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crispr cas9 sgrna ko mouse metabolism library  (Addgene inc)


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    Addgene inc crispr cas9 sgrna ko mouse metabolism library
    Figure 1. <t>Metabolism-Focused</t> <t>CRISPR</t> Screens In Vivo Reveal Metabolic Dependencies of Pancreatic Tumors (A) Schematic of genetics screens to identify metabolic dependencies of KP pancreatic cancer specifically in vivo. (B) Cumulative frequency curve of represented guides in genetic screens. (C) Gene scores of in vivo versus in vitro genetic screens of KP pancreatic cancer growth. (D) Volcano plot of differential gene scores comparing in vivo against in vitro conditions (left). Top 20 genes scoring as differentially required in vivo. Genes involved in specific metabolic pathways are indicated (right). (E) Gene sets enriched in differentially required genes in vivo versus in vitro for pancreatic cancer growth. The heatmap generated by iPAGE represents the extent to which each gene set is enriched among the genes that are essential for tumor growth in vivo. See also Figure S1.
    Crispr Cas9 Sgrna Ko Mouse Metabolism Library, supplied by Addgene inc, used in various techniques. Bioz Stars score: 91/100, based on 2 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/crispr+cas9+sgrna+ko+mouse+metabolism+library/pm33152324-168-0-15?v=Addgene+inc
    Average 91 stars, based on 2 article reviews
    crispr cas9 sgrna ko mouse metabolism library - by Bioz Stars, 2026-07
    91/100 stars

    Images

    1) Product Images from "Functional Genomics In Vivo Reveal Metabolic Dependencies of Pancreatic Cancer Cells."

    Article Title: Functional Genomics In Vivo Reveal Metabolic Dependencies of Pancreatic Cancer Cells.

    Journal: Cell metabolism

    doi: 10.1016/j.cmet.2020.10.017

    Figure 1. Metabolism-Focused CRISPR Screens In Vivo Reveal Metabolic Dependencies of Pancreatic Tumors (A) Schematic of genetics screens to identify metabolic dependencies of KP pancreatic cancer specifically in vivo. (B) Cumulative frequency curve of represented guides in genetic screens. (C) Gene scores of in vivo versus in vitro genetic screens of KP pancreatic cancer growth. (D) Volcano plot of differential gene scores comparing in vivo against in vitro conditions (left). Top 20 genes scoring as differentially required in vivo. Genes involved in specific metabolic pathways are indicated (right). (E) Gene sets enriched in differentially required genes in vivo versus in vitro for pancreatic cancer growth. The heatmap generated by iPAGE represents the extent to which each gene set is enriched among the genes that are essential for tumor growth in vivo. See also Figure S1.
    Figure Legend Snippet: Figure 1. Metabolism-Focused CRISPR Screens In Vivo Reveal Metabolic Dependencies of Pancreatic Tumors (A) Schematic of genetics screens to identify metabolic dependencies of KP pancreatic cancer specifically in vivo. (B) Cumulative frequency curve of represented guides in genetic screens. (C) Gene scores of in vivo versus in vitro genetic screens of KP pancreatic cancer growth. (D) Volcano plot of differential gene scores comparing in vivo against in vitro conditions (left). Top 20 genes scoring as differentially required in vivo. Genes involved in specific metabolic pathways are indicated (right). (E) Gene sets enriched in differentially required genes in vivo versus in vitro for pancreatic cancer growth. The heatmap generated by iPAGE represents the extent to which each gene set is enriched among the genes that are essential for tumor growth in vivo. See also Figure S1.

