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mouse pgc1a shrna plasmid  (Santa Cruz Biotechnology)


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    Santa Cruz Biotechnology mouse pgc1a shrna plasmid
    Figure 1. Meta-analysis of stemness programs and metabolic states in IPMN- and PanIN-mediated PDAC progression. NCBI GEO datasets (GSE19650 and GSE43288) were used to investigate the differential transcriptomic signatures of stemness and metabolic genes. The data analysis and processing were performed by quantile normalization and log2 transformation. A–N, Representation of the differentially expressed glycolysis genes (A–G), OXPhos genes (H–K), MYC (L), <t>PPARGC1A</t> (M), and CPT2 (N) in indicated samples: NP (N ¼ 7), IPMN-derived PDAC (IPMN-PDAC; n ¼ 3), IPMA or IPMN with low-grade dysplasia (n ¼ 6), and IPMC or IPMN with high- grade dysplasia (n ¼ 6). O–X, Representation of the differentially expressed glycolysis genes (O–U), fatty acid b-oxidation genes (V–W), and PPARGC1A (X) in indicated samples: NP (n ¼ 3), PanIN (n ¼ 13), and PDAC (n ¼ 4). Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (P < 0.05; , P < 0.05; , P < 0.01; P < 0.001.) Y, Venn diagram showing common and unique overexpressed stemness genes in PanIN and IPMN. Data represent mean SD. P valueswere calculated using ordinary one-way ANOVA (multiple comparisons; ,P < 0.05). Z, Network analysis of the differentially expressed stemness and metabolic genes from the GSE19650 dataset using IPA. The network shows that the PPARGC1A is central to stemness, FAO, and OXPhos pathways in IPMN.
    Mouse Pgc1a Shrna Plasmid, supplied by Santa Cruz Biotechnology, used in various techniques. Bioz Stars score: 93/100, based on 3 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/mouse+pgc1a+shrna+plasmid/PGC-1%CE%B1+shRNA+Plasmid/10__1158_slash_1078___0432__ccr___20___5020-71-11-15
    Average 93 stars, based on 3 article reviews
    mouse pgc1a shrna plasmid - by Bioz Stars, 2026-10
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    1) Product Images from "PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions"

    Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

    Journal: Clinical Cancer Research

    doi: 10.1158/1078-0432.ccr-20-5020

    Figure 1. Meta-analysis of stemness programs and metabolic states in IPMN- and PanIN-mediated PDAC progression. NCBI GEO datasets (GSE19650 and GSE43288) were used to investigate the differential transcriptomic signatures of stemness and metabolic genes. The data analysis and processing were performed by quantile normalization and log2 transformation. A–N, Representation of the differentially expressed glycolysis genes (A–G), OXPhos genes (H–K), MYC (L), PPARGC1A (M), and CPT2 (N) in indicated samples: NP (N ¼ 7), IPMN-derived PDAC (IPMN-PDAC; n ¼ 3), IPMA or IPMN with low-grade dysplasia (n ¼ 6), and IPMC or IPMN with high- grade dysplasia (n ¼ 6). O–X, Representation of the differentially expressed glycolysis genes (O–U), fatty acid b-oxidation genes (V–W), and PPARGC1A (X) in indicated samples: NP (n ¼ 3), PanIN (n ¼ 13), and PDAC (n ¼ 4). Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (P < 0.05; , P < 0.05; , P < 0.01; P < 0.001.) Y, Venn diagram showing common and unique overexpressed stemness genes in PanIN and IPMN. Data represent mean SD. P valueswere calculated using ordinary one-way ANOVA (multiple comparisons; ,P < 0.05). Z, Network analysis of the differentially expressed stemness and metabolic genes from the GSE19650 dataset using IPA. The network shows that the PPARGC1A is central to stemness, FAO, and OXPhos pathways in IPMN.
    Figure Legend Snippet: Figure 1. Meta-analysis of stemness programs and metabolic states in IPMN- and PanIN-mediated PDAC progression. NCBI GEO datasets (GSE19650 and GSE43288) were used to investigate the differential transcriptomic signatures of stemness and metabolic genes. The data analysis and processing were performed by quantile normalization and log2 transformation. A–N, Representation of the differentially expressed glycolysis genes (A–G), OXPhos genes (H–K), MYC (L), PPARGC1A (M), and CPT2 (N) in indicated samples: NP (N ¼ 7), IPMN-derived PDAC (IPMN-PDAC; n ¼ 3), IPMA or IPMN with low-grade dysplasia (n ¼ 6), and IPMC or IPMN with high- grade dysplasia (n ¼ 6). O–X, Representation of the differentially expressed glycolysis genes (O–U), fatty acid b-oxidation genes (V–W), and PPARGC1A (X) in indicated samples: NP (n ¼ 3), PanIN (n ¼ 13), and PDAC (n ¼ 4). Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (P < 0.05; , P < 0.05; , P < 0.01; P < 0.001.) Y, Venn diagram showing common and unique overexpressed stemness genes in PanIN and IPMN. Data represent mean SD. P valueswere calculated using ordinary one-way ANOVA (multiple comparisons; ,P < 0.05). Z, Network analysis of the differentially expressed stemness and metabolic genes from the GSE19650 dataset using IPA. The network shows that the PPARGC1A is central to stemness, FAO, and OXPhos pathways in IPMN.

