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human colorectal cancer cell lines sw480  (ATCC)


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    ATCC human colorectal cancer cell lines sw480
    ACLY activity regulates MDR1 expression in colorectal cancer. (A) Transcript levels of ACLY and MDR1 (ABCB1) in colorectal cancer (red) and normal colon tissues (grey) analyzed using GEPIA (TCGA/GTEx datasets). (B) Immunoblot analysis of MDR1 in <t>SW480</t> and DLD1 cells treated with the ACLY inhibitor BMS-303141 (20 or 50 μM, 48 h). (C) Immunoblot analysis of ACLY and MDR1 in SW480 and DLD1 cells transduced with empty vector (pLV) or ACLY-overexpressing vector (pLV[Exp]-hACLY). (D) Immunoblot analysis of ACLY and MDR1 in control and ACLY-overexpressing cells treated with BMS-303141 (50 μM, 48 h). (E) Relative ABCB1 mRNA levels in control and ACLY-overexpressing cells, and in cells treated with BMS-303141. (F) Relative ACLY mRNA levels under the same conditions. Data are presented as mean ± SD (n = 3 unless otherwise indicated). Statistical significance was determined using unpaired two-tailed t-tests or one-way ANOVA with Tukey’s post hoc test. *P < 0.05; **P < 0.01; ***P < 0.001.
    Human Colorectal Cancer Cell Lines Sw480, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 7314 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/colorectal+cancer+cell+lines+sw480/pmc13142016-33-0-14?v=ATCC
    Average 99 stars, based on 7314 article reviews
    human colorectal cancer cell lines sw480 - by Bioz Stars, 2026-08
    99/100 stars

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    1) Product Images from "Metabolic regulation of histone acetylation by ACLY supports MDR1 expression in colorectal cancer and highlights a targetable vulnerability"

    Article Title: Metabolic regulation of histone acetylation by ACLY supports MDR1 expression in colorectal cancer and highlights a targetable vulnerability

    Journal: Neoplasia (New York, N.Y.)

    doi: 10.1016/j.neo.2026.101314

    ACLY activity regulates MDR1 expression in colorectal cancer. (A) Transcript levels of ACLY and MDR1 (ABCB1) in colorectal cancer (red) and normal colon tissues (grey) analyzed using GEPIA (TCGA/GTEx datasets). (B) Immunoblot analysis of MDR1 in SW480 and DLD1 cells treated with the ACLY inhibitor BMS-303141 (20 or 50 μM, 48 h). (C) Immunoblot analysis of ACLY and MDR1 in SW480 and DLD1 cells transduced with empty vector (pLV) or ACLY-overexpressing vector (pLV[Exp]-hACLY). (D) Immunoblot analysis of ACLY and MDR1 in control and ACLY-overexpressing cells treated with BMS-303141 (50 μM, 48 h). (E) Relative ABCB1 mRNA levels in control and ACLY-overexpressing cells, and in cells treated with BMS-303141. (F) Relative ACLY mRNA levels under the same conditions. Data are presented as mean ± SD (n = 3 unless otherwise indicated). Statistical significance was determined using unpaired two-tailed t-tests or one-way ANOVA with Tukey’s post hoc test. *P < 0.05; **P < 0.01; ***P < 0.001.
    Figure Legend Snippet: ACLY activity regulates MDR1 expression in colorectal cancer. (A) Transcript levels of ACLY and MDR1 (ABCB1) in colorectal cancer (red) and normal colon tissues (grey) analyzed using GEPIA (TCGA/GTEx datasets). (B) Immunoblot analysis of MDR1 in SW480 and DLD1 cells treated with the ACLY inhibitor BMS-303141 (20 or 50 μM, 48 h). (C) Immunoblot analysis of ACLY and MDR1 in SW480 and DLD1 cells transduced with empty vector (pLV) or ACLY-overexpressing vector (pLV[Exp]-hACLY). (D) Immunoblot analysis of ACLY and MDR1 in control and ACLY-overexpressing cells treated with BMS-303141 (50 μM, 48 h). (E) Relative ABCB1 mRNA levels in control and ACLY-overexpressing cells, and in cells treated with BMS-303141. (F) Relative ACLY mRNA levels under the same conditions. Data are presented as mean ± SD (n = 3 unless otherwise indicated). Statistical significance was determined using unpaired two-tailed t-tests or one-way ANOVA with Tukey’s post hoc test. *P < 0.05; **P < 0.01; ***P < 0.001.

