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ccrcc cell lines 786o  (ATCC)


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    Structured Review

    ATCC ccrcc cell lines 786o
    Identification of 11 Important DEGs in <t>ccRCC.</t> (A) Venn diagram of genes in the TCGA and DEPMap datasets. (B) Expression heatmap of the eleven genes in normal versus tumor samples. (C) Differential expression levels of the eleven genes in normal and tumor samples. (D) Locations of the DEGs on chromosomes. (E) Expression correlation analysis of the eleven DEGs. *p < 0.05; **p < 0.01; ***p < 0.001.
    Ccrcc Cell Lines 786o, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 2265 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/ccrcc+cell+lines+786o/786-O/pmc12287010-70-1-12
    Average 99 stars, based on 2265 article reviews
    ccrcc cell lines 786o - by Bioz Stars, 2026-09
    99/100 stars

    Images

    1) Product Images from "CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis"

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis

    Journal: Frontiers in Immunology

    doi: 10.3389/fimmu.2025.1619361

    Identification of 11 Important DEGs in ccRCC. (A) Venn diagram of genes in the TCGA and DEPMap datasets. (B) Expression heatmap of the eleven genes in normal versus tumor samples. (C) Differential expression levels of the eleven genes in normal and tumor samples. (D) Locations of the DEGs on chromosomes. (E) Expression correlation analysis of the eleven DEGs. *p < 0.05; **p < 0.01; ***p < 0.001.
    Figure Legend Snippet: Identification of 11 Important DEGs in ccRCC. (A) Venn diagram of genes in the TCGA and DEPMap datasets. (B) Expression heatmap of the eleven genes in normal versus tumor samples. (C) Differential expression levels of the eleven genes in normal and tumor samples. (D) Locations of the DEGs on chromosomes. (E) Expression correlation analysis of the eleven DEGs. *p < 0.05; **p < 0.01; ***p < 0.001.

    Techniques Used: Expressing, Quantitative Proteomics

    Multi method validation of risk score-derived prognostic models. (A) KM survival curves demonstrated markedly shorter overall survival in high-risk ccRCC patients relative to those in the low-risk group. (B) ROC analysis of the DEGs prognostic signature for predicting the 1/3/5-year survival. (C, D) Risk score stratification and survival duration distribution in ccRCC cohort. (E) PCA discriminates high- and low-risk groups using whole transcriptome data. (F) KM survival analysis of ccRCC patients stratified by risk score in the GEO validation cohort ( GSE26909 , n=39).
    Figure Legend Snippet: Multi method validation of risk score-derived prognostic models. (A) KM survival curves demonstrated markedly shorter overall survival in high-risk ccRCC patients relative to those in the low-risk group. (B) ROC analysis of the DEGs prognostic signature for predicting the 1/3/5-year survival. (C, D) Risk score stratification and survival duration distribution in ccRCC cohort. (E) PCA discriminates high- and low-risk groups using whole transcriptome data. (F) KM survival analysis of ccRCC patients stratified by risk score in the GEO validation cohort ( GSE26909 , n=39).

    Techniques Used: Biomarker Discovery, Derivative Assay

    Construction of a nomogram for prediction prognosis. (A) Univariate Cox regression analysis identified grade, stage, T stage, M stage, and risk score as significant prognostic factors. (B) Multivariate Cox regression identifies risk score and age as independent prognostic predictors. (C) Prognostic nomogram incorporating risk score and age for ccRCC survival probability. (D–F) Calibration curves demonstrate the accuracy of 1-year, 3-year, and 5-year overall survival predictions.
    Figure Legend Snippet: Construction of a nomogram for prediction prognosis. (A) Univariate Cox regression analysis identified grade, stage, T stage, M stage, and risk score as significant prognostic factors. (B) Multivariate Cox regression identifies risk score and age as independent prognostic predictors. (C) Prognostic nomogram incorporating risk score and age for ccRCC survival probability. (D–F) Calibration curves demonstrate the accuracy of 1-year, 3-year, and 5-year overall survival predictions.

    Techniques Used:

    Correlation of immune microenvironment with risk score. (A) Immune cell infiltration landscape in ccRCC revealed by CIBERSORT. (B–F) Linear regression models demonstrate risk score-dependent immune cell infiltration patterns. (G) Differential immune cell distribution between risk groups. (H–J) Risk-stratified therapeutic sensitivity to pazopanib, sunitinib, and temsirolimus.
    Figure Legend Snippet: Correlation of immune microenvironment with risk score. (A) Immune cell infiltration landscape in ccRCC revealed by CIBERSORT. (B–F) Linear regression models demonstrate risk score-dependent immune cell infiltration patterns. (G) Differential immune cell distribution between risk groups. (H–J) Risk-stratified therapeutic sensitivity to pazopanib, sunitinib, and temsirolimus.

    Techniques Used:

    MELK is a poor prognostic marker in ccRCC. (A) Significant variations in overall survival between ccRCC patients with high and low MELK expression. (B, C) Immunohistochemical evidence of MELK overexpression in tumor tissues versus NAT. (D) Successful MELK knockdown confirmed by western blot across 769P, 786O and Caki-1 cell lines. (E) Silencing MELK suppressed proliferation abilities in 769P, 786O and Caki-1 cells. (F–I) Silencing MELK suppressed migration abilities as measured via transwell assay (F) and scratch assay (G–I) in 769P, 786O and Caki-1 cells. * p < 0.05; ** p < 0.01; *** p < 0.001.
    Figure Legend Snippet: MELK is a poor prognostic marker in ccRCC. (A) Significant variations in overall survival between ccRCC patients with high and low MELK expression. (B, C) Immunohistochemical evidence of MELK overexpression in tumor tissues versus NAT. (D) Successful MELK knockdown confirmed by western blot across 769P, 786O and Caki-1 cell lines. (E) Silencing MELK suppressed proliferation abilities in 769P, 786O and Caki-1 cells. (F–I) Silencing MELK suppressed migration abilities as measured via transwell assay (F) and scratch assay (G–I) in 769P, 786O and Caki-1 cells. * p < 0.05; ** p < 0.01; *** p < 0.001.

    Techniques Used: Marker, Expressing, Immunohistochemical staining, Over Expression, Knockdown, Western Blot, Migration, Transwell Assay, Wound Healing Assay

    Related Articles

    Expressing:

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis
    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).. The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.

    Quantitative Proteomics:

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis
    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).. The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.

    Biomarker Discovery:

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis
    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).. The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.

    Derivative Assay:

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis
    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).. The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.

    Marker:

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis
    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).. The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.

    Immunohistochemical staining:

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis
    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).. The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.

    Over Expression:

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis
    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).. The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.

    Knockdown:

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis
    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).. The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.

    Western Blot:

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis
    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).. The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.

    Migration:

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis
    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).. The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.

    Transwell Assay:

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis
    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).. The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.

    Wound Healing Assay:

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis
    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).. The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.The cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin.