    Techniques Used: CRISPR, In Vivo, In Vitro, Generated

    Figure 3. Heme Synthesis Is a Metabolic Dependency of Kras-Driven Tumors In Vivo (A) Immunoblot of HMBS in the indicated KP pancreas and KP lung cancer cell lines. GAPDH was used as loading control. (B) Fold change in cell number (log2) of the indicated KP pancreas and KP lung cancer cell lines after culturing in vitro for the indicated durations (mean ± SD, n = 3). ***p < 0.001 versus sgControl. (C) Tumor weights of the indicated KP pancreas and KP lung tumors engrafted subcutaneously in C57BL/6J mice (box and whisker, n = 8). *p < 0.05, ***p < 0.001 versus sgControl (left). Images of the indicated KP pancreas and KP lung tumors (right). (D) Immunoblot of HMOX1 in KP pancreas and KP lung cancer cells grown in vitro under normoxia, under hypoxia (0.5% oxygen) for 48 h, and in subcutaneous tumors. GAPDH was used as loading control. (E) Immunoblots of HMOX1 and HMBS in the indicated KP pancreas cell lines. GAPDH was used as loading control. (F) Relative tumor weights of the indicated KP pancreas Hmbs_KO tumors engrafted subcutaneously in C57BL/6J mice (box and whisker, n = 23). *p < 0.05 versus control (top). Representative image of the indicated KP pancreas Hmbs_KO tumors (bottom). (G) Schematic of competition assay using PDAC patient-derived xenograft cells infected with the indicated sgRNAs. Cells were then engrafted subcutaneously in NSG mice (left). Relative fold change in sgRNA abundance (log2) from the PDX (mean ± SD, n = 5). **p < 0.01 versus sgControl (right). (H) Disease-free survival rates of TCGA PDAC patients with high or low heme synthesis gene expressions. Weighted average expressions of CPOX, HMBS, PPOX, and UROS were used (low heme n = 83, high heme n = 28). See also Figure S2.
    Figure Legend Snippet: Figure 3. Heme Synthesis Is a Metabolic Dependency of Kras-Driven Tumors In Vivo (A) Immunoblot of HMBS in the indicated KP pancreas and KP lung cancer cell lines. GAPDH was used as loading control. (B) Fold change in cell number (log2) of the indicated KP pancreas and KP lung cancer cell lines after culturing in vitro for the indicated durations (mean ± SD, n = 3). ***p < 0.001 versus sgControl. (C) Tumor weights of the indicated KP pancreas and KP lung tumors engrafted subcutaneously in C57BL/6J mice (box and whisker, n = 8). *p < 0.05, ***p < 0.001 versus sgControl (left). Images of the indicated KP pancreas and KP lung tumors (right). (D) Immunoblot of HMOX1 in KP pancreas and KP lung cancer cells grown in vitro under normoxia, under hypoxia (0.5% oxygen) for 48 h, and in subcutaneous tumors. GAPDH was used as loading control. (E) Immunoblots of HMOX1 and HMBS in the indicated KP pancreas cell lines. GAPDH was used as loading control. (F) Relative tumor weights of the indicated KP pancreas Hmbs_KO tumors engrafted subcutaneously in C57BL/6J mice (box and whisker, n = 23). *p < 0.05 versus control (top). Representative image of the indicated KP pancreas Hmbs_KO tumors (bottom). (G) Schematic of competition assay using PDAC patient-derived xenograft cells infected with the indicated sgRNAs. Cells were then engrafted subcutaneously in NSG mice (left). Relative fold change in sgRNA abundance (log2) from the PDX (mean ± SD, n = 5). **p < 0.01 versus sgControl (right). (H) Disease-free survival rates of TCGA PDAC patients with high or low heme synthesis gene expressions. Weighted average expressions of CPOX, HMBS, PPOX, and UROS were used (low heme n = 83, high heme n = 28). See also Figure S2.

    Techniques Used: In Vivo, Western Blot, Control, In Vitro, Whisker Assay, Competitive Binding Assay, Derivative Assay, Infection



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    Addgene inc crispr cas9 sgrna ko mouse metabolism library
    Figure 1. <t>Metabolism-Focused</t> <t>CRISPR</t> Screens In Vivo Reveal Metabolic Dependencies of Pancreatic Tumors (A) Schematic of genetics screens to identify metabolic dependencies of KP pancreatic cancer specifically in vivo. (B) Cumulative frequency curve of represented guides in genetic screens. (C) Gene scores of in vivo versus in vitro genetic screens of KP pancreatic cancer growth. (D) Volcano plot of differential gene scores comparing in vivo against in vitro conditions (left). Top 20 genes scoring as differentially required in vivo. Genes involved in specific metabolic pathways are indicated (right). (E) Gene sets enriched in differentially required genes in vivo versus in vitro for pancreatic cancer growth. The heatmap generated by iPAGE represents the extent to which each gene set is enriched among the genes that are essential for tumor growth in vivo. See also Figure S1.
    Crispr Cas9 Sgrna Ko Mouse Metabolism Library, supplied by Addgene inc, used in various techniques. Bioz Stars score: 91/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/crispr+cas9+sgrna+ko+mouse+metabolism+library/pm33152324-168-0-15?v=Addgene+inc
    Average 91 stars, based on 1 article reviews
    crispr cas9 sgrna ko mouse metabolism library - by Bioz Stars, 2026-07
    91/100 stars
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    Figure 1. Metabolism-Focused CRISPR Screens In Vivo Reveal Metabolic Dependencies of Pancreatic Tumors (A) Schematic of genetics screens to identify metabolic dependencies of KP pancreatic cancer specifically in vivo. (B) Cumulative frequency curve of represented guides in genetic screens. (C) Gene scores of in vivo versus in vitro genetic screens of KP pancreatic cancer growth. (D) Volcano plot of differential gene scores comparing in vivo against in vitro conditions (left). Top 20 genes scoring as differentially required in vivo. Genes involved in specific metabolic pathways are indicated (right). (E) Gene sets enriched in differentially required genes in vivo versus in vitro for pancreatic cancer growth. The heatmap generated by iPAGE represents the extent to which each gene set is enriched among the genes that are essential for tumor growth in vivo. See also Figure S1.