    Techniques Used: Transformation Assay, Derivative Assay

    Figure 2. Differential expression of metabolic regulators, PGC1a and CPT1A, in different stages of PDAC development. A–F, IHC analysis of PGC1a (A–C) and CPT1A (D–F) in indicated samples. A histoscore was calculated by multiplying intensity and positivity. Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (, P < 0.05; , P < 0.01; , P < 0.001). Scale bar 200 mm. C and F, Magnified PanIN2 and IPMN regions duplicated from the original PanIN2 and IPMN IHC images of A and D to show the subcellular localization of PGC1a (C) and CPT1A (F) were shown.
    Figure Legend Snippet: Figure 2. Differential expression of metabolic regulators, PGC1a and CPT1A, in different stages of PDAC development. A–F, IHC analysis of PGC1a (A–C) and CPT1A (D–F) in indicated samples. A histoscore was calculated by multiplying intensity and positivity. Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (, P < 0.05; , P < 0.01; , P < 0.001). Scale bar 200 mm. C and F, Magnified PanIN2 and IPMN regions duplicated from the original PanIN2 and IPMN IHC images of A and D to show the subcellular localization of PGC1a (C) and CPT1A (F) were shown.

    Techniques Used: Quantitative Proteomics

    Figure 4. ADM/PanIN and IPMN show upregulation of PGC1a and display unique metabolic states. A and B, IHC analysis of PGC1a in PBS- or cerulean-treated KC pancreas samples. The histogram to the right shows the histoscore of PGC1a. Data represent mean SD (n ¼ 3). Scale bar 200 mm. C and D, qRT- PCR analysis of PPARGC1A and CPT1A in indicated samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). E and F, Maximal respiration and spare respiratory capacity reflected by OCR were measured using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 6). G and H, Glycolysis and glycolytic capacity reflected by ECAR was measured in indicated samples using Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 6). I, Maximal endogenous OCR due to FAO measured by XF Palmitate-BSA FAO Substrate with the XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). J and K, Immunofluorescence images of pancreas harvested from PBS- or cerulean-treated KC mice stained with PNA-Rhodamine, DBA-FITC, UEA1-FITC, CD133, PGC1a, CPT1A, and DAPI (as indicated). Scale bar 100 mm. L and M, qRT- PCR analysis of indicated genes in indicated samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). N, Basal OCR was measured in acinar, AD, and ductal populations using XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). O, Immunofluorescence images of pancreas harvested from 10-week-old KC and WT mice stained with CD133, PGC1a, cKIT, and DAPI (as indicated). Scale bar 50 mm. P, qRT- PCR analysis of indicated genes in LGKC1 control and doxycycline (Dox)-induced samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). Q, OCR was measured following the addition of oligomycin (O; 1 mmol/L), FCCP (F; 0.5 mmol/L), and electron transport inhibitor rotenone/antimycin A (R/A; 0.5 mmol/L). Data are mean SD (n ¼ 6). R, ECAR was measured following the addition of glucose (Glc; 10 mmol/L), oligomycin (O; 1 mmol/L), and 2-deoxyglucose (2DG; 50 mmol/L). Data are mean SEM (n ¼ 6). S, Immunofluorescence images of human IPMN organoids stained with PGC1a, CPT1A, and DAPI (as indicated). Scale bar 50 mm.
    Figure Legend Snippet: Figure 4. ADM/PanIN and IPMN show upregulation of PGC1a and display unique metabolic states. A and B, IHC analysis of PGC1a in PBS- or cerulean-treated KC pancreas samples. The histogram to the right shows the histoscore of PGC1a. Data represent mean SD (n ¼ 3). Scale bar 200 mm. C and D, qRT- PCR analysis of PPARGC1A and CPT1A in indicated samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). E and F, Maximal respiration and spare respiratory capacity reflected by OCR were measured using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 6). G and H, Glycolysis and glycolytic capacity reflected by ECAR was measured in indicated samples using Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 