2a (n=5) or a-GM-CSF (n=7). Values represent relative fold changes compared to one IgG2a-treated sample. Ubc was used as a housekeeping gene. G. Barplot depicting the relative tumor growth of LOI-induced Nras G12D / Pten KO HCC at 2 weeks post-treatment initiation with either a-IgG2a (n = 10) or a-GM-CSF (n = 16). H. Barplot depicting the percentage of intratumoral Ly6C low F4/80 low cells relative to total CD45 + leukocytes in LOI-induced Nras G12D / Pten KO HCC post-preclinical trial treatment with a-IgG2a (n = 8) or a-GM-CSF (n = 9). I. Barplot depicting the percentage of CD45 - Ki67 + cells in LOI-induced Nras G12D / Pten KO HCC post-preclinical trial treatment with a-IgG2a (n = 8) or a-GM-CSF (n = 9). J. Barplot depicting the percentage of Ki67 + Ly6C low F4/80 low cells in LOI-induced Nras G12D / Pten KO HCC post-preclinical trial treatment with a-IgG2a (n = 8) or a-GM- CSF (n = 9). K. Barplot depicting the percentage of intratumoral Ly6C low F4/80 low cells relative to total CD45 + leukocytes in LOI-induced Nras G12D / Pten KO HCC post-preclinical trial treatment with a-IgG2a (n = 9), a-GM-CSF (n = 12), a-GM-CSF+a-PD-L1 (n =4), a- GM-CSF- + a-VEGF (4), and a-VEGF + a-PD-L1 (n = 6). LOI-induced Nras G12D / Pten KO HCC-bearing mice treated with a-IgG2a (n=8) and a-GM-CSF (n=9) shown in Fig. S8H are included in this graph. L. 1. Cancer cell genetics shape distinct histopathological features and TME contexture in genetically-distinct murine HCC, which overall predict the prognostic rates of distinct human HCC subclasses 2. Nras G12D / Pten KO secretome fosters a myeloid dominant, pro-inflammatory/immunosuppressive TME wherein Nras G12D driven, ERK1/2-SP1-dependent GM-CSF expression drives the accumulation of pro-tumoral Ly6C low monocyte-derived cells. 3. Neutralizing GM-CSF and VEGF in Nras G12D /Pten KO HCC reprograms the TME, promotes cancer cell death and significantly extends animal survival. Graph shows mean ± SEM ( B, D-K ). Statistical significance was determined by unpaired Student’s T ( E- K ). *p < 0.05; **p<0.01; ***p < 0.001.

Figure Legend Snippet: A. Representative IHC images of H&E and Masson Trichrome staining performed on liver sections from HDTVi- and LOI-induced Nras G12D / Pten KO HCC-bearing mice at end-stage. B. Barplot depicting the quantification of intratumoral GM-CSF levels present in end-stage HDTVi- (n=7) and LOI-induced (n=4) Nras G12D / Pten KO HCC. C. Quantification of the content of myeloid (CD45 + CD11b + ) and lymphoid (CD45 + CD11b - ) cells relative to total CD45 + leukocytes in tumors collected from end-stage HDTVi- (n=7) and LOI-induced (n=5) Nras G12D / Pten KO HCC. HDTVi-induced end-stage Nras G12D / Pten KO HCC-bearing mice shown in are included in this graph. D. Barplots depicting the percentage of intratumoral Ly6C high monocytes, neutrophils and Ly6C low subsets relative to total CD45 + leukocytes in end-stage HDTVi- (n=7) and LOI-induced (n=3) Nras G12D / Pten KO HCC. E-F. Barplot depicting the relative mRNA expression of Ccl6 ( E ) and Ccl17 ( F ) genes in end-stage LOI-induced Nras G12D / Pten KO HCC post-preclinical trial treatment with a- IgG2a (n=5) or a-GM-CSF (n=7). Values represent relative fold changes compared to one IgG2a-treated sample. Ubc was used as a housekeeping gene. G. Barplot depicting the relative tumor growth of LOI-induced Nras G12D / Pten KO HCC at 2 weeks post-treatment initiation with either a-IgG2a (n = 10) or a-GM-CSF (n = 16). H. Barplot depicting the percentage of intratumoral Ly6C low F4/80 low cells relative to total CD45 + leukocytes in LOI-induced Nras G12D / Pten KO HCC post-preclinical trial treatment with a-IgG2a (n = 8) or a-GM-CSF (n = 9). I. Barplot depicting the percentage of CD45 - Ki67 + cells in LOI-induced Nras G12D / Pten KO HCC post-preclinical trial treatment with a-IgG2a (n = 8) or a-GM-CSF (n = 9). J. Barplot depicting the percentage of Ki67 + Ly6C low F4/80 low cells in LOI-induced Nras G12D / Pten KO HCC post-preclinical trial treatment with a-IgG2a (n = 8) or a-GM- CSF (n = 9). K. Barplot depicting the percentage of intratumoral Ly6C low F4/80 low cells relative to total CD45 + leukocytes in LOI-induced Nras G12D / Pten KO HCC post-preclinical trial treatment with a-IgG2a (n = 9), a-GM-CSF (n = 12), a-GM-CSF+a-PD-L1 (n =4), a- GM-CSF- + a-VEGF (4), and a-VEGF + a-PD-L1 (n = 6). LOI-induced Nras G12D / Pten KO HCC-bearing mice treated with a-IgG2a (n=8) and a-GM-CSF (n=9) shown in Fig. S8H are included in this graph. L. 1. Cancer cell genetics shape distinct histopathological features and TME contexture in genetically-distinct murine HCC, which overall predict the prognostic rates of distinct human HCC subclasses 2. Nras G12D / Pten KO secretome fosters a myeloid dominant, pro-inflammatory/immunosuppressive TME wherein Nras G12D driven, ERK1/2-SP1-dependent GM-CSF expression drives the accumulation of pro-tumoral Ly6C low monocyte-derived cells. 3. Neutralizing GM-CSF and VEGF in Nras G12D /Pten KO HCC reprograms the TME, promotes cancer cell death and significantly extends animal survival. Graph shows mean ± SEM ( B, D-K ). Statistical significance was determined by unpaired Student’s T ( E- K ). *p < 0.05; **p<0.01; ***p < 0.001.

Techniques Used: Staining, Expressing, Derivative Assay

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1) Product Images from "Cancer cell genetics shaping of the tumor microenvironment reveals myeloid cell-centric exploitable vulnerabilities in hepatocellular carcinoma"

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