    Techniques Used: Activity Assay, Expressing, Western Blot, Transduction, Plasmid Preparation, Control, Two Tailed Test

    ACLY activity modulates histone acetylation and MDR1 expression. (A) Immunoblot analysis of MDR1 in SW480 and DLD1 cells treated with the histone deacetylase inhibitor vorinostat (VOR; 0.5 μM for SW480 and 3.5 μM for DLD1) or DMSO for 24 h. Representative blots and densitometric quantification relative to control are shown. (B) Immunoblot analysis of acetylated histone H3 (H3K9ac) and histone H4 (H4K16ac) in SW480 wild-type (WT) and ACLY-overexpressing (OE) cells treated with vehicle or the ACLY inhibitor BMS-303141 (50 μM, 48 h). (C) Immunoblot analysis of H3K9ac and H4K16ac in DLD1 cells under the same conditions. β-actin was used as a loading control. Data are presented as mean ± SD (n = 3). Statistical significance was determined using unpaired two-tailed t-tests. *P < 0.05; **P < 0.01; ***P < 0.001.
    Figure Legend Snippet: ACLY activity modulates histone acetylation and MDR1 expression. (A) Immunoblot analysis of MDR1 in SW480 and DLD1 cells treated with the histone deacetylase inhibitor vorinostat (VOR; 0.5 μM for SW480 and 3.5 μM for DLD1) or DMSO for 24 h. Representative blots and densitometric quantification relative to control are shown. (B) Immunoblot analysis of acetylated histone H3 (H3K9ac) and histone H4 (H4K16ac) in SW480 wild-type (WT) and ACLY-overexpressing (OE) cells treated with vehicle or the ACLY inhibitor BMS-303141 (50 μM, 48 h). (C) Immunoblot analysis of H3K9ac and H4K16ac in DLD1 cells under the same conditions. β-actin was used as a loading control. Data are presented as mean ± SD (n = 3). Statistical significance was determined using unpaired two-tailed t-tests. *P < 0.05; **P < 0.01; ***P < 0.001.

    Techniques Used: Activity Assay, Expressing, Western Blot, Histone Deacetylase Assay, Control, Two Tailed Test

    ACLY expression is associated with resistance-related transcriptional programs in colorectal cancer. (A) Correlation analysis between ACLY expression and a gene set associated with lipid metabolism (ACLY, ACSS2, ACSS1, FASN, SREBP1) and drug transport pathways (ABCB1, ABCC2, ABCG5, EpCAM, CD24) in colorectal cancer samples using GEPIA2 (TCGA dataset). (B) Schematic representation of a proposed model linking ACLY-dependent acetyl-CoA production to histone acetylation and transcriptional regulation in CRC cells. (C) Relative mRNA expression of EpCAM, ABCC2, and CD24 in SW480 and DLD1 cells overexpressing ACLY compared with empty vector controls. (D) Relative mRNA expression of EpCAM, ABCC2, and CD24 in SW480 and DLD1 cells treated with the ACLY inhibitor BMS-303141 (50 μM) compared with vehicle-treated controls. Gene expression levels were determined by qPCR and normalized to ACTB. Data are presented as mean ± SEM (n = 3). Statistical significance was determined using unpaired two-tailed t-tests. *P < 0.05; **P < 0.01; ***P < 0.001.
    Figure Legend Snippet: ACLY expression is associated with resistance-related transcriptional programs in colorectal cancer. (A) Correlation analysis between ACLY expression and a gene set associated with lipid metabolism (ACLY, ACSS2, ACSS1, FASN, SREBP1) and drug transport pathways (ABCB1, ABCC2, ABCG5, EpCAM, CD24) in colorectal cancer samples using GEPIA2 (TCGA dataset). (B) Schematic representation of a proposed model linking ACLY-dependent acetyl-CoA production to histone acetylation and transcriptional regulation in CRC cells. (C) Relative mRNA expression of EpCAM, ABCC2, and CD24 in SW480 and DLD1 cells overexpressing ACLY compared with empty vector controls. (D) Relative mRNA expression of EpCAM, ABCC2, and CD24 in SW480 and DLD1 cells treated with the ACLY inhibitor BMS-303141 (50 μM) compared with vehicle-treated controls. Gene expression levels were determined by qPCR and normalized to ACTB. Data are presented as mean ± SEM (n = 3). Statistical significance was determined using unpaired two-tailed t-tests. *P < 0.05; **P < 0.01; ***P < 0.001.

    Techniques Used: Expressing, Drug Transport Assay, Plasmid Preparation, Gene Expression, Two Tailed Test

    Vitamin C induces coordinated changes in metabolic and chromatin-associated pathways in colorectal cancer cells. (A) Gene Ontology (GO) enrichment analysis of proteins differentially expressed following vitamin C treatment (5 mM, 4 h). (B) Volcano plot showing significantly upregulated and downregulated proteins (log₂ fold change > 1, p < 0.05). (C) KEGG pathway enrichment analysis highlighting pathways related to chromatin organization, DNA replication, nucleotide metabolism, and cell cycle regulation. (D) GO Cellular Component analysis showing enrichment of chromatin-associated complexes, including transcription regulator complexes, histone acetyltransferase-containing complexes, and Polycomb group (PcG) assemblies. (E) Heatmap representation of differentially expressed chromatin-associated proteins in control and vitamin C-treated cells. Proteomic analysis was performed in SW480 and DLD1 cells using label-free LC–MS/MS (diaPASEF). Data represent combined analysis of both cell lines.
    Figure Legend Snippet: Vitamin C induces coordinated changes in metabolic and chromatin-associated pathways in colorectal cancer cells. (A) Gene Ontology (GO) enrichment analysis of proteins differentially expressed following vitamin C treatment (5 mM, 4 h). (B) Volcano plot showing significantly upregulated and downregulated proteins (log₂ fold change > 1, p < 0.05). (C) KEGG pathway enrichment analysis highlighting pathways related to chromatin organization, DNA replication, nucleotide metabolism, and cell cycle regulation. (D) GO Cellular Component analysis showing enrichment of chromatin-associated complexes, including transcription regulator complexes, histone acetyltransferase-containing complexes, and Polycomb group (PcG) assemblies. (E) Heatmap representation of differentially expressed chromatin-associated proteins in control and vitamin C-treated cells. Proteomic analysis was performed in SW480 and DLD1 cells using label-free LC–MS/MS (diaPASEF). Data represent combined analysis of both cell lines.