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    Fig. 1 GPX8 is associated with higher grade and poor prognosis in <t>ccRCC</t> A, Two-tiered bioinformatic screening to find genes correlated with metabolites (top; CCLE database) and genes (bottom; TCGA-KIRC (Kidney renal clear cell carcinoma) database) of glycogen and lipid metabolism in ccRCC. The metabolites and genes used as queries are indicated in each Venn diagram. The criteria were set to FDR < 0.0001 and |r|< 0.15. The numbers in the Venn diagram represent the numbers of genes that meet the criteria. B-D, Violin plots for the mRNA expression levels of GPX8 according to (B) normal vs. tumor, (C) neoplasm histologic grade, and (D) alive or dead-tumor-free group vs. dead-with-tumor group among ccRCC patients. The mRNA expression values were obtained from the TCGA-KIRC dataset. P-values were determined by Mann–Whitney U test. E, Overall survival according to GPX8 mRNA expression for ccRCC patients from TCGA-KIRC database. F, GPX8 IHC staining for tumor array sections (KD482_ biomax) from ccRCC patients. Magnification 400X
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    GPX8 is associated with higher grade and poor prognosis in <t>ccRCC</t> A , Two-tiered bioinformatic screening to find genes correlated with metabolites (top; CCLE database) and genes (bottom; TCGA-KIRC (Kidney renal clear cell carcinoma) database) of glycogen and lipid metabolism in ccRCC. The metabolites and genes used as queries are indicated in each Venn diagram. The criteria were set to FDR < 0.0001 and |r|< 0.15. The numbers in the Venn diagram represent the numbers of genes that meet the criteria. B-D, Violin plots for the mRNA expression levels of GPX8 according to ( B ) normal vs. tumor, ( C ) neoplasm histologic grade, and ( D ) alive or dead-tumor-free group vs. dead-with-tumor group among ccRCC patients. The mRNA expression values were obtained from the TCGA-KIRC dataset. P -values were determined by Mann–Whitney U test. E , Overall survival according to GPX8 mRNA expression for ccRCC patients from TCGA-KIRC database. F , GPX8 IHC staining for tumor array sections (KD482_biomax) from ccRCC patients. Magnification 400X
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    (A) Decreased FABP5 mRNA levels in Caki-1 and <t>786O</t> cells in the FABP5-RNAi group. Decreased viability of (B) Caki-1 and (C) 786O cells in the FABP5-RNAi group at all time points. (D) Fewer EdU-positive Caki-1 and 786O cells were observed in the FABP5-RNAi group when compared with the NC-RNAi control group (scale bar, 200 µ m). (E) Quantification of the EdU staining results. * P<0.05, ** P<0.01 and *** P<0.001 vs. NC-RNAi group. FABP5, fatty acid binding protein 5; RNAi, RNA interference; NC, negative control; EdU, 5-ethynyl-2′-deoxyuridine.
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    Image Search Results


    Identification of 11 Important DEGs in ccRCC. (A) Venn diagram of genes in the TCGA and DEPMap datasets. (B) Expression heatmap of the eleven genes in normal versus tumor samples. (C) Differential expression levels of the eleven genes in normal and tumor samples. (D) Locations of the DEGs on chromosomes. (E) Expression correlation analysis of the eleven DEGs. *p < 0.05; **p < 0.01; ***p < 0.001.

    Journal: Frontiers in Immunology

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis

    doi: 10.3389/fimmu.2025.1619361

    Figure Lengend Snippet: Identification of 11 Important DEGs in ccRCC. (A) Venn diagram of genes in the TCGA and DEPMap datasets. (B) Expression heatmap of the eleven genes in normal versus tumor samples. (C) Differential expression levels of the eleven genes in normal and tumor samples. (D) Locations of the DEGs on chromosomes. (E) Expression correlation analysis of the eleven DEGs. *p < 0.05; **p < 0.01; ***p < 0.001.

    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).

    Techniques: Expressing, Quantitative Proteomics

    Multi method validation of risk score-derived prognostic models. (A) KM survival curves demonstrated markedly shorter overall survival in high-risk ccRCC patients relative to those in the low-risk group. (B) ROC analysis of the DEGs prognostic signature for predicting the 1/3/5-year survival. (C, D) Risk score stratification and survival duration distribution in ccRCC cohort. (E) PCA discriminates high- and low-risk groups using whole transcriptome data. (F) KM survival analysis of ccRCC patients stratified by risk score in the GEO validation cohort ( GSE26909 , n=39).

    Journal: Frontiers in Immunology

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis

    doi: 10.3389/fimmu.2025.1619361

    Figure Lengend Snippet: Multi method validation of risk score-derived prognostic models. (A) KM survival curves demonstrated markedly shorter overall survival in high-risk ccRCC patients relative to those in the low-risk group. (B) ROC analysis of the DEGs prognostic signature for predicting the 1/3/5-year survival. (C, D) Risk score stratification and survival duration distribution in ccRCC cohort. (E) PCA discriminates high- and low-risk groups using whole transcriptome data. (F) KM survival analysis of ccRCC patients stratified by risk score in the GEO validation cohort ( GSE26909 , n=39).

    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).

    Techniques: Biomarker Discovery, Derivative Assay

    Construction of a nomogram for prediction prognosis. (A) Univariate Cox regression analysis identified grade, stage, T stage, M stage, and risk score as significant prognostic factors. (B) Multivariate Cox regression identifies risk score and age as independent prognostic predictors. (C) Prognostic nomogram incorporating risk score and age for ccRCC survival probability. (D–F) Calibration curves demonstrate the accuracy of 1-year, 3-year, and 5-year overall survival predictions.

    Journal: Frontiers in Immunology

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis

    doi: 10.3389/fimmu.2025.1619361

    Figure Lengend Snippet: Construction of a nomogram for prediction prognosis. (A) Univariate Cox regression analysis identified grade, stage, T stage, M stage, and risk score as significant prognostic factors. (B) Multivariate Cox regression identifies risk score and age as independent prognostic predictors. (C) Prognostic nomogram incorporating risk score and age for ccRCC survival probability. (D–F) Calibration curves demonstrate the accuracy of 1-year, 3-year, and 5-year overall survival predictions.

    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).

    Techniques:

    Correlation of immune microenvironment with risk score. (A) Immune cell infiltration landscape in ccRCC revealed by CIBERSORT. (B–F) Linear regression models demonstrate risk score-dependent immune cell infiltration patterns. (G) Differential immune cell distribution between risk groups. (H–J) Risk-stratified therapeutic sensitivity to pazopanib, sunitinib, and temsirolimus.

    Journal: Frontiers in Immunology

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis

    doi: 10.3389/fimmu.2025.1619361

    Figure Lengend Snippet: Correlation of immune microenvironment with risk score. (A) Immune cell infiltration landscape in ccRCC revealed by CIBERSORT. (B–F) Linear regression models demonstrate risk score-dependent immune cell infiltration patterns. (G) Differential immune cell distribution between risk groups. (H–J) Risk-stratified therapeutic sensitivity to pazopanib, sunitinib, and temsirolimus.

    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).

    Techniques:

    MELK is a poor prognostic marker in ccRCC. (A) Significant variations in overall survival between ccRCC patients with high and low MELK expression. (B, C) Immunohistochemical evidence of MELK overexpression in tumor tissues versus NAT. (D) Successful MELK knockdown confirmed by western blot across 769P, 786O and Caki-1 cell lines. (E) Silencing MELK suppressed proliferation abilities in 769P, 786O and Caki-1 cells. (F–I) Silencing MELK suppressed migration abilities as measured via transwell assay (F) and scratch assay (G–I) in 769P, 786O and Caki-1 cells. * p < 0.05; ** p < 0.01; *** p < 0.001.

    Journal: Frontiers in Immunology

    Article Title: CRISPR/Cas9-based discovery of ccRCC therapeutic opportunities through molecular mechanism and immune microenvironment analysis

    doi: 10.3389/fimmu.2025.1619361

    Figure Lengend Snippet: MELK is a poor prognostic marker in ccRCC. (A) Significant variations in overall survival between ccRCC patients with high and low MELK expression. (B, C) Immunohistochemical evidence of MELK overexpression in tumor tissues versus NAT. (D) Successful MELK knockdown confirmed by western blot across 769P, 786O and Caki-1 cell lines. (E) Silencing MELK suppressed proliferation abilities in 769P, 786O and Caki-1 cells. (F–I) Silencing MELK suppressed migration abilities as measured via transwell assay (F) and scratch assay (G–I) in 769P, 786O and Caki-1 cells. * p < 0.05; ** p < 0.01; *** p < 0.001.

    Article Snippet: The ccRCC cell lines 786O, 769P, and Caki-1 were obtained from the American Type Culture Collection (ATCC).