    Journal: Cell metabolism

    Article Title: Functional Genomics In Vivo Reveal Metabolic Dependencies of Pancreatic Cancer Cells.

    doi: 10.1016/j.cmet.2020.10.017

    Figure Lengend Snippet: Figure 1. Metabolism-Focused CRISPR Screens In Vivo Reveal Metabolic Dependencies of Pancreatic Tumors (A) Schematic of genetics screens to identify metabolic dependencies of KP pancreatic cancer specifically in vivo. (B) Cumulative frequency curve of represented guides in genetic screens. (C) Gene scores of in vivo versus in vitro genetic screens of KP pancreatic cancer growth. (D) Volcano plot of differential gene scores comparing in vivo against in vitro conditions (left). Top 20 genes scoring as differentially required in vivo. Genes involved in specific metabolic pathways are indicated (right). (E) Gene sets enriched in differentially required genes in vivo versus in vitro for pancreatic cancer growth. The heatmap generated by iPAGE represents the extent to which each gene set is enriched among the genes that are essential for tumor growth in vivo. See also Figure S1.

    Article Snippet: CRISPR Cas9 sgRNA KO mouse metabolism library generated in this study has been deposited to Addgene (ID 160129).

    Techniques: CRISPR, In Vivo, In Vitro, Generated

    Figure 3. Heme Synthesis Is a Metabolic Dependency of Kras-Driven Tumors In Vivo (A) Immunoblot of HMBS in the indicated KP pancreas and KP lung cancer cell lines. GAPDH was used as loading control. (B) Fold change in cell number (log2) of the indicated KP pancreas and KP lung cancer cell lines after culturing in vitro for the indicated durations (mean ± SD, n = 3). ***p < 0.001 versus sgControl. (C) Tumor weights of the indicated KP pancreas and KP lung tumors engrafted subcutaneously in C57BL/6J mice (box and whisker, n = 8). *p < 0.05, ***p < 0.001 versus sgControl (left). Images of the indicated KP pancreas and KP lung tumors (right). (D) Immunoblot of HMOX1 in KP pancreas and KP lung cancer cells grown in vitro under normoxia, under hypoxia (0.5% oxygen) for 48 h, and in subcutaneous tumors. GAPDH was used as loading control. (E) Immunoblots of HMOX1 and HMBS in the indicated KP pancreas cell lines. GAPDH was used as loading control. (F) Relative tumor weights of the indicated KP pancreas Hmbs_KO tumors engrafted subcutaneously in C57BL/6J mice (box and whisker, n = 23). *p < 0.05 versus control (top). Representative image of the indicated KP pancreas Hmbs_KO tumors (bottom). (G) Schematic of competition assay using PDAC patient-derived xenograft cells infected with the indicated sgRNAs. Cells were then engrafted subcutaneously in NSG mice (left). Relative fold change in sgRNA abundance (log2) from the PDX (mean ± SD, n = 5). **p < 0.01 versus sgControl (right). (H) Disease-free survival rates of TCGA PDAC patients with high or low heme synthesis gene expressions. Weighted average expressions of CPOX, HMBS, PPOX, and UROS were used (low heme n = 83, high heme n = 28). See also Figure S2.

    Journal: Cell metabolism

    Article Title: Functional Genomics In Vivo Reveal Metabolic Dependencies of Pancreatic Cancer Cells.

    doi: 10.1016/j.cmet.2020.10.017

    Figure Lengend Snippet: Figure 3. Heme Synthesis Is a Metabolic Dependency of Kras-Driven Tumors In Vivo (A) Immunoblot of HMBS in the indicated KP pancreas and KP lung cancer cell lines. GAPDH was used as loading control. (B) Fold change in cell number (log2) of the indicated KP pancreas and KP lung cancer cell lines after culturing in vitro for the indicated durations (mean ± SD, n = 3). ***p < 0.001 versus sgControl. (C) Tumor weights of the indicated KP pancreas and KP lung tumors engrafted subcutaneously in C57BL/6J mice (box and whisker, n = 8). *p < 0.05, ***p < 0.001 versus sgControl (left). Images of the indicated KP pancreas and KP lung tumors (right). (D) Immunoblot of HMOX1 in KP pancreas and KP lung cancer cells grown in vitro under normoxia, under hypoxia (0.5% oxygen) for 48 h, and in subcutaneous tumors. GAPDH was used as loading control. (E) Immunoblots of HMOX1 and HMBS in the indicated KP pancreas cell lines. GAPDH was used as loading control. (F) Relative tumor weights of the indicated KP pancreas Hmbs_KO tumors engrafted subcutaneously in C57BL/6J mice (box and whisker, n = 23). *p < 0.05 versus control (top). Representative image of the indicated KP pancreas Hmbs_KO tumors (bottom). (G) Schematic of competition assay using PDAC patient-derived xenograft cells infected with the indicated sgRNAs. Cells were then engrafted subcutaneously in NSG mice (left). Relative fold change in sgRNA abundance (log2) from the PDX (mean ± SD, n = 5). **p < 0.01 versus sgControl (right). (H) Disease-free survival rates of TCGA PDAC patients with high or low heme synthesis gene expressions. Weighted average expressions of CPOX, HMBS, PPOX, and UROS were used (low heme n = 83, high heme n = 28). See also Figure S2.

    Article Snippet: CRISPR Cas9 sgRNA KO mouse metabolism library generated in this study has been deposited to Addgene (ID 160129).

    Techniques: In Vivo, Western Blot, Control, In Vitro, Whisker Assay, Competitive Binding Assay, Derivative Assay, Infection