    Techniques Used: Control, Liquid Chromatography with Mass Spectroscopy, Data-independent acquisition

    Metabolic and epigenetic consequences of vitamin C treatment in colorectal cancer cells. (A) Quantification of ¹³C-glucose-derived citrate in SW480 and DLD1 cells treated with vitamin C (5 mM) for 4 h (n = 3). (B) Immunoblot analysis of total ACLY and phosphorylated ACLY at Ser455 following vitamin C treatment (5 mM) (n = 3). (C) Immunoblot analysis and quantification of acetylated histone H4 (AcH4K16) and histone H3 (AcH3K9) in SW480 and DLD1 cells after vitamin C exposure (n = 3). (D) MDR1 (ABCB1) protein levels in SW480 and DLD1 cells treated with vitamin C (5 mM), quantified relative to vehicle control (n = 3). (E) Relative ACLY and ABCB1 mRNA expression determined by qPCR after 6 h of vitamin C treatment (5 mM) in SW480 and DLD1 cells (n = 3). Data are presented as mean ± SEM. Statistical significance was determined using unpaired two-tailed t-tests. *P < 0.05; **P < 0.01; ***P < 0.001.
    Figure Legend Snippet: Metabolic and epigenetic consequences of vitamin C treatment in colorectal cancer cells. (A) Quantification of ¹³C-glucose-derived citrate in SW480 and DLD1 cells treated with vitamin C (5 mM) for 4 h (n = 3). (B) Immunoblot analysis of total ACLY and phosphorylated ACLY at Ser455 following vitamin C treatment (5 mM) (n = 3). (C) Immunoblot analysis and quantification of acetylated histone H4 (AcH4K16) and histone H3 (AcH3K9) in SW480 and DLD1 cells after vitamin C exposure (n = 3). (D) MDR1 (ABCB1) protein levels in SW480 and DLD1 cells treated with vitamin C (5 mM), quantified relative to vehicle control (n = 3). (E) Relative ACLY and ABCB1 mRNA expression determined by qPCR after 6 h of vitamin C treatment (5 mM) in SW480 and DLD1 cells (n = 3). Data are presented as mean ± SEM. Statistical significance was determined using unpaired two-tailed t-tests. *P < 0.05; **P < 0.01; ***P < 0.001.

    Techniques Used: Derivative Assay, Western Blot, Control, Expressing, Two Tailed Test



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    ACLY activity regulates MDR1 expression in colorectal cancer. (A) Transcript levels of ACLY and MDR1 (ABCB1) in colorectal cancer (red) and normal colon tissues (grey) analyzed using GEPIA (TCGA/GTEx datasets). (B) Immunoblot analysis of MDR1 in <t>SW480</t> and DLD1 cells treated with the ACLY inhibitor BMS-303141 (20 or 50 μM, 48 h). (C) Immunoblot analysis of ACLY and MDR1 in SW480 and DLD1 cells transduced with empty vector (pLV) or ACLY-overexpressing vector (pLV[Exp]-hACLY). (D) Immunoblot analysis of ACLY and MDR1 in control and ACLY-overexpressing cells treated with BMS-303141 (50 μM, 48 h). (E) Relative ABCB1 mRNA levels in control and ACLY-overexpressing cells, and in cells treated with BMS-303141. (F) Relative ACLY mRNA levels under the same conditions. Data are presented as mean ± SD (n = 3 unless otherwise indicated). Statistical significance was determined using unpaired two-tailed t-tests or one-way ANOVA with Tukey’s post hoc test. *P < 0.05; **P < 0.01; ***P < 0.001.
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    ACLY activity regulates MDR1 expression in colorectal cancer. (A) Transcript levels of ACLY and MDR1 (ABCB1) in colorectal cancer (red) and normal colon tissues (grey) analyzed using GEPIA (TCGA/GTEx datasets). (B) Immunoblot analysis of MDR1 in <t>SW480</t> and DLD1 cells treated with the ACLY inhibitor BMS-303141 (20 or 50 μM, 48 h). (C) Immunoblot analysis of ACLY and MDR1 in SW480 and DLD1 cells transduced with empty vector (pLV) or ACLY-overexpressing vector (pLV[Exp]-hACLY). (D) Immunoblot analysis of ACLY and MDR1 in control and ACLY-overexpressing cells treated with BMS-303141 (50 μM, 48 h). (E) Relative ABCB1 mRNA levels in control and ACLY-overexpressing cells, and in cells treated with BMS-303141. (F) Relative ACLY mRNA levels under the same conditions. Data are presented as mean ± SD (n = 3 unless otherwise indicated). Statistical significance was determined using unpaired two-tailed t-tests or one-way ANOVA with Tukey’s post hoc test. *P < 0.05; **P < 0.01; ***P < 0.001.
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    Image Search Results