    Techniques: Marker, Expressing, Immunohistochemical staining, Over Expression, Knockdown, Western Blot, Migration, Transwell Assay, Wound Healing Assay

    Fig. 1 GPX8 is associated with higher grade and poor prognosis in ccRCC A, Two-tiered bioinformatic screening to find genes correlated with metabolites (top; CCLE database) and genes (bottom; TCGA-KIRC (Kidney renal clear cell carcinoma) database) of glycogen and lipid metabolism in ccRCC. The metabolites and genes used as queries are indicated in each Venn diagram. The criteria were set to FDR < 0.0001 and |r|< 0.15. The numbers in the Venn diagram represent the numbers of genes that meet the criteria. B-D, Violin plots for the mRNA expression levels of GPX8 according to (B) normal vs. tumor, (C) neoplasm histologic grade, and (D) alive or dead-tumor-free group vs. dead-with-tumor group among ccRCC patients. The mRNA expression values were obtained from the TCGA-KIRC dataset. P-values were determined by Mann–Whitney U test. E, Overall survival according to GPX8 mRNA expression for ccRCC patients from TCGA-KIRC database. F, GPX8 IHC staining for tumor array sections (KD482_ biomax) from ccRCC patients. Magnification 400X

    Journal: Journal of experimental & clinical cancer research : CR

    Article Title: GPX8 regulates clear cell renal cell carcinoma tumorigenesis through promoting lipogenesis by NNMT.

    doi: 10.1186/s13046-023-02607-2

    Figure Lengend Snippet: Fig. 1 GPX8 is associated with higher grade and poor prognosis in ccRCC A, Two-tiered bioinformatic screening to find genes correlated with metabolites (top; CCLE database) and genes (bottom; TCGA-KIRC (Kidney renal clear cell carcinoma) database) of glycogen and lipid metabolism in ccRCC. The metabolites and genes used as queries are indicated in each Venn diagram. The criteria were set to FDR < 0.0001 and |r|< 0.15. The numbers in the Venn diagram represent the numbers of genes that meet the criteria. B-D, Violin plots for the mRNA expression levels of GPX8 according to (B) normal vs. tumor, (C) neoplasm histologic grade, and (D) alive or dead-tumor-free group vs. dead-with-tumor group among ccRCC patients. The mRNA expression values were obtained from the TCGA-KIRC dataset. P-values were determined by Mann–Whitney U test. E, Overall survival according to GPX8 mRNA expression for ccRCC patients from TCGA-KIRC database. F, GPX8 IHC staining for tumor array sections (KD482_ biomax) from ccRCC patients. Magnification 400X

    Article Snippet: Cell culture and isotope labeling experiment condition Human ccRCC cell lines 786O (from ATCC), Caki1, and A498 (Korean Cell Line Bank) were cultured in DMEM (786O and Caki1) or MEM (A498), supplemented with 10% FBS, 1% penicillin–streptomycin.

    Techniques: Expressing, MANN-WHITNEY, Immunohistochemistry

    Fig. 2 GPX8 is involved in ccRCC cell growth in vitro and in vivo A-D, The effect of GPX8 KO in Caki1 and shGPX8 in 786O cells in vitro. Western blot analysis of GPX8 protein expression (A), relative growth rates measured by CCK8 kit (B), migrating cells in scratch assay at 0, 24, and 48 h (top) and bar graphs for relative wound areas for WT and GPX8-KO Caki1 cells (bottom) (n = 3) (C), and clonogenic assay after plating 200 cells in 6-well plate for 2 weeks (top) and bar graphs for number of colonies of WT and GPX8-KO Caki1 (bottom) (n = 3) (D). E, Tumor growths by WT and GPX8-KO Caki1 cells xenografted in nude mice (n = 6). One mouse in the GPX8-KO group did not develop a visible tumor, and the tumor photo shows 5 tumors. See Fig. S2C for the photos for the whole body mouse images. Tumor volume (top, left), tumor weight (top, right), and photograph of tumors (bottom) obtained at day 28 after implantation. Data presented in panels (B), (C), (D), and (E) are means ± SD (n ≥ 3). P-value was calculated by two-way ANOVA with Geisser–Greenhouse correction for (B) and (E) (top, left panel); unpaired t-test for (C), (D) and (E) (top, right panel)

    Journal: Journal of experimental & clinical cancer research : CR

    Article Title: GPX8 regulates clear cell renal cell carcinoma tumorigenesis through promoting lipogenesis by NNMT.

    doi: 10.1186/s13046-023-02607-2

    Figure Lengend Snippet: Fig. 2 GPX8 is involved in ccRCC cell growth in vitro and in vivo A-D, The effect of GPX8 KO in Caki1 and shGPX8 in 786O cells in vitro. Western blot analysis of GPX8 protein expression (A), relative growth rates measured by CCK8 kit (B), migrating cells in scratch assay at 0, 24, and 48 h (top) and bar graphs for relative wound areas for WT and GPX8-KO Caki1 cells (bottom) (n = 3) (C), and clonogenic assay after plating 200 cells in 6-well plate for 2 weeks (top) and bar graphs for number of colonies of WT and GPX8-KO Caki1 (bottom) (n = 3) (D). E, Tumor growths by WT and GPX8-KO Caki1 cells xenografted in nude mice (n = 6). One mouse in the GPX8-KO group did not develop a visible tumor, and the tumor photo shows 5 tumors. See Fig. S2C for the photos for the whole body mouse images. Tumor volume (top, left), tumor weight (top, right), and photograph of tumors (bottom) obtained at day 28 after implantation. Data presented in panels (B), (C), (D), and (E) are means ± SD (n ≥ 3). P-value was calculated by two-way ANOVA with Geisser–Greenhouse correction for (B) and (E) (top, left panel); unpaired t-test for (C), (D) and (E) (top, right panel)

    Article Snippet: Cell culture and isotope labeling experiment condition Human ccRCC cell lines 786O (from ATCC), Caki1, and A498 (Korean Cell Line Bank) were cultured in DMEM (786O and Caki1) or MEM (A498), supplemented with 10% FBS, 1% penicillin–streptomycin.

    Techniques: In Vitro, In Vivo, Western Blot, Expressing, Wound Healing Assay, Clonogenic Assay

    Fig. 4 GPX8 enhances lipid accumulation by inhibiting AMPK. A, Correlation between GPX8 mRNA expression and phosphorylated AMPKα1 (PRKAA1_PT172) level obtained from Reverse Phase Protein Arrays (RPPA) data of TCGA-KIRC dataset. B-C, Western blot analysis for phosphorylated and total forms of ACC (Ser 79) and AMPK α1 (T183) α2 (T172) in GPX8 WT and KO cells (B) and effects of compound C on GPX8-KO Caki1 cells for 2 days (C). D, shGPX8 786O cells were incubated with or without doxycycline (100 ng/mL) for 3 days. These cells then were treated with compound C in a range of concentration for 2 days. Western blot analysis for the effects of compound C on phosphorylated forms of ACC (Ser 79) and AMPK α1 (T183) α2 (T172). E, Relative cell viability of WT and GPX8-KO Caki1 cells upon treatment of different concentrations of compound C for 3 days. F, FA de novo synthesis and triacylglycerol synthesis in GPX8-KO with and without compound C (0.2 µM) as in Fig. 3H. G, Representative pictures from quadruplicates (left) of neutral lipid BODIPY 493/503 staining of GPX8-KO Caki1 cells treated with different concentrations of compound C for 3 days. Quantitation of the lipid droplet (right) (n = 4) as in Fig. 3F. H, Representative pictures from triplicates (left) and quantitation (right) for lipid staining for shGPX8 786O cells as in Fig. 3F (n = 3). Data presented in panels (E), (F), (G), and (H) are means ± SD (n ≥ 3). P-values were determined by unpaired t-test

    Journal: Journal of experimental & clinical cancer research : CR

    Article Title: GPX8 regulates clear cell renal cell carcinoma tumorigenesis through promoting lipogenesis by NNMT.