6). I, Maximal endogenous OCR due to FAO measured by XF Palmitate-BSA FAO Substrate with the XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). J and K, Immunofluorescence images of pancreas harvested from PBS- or cerulean-treated KC mice stained with PNA-Rhodamine, DBA-FITC, UEA1-FITC, CD133, PGC1a, CPT1A, and DAPI (as indicated). Scale bar 100 mm. L and M, qRT- PCR analysis of indicated genes in indicated samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). N, Basal OCR was measured in acinar, AD, and ductal populations using XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). O, Immunofluorescence images of pancreas harvested from 10-week-old KC and WT mice stained with CD133, PGC1a, cKIT, and DAPI (as indicated). Scale bar 50 mm. P, qRT- PCR analysis of indicated genes in LGKC1 control and doxycycline (Dox)-induced samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). Q, OCR was measured following the addition of oligomycin (O; 1 mmol/L), FCCP (F; 0.5 mmol/L), and electron transport inhibitor rotenone/antimycin A (R/A; 0.5 mmol/L). Data are mean SD (n ¼ 6). R, ECAR was measured following the addition of glucose (Glc; 10 mmol/L), oligomycin (O; 1 mmol/L), and 2-deoxyglucose (2DG; 50 mmol/L). Data are mean SEM (n ¼ 6). S, Immunofluorescence images of human IPMN organoids stained with PGC1a, CPT1A, and DAPI (as indicated). Scale bar 50 mm.

    Techniques Used: Quantitative RT-PCR, Staining, Control

    Figure 5. ADM/PanIN and IPMN show the upregulation of unique PGC1a-interacting partners. A, Protein–protein interactions analysis of PPARGC1A using “STRING” software. B–I, A meta-analysis of genes that encode PGC1a-interacting proteins using the human IPMN progression dataset GSE19650. Datasets were processed using standard GEO2R analysis, followed by quantile normalization and log2 transformation. Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP. J, qRT-PCR analysis of indicated genes in acinar and AD cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). K and L, Immunofluorescence images with PGC1a, PPARg, and DAPI staining on indicated samples. M and N, Immunofluorescence images. NRF1 staining along with DAPI on pancreatic tissues harvested from control (KC) and cerulean-treated KC (KCþCer) mouse (M). The KCþCer immunofluorescence image, which was shown for NRF1 staining in M (bottom image), was further showed for the co-expression of NRF1 with PGC1a (N, bottom images). The co-expression of NRF1 with PGC1a was shown in another KCþCer tissue section (N, top images). O, Immunofluorescence images with PGC1a, NRF1, and DAPI staining on indicated samples. Scale bar 50 mm. For all histograms, P values were calculated by Student t test (, P < 0.05; , P < 0.01; , P < 0.001.)
    Figure Legend Snippet: Figure 5. ADM/PanIN and IPMN show the upregulation of unique PGC1a-interacting partners. A, Protein–protein interactions analysis of PPARGC1A using “STRING” software. B–I, A meta-analysis of genes that encode PGC1a-interacting proteins using the human IPMN progression dataset GSE19650. Datasets were processed using standard GEO2R analysis, followed by quantile normalization and log2 transformation. Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP. J, qRT-PCR analysis of indicated genes in acinar and AD cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). K and L, Immunofluorescence images with PGC1a, PPARg, and DAPI staining on indicated samples. M and N, Immunofluorescence images. NRF1 staining along with DAPI on pancreatic tissues harvested from control (KC) and cerulean-treated KC (KCþCer) mouse (M). The KCþCer immunofluorescence image, which was shown for NRF1 staining in M (bottom image), was further showed for the co-expression of NRF1 with PGC1a (N, bottom images). The co-expression of NRF1 with PGC1a was shown in another KCþCer tissue section (N, top images). O, Immunofluorescence images with PGC1a, NRF1, and DAPI staining on indicated samples. Scale bar 50 mm. For all histograms, P values were calculated by Student t test (, P < 0.05; , P < 0.01; , P < 0.001.)