    ACLY activity regulates MDR1 expression in colorectal cancer. (A) Transcript levels of ACLY and MDR1 (ABCB1) in colorectal cancer (red) and normal colon tissues (grey) analyzed using GEPIA (TCGA/GTEx datasets). (B) Immunoblot analysis of MDR1 in SW480 and DLD1 cells treated with the ACLY inhibitor BMS-303141 (20 or 50 μM, 48 h). (C) Immunoblot analysis of ACLY and MDR1 in SW480 and DLD1 cells transduced with empty vector (pLV) or ACLY-overexpressing vector (pLV[Exp]-hACLY). (D) Immunoblot analysis of ACLY and MDR1 in control and ACLY-overexpressing cells treated with BMS-303141 (50 μM, 48 h). (E) Relative ABCB1 mRNA levels in control and ACLY-overexpressing cells, and in cells treated with BMS-303141. (F) Relative ACLY mRNA levels under the same conditions. Data are presented as mean ± SD (n = 3 unless otherwise indicated). Statistical significance was determined using unpaired two-tailed t-tests or one-way ANOVA with Tukey’s post hoc test. *P < 0.05; **P < 0.01; ***P < 0.001.

    Journal: Neoplasia (New York, N.Y.)

    Article Title: Metabolic regulation of histone acetylation by ACLY supports MDR1 expression in colorectal cancer and highlights a targetable vulnerability

    doi: 10.1016/j.neo.2026.101314

    Figure Lengend Snippet: ACLY activity regulates MDR1 expression in colorectal cancer. (A) Transcript levels of ACLY and MDR1 (ABCB1) in colorectal cancer (red) and normal colon tissues (grey) analyzed using GEPIA (TCGA/GTEx datasets). (B) Immunoblot analysis of MDR1 in SW480 and DLD1 cells treated with the ACLY inhibitor BMS-303141 (20 or 50 μM, 48 h). (C) Immunoblot analysis of ACLY and MDR1 in SW480 and DLD1 cells transduced with empty vector (pLV) or ACLY-overexpressing vector (pLV[Exp]-hACLY). (D) Immunoblot analysis of ACLY and MDR1 in control and ACLY-overexpressing cells treated with BMS-303141 (50 μM, 48 h). (E) Relative ABCB1 mRNA levels in control and ACLY-overexpressing cells, and in cells treated with BMS-303141. (F) Relative ACLY mRNA levels under the same conditions. Data are presented as mean ± SD (n = 3 unless otherwise indicated). Statistical significance was determined using unpaired two-tailed t-tests or one-way ANOVA with Tukey’s post hoc test. *P < 0.05; **P < 0.01; ***P < 0.001.

    Article Snippet: Human colorectal cancer cell lines SW480 (KRASG12V) and DLD1 (KRASG13D) were obtained from the American Type Culture Collection (ATCC) and authenticated by short tandem repeat profiling.

    Techniques: Activity Assay, Expressing, Western Blot, Transduction, Plasmid Preparation, Control, Two Tailed Test

    ACLY activity modulates histone acetylation and MDR1 expression. (A) Immunoblot analysis of MDR1 in SW480 and DLD1 cells treated with the histone deacetylase inhibitor vorinostat (VOR; 0.5 μM for SW480 and 3.5 μM for DLD1) or DMSO for 24 h. Representative blots and densitometric quantification relative to control are shown. (B) Immunoblot analysis of acetylated histone H3 (H3K9ac) and histone H4 (H4K16ac) in SW480 wild-type (WT) and ACLY-overexpressing (OE) cells treated with vehicle or the ACLY inhibitor BMS-303141 (50 μM, 48 h). (C) Immunoblot analysis of H3K9ac and H4K16ac in DLD1 cells under the same conditions. β-actin was used as a loading control. Data are presented as mean ± SD (n = 3). Statistical significance was determined using unpaired two-tailed t-tests. *P < 0.05; **P < 0.01; ***P < 0.001.

    Journal: Neoplasia (New York, N.Y.)