    doi: 10.1186/s13046-023-02607-2

    Figure Lengend Snippet: Fig. 4 GPX8 enhances lipid accumulation by inhibiting AMPK. A, Correlation between GPX8 mRNA expression and phosphorylated AMPKα1 (PRKAA1_PT172) level obtained from Reverse Phase Protein Arrays (RPPA) data of TCGA-KIRC dataset. B-C, Western blot analysis for phosphorylated and total forms of ACC (Ser 79) and AMPK α1 (T183) α2 (T172) in GPX8 WT and KO cells (B) and effects of compound C on GPX8-KO Caki1 cells for 2 days (C). D, shGPX8 786O cells were incubated with or without doxycycline (100 ng/mL) for 3 days. These cells then were treated with compound C in a range of concentration for 2 days. Western blot analysis for the effects of compound C on phosphorylated forms of ACC (Ser 79) and AMPK α1 (T183) α2 (T172). E, Relative cell viability of WT and GPX8-KO Caki1 cells upon treatment of different concentrations of compound C for 3 days. F, FA de novo synthesis and triacylglycerol synthesis in GPX8-KO with and without compound C (0.2 µM) as in Fig. 3H. G, Representative pictures from quadruplicates (left) of neutral lipid BODIPY 493/503 staining of GPX8-KO Caki1 cells treated with different concentrations of compound C for 3 days. Quantitation of the lipid droplet (right) (n = 4) as in Fig. 3F. H, Representative pictures from triplicates (left) and quantitation (right) for lipid staining for shGPX8 786O cells as in Fig. 3F (n = 3). Data presented in panels (E), (F), (G), and (H) are means ± SD (n ≥ 3). P-values were determined by unpaired t-test

    Article Snippet: Cell culture and isotope labeling experiment condition Human ccRCC cell lines 786O (from ATCC), Caki1, and A498 (Korean Cell Line Bank) were cultured in DMEM (786O and Caki1) or MEM (A498), supplemented with 10% FBS, 1% penicillin–streptomycin.

    Techniques: Expressing, Western Blot, Incubation, Concentration Assay, Staining, Quantitation Assay

    Fig. 7 GPX8 modulates the NNMT expression through IL6-STAT3 signaling. A, Volcano plot for IL6 expression from our RNA-seq data. B, mRNA expression of IL6 by RT-qPCR comparing WT vs. GPX8-KO Caki1 cells (left) and shGPX8 786O with or without doxycycline (100 ng/mL) for 3 days (right). C, Western blot analysis of total and phosphorylated form of STAT3 (Ser 727), NNMT, and GPX8 normalized by β-actin from WT vs. GPX8-KO Caki1 with and without hyper-IL6 treatment (50 ng/mL) for 3 days. D, Representative picture (left) of neutral lipid BODIPY 493/503 staining of GPX8-KO Caki1 with and without hyper-IL6 treatment with same condition as in (C). Quantitation of the lipid droplet (right) (n = 3) as in Fig. 3F. E, shGPX8 786O cells were incubated with or without doxycycline (100 ng/mL) for 3 days before incubation with or without Hyper-IL6 (50 ng/mL) for 2 days. Western blot analysis of total and phosphorylated forms of STAT3 (Ser 727), NNMT, GPX8, and β-actin. F, Representative pictures (left) of neutral lipid BODIPY 493/503 staining of shGPX8 786O with or without Hyper-IL6 treatment with the same condition as in (E). Quantitation of the lipid droplet (right) (n ≥ 3) as in Fig. 3F. Data presented in panels (B), (D) and (F) are means ± SD (n ≥ 3). P-values were determined by unpaired t-test

    Journal: Journal of experimental & clinical cancer research : CR

    Article Title: GPX8 regulates clear cell renal cell carcinoma tumorigenesis through promoting lipogenesis by NNMT.

    doi: 10.1186/s13046-023-02607-2

    Figure Lengend Snippet: Fig. 7 GPX8 modulates the NNMT expression through IL6-STAT3 signaling. A, Volcano plot for IL6 expression from our RNA-seq data. B, mRNA expression of IL6 by RT-qPCR comparing WT vs. GPX8-KO Caki1 cells (left) and shGPX8 786O with or without doxycycline (100 ng/mL) for 3 days (right). C, Western blot analysis of total and phosphorylated form of STAT3 (Ser 727), NNMT, and GPX8 normalized by β-actin from WT vs. GPX8-KO Caki1 with and without hyper-IL6 treatment (50 ng/mL) for 3 days. D, Representative picture (left) of neutral lipid BODIPY 493/503 staining of GPX8-KO Caki1 with and without hyper-IL6 treatment with same condition as in (C). Quantitation of the lipid droplet (right) (n = 3) as in Fig. 3F. E, shGPX8 786O cells were incubated with or without doxycycline (100 ng/mL) for 3 days before incubation with or without Hyper-IL6 (50 ng/mL) for 2 days. Western blot analysis of total and phosphorylated forms of STAT3 (Ser 727), NNMT, GPX8, and β-actin. F, Representative pictures (left) of neutral lipid BODIPY 493/503 staining of shGPX8 786O with or without Hyper-IL6 treatment with the same condition as in (E). Quantitation of the lipid droplet (right) (n ≥ 3) as in Fig. 3F. Data presented in panels (B), (D) and (F) are means ± SD (n ≥ 3). P-values were determined by unpaired t-test

    Article Snippet: Cell culture and isotope labeling experiment condition Human ccRCC cell lines 786O (from ATCC), Caki1, and A498 (Korean Cell Line Bank) were cultured in DMEM (786O and Caki1) or MEM (A498), supplemented with 10% FBS, 1% penicillin–streptomycin.

    Techniques: Expressing, RNA Sequencing, Quantitative RT-PCR, Western Blot, Staining, Quantitation Assay, Incubation

    GPX8 is associated with higher grade and poor prognosis in ccRCC A , Two-tiered bioinformatic screening to find genes correlated with metabolites (top; CCLE database) and genes (bottom; TCGA-KIRC (Kidney renal clear cell carcinoma) database) of glycogen and lipid metabolism in ccRCC. The metabolites and genes used as queries are indicated in each Venn diagram. The criteria were set to FDR < 0.0001 and |r|< 0.15. The numbers in the Venn diagram represent the numbers of genes that meet the criteria. B-D, Violin plots for the mRNA expression levels of GPX8 according to ( B ) normal vs. tumor, ( C ) neoplasm histologic grade, and ( D ) alive or dead-tumor-free group vs. dead-with-tumor group among ccRCC patients. The mRNA expression values were obtained from the TCGA-KIRC dataset. P -values were determined by Mann–Whitney U test. E , Overall survival according to GPX8 mRNA expression for ccRCC patients from TCGA-KIRC database. F , GPX8 IHC staining for tumor array sections (KD482_biomax) from ccRCC patients. Magnification 400X

    Journal: Journal of Experimental & Clinical Cancer Research : CR

    Article Title: GPX8 regulates clear cell renal cell carcinoma tumorigenesis through promoting lipogenesis by NNMT

    doi: 10.1186/s13046-023-02607-2

    Figure Lengend Snippet: GPX8 is associated with higher grade and poor prognosis in ccRCC A , Two-tiered bioinformatic screening to find genes correlated with metabolites (top; CCLE database) and genes (bottom; TCGA-KIRC (Kidney renal clear cell carcinoma) database) of glycogen and lipid metabolism in ccRCC. The metabolites and genes used as queries are indicated in each Venn diagram. The criteria were set to FDR < 0.0001 and |r|< 0.15. The numbers in the Venn diagram represent the numbers of genes that meet the criteria. B-D, Violin plots for the mRNA expression levels of GPX8 according to ( B ) normal vs. tumor, ( C ) neoplasm histologic grade, and ( D ) alive or dead-tumor-free group vs. dead-with-tumor group among ccRCC patients. The mRNA expression values were obtained from the TCGA-KIRC dataset. P -values were determined by Mann–Whitney U test. E , Overall survival according to GPX8 mRNA expression for ccRCC patients from TCGA-KIRC database. F , GPX8 IHC staining for tumor array sections (KD482_biomax) from ccRCC patients. Magnification 400X

    Article Snippet: Human ccRCC cell lines 786O (from ATCC), Caki1, and A498 (Korean Cell Line Bank) were cultured in DMEM (786O and Caki1) or MEM (A498), supplemented with 10% FBS, 1% penicillin–streptomycin.