    Techniques Used: Protein-Protein interactions, Software, Transformation Assay, Quantitative RT-PCR, Staining, Control, Expressing

    Figure 6. PGC1a-mediated OXPhos and FAO-OXPhos regulate stemness in ADM/PanIN and IPMN, respectively. A, qRT-PCR analysis of Ppargc1a in the scramble and PGC1a KD in LGKC1 cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). B, LGKC1 SCR and PGC1a KD cells were injected subcutaneously into nude mice and maintained with doxycycline (DOX) in water. The subcutaneous tumors were excised 21 days after implantation, followed by the measurement of tumor volume and weight (bar graphs). Data are mean SD (n ¼ 4). The significance was determined by a t test (, P < 0.05; , P < 0.01; , P < 0.001). C, qRT-PCR analysis of indicated genes in the scramble and PGC1a KD LGKC1þDOX cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). D–F, Basal, maximal respiration, and spare respiratory capacity reflected by OCR due to FAO measured by XF Palmitate-BSA FAO Substrate with the XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). G and H, Morphology of human IPMN organoids growing in the presence and absence of SR18292. (Continued on the following page.)
    Figure Legend Snippet: Figure 6. PGC1a-mediated OXPhos and FAO-OXPhos regulate stemness in ADM/PanIN and IPMN, respectively. A, qRT-PCR analysis of Ppargc1a in the scramble and PGC1a KD in LGKC1 cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). B, LGKC1 SCR and PGC1a KD cells were injected subcutaneously into nude mice and maintained with doxycycline (DOX) in water. The subcutaneous tumors were excised 21 days after implantation, followed by the measurement of tumor volume and weight (bar graphs). Data are mean SD (n ¼ 4). The significance was determined by a t test (, P < 0.05; , P < 0.01; , P < 0.001). C, qRT-PCR analysis of indicated genes in the scramble and PGC1a KD LGKC1þDOX cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). D–F, Basal, maximal respiration, and spare respiratory capacity reflected by OCR due to FAO measured by XF Palmitate-BSA FAO Substrate with the XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). G and H, Morphology of human IPMN organoids growing in the presence and absence of SR18292. (Continued on the following page.)

    Techniques Used: Quantitative RT-PCR, Injection

    Related Articles

    Generated:

    Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions
    Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260). .. LGKC1 cells with stable KD of PGC1a were generated using a mouse PGC1a shRNA plasmid (Santa Cruz Biotechnology, catalog no. Sc-38885-SH) and control shRNA plasmid B (Sc-108065). .. Cells were transfected with SCR and short hairpin (shRNA) plasmids using TurboFectin 8.0 transfection reagent (Origene, TF81001).

    shRNA:

    Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions
    Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260). .. LGKC1 cells with stable KD of PGC1a were generated using a mouse PGC1a shRNA plasmid (Santa Cruz Biotechnology, catalog no. Sc-38885-SH) and control shRNA plasmid B (Sc-108065). .. Cells were transfected with SCR and short hairpin (shRNA) plasmids using TurboFectin 8.0 transfection reagent (Origene, TF81001).

    Plasmid Preparation:

    Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions
    Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260). .. LGKC1 cells with stable KD of PGC1a were generated using a mouse PGC1a shRNA plasmid (Santa Cruz Biotechnology, catalog no. Sc-38885-SH) and control shRNA plasmid B (Sc-108065). .. Cells were transfected with SCR and short hairpin (shRNA) plasmids using TurboFectin 8.0 transfection reagent (Origene, TF81001).

    Control:

    Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions
    Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260). .. LGKC1 cells with stable KD of PGC1a were generated using a mouse PGC1a shRNA plasmid (Santa Cruz Biotechnology, catalog no. Sc-38885-SH) and control shRNA plasmid B (Sc-108065). .. Cells were transfected with SCR and short hairpin (shRNA) plasmids using TurboFectin 8.0 transfection reagent (Origene, TF81001).