    Article Title: Metabolic regulation of histone acetylation by ACLY supports MDR1 expression in colorectal cancer and highlights a targetable vulnerability

    doi: 10.1016/j.neo.2026.101314

    Figure Lengend Snippet: ACLY activity modulates histone acetylation and MDR1 expression. (A) Immunoblot analysis of MDR1 in SW480 and DLD1 cells treated with the histone deacetylase inhibitor vorinostat (VOR; 0.5 μM for SW480 and 3.5 μM for DLD1) or DMSO for 24 h. Representative blots and densitometric quantification relative to control are shown. (B) Immunoblot analysis of acetylated histone H3 (H3K9ac) and histone H4 (H4K16ac) in SW480 wild-type (WT) and ACLY-overexpressing (OE) cells treated with vehicle or the ACLY inhibitor BMS-303141 (50 μM, 48 h). (C) Immunoblot analysis of H3K9ac and H4K16ac in DLD1 cells under the same conditions. β-actin was used as a loading control. Data are presented as mean ± SD (n = 3). Statistical significance was determined using unpaired two-tailed t-tests. *P < 0.05; **P < 0.01; ***P < 0.001.

    Article Snippet: Human colorectal cancer cell lines SW480 (KRASG12V) and DLD1 (KRASG13D) were obtained from the American Type Culture Collection (ATCC) and authenticated by short tandem repeat profiling.

    Techniques: Activity Assay, Expressing, Western Blot, Histone Deacetylase Assay, Control, Two Tailed Test

    ACLY expression is associated with resistance-related transcriptional programs in colorectal cancer. (A) Correlation analysis between ACLY expression and a gene set associated with lipid metabolism (ACLY, ACSS2, ACSS1, FASN, SREBP1) and drug transport pathways (ABCB1, ABCC2, ABCG5, EpCAM, CD24) in colorectal cancer samples using GEPIA2 (TCGA dataset). (B) Schematic representation of a proposed model linking ACLY-dependent acetyl-CoA production to histone acetylation and transcriptional regulation in CRC cells. (C) Relative mRNA expression of EpCAM, ABCC2, and CD24 in SW480 and DLD1 cells overexpressing ACLY compared with empty vector controls. (D) Relative mRNA expression of EpCAM, ABCC2, and CD24 in SW480 and DLD1 cells treated with the ACLY inhibitor BMS-303141 (50 μM) compared with vehicle-treated controls. Gene expression levels were determined by qPCR and normalized to ACTB. Data are presented as mean ± SEM (n = 3). Statistical significance was determined using unpaired two-tailed t-tests. *P < 0.05; **P < 0.01; ***P < 0.001.

    Journal: Neoplasia (New York, N.Y.)

    Article Title: Metabolic regulation of histone acetylation by ACLY supports MDR1 expression in colorectal cancer and highlights a targetable vulnerability

    doi: 10.1016/j.neo.2026.101314

    Figure Lengend Snippet: ACLY expression is associated with resistance-related transcriptional programs in colorectal cancer. (A) Correlation analysis between ACLY expression and a gene set associated with lipid metabolism (ACLY, ACSS2, ACSS1, FASN, SREBP1) and drug transport pathways (ABCB1, ABCC2, ABCG5, EpCAM, CD24) in colorectal cancer samples using GEPIA2 (TCGA dataset). (B) Schematic representation of a proposed model linking ACLY-dependent acetyl-CoA production to histone acetylation and transcriptional regulation in CRC cells. (C) Relative mRNA expression of EpCAM, ABCC2, and CD24 in SW480 and DLD1 cells overexpressing ACLY compared with empty vector controls. (D) Relative mRNA expression of EpCAM, ABCC2, and CD24 in SW480 and DLD1 cells treated with the ACLY inhibitor BMS-303141 (50 μM) compared with vehicle-treated controls. Gene expression levels were determined by qPCR and normalized to ACTB. Data are presented as mean ± SEM (n = 3). Statistical significance was determined using unpaired two-tailed t-tests. *P < 0.05; **P < 0.01; ***P < 0.001.

    Article Snippet: Human colorectal cancer cell lines SW480 (KRASG12V) and DLD1 (KRASG13D) were obtained from the American Type Culture Collection (ATCC) and authenticated by short tandem repeat profiling.

    Techniques: Expressing, Drug Transport Assay, Plasmid Preparation, Gene Expression, Two Tailed Test

    Vitamin C induces coordinated changes in metabolic and chromatin-associated pathways in colorectal cancer cells. (A) Gene Ontology (GO) enrichment analysis of proteins differentially expressed following vitamin C treatment (5 mM, 4 h). (B) Volcano plot showing significantly upregulated and downregulated proteins (log₂ fold change > 1, p < 0.05). (C) KEGG pathway enrichment analysis highlighting pathways related to chromatin organization, DNA replication, nucleotide metabolism, and cell cycle regulation. (D) GO Cellular Component analysis showing enrichment of chromatin-associated complexes, including transcription regulator complexes, histone acetyltransferase-containing complexes, and Polycomb group (PcG) assemblies. (E) Heatmap representation of differentially expressed chromatin-associated proteins in control and vitamin C-treated cells. Proteomic analysis was performed in SW480 and DLD1 cells using label-free LC–MS/MS (diaPASEF). Data represent combined analysis of both cell lines.