    Techniques: Expressing, MANN-WHITNEY, Immunohistochemistry

    GPX8 regulates lipid metabolism in ccRCC A-B, Heat map (A) and metabolic pathway enrichment analysis (B) of significantly different metabolite levels from untargeted metabolomics comparing GPX8-KO vs. WT Caki1 ( n = 5). Red asterisks indicate metabolites related to the glycerophospholipid pathway (A). C-D, Volcano plot (C) and pathway analysis of downregulated genes (KEGG pathway) (D) from RNA-seq data for GPX8-KO vs. WT Caki1. Lipid metabolism-related pathways are in red box (D). Criteria: |Log2(fold change)|≥ 2 with P -value ≤ 0.05. E, GSEA analysis of GPX8 correlation with lipid metabolism pathways: regulation of FAO (from Gene ontology) and lysophospholipid pathway (from Pathway Interaction Database). F, Representative pictures (left) of neutral lipid BODIPY 493/503 staining from WT vs. GPX8-KO Caki1 and shGPX8 786O cells with or without doxycycline (100 ng/mL). Quantitation of the lipid droplet (right) ( n = 3): The number of lipid droplets per cell was quantified as detailed in the Methods section. G, Representative pictures of BODIPY 500/510 C1, C12 staining for WT and GPX8-KO Caki1 cells for lipid uptake as measured by fluorescent intensity with flow cytometry (right). H-I, FA de novo synthesis (CH3ω) and triacylglycerol synthesis (esterified-glycerol) from U 13 C-glucose with NMR (H), and bar graphs for their relative levels normalized by total protein level (BCA) comparing WT vs. GPX8-KO Caki1 cells (left) and shGPX8 786O cells with or without doxycycline (100 ng/mL) for 3 days (right) (I). Data presented in panels (F) and (I) are means ± SD ( n ≥ 3). P -value was calculated by unpaired t -test

    Journal: Journal of Experimental & Clinical Cancer Research : CR

    Article Title: GPX8 regulates clear cell renal cell carcinoma tumorigenesis through promoting lipogenesis by NNMT

    doi: 10.1186/s13046-023-02607-2

    Figure Lengend Snippet: GPX8 regulates lipid metabolism in ccRCC A-B, Heat map (A) and metabolic pathway enrichment analysis (B) of significantly different metabolite levels from untargeted metabolomics comparing GPX8-KO vs. WT Caki1 ( n = 5). Red asterisks indicate metabolites related to the glycerophospholipid pathway (A). C-D, Volcano plot (C) and pathway analysis of downregulated genes (KEGG pathway) (D) from RNA-seq data for GPX8-KO vs. WT Caki1. Lipid metabolism-related pathways are in red box (D). Criteria: |Log2(fold change)|≥ 2 with P -value ≤ 0.05. E, GSEA analysis of GPX8 correlation with lipid metabolism pathways: regulation of FAO (from Gene ontology) and lysophospholipid pathway (from Pathway Interaction Database). F, Representative pictures (left) of neutral lipid BODIPY 493/503 staining from WT vs. GPX8-KO Caki1 and shGPX8 786O cells with or without doxycycline (100 ng/mL). Quantitation of the lipid droplet (right) ( n = 3): The number of lipid droplets per cell was quantified as detailed in the Methods section. G, Representative pictures of BODIPY 500/510 C1, C12 staining for WT and GPX8-KO Caki1 cells for lipid uptake as measured by fluorescent intensity with flow cytometry (right). H-I, FA de novo synthesis (CH3ω) and triacylglycerol synthesis (esterified-glycerol) from U 13 C-glucose with NMR (H), and bar graphs for their relative levels normalized by total protein level (BCA) comparing WT vs. GPX8-KO Caki1 cells (left) and shGPX8 786O cells with or without doxycycline (100 ng/mL) for 3 days (right) (I). Data presented in panels (F) and (I) are means ± SD ( n ≥ 3). P -value was calculated by unpaired t -test

    Article Snippet: Human ccRCC cell lines 786O (from ATCC), Caki1, and A498 (Korean Cell Line Bank) were cultured in DMEM (786O and Caki1) or MEM (A498), supplemented with 10% FBS, 1% penicillin–streptomycin.

    Techniques: RNA Sequencing, Staining, Quantitation Assay, Flow Cytometry

    GPX8 is involved in ccRCC cell growth in vitro and in vivo A-D, The effect of GPX8 KO in Caki1 and shGPX8 in 786O cells in vitro. Western blot analysis of GPX8 protein expression (A), relative growth rates measured by CCK8 kit (B), migrating cells in scratch assay at 0, 24, and 48 h (top) and bar graphs for relative wound areas for WT and GPX8-KO Caki1 cells (bottom) ( n = 3) (C), and clonogenic assay after plating 200 cells in 6-well plate for 2 weeks (top) and bar graphs for number of colonies of WT and GPX8-KO Caki1 (bottom) ( n = 3) (D). E, Tumor growths by WT and GPX8-KO Caki1 cells xenografted in nude mice ( n = 6). One mouse in the GPX8-KO group did not develop a visible tumor, and the tumor photo shows 5 tumors. See Fig. S C for the photos for the whole body mouse images. Tumor volume (top, left), tumor weight (top, right), and photograph of tumors (bottom) obtained at day 28 after implantation. Data presented in panels (B), (C), (D), and (E) are means ± SD ( n ≥ 3). P -value was calculated by two-way ANOVA with Geisser–Greenhouse correction for (B) and (E) (top, left panel); unpaired t -test for (C), (D) and (E) (top, right panel)

    Journal: Journal of Experimental & Clinical Cancer Research : CR

    Article Title: GPX8 regulates clear cell renal cell carcinoma tumorigenesis through promoting lipogenesis by NNMT

    doi: 10.1186/s13046-023-02607-2

    Figure Lengend Snippet: GPX8 is involved in ccRCC cell growth in vitro and in vivo A-D, The effect of GPX8 KO in Caki1 and shGPX8 in 786O cells in vitro. Western blot analysis of GPX8 protein expression (A), relative growth rates measured by CCK8 kit (B), migrating cells in scratch assay at 0, 24, and 48 h (top) and bar graphs for relative wound areas for WT and GPX8-KO Caki1 cells (bottom) ( n = 3) (C), and clonogenic assay after plating 200 cells in 6-well plate for 2 weeks (top) and bar graphs for number of colonies of WT and GPX8-KO Caki1 (bottom) ( n = 3) (D). E, Tumor growths by WT and GPX8-KO Caki1 cells xenografted in nude mice ( n = 6). One mouse in the GPX8-KO group did not develop a visible tumor, and the tumor photo shows 5 tumors. See Fig. S C for the photos for the whole body mouse images. Tumor volume (top, left), tumor weight (top, right), and photograph of tumors (bottom) obtained at day 28 after implantation. Data presented in panels (B), (C), (D), and (E) are means ± SD ( n ≥ 3). P -value was calculated by two-way ANOVA with Geisser–Greenhouse correction for (B) and (E) (top, left panel); unpaired t -test for (C), (D) and (E) (top, right panel)

    Article Snippet: Human ccRCC cell lines 786O (from ATCC), Caki1, and A498 (Korean Cell Line Bank) were cultured in DMEM (786O and Caki1) or MEM (A498), supplemented with 10% FBS, 1% penicillin–streptomycin.