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    mouse pgc1a shrna plasmid  (Santa Cruz Biotechnology)
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    Santa Cruz Biotechnology mouse pgc1a shrna plasmid
    Figure 1. Meta-analysis of stemness programs and metabolic states in IPMN- and PanIN-mediated PDAC progression. NCBI GEO datasets (GSE19650 and GSE43288) were used to investigate the differential transcriptomic signatures of stemness and metabolic genes. The data analysis and processing were performed by quantile normalization and log2 transformation. A–N, Representation of the differentially expressed glycolysis genes (A–G), OXPhos genes (H–K), MYC (L), <t>PPARGC1A</t> (M), and CPT2 (N) in indicated samples: NP (N ¼ 7), IPMN-derived PDAC (IPMN-PDAC; n ¼ 3), IPMA or IPMN with low-grade dysplasia (n ¼ 6), and IPMC or IPMN with high- grade dysplasia (n ¼ 6). O–X, Representation of the differentially expressed glycolysis genes (O–U), fatty acid b-oxidation genes (V–W), and PPARGC1A (X) in indicated samples: NP (n ¼ 3), PanIN (n ¼ 13), and PDAC (n ¼ 4). Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (P < 0.05; , P < 0.05; , P < 0.01; P < 0.001.) Y, Venn diagram showing common and unique overexpressed stemness genes in PanIN and IPMN. Data represent mean SD. P valueswere calculated using ordinary one-way ANOVA (multiple comparisons; ,P < 0.05). Z, Network analysis of the differentially expressed stemness and metabolic genes from the GSE19650 dataset using IPA. The network shows that the PPARGC1A is central to stemness, FAO, and OXPhos pathways in IPMN.
    Mouse Pgc1a Shrna Plasmid, supplied by Santa Cruz Biotechnology, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/mouse+pgc1a+shrna+plasmid/PGC-1%CE%B1+shRNA+Plasmid/10__1158_slash_1078___0432__ccr___20___5020-71-11-15
    Average 93 stars, based on 1 article reviews
    mouse pgc1a shrna plasmid - by Bioz Stars, 2026-10
    93/100 stars
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    Figure 1. Meta-analysis of stemness programs and metabolic states in IPMN- and PanIN-mediated PDAC progression. NCBI GEO datasets (GSE19650 and GSE43288) were used to investigate the differential transcriptomic signatures of stemness and metabolic genes. The data analysis and processing were performed by quantile normalization and log2 transformation. A–N, Representation of the differentially expressed glycolysis genes (A–G), OXPhos genes (H–K), MYC (L), PPARGC1A (M), and CPT2 (N) in indicated samples: NP (N ¼ 7), IPMN-derived PDAC (IPMN-PDAC; n ¼ 3), IPMA or IPMN with low-grade dysplasia (n ¼ 6), and IPMC or IPMN with high- grade dysplasia (n ¼ 6). O–X, Representation of the differentially expressed glycolysis genes (O–U), fatty acid b-oxidation genes (V–W), and PPARGC1A (X) in indicated samples: NP (n ¼ 3), PanIN (n ¼ 13), and PDAC (n ¼ 4). Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (P < 0.05; , P < 0.05; , P < 0.01; P < 0.001.) Y, Venn diagram showing common and unique overexpressed stemness genes in PanIN and IPMN. Data represent mean SD. P valueswere calculated using ordinary one-way ANOVA (multiple comparisons; ,P < 0.05). Z, Network analysis of the differentially expressed stemness and metabolic genes from the GSE19650 dataset using IPA. The network shows that the PPARGC1A is central to stemness, FAO, and OXPhos pathways in IPMN.