    Journal: Neoplasia (New York, N.Y.)

    Article Title: Metabolic regulation of histone acetylation by ACLY supports MDR1 expression in colorectal cancer and highlights a targetable vulnerability

    doi: 10.1016/j.neo.2026.101314

    Figure Lengend Snippet: Vitamin C induces coordinated changes in metabolic and chromatin-associated pathways in colorectal cancer cells. (A) Gene Ontology (GO) enrichment analysis of proteins differentially expressed following vitamin C treatment (5 mM, 4 h). (B) Volcano plot showing significantly upregulated and downregulated proteins (log₂ fold change > 1, p < 0.05). (C) KEGG pathway enrichment analysis highlighting pathways related to chromatin organization, DNA replication, nucleotide metabolism, and cell cycle regulation. (D) GO Cellular Component analysis showing enrichment of chromatin-associated complexes, including transcription regulator complexes, histone acetyltransferase-containing complexes, and Polycomb group (PcG) assemblies. (E) Heatmap representation of differentially expressed chromatin-associated proteins in control and vitamin C-treated cells. Proteomic analysis was performed in SW480 and DLD1 cells using label-free LC–MS/MS (diaPASEF). Data represent combined analysis of both cell lines.

    Article Snippet: Human colorectal cancer cell lines SW480 (KRASG12V) and DLD1 (KRASG13D) were obtained from the American Type Culture Collection (ATCC) and authenticated by short tandem repeat profiling.

    Techniques: Control, Liquid Chromatography with Mass Spectroscopy, Data-independent acquisition

    Metabolic and epigenetic consequences of vitamin C treatment in colorectal cancer cells. (A) Quantification of ¹³C-glucose-derived citrate in SW480 and DLD1 cells treated with vitamin C (5 mM) for 4 h (n = 3). (B) Immunoblot analysis of total ACLY and phosphorylated ACLY at Ser455 following vitamin C treatment (5 mM) (n = 3). (C) Immunoblot analysis and quantification of acetylated histone H4 (AcH4K16) and histone H3 (AcH3K9) in SW480 and DLD1 cells after vitamin C exposure (n = 3). (D) MDR1 (ABCB1) protein levels in SW480 and DLD1 cells treated with vitamin C (5 mM), quantified relative to vehicle control (n = 3). (E) Relative ACLY and ABCB1 mRNA expression determined by qPCR after 6 h of vitamin C treatment (5 mM) in SW480 and DLD1 cells (n = 3). Data are presented as mean ± SEM. Statistical significance was determined using unpaired two-tailed t-tests. *P < 0.05; **P < 0.01; ***P < 0.001.

    Journal: Neoplasia (New York, N.Y.)

    Article Title: Metabolic regulation of histone acetylation by ACLY supports MDR1 expression in colorectal cancer and highlights a targetable vulnerability

    doi: 10.1016/j.neo.2026.101314

    Figure Lengend Snippet: Metabolic and epigenetic consequences of vitamin C treatment in colorectal cancer cells. (A) Quantification of ¹³C-glucose-derived citrate in SW480 and DLD1 cells treated with vitamin C (5 mM) for 4 h (n = 3). (B) Immunoblot analysis of total ACLY and phosphorylated ACLY at Ser455 following vitamin C treatment (5 mM) (n = 3). (C) Immunoblot analysis and quantification of acetylated histone H4 (AcH4K16) and histone H3 (AcH3K9) in SW480 and DLD1 cells after vitamin C exposure (n = 3). (D) MDR1 (ABCB1) protein levels in SW480 and DLD1 cells treated with vitamin C (5 mM), quantified relative to vehicle control (n = 3). (E) Relative ACLY and ABCB1 mRNA expression determined by qPCR after 6 h of vitamin C treatment (5 mM) in SW480 and DLD1 cells (n = 3). Data are presented as mean ± SEM. Statistical significance was determined using unpaired two-tailed t-tests. *P < 0.05; **P < 0.01; ***P < 0.001.

    Article Snippet: Human colorectal cancer cell lines SW480 (KRASG12V) and DLD1 (KRASG13D) were obtained from the American Type Culture Collection (ATCC) and authenticated by short tandem repeat profiling.

    Techniques: Derivative Assay, Western Blot, Control, Expressing, Two Tailed Test

    Identification and functional characterization of senescence- and circadian rhythm-related genes in colorectal cancer (CRC). (A) Volcano plot showing differentially expressed genes (DEGs) between CRC tumor tissues and adjacent non-tumor tissues in the training cohort. Upregulated genes are shown in yellow, downregulated genes in green, and non-significant genes in gray. (B) Heatmap illustrating the expression patterns of representative DEGs between CRC and normal samples. (C) Venn diagram depicting the intersection of DEGs, senescence-related genes, and circadian rhythm-related genes. ACR, Aging-Circadian Rhythm intersection (D) Gene Ontology (GO) enrichment analysis, including biological processes (BP), cellular components (CC), and molecular functions (MF), together with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the 10 candidate genes. (E) Protein-protein interaction (PPI) network of the 10 candidate genes.