    Techniques: In Vitro, In Vivo, Western Blot, Expressing, Wound Healing Assay, Clonogenic Assay

    GPX8 modulates the NNMT expression through IL6-STAT3 signaling. A, Volcano plot for IL6 expression from our RNA-seq data. B, mRNA expression of IL6 by RT-qPCR comparing WT vs. GPX8-KO Caki1 cells (left) and shGPX8 786O with or without doxycycline (100 ng/mL) for 3 days (right). C, Western blot analysis of total and phosphorylated form of STAT3 (Ser 727), NNMT, and GPX8 normalized by β-actin from WT vs. GPX8-KO Caki1 with and without hyper-IL6 treatment (50 ng/mL) for 3 days. D, Representative picture (left) of neutral lipid BODIPY 493/503 staining of GPX8-KO Caki1 with and without hyper-IL6 treatment with same condition as in (C). Quantitation of the lipid droplet (right) ( n = 3) as in Fig. F. E, shGPX8 786O cells were incubated with or without doxycycline (100 ng/mL) for 3 days before incubation with or without Hyper-IL6 (50 ng/mL) for 2 days. Western blot analysis of total and phosphorylated forms of STAT3 (Ser 727), NNMT, GPX8, and β-actin. F, Representative pictures (left) of neutral lipid BODIPY 493/503 staining of shGPX8 786O with or without Hyper-IL6 treatment with the same condition as in (E). Quantitation of the lipid droplet (right) ( n ≥ 3) as in Fig. F. Data presented in panels (B), (D) and (F) are means ± SD ( n ≥ 3). P -values were determined by unpaired t -test

    Journal: Journal of Experimental & Clinical Cancer Research : CR

    Article Title: GPX8 regulates clear cell renal cell carcinoma tumorigenesis through promoting lipogenesis by NNMT

    doi: 10.1186/s13046-023-02607-2

    Figure Lengend Snippet: GPX8 modulates the NNMT expression through IL6-STAT3 signaling. A, Volcano plot for IL6 expression from our RNA-seq data. B, mRNA expression of IL6 by RT-qPCR comparing WT vs. GPX8-KO Caki1 cells (left) and shGPX8 786O with or without doxycycline (100 ng/mL) for 3 days (right). C, Western blot analysis of total and phosphorylated form of STAT3 (Ser 727), NNMT, and GPX8 normalized by β-actin from WT vs. GPX8-KO Caki1 with and without hyper-IL6 treatment (50 ng/mL) for 3 days. D, Representative picture (left) of neutral lipid BODIPY 493/503 staining of GPX8-KO Caki1 with and without hyper-IL6 treatment with same condition as in (C). Quantitation of the lipid droplet (right) ( n = 3) as in Fig. F. E, shGPX8 786O cells were incubated with or without doxycycline (100 ng/mL) for 3 days before incubation with or without Hyper-IL6 (50 ng/mL) for 2 days. Western blot analysis of total and phosphorylated forms of STAT3 (Ser 727), NNMT, GPX8, and β-actin. F, Representative pictures (left) of neutral lipid BODIPY 493/503 staining of shGPX8 786O with or without Hyper-IL6 treatment with the same condition as in (E). Quantitation of the lipid droplet (right) ( n ≥ 3) as in Fig. F. Data presented in panels (B), (D) and (F) are means ± SD ( n ≥ 3). P -values were determined by unpaired t -test

    Article Snippet: Human ccRCC cell lines 786O (from ATCC), Caki1, and A498 (Korean Cell Line Bank) were cultured in DMEM (786O and Caki1) or MEM (A498), supplemented with 10% FBS, 1% penicillin–streptomycin.

    Techniques: Expressing, RNA Sequencing, Quantitative RT-PCR, Western Blot, Staining, Quantitation Assay, Incubation

    GPX8-NNMT axis is independent of VHL mutation status and regulated by ROS. A, Single-cell RNA-seq data for ccRCC tumors with WT-VHL and MT-VHL. Tumor cells are indicated with black ellipses. B, NNMT expression levels in tumor cells from (A). C, mRNA expression levels of GPX8 (left) and NNMT (right) according to normal and VHL status of tumors in ccRCC patients. The mRNA expression values were obtained from the TCGA-KIRC dataset. P -values were determined by Mann–Whitney U test. D-F, Western blot analysis of VHL, HIFs, pAMPK α1 (T183), α2 (T172), GPX8, and NNMT upon ectopic expression of VHL in 786O and A498 cells, or VHL siRNA and CoCl2 treatment in Caki1 cells. G, Total DNL measurement by incorporation of deuterium from 10% D 2 O for 2 days. The fractions of M + 2, M + 3, and M + 4 normalized by M + 0 fraction of palmitate, as measured with LC–MS, from 786O cells with or without VHL-OE. H-J, The effects of treatment of serial concentrations of H 2 O 2 to WT and GPX8-KO Caki1. Western blot analysis of GPX8 upon 1-h incubation (H), representative pictures of neutral lipid staining (top) upon 6-h treatment and quantitation of the lipid droplet (bottom) ( n = 3) as in Fig. F (I), and relative cell viability upon 24-h treatment (J). K, Western blot analysis of NRF2 and GPX8 from Caki1 upon treatment of scrambled or NRF2 siRNA. Data presented in (G), (I), and (J) are means ± SD ( n ≥ 3). P -value in (I) were determined by unpaired t -test. P -value in (J) was calculated by two-way ANOVA with Geisser Greenhouse correction. ns, not significant

    Journal: Journal of Experimental & Clinical Cancer Research : CR

    Article Title: GPX8 regulates clear cell renal cell carcinoma tumorigenesis through promoting lipogenesis by NNMT

    doi: 10.1186/s13046-023-02607-2

    Figure Lengend Snippet: GPX8-NNMT axis is independent of VHL mutation status and regulated by ROS. A, Single-cell RNA-seq data for ccRCC tumors with WT-VHL and MT-VHL. Tumor cells are indicated with black ellipses. B, NNMT expression levels in tumor cells from (A). C, mRNA expression levels of GPX8 (left) and NNMT (right) according to normal and VHL status of tumors in ccRCC patients. The mRNA expression values were obtained from the TCGA-KIRC dataset. P -values were determined by Mann–Whitney U test. D-F, Western blot analysis of VHL, HIFs, pAMPK α1 (T183), α2 (T172), GPX8, and NNMT upon ectopic expression of VHL in 786O and A498 cells, or VHL siRNA and CoCl2 treatment in Caki1 cells. G, Total DNL measurement by incorporation of deuterium from 10% D 2 O for 2 days. The fractions of M + 2, M + 3, and M + 4 normalized by M + 0 fraction of palmitate, as measured with LC–MS, from 786O cells with or without VHL-OE. H-J, The effects of treatment of serial concentrations of H 2 O 2 to WT and GPX8-KO Caki1. Western blot analysis of GPX8 upon 1-h incubation (H), representative pictures of neutral lipid staining (top) upon 6-h treatment and quantitation of the lipid droplet (bottom) ( n = 3) as in Fig. F (I), and relative cell viability upon 24-h treatment (J). K, Western blot analysis of NRF2 and GPX8 from Caki1 upon treatment of scrambled or NRF2 siRNA. Data presented in (G), (I), and (J) are means ± SD ( n ≥ 3). P -value in (I) were determined by unpaired t -test. P -value in (J) was calculated by two-way ANOVA with Geisser Greenhouse correction. ns, not significant

    Article Snippet: Human ccRCC cell lines 786O (from ATCC), Caki1, and A498 (Korean Cell Line Bank) were cultured in DMEM (786O and Caki1) or MEM (A498), supplemented with 10% FBS, 1% penicillin–streptomycin.

    Techniques: Mutagenesis, RNA Sequencing, Expressing, MANN-WHITNEY, Western Blot, Liquid Chromatography with Mass Spectroscopy, Incubation, Staining, Quantitation Assay

    PBMCs from ccRCC patients confer resistance to cabozantinib treatment. (A–E) Schematic of the experimental set-up. microDUO, high throughput 384-well open microchannel multi-culture plates (Onexio Biosystems) were used to determine the effect of ccRCC PBMCs on angiogenesis. (F) The total length of the endothelial tubes was normalized to EC + DMSO-only control condition (dotted line).

    Journal: Integrative Biology

    Article Title: Immune cell mediated cabozantinib resistance for patients with renal cell carcinoma

    doi: 10.1093/intbio/zyab018

    Figure Lengend Snippet: PBMCs from ccRCC patients confer resistance to cabozantinib treatment. (A–E) Schematic of the experimental set-up. microDUO, high throughput 384-well open microchannel multi-culture plates (Onexio Biosystems) were used to determine the effect of ccRCC PBMCs on angiogenesis. (F) The total length of the endothelial tubes was normalized to EC + DMSO-only control condition (dotted line).

    Article Snippet: 786O ccRCC cancer cell line was purchased from ATCC (ATCC, Cat. CRL-1932TM) and were cultured in RPMI-1640 (ThermoFisher Scientific, Cat. 11875119) media supplemented with 10% fetal bovine serum (VWR) and 100 U/ml penicillin/streptomycin (ThermoFisher Scientific).