    Journal: Clinical Cancer Research

    Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

    doi: 10.1158/1078-0432.ccr-20-5020

    Figure Lengend Snippet: Figure 1. Meta-analysis of stemness programs and metabolic states in IPMN- and PanIN-mediated PDAC progression. NCBI GEO datasets (GSE19650 and GSE43288) were used to investigate the differential transcriptomic signatures of stemness and metabolic genes. The data analysis and processing were performed by quantile normalization and log2 transformation. A–N, Representation of the differentially expressed glycolysis genes (A–G), OXPhos genes (H–K), MYC (L), PPARGC1A (M), and CPT2 (N) in indicated samples: NP (N ¼ 7), IPMN-derived PDAC (IPMN-PDAC; n ¼ 3), IPMA or IPMN with low-grade dysplasia (n ¼ 6), and IPMC or IPMN with high- grade dysplasia (n ¼ 6). O–X, Representation of the differentially expressed glycolysis genes (O–U), fatty acid b-oxidation genes (V–W), and PPARGC1A (X) in indicated samples: NP (n ¼ 3), PanIN (n ¼ 13), and PDAC (n ¼ 4). Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (P < 0.05; , P < 0.05; , P < 0.01; P < 0.001.) Y, Venn diagram showing common and unique overexpressed stemness genes in PanIN and IPMN. Data represent mean SD. P valueswere calculated using ordinary one-way ANOVA (multiple comparisons; ,P < 0.05). Z, Network analysis of the differentially expressed stemness and metabolic genes from the GSE19650 dataset using IPA. The network shows that the PPARGC1A is central to stemness, FAO, and OXPhos pathways in IPMN.

    Article Snippet: LGKC1 cells with stable KD of PGC1a were generated using a mouse PGC1a shRNA plasmid (Santa Cruz Biotechnology, catalog no. Sc-38885-SH) and control shRNA plasmid B (Sc-108065).

    Techniques: Transformation Assay, Derivative Assay

    Figure 2. Differential expression of metabolic regulators, PGC1a and CPT1A, in different stages of PDAC development. A–F, IHC analysis of PGC1a (A–C) and CPT1A (D–F) in indicated samples. A histoscore was calculated by multiplying intensity and positivity. Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (, P < 0.05; , P < 0.01; , P < 0.001). Scale bar 200 mm. C and F, Magnified PanIN2 and IPMN regions duplicated from the original PanIN2 and IPMN IHC images of A and D to show the subcellular localization of PGC1a (C) and CPT1A (F) were shown.

    Journal: Clinical Cancer Research

    Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

    doi: 10.1158/1078-0432.ccr-20-5020

    Figure Lengend Snippet: Figure 2. Differential expression of metabolic regulators, PGC1a and CPT1A, in different stages of PDAC development. A–F, IHC analysis of PGC1a (A–C) and CPT1A (D–F) in indicated samples. A histoscore was calculated by multiplying intensity and positivity. Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (, P < 0.05; , P < 0.01; , P < 0.001). Scale bar 200 mm. C and F, Magnified PanIN2 and IPMN regions duplicated from the original PanIN2 and IPMN IHC images of A and D to show the subcellular localization of PGC1a (C) and CPT1A (F) were shown.

    Article Snippet: LGKC1 cells with stable KD of PGC1a were generated using a mouse PGC1a shRNA plasmid (Santa Cruz Biotechnology, catalog no. Sc-38885-SH) and control shRNA plasmid B (Sc-108065).

    Techniques: Quantitative Proteomics

    Figure 4. ADM/PanIN and IPMN show upregulation of PGC1a and display unique metabolic states. A and B, IHC analysis of PGC1a in PBS- or cerulean-treated KC pancreas samples. The histogram to the right shows the histoscore of PGC1a. Data represent mean SD (n ¼ 3). Scale bar 200 mm. C and D, qRT- PCR analysis of PPARGC1A and CPT1A in indicated samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). E and F, Maximal respiration and spare respiratory capacity reflected by OCR were measured using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 6). G and H, Glycolysis and glycolytic capacity reflected by ECAR was measured in indicated samples using Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 6). I, Maximal endogenous OCR due to FAO measured by XF Palmitate-BSA FAO Substrate with the XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). J and K, Immunofluorescence images of pancreas harvested from PBS- or cerulean-treated KC mice stained with PNA-Rhodamine, DBA-FITC, UEA1-FITC, CD133, PGC1a, CPT1A, and DAPI (as indicated). Scale bar 100 mm. L and M, qRT- PCR analysis of indicated genes in indicated samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). N, Basal OCR was measured in acinar, AD, and ductal populations using XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). O, Immunofluorescence images of pancreas harvested from 10-week-old KC and WT mice stained with CD133, PGC1a, cKIT, and DAPI (as indicated). Scale bar 50 mm. P, qRT- PCR analysis of indicated genes in LGKC1 control and doxycycline (Dox)-induced samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). Q, OCR was measured following the addition of oligomycin (O; 1 mmol/L), FCCP (F; 0.5 mmol/L), and electron transport inhibitor rotenone/antimycin A (R/A; 0.5 mmol/L). Data are mean SD (n ¼ 6). R, ECAR was measured following the addition of glucose (Glc; 10 mmol/L), oligomycin (O; 1 mmol/L), and 2-deoxyglucose (2DG; 50 mmol/L). Data are mean SEM (n ¼ 6). S, Immunofluorescence images of human IPMN organoids stained with PGC1a, CPT1A, and DAPI (as indicated). Scale bar 50 mm.