    Journal: Frontiers in Immunology

    Article Title: Senescence-circadian interplay stratifies patient prognosis and reveals immune remodeling heterogeneity in colorectal cancer

    doi: 10.3389/fimmu.2026.1804974

    Figure Lengend Snippet: Identification and functional characterization of senescence- and circadian rhythm-related genes in colorectal cancer (CRC). (A) Volcano plot showing differentially expressed genes (DEGs) between CRC tumor tissues and adjacent non-tumor tissues in the training cohort. Upregulated genes are shown in yellow, downregulated genes in green, and non-significant genes in gray. (B) Heatmap illustrating the expression patterns of representative DEGs between CRC and normal samples. (C) Venn diagram depicting the intersection of DEGs, senescence-related genes, and circadian rhythm-related genes. ACR, Aging-Circadian Rhythm intersection (D) Gene Ontology (GO) enrichment analysis, including biological processes (BP), cellular components (CC), and molecular functions (MF), together with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the 10 candidate genes. (E) Protein-protein interaction (PPI) network of the 10 candidate genes.

    Article Snippet: Human colorectal cancer cell lines (DLD1, SW620, SW480, HCT15, HCT116, HT29, and RKO) and the normal human intestinal epithelial cell line NCM460 were obtained from the American Type Culture Collection (ATCC; Manassas, VA, USA) and the Shanghai Cell Bank of the Chinese Academy of Sciences (Shanghai, China).

    Techniques: Functional Assay, Expressing

    Development, validation, and experimental verification of a senescence- and circadian rhythm-related prognostic risk model in CRC. (A) Forest plot of univariate Cox proportional hazards regression analysis showing the associations between NOX4, CXCL1, CDKN2A, and SIX1 expression and overall survival in the training cohort. (B) Kaplan-Meier survival curves comparing overall survival between the high-SCore group (HSG) and low-SCore group (LSG) in the training cohort. (C) Time-dependent receiver operating characteristic (ROC) curves evaluating the predictive performance of the risk model in the training cohort, with area under the curve (AUC) values shown for 1-, 2-, and 3-year overall survival. (D) Kaplan-Meier survival curves comparing overall survival between the HSG and LSG in the external validation cohort GSE12945 . (E) Time-dependent ROC curves assessing the predictive accuracy of the prognostic model in GSE12945 , with AUC values shown for 1-, 2-, and 3-year overall survival. (F, G) Relative mRNA expression levels of the four prognostic genes in the normal colon epithelial cell line NCM460 and CRC cell lines DLD1, SW480, HCT15, HT29, and RKO, as measured by reverse transcription-quantitative PCR (RT-qPCR): NOX4 (F) , CXCL1 (G) . (H, I) Quantitative immunohistochemical validation of NOX4 and CXCL1 expression in the SYSUCC-CRC tissue microarray. IHC scores were significantly higher in colorectal cancer tissues than in paired adjacent non-tumor tissues (n = 120). (J) Spearman correlation heatmap among prognostic genes. The heatmap displays pairwise expression correlations among the four prognostic genes (CXCL1, CDKN2A, NOX4, SIX1). Color gradient represents the magnitude of Spearman correlation coefficients, with red indicating positive correlation and blue indicating negative correlation. Numerical values within cells indicate correlation coefficients. Significance annotation: *P < 0.05, **P < 0.01, ***P < 0.001. All P values were adjusted by the Benjamini−Hochberg (BH) method for multiple testing. (K) Spearman correlation heatmap between prognostic gene expression and pathway activity. The heatmap displays correlations between the expression levels of the four prognostic genes and the GSVA activity scores of the oxidative stress and SASP inflammatory response pathways. Color gradient represents the magnitude of Spearman correlation coefficients, with red indicating positive correlation and blue indicating negative correlation. Numerical values within cells indicate correlation coefficients. Significance annotation: *P < 0.05, **P < 0.01, ***P < 0.001. All P values were adjusted by the BH method for multiple testing.

    Journal: Frontiers in Immunology

    Article Title: Senescence-circadian interplay stratifies patient prognosis and reveals immune remodeling heterogeneity in colorectal cancer