    Techniques: High Throughput Screening Assay, Control

    PBMCs from patients with ccRCC upregulated secretion of pro-angiogenic factors in response to cabozantinib treatment. (A) The concentration of pro-angiogenic factors was quantified using a multiplex magnetic bead-based assay (R&D Systems). The heatmap was used to visualize the differential regulation of pro-angiogenic factors in response to cabozantinib treatment in the absence and presence of cancer cells and ccRCC PBMCs. (B) The concentration of pro-angiogenic cytokines and growth factors obtained from conditioned media from mono-culture, co-culture, and tri-culture conditions treated with cabozantinib. Bars represent average ± SD of n = 3 wells for EC + DMSO, EC + cabozantinib, EC + 786O + cabozantinib, and n = 9 wells (three wells per patient, three patients in total) ( * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.005, and # P ≤ 0.0001).

    Journal: Integrative Biology

    Article Title: Immune cell mediated cabozantinib resistance for patients with renal cell carcinoma

    doi: 10.1093/intbio/zyab018

    Figure Lengend Snippet: PBMCs from patients with ccRCC upregulated secretion of pro-angiogenic factors in response to cabozantinib treatment. (A) The concentration of pro-angiogenic factors was quantified using a multiplex magnetic bead-based assay (R&D Systems). The heatmap was used to visualize the differential regulation of pro-angiogenic factors in response to cabozantinib treatment in the absence and presence of cancer cells and ccRCC PBMCs. (B) The concentration of pro-angiogenic cytokines and growth factors obtained from conditioned media from mono-culture, co-culture, and tri-culture conditions treated with cabozantinib. Bars represent average ± SD of n = 3 wells for EC + DMSO, EC + cabozantinib, EC + 786O + cabozantinib, and n = 9 wells (three wells per patient, three patients in total) ( * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.005, and # P ≤ 0.0001).

    Article Snippet: 786O ccRCC cancer cell line was purchased from ATCC (ATCC, Cat. CRL-1932TM) and were cultured in RPMI-1640 (ThermoFisher Scientific, Cat. 11875119) media supplemented with 10% fetal bovine serum (VWR) and 100 U/ml penicillin/streptomycin (ThermoFisher Scientific).

    Techniques: Concentration Assay, Multiplex Assay, Bead-based Assay, Co-Culture Assay

    PLSR analysis of MDSC and T cell subsets and cabozantinib resistance. PBMCs isolated from nine patients with ccRCC undergoing systemic therapy were profiled for MDSC and T cell subtypes using flow cytometry. A PLSR model was generated using flow cytometry data as independent variables and cabozantinib resistance quantified by total tube length from tri-culture angiogenesis assay as a dependent variable. (A) Scores plot separated patients according to the degree of resistance measured in the tri-culture model along the principal component 1 (PC1). (B) Loadings plot shows covariance among the immune cell subtypes with the cabozantinib resistance. (C) VIP of immune cell subtypes with VIP score >1. (D) Changes in Th9, Th17, Th22, and Th2 cells for four patients who are receiving cabozantinib treatment (solid lines) were compared to five patients who are undergoing other therapies (dotted lines, three patients for nivolumab and two patients for pazopanib). (E) Immune gene-signature analysis of 530 patients with ccRCC from TCGA cohort showed that patients with higher expressions of the Th22 gene signature had significantly better overall survival (log-rank test P = 0.027). There was no significant correlation between the Th9 gene signature and overall survival.

    Journal: Integrative Biology

    Article Title: Immune cell mediated cabozantinib resistance for patients with renal cell carcinoma

    doi: 10.1093/intbio/zyab018

    Figure Lengend Snippet: PLSR analysis of MDSC and T cell subsets and cabozantinib resistance. PBMCs isolated from nine patients with ccRCC undergoing systemic therapy were profiled for MDSC and T cell subtypes using flow cytometry. A PLSR model was generated using flow cytometry data as independent variables and cabozantinib resistance quantified by total tube length from tri-culture angiogenesis assay as a dependent variable. (A) Scores plot separated patients according to the degree of resistance measured in the tri-culture model along the principal component 1 (PC1). (B) Loadings plot shows covariance among the immune cell subtypes with the cabozantinib resistance. (C) VIP of immune cell subtypes with VIP score >1. (D) Changes in Th9, Th17, Th22, and Th2 cells for four patients who are receiving cabozantinib treatment (solid lines) were compared to five patients who are undergoing other therapies (dotted lines, three patients for nivolumab and two patients for pazopanib). (E) Immune gene-signature analysis of 530 patients with ccRCC from TCGA cohort showed that patients with higher expressions of the Th22 gene signature had significantly better overall survival (log-rank test P = 0.027). There was no significant correlation between the Th9 gene signature and overall survival.

    Article Snippet: 786O ccRCC cancer cell line was purchased from ATCC (ATCC, Cat. CRL-1932TM) and were cultured in RPMI-1640 (ThermoFisher Scientific, Cat. 11875119) media supplemented with 10% fetal bovine serum (VWR) and 100 U/ml penicillin/streptomycin (ThermoFisher Scientific).

    Techniques: Isolation, Flow Cytometry, Generated, Angiogenesis Assay

    (A) Decreased FABP5 mRNA levels in Caki-1 and 786O cells in the FABP5-RNAi group. Decreased viability of (B) Caki-1 and (C) 786O cells in the FABP5-RNAi group at all time points. (D) Fewer EdU-positive Caki-1 and 786O cells were observed in the FABP5-RNAi group when compared with the NC-RNAi control group (scale bar, 200 µ m). (E) Quantification of the EdU staining results. * P<0.05, ** P<0.01 and *** P<0.001 vs. NC-RNAi group. FABP5, fatty acid binding protein 5; RNAi, RNA interference; NC, negative control; EdU, 5-ethynyl-2′-deoxyuridine.

    Journal: International Journal of Oncology

    Article Title: FABP5 regulates the proliferation of clear cell renal cell carcinoma cells via the PI3K/AKT signaling pathway

    doi: 10.3892/ijo.2019.4721

    Figure Lengend Snippet: (A) Decreased FABP5 mRNA levels in Caki-1 and 786O cells in the FABP5-RNAi group. Decreased viability of (B) Caki-1 and (C) 786O cells in the FABP5-RNAi group at all time points. (D) Fewer EdU-positive Caki-1 and 786O cells were observed in the FABP5-RNAi group when compared with the NC-RNAi control group (scale bar, 200 µ m). (E) Quantification of the EdU staining results. * P<0.05, ** P<0.01 and *** P<0.001 vs. NC-RNAi group. FABP5, fatty acid binding protein 5; RNAi, RNA interference; NC, negative control; EdU, 5-ethynyl-2′-deoxyuridine.

    Article Snippet: Caki-1 (cat. no. GCC-KI0004RT) and 786O (cat. no. GCC-KI0003RT) ccRCC cell lines were purchased from Shanghai GeneChem, Co., Ltd. (Shanghai, China).

    Techniques: Control, Staining, Binding Assay, Negative Control

    Western blotting results demonstrating that FABP5 and p-AKT protein levels were decreased in (A and B) Caki-1 and (C and D) 786O cells in the FABP5-RNAi group when compared with the respective NC-RNAi groups. ** P<0.01 and *** P<0.001 vs. NC-RNAi. FABP5, fatty acid binding protein 5; p-, phosphorylated; RNAi, RNA interference; NC, negative control.

    Journal: International Journal of Oncology

    Article Title: FABP5 regulates the proliferation of clear cell renal cell carcinoma cells via the PI3K/AKT signaling pathway

    doi: 10.3892/ijo.2019.4721

    Figure Lengend Snippet: Western blotting results demonstrating that FABP5 and p-AKT protein levels were decreased in (A and B) Caki-1 and (C and D) 786O cells in the FABP5-RNAi group when compared with the respective NC-RNAi groups. ** P<0.01 and *** P<0.001 vs. NC-RNAi. FABP5, fatty acid binding protein 5; p-, phosphorylated; RNAi, RNA interference; NC, negative control.