    Journal: Clinical Cancer Research

    Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

    doi: 10.1158/1078-0432.ccr-20-5020

    Figure Lengend Snippet: Figure 4. ADM/PanIN and IPMN show upregulation of PGC1a and display unique metabolic states. A and B, IHC analysis of PGC1a in PBS- or cerulean-treated KC pancreas samples. The histogram to the right shows the histoscore of PGC1a. Data represent mean SD (n ¼ 3). Scale bar 200 mm. C and D, qRT- PCR analysis of PPARGC1A and CPT1A in indicated samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). E and F, Maximal respiration and spare respiratory capacity reflected by OCR were measured using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 6). G and H, Glycolysis and glycolytic capacity reflected by ECAR was measured in indicated samples using Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 6). I, Maximal endogenous OCR due to FAO measured by XF Palmitate-BSA FAO Substrate with the XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). J and K, Immunofluorescence images of pancreas harvested from PBS- or cerulean-treated KC mice stained with PNA-Rhodamine, DBA-FITC, UEA1-FITC, CD133, PGC1a, CPT1A, and DAPI (as indicated). Scale bar 100 mm. L and M, qRT- PCR analysis of indicated genes in indicated samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). N, Basal OCR was measured in acinar, AD, and ductal populations using XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). O, Immunofluorescence images of pancreas harvested from 10-week-old KC and WT mice stained with CD133, PGC1a, cKIT, and DAPI (as indicated). Scale bar 50 mm. P, qRT- PCR analysis of indicated genes in LGKC1 control and doxycycline (Dox)-induced samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). Q, OCR was measured following the addition of oligomycin (O; 1 mmol/L), FCCP (F; 0.5 mmol/L), and electron transport inhibitor rotenone/antimycin A (R/A; 0.5 mmol/L). Data are mean SD (n ¼ 6). R, ECAR was measured following the addition of glucose (Glc; 10 mmol/L), oligomycin (O; 1 mmol/L), and 2-deoxyglucose (2DG; 50 mmol/L). Data are mean SEM (n ¼ 6). S, Immunofluorescence images of human IPMN organoids stained with PGC1a, CPT1A, and DAPI (as indicated). Scale bar 50 mm.

    Article Snippet: LGKC1 cells with stable KD of PGC1a were generated using a mouse PGC1a shRNA plasmid (Santa Cruz Biotechnology, catalog no. Sc-38885-SH) and control shRNA plasmid B (Sc-108065).

    Techniques: Quantitative RT-PCR, Staining, Control

    Figure 5. ADM/PanIN and IPMN show the upregulation of unique PGC1a-interacting partners. A, Protein–protein interactions analysis of PPARGC1A using “STRING” software. B–I, A meta-analysis of genes that encode PGC1a-interacting proteins using the human IPMN progression dataset GSE19650. Datasets were processed using standard GEO2R analysis, followed by quantile normalization and log2 transformation. Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP. J, qRT-PCR analysis of indicated genes in acinar and AD cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). K and L, Immunofluorescence images with PGC1a, PPARg, and DAPI staining on indicated samples. M and N, Immunofluorescence images. NRF1 staining along with DAPI on pancreatic tissues harvested from control (KC) and cerulean-treated KC (KCþCer) mouse (M). The KCþCer immunofluorescence image, which was shown for NRF1 staining in M (bottom image), was further showed for the co-expression of NRF1 with PGC1a (N, bottom images). The co-expression of NRF1 with PGC1a was shown in another KCþCer tissue section (N, top images). O, Immunofluorescence images with PGC1a, NRF1, and DAPI staining on indicated samples. Scale bar 50 mm. For all histograms, P values were calculated by Student t test (, P < 0.05; , P < 0.01; , P < 0.001.)