    doi: 10.3389/fimmu.2026.1804974

    Figure Lengend Snippet: Development, validation, and experimental verification of a senescence- and circadian rhythm-related prognostic risk model in CRC. (A) Forest plot of univariate Cox proportional hazards regression analysis showing the associations between NOX4, CXCL1, CDKN2A, and SIX1 expression and overall survival in the training cohort. (B) Kaplan-Meier survival curves comparing overall survival between the high-SCore group (HSG) and low-SCore group (LSG) in the training cohort. (C) Time-dependent receiver operating characteristic (ROC) curves evaluating the predictive performance of the risk model in the training cohort, with area under the curve (AUC) values shown for 1-, 2-, and 3-year overall survival. (D) Kaplan-Meier survival curves comparing overall survival between the HSG and LSG in the external validation cohort GSE12945 . (E) Time-dependent ROC curves assessing the predictive accuracy of the prognostic model in GSE12945 , with AUC values shown for 1-, 2-, and 3-year overall survival. (F, G) Relative mRNA expression levels of the four prognostic genes in the normal colon epithelial cell line NCM460 and CRC cell lines DLD1, SW480, HCT15, HT29, and RKO, as measured by reverse transcription-quantitative PCR (RT-qPCR): NOX4 (F) , CXCL1 (G) . (H, I) Quantitative immunohistochemical validation of NOX4 and CXCL1 expression in the SYSUCC-CRC tissue microarray. IHC scores were significantly higher in colorectal cancer tissues than in paired adjacent non-tumor tissues (n = 120). (J) Spearman correlation heatmap among prognostic genes. The heatmap displays pairwise expression correlations among the four prognostic genes (CXCL1, CDKN2A, NOX4, SIX1). Color gradient represents the magnitude of Spearman correlation coefficients, with red indicating positive correlation and blue indicating negative correlation. Numerical values within cells indicate correlation coefficients. Significance annotation: *P < 0.05, **P < 0.01, ***P < 0.001. All P values were adjusted by the Benjamini−Hochberg (BH) method for multiple testing. (K) Spearman correlation heatmap between prognostic gene expression and pathway activity. The heatmap displays correlations between the expression levels of the four prognostic genes and the GSVA activity scores of the oxidative stress and SASP inflammatory response pathways. Color gradient represents the magnitude of Spearman correlation coefficients, with red indicating positive correlation and blue indicating negative correlation. Numerical values within cells indicate correlation coefficients. Significance annotation: *P < 0.05, **P < 0.01, ***P < 0.001. All P values were adjusted by the BH method for multiple testing.

    Article Snippet: Human colorectal cancer cell lines (DLD1, SW620, SW480, HCT15, HCT116, HT29, and RKO) and the normal human intestinal epithelial cell line NCM460 were obtained from the American Type Culture Collection (ATCC; Manassas, VA, USA) and the Shanghai Cell Bank of the Chinese Academy of Sciences (Shanghai, China).

    Techniques: Biomarker Discovery, Expressing, Reverse Transcription, Real-time Polymerase Chain Reaction, Quantitative RT-PCR, Immunohistochemical staining, Microarray, Gene Expression, Activity Assay

    Cell-cell communication, pseudotime dynamics, and functional characteristics of T cells in CRC. (A, B) Global cell-cell communication networks inferred from ligand-receptor interactions in normal colorectal tissues (A) and CRC tumor tissues (B) . Node size indicates the number of interactions, and edge thickness reflects interaction strength. (C, D) T cell-centered communication networks in normal tissues (C) and CRC tumor tissues (D) . (E,3F) Bubble plots showing ligand-receptor interactions between T cells and other cell types in normal tissues (E) and CRC tumor tissues (F) . (G) Pseudotime trajectory analysis of T cells, depicting differentiation into 11 cellular states along pseudotime. (H) Heatmap showing dynamic expression patterns of prognostic genes (SIX1, NOX4, CDKN2A, and CXCL1) along the T-cell pseudotime trajectory. (I) Dot plot illustrating activity levels of multiple metabolic pathways across different cell types. (J) Integrated pathway enrichment analysis (irGSEA) across multiple algorithms for different cell types.

    Journal: Frontiers in Immunology

    Article Title: Senescence-circadian interplay stratifies patient prognosis and reveals immune remodeling heterogeneity in colorectal cancer

    doi: 10.3389/fimmu.2026.1804974

    Figure Lengend Snippet: Cell-cell communication, pseudotime dynamics, and functional characteristics of T cells in CRC. (A, B) Global cell-cell communication networks inferred from ligand-receptor interactions in normal colorectal tissues (A) and CRC tumor tissues (B) . Node size indicates the number of interactions, and edge thickness reflects interaction strength. (C, D) T cell-centered communication networks in normal tissues (C) and CRC tumor tissues (D) . (E,3F) Bubble plots showing ligand-receptor interactions between T cells and other cell types in normal tissues (E) and CRC tumor tissues (F) . (G) Pseudotime trajectory analysis of T cells, depicting differentiation into 11 cellular states along pseudotime. (H) Heatmap showing dynamic expression patterns of prognostic genes (SIX1, NOX4, CDKN2A, and CXCL1) along the T-cell pseudotime trajectory. (I) Dot plot illustrating activity levels of multiple metabolic pathways across different cell types. (J) Integrated pathway enrichment analysis (irGSEA) across multiple algorithms for different cell types.

    Article Snippet: Human colorectal cancer cell lines (DLD1, SW620, SW480, HCT15, HCT116, HT29, and RKO) and the normal human intestinal epithelial cell line NCM460 were obtained from the American Type Culture Collection (ATCC; Manassas, VA, USA) and the Shanghai Cell Bank of the Chinese Academy of Sciences (Shanghai, China).

    Techniques: Functional Assay, Expressing, Activity Assay