    Article Snippet: Caki-1 (cat. no. GCC-KI0004RT) and 786O (cat. no. GCC-KI0003RT) ccRCC cell lines were purchased from Shanghai GeneChem, Co., Ltd. (Shanghai, China).

    Techniques: Western Blot, Binding Assay, Negative Control

    Following transfection of Caki-1 and 786O cells with LV-NC or LV-FABP5, (A) cells were observed to express green fluorescent protein (scale bar, 200 µ m). (B) FABP5 mRNA levels were increased in LV-FABP5-transfected Caki-1 and 786O cells. The viability of (C) Caki-1 and (D) 786O cells was increased in the LV-FABP5 group when compared with the LV-NC group at all time points. (E) The number of EdU-positive Caki-1 and 786O cells in the LV-FABP5 group was higher than the LV-NC group (scale bar, 200 µ m). (F) Quantification of the EdU staining results. * P<0.05, ** P<0.01 and *** P<0.001 vs. LV-NC. LV, lentivirus; NC, negative control; FABP5, fatty acid binding protein 5; EdU, 5-ethynyl-2′-deoxyuridine.

    Journal: International Journal of Oncology

    Article Title: FABP5 regulates the proliferation of clear cell renal cell carcinoma cells via the PI3K/AKT signaling pathway

    doi: 10.3892/ijo.2019.4721

    Figure Lengend Snippet: Following transfection of Caki-1 and 786O cells with LV-NC or LV-FABP5, (A) cells were observed to express green fluorescent protein (scale bar, 200 µ m). (B) FABP5 mRNA levels were increased in LV-FABP5-transfected Caki-1 and 786O cells. The viability of (C) Caki-1 and (D) 786O cells was increased in the LV-FABP5 group when compared with the LV-NC group at all time points. (E) The number of EdU-positive Caki-1 and 786O cells in the LV-FABP5 group was higher than the LV-NC group (scale bar, 200 µ m). (F) Quantification of the EdU staining results. * P<0.05, ** P<0.01 and *** P<0.001 vs. LV-NC. LV, lentivirus; NC, negative control; FABP5, fatty acid binding protein 5; EdU, 5-ethynyl-2′-deoxyuridine.

    Article Snippet: Caki-1 (cat. no. GCC-KI0004RT) and 786O (cat. no. GCC-KI0003RT) ccRCC cell lines were purchased from Shanghai GeneChem, Co., Ltd. (Shanghai, China).

    Techniques: Transfection, Staining, Negative Control, Binding Assay

    Exogenous FABP5 expression increased the viability of (A) Caki-1 and (B) 786O cells, whereas LY294002 treatment decreased the viability of FABP5-overexpressing cells as determined using the CCK-8 assay. (C) An EdU assay demonstrated that the proportion of EdU-positive Caki-1 and 786O cells in the LV-FABP5 group were decreased following LY294002 treatment (scale bar, 200 µ m). Quantification of the EdU staining results in (D) Caki-1 and (E) 786O cells. (F) Western blotting results demonstrating exogenous FABP5 expression in the LV-FABP5 group (indicated as FABP5-FLAG and FLAG) and the upregulation of p-AKT in Caki-1 cells from the LV-FABP5 group. LY294002 treatment decreased the level of p-AKT in FABP5-overexpressing Caki-1 cells. (G) Quantification of the western blotting results in Caki-1 cells. (H) Western blotting results demonstrating exogenous FABP5 expression in the LV-FABP5 group (indicated as FABP5-FLAG and FLAG) and the upregulation of p-AKT in 786O cells from the LV-FABP5 group. LY294002 treatment decreased the level of p-AKT in FABP5-overexpressing 786O cells. (I) Quantification of the western blotting results in 786O cells. * P<0.05, ** P<0.01 and *** P<0.001, as indicated. FABP5, fatty acid binding protein 5; CCK-8, Cell Counting kit-8; EdU, 5-ethynyl-2′-deoxyuridine; LV, lentivirus; p-, phosphorylated; NC, negative control.

    Journal: International Journal of Oncology

    Article Title: FABP5 regulates the proliferation of clear cell renal cell carcinoma cells via the PI3K/AKT signaling pathway

    doi: 10.3892/ijo.2019.4721

    Figure Lengend Snippet: Exogenous FABP5 expression increased the viability of (A) Caki-1 and (B) 786O cells, whereas LY294002 treatment decreased the viability of FABP5-overexpressing cells as determined using the CCK-8 assay. (C) An EdU assay demonstrated that the proportion of EdU-positive Caki-1 and 786O cells in the LV-FABP5 group were decreased following LY294002 treatment (scale bar, 200 µ m). Quantification of the EdU staining results in (D) Caki-1 and (E) 786O cells. (F) Western blotting results demonstrating exogenous FABP5 expression in the LV-FABP5 group (indicated as FABP5-FLAG and FLAG) and the upregulation of p-AKT in Caki-1 cells from the LV-FABP5 group. LY294002 treatment decreased the level of p-AKT in FABP5-overexpressing Caki-1 cells. (G) Quantification of the western blotting results in Caki-1 cells. (H) Western blotting results demonstrating exogenous FABP5 expression in the LV-FABP5 group (indicated as FABP5-FLAG and FLAG) and the upregulation of p-AKT in 786O cells from the LV-FABP5 group. LY294002 treatment decreased the level of p-AKT in FABP5-overexpressing 786O cells. (I) Quantification of the western blotting results in 786O cells. * P<0.05, ** P<0.01 and *** P<0.001, as indicated. FABP5, fatty acid binding protein 5; CCK-8, Cell Counting kit-8; EdU, 5-ethynyl-2′-deoxyuridine; LV, lentivirus; p-, phosphorylated; NC, negative control.

    Article Snippet: Caki-1 (cat. no. GCC-KI0004RT) and 786O (cat. no. GCC-KI0003RT) ccRCC cell lines were purchased from Shanghai GeneChem, Co., Ltd. (Shanghai, China).

    Techniques: Expressing, CCK-8 Assay, EdU Assay, Staining, Western Blot, Binding Assay, Cell Counting, Negative Control

    Effect of FABP5 (A) knockdown on Caki-1 cell migration (scale bar, 200 µ m) and (B) quantification of the results. Effect of FABP5 (C) overexpres-sion on Caki-1 cell migration (scale bar, 200 µ m) and (D) quantification of the results. Effect of FABP5 (E) knockdown on 786O cell migration (scale bar, 200 µ m) and (F) quantification of the results. Effect of FABP5 (G) overexpression on 786O cell migration (scale bar, 200 µ m) and (H) quantification of the results. Effect of FABP5 (I) knockdown and (J) overexpression on the invasion of Caki-1 and 786O cells (scale bar, 100 μm). FABP5, fatty acid binding protein 5; LV, lentivirus; NC, negative control; RNAi, RNA interference.

    Journal: International Journal of Oncology

    Article Title: FABP5 regulates the proliferation of clear cell renal cell carcinoma cells via the PI3K/AKT signaling pathway

    doi: 10.3892/ijo.2019.4721

    Figure Lengend Snippet: Effect of FABP5 (A) knockdown on Caki-1 cell migration (scale bar, 200 µ m) and (B) quantification of the results. Effect of FABP5 (C) overexpres-sion on Caki-1 cell migration (scale bar, 200 µ m) and (D) quantification of the results. Effect of FABP5 (E) knockdown on 786O cell migration (scale bar, 200 µ m) and (F) quantification of the results. Effect of FABP5 (G) overexpression on 786O cell migration (scale bar, 200 µ m) and (H) quantification of the results. Effect of FABP5 (I) knockdown and (J) overexpression on the invasion of Caki-1 and 786O cells (scale bar, 100 μm). FABP5, fatty acid binding protein 5; LV, lentivirus; NC, negative control; RNAi, RNA interference.

    Article Snippet: Caki-1 (cat. no. GCC-KI0004RT) and 786O (cat. no. GCC-KI0003RT) ccRCC cell lines were purchased from Shanghai GeneChem, Co., Ltd. (Shanghai, China).

    Techniques: Knockdown, Migration, Over Expression, Binding Assay, Negative Control