    Journal: Clinical Cancer Research

    Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

    doi: 10.1158/1078-0432.ccr-20-5020

    Figure Lengend Snippet: Figure 5. ADM/PanIN and IPMN show the upregulation of unique PGC1a-interacting partners. A, Protein–protein interactions analysis of PPARGC1A using “STRING” software. B–I, A meta-analysis of genes that encode PGC1a-interacting proteins using the human IPMN progression dataset GSE19650. Datasets were processed using standard GEO2R analysis, followed by quantile normalization and log2 transformation. Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP. J, qRT-PCR analysis of indicated genes in acinar and AD cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). K and L, Immunofluorescence images with PGC1a, PPARg, and DAPI staining on indicated samples. M and N, Immunofluorescence images. NRF1 staining along with DAPI on pancreatic tissues harvested from control (KC) and cerulean-treated KC (KCþCer) mouse (M). The KCþCer immunofluorescence image, which was shown for NRF1 staining in M (bottom image), was further showed for the co-expression of NRF1 with PGC1a (N, bottom images). The co-expression of NRF1 with PGC1a was shown in another KCþCer tissue section (N, top images). O, Immunofluorescence images with PGC1a, NRF1, and DAPI staining on indicated samples. Scale bar 50 mm. For all histograms, P values were calculated by Student t test (, P < 0.05; , P < 0.01; , P < 0.001.)

    Article Snippet: LGKC1 cells with stable KD of PGC1a were generated using a mouse PGC1a shRNA plasmid (Santa Cruz Biotechnology, catalog no. Sc-38885-SH) and control shRNA plasmid B (Sc-108065).

    Techniques: Protein-Protein interactions, Software, Transformation Assay, Quantitative RT-PCR, Staining, Control, Expressing

    Figure 6. PGC1a-mediated OXPhos and FAO-OXPhos regulate stemness in ADM/PanIN and IPMN, respectively. A, qRT-PCR analysis of Ppargc1a in the scramble and PGC1a KD in LGKC1 cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). B, LGKC1 SCR and PGC1a KD cells were injected subcutaneously into nude mice and maintained with doxycycline (DOX) in water. The subcutaneous tumors were excised 21 days after implantation, followed by the measurement of tumor volume and weight (bar graphs). Data are mean SD (n ¼ 4). The significance was determined by a t test (, P < 0.05; , P < 0.01; , P < 0.001). C, qRT-PCR analysis of indicated genes in the scramble and PGC1a KD LGKC1þDOX cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). D–F, Basal, maximal respiration, and spare respiratory capacity reflected by OCR due to FAO measured by XF Palmitate-BSA FAO Substrate with the XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). G and H, Morphology of human IPMN organoids growing in the presence and absence of SR18292. (Continued on the following page.)

    Journal: Clinical Cancer Research

    Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

    doi: 10.1158/1078-0432.ccr-20-5020

    Figure Lengend Snippet: Figure 6. PGC1a-mediated OXPhos and FAO-OXPhos regulate stemness in ADM/PanIN and IPMN, respectively. A, qRT-PCR analysis of Ppargc1a in the scramble and PGC1a KD in LGKC1 cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). B, LGKC1 SCR and PGC1a KD cells were injected subcutaneously into nude mice and maintained with doxycycline (DOX) in water. The subcutaneous tumors were excised 21 days after implantation, followed by the measurement of tumor volume and weight (bar graphs). Data are mean SD (n ¼ 4). The significance was determined by a t test (, P < 0.05; , P < 0.01; , P < 0.001). C, qRT-PCR analysis of indicated genes in the scramble and PGC1a KD LGKC1þDOX cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). D–F, Basal, maximal respiration, and spare respiratory capacity reflected by OCR due to FAO measured by XF Palmitate-BSA FAO Substrate with the XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). G and H, Morphology of human IPMN organoids growing in the presence and absence of SR18292. (Continued on the following page.)

    Article Snippet: LGKC1 cells with stable KD of PGC1a were generated using a mouse PGC1a shRNA plasmid (Santa Cruz Biotechnology, catalog no. Sc-38885-SH) and control shRNA plasmid B (Sc-108065).

    Techniques: Quantitative RT-PCR, Injection