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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:
Techniques: Activity Assay, Expressing, Western Blot, Transduction, Plasmid Preparation, Control, Two Tailed Test
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:
Techniques: Activity Assay, Expressing, Western Blot, Histone Deacetylase Assay, Control, Two Tailed Test
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:
Techniques: Expressing, Drug Transport Assay, Plasmid Preparation, Gene Expression, Two Tailed Test
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:
Techniques: Control, Liquid Chromatography with Mass Spectroscopy, Data-independent acquisition
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:
Techniques: Derivative Assay, Western Blot, Control, Expressing, Two Tailed Test
Journal: Journal of Cell Communication and Signaling
Article Title: Inflammatory cytokine IL‐6 regulates ADAMTS14 expression through MAPK and PI3K signaling in colorectal cancer
doi: 10.1002/ccs3.70092
Figure Lengend Snippet: Determination of the effect of IL‐6 application on ADAMTS14 expression. (A) Basal mRNA expression levels of the ADAMTS14 gene in different cancer cell lines were analyzed by qRT‐PCR. (B) SW480 cells were treated with 20 ng/mL IL‐6, and ADAMTS14 mRNA expression levels were determined by qRT‐PCR after the specified time periods (1, 6, 24, and 48 h). (C) ADAMTS14 protein levels after IL‐6 application were analyzed by Western blot, and β‐actin was used as a loading control. Protein band densities were analyzed densitometrically, and the fold change is shown in the graph. Western blot analysis was performed from a single experimental replicate; therefore, no error bars or SD values are presented. (D) ADAMTS14 protein expression was examined by immunofluorescence staining. Nuclei were stained with DAPI. Scale bar: 10 μm. All experiments were performed in triplicate, and data are presented as mean ± SD. Western blot analysis was performed from a single experimental replicate. Statistical analysis was performed using ANOVA, with * p < 0.05, ** p < 0.01, and *** p < 0.001 values. ANOVA, Analysis of Variance; DAPI, 4′,6‐Diamidino‐2‐Phenylindole; IL‐6, Interleukin‐6; qRT‐PCR, quantitative real‐time Polymerase Chain Reaction; SD, standard deviation.
Article Snippet: The human
Techniques: Expressing, Quantitative RT-PCR, Western Blot, Control, Immunofluorescence, Staining, Real-time Polymerase Chain Reaction, Standard Deviation
Journal: Journal of Cell Communication and Signaling
Article Title: Inflammatory cytokine IL‐6 regulates ADAMTS14 expression through MAPK and PI3K signaling in colorectal cancer
doi: 10.1002/ccs3.70092
Figure Lengend Snippet: Sequence analysis of the ADAMTS14 promoter region, promoter deletion constructions, and the effect of IL‐6 on promoter activity. (A) Multiple sequence alignment analysis of human, mouse, and rat ADAMTS14 promoter regions. Conserved nucleotide regions are shown in shaded form. (B) Base composition and CpG island analyses of the ADAMTS14 promoter region are shown. (C) Schematic representation of 5′ deletion constructions (−381/+297, −145/+297, and −43/+297) generated from the ADAMTS14 promoter region and cloning of these regions into the pMetLuc report vector. (D) Determination of the effect of IL‐6 (20 ng/mL) administration on ADAMTS14 promoter activity in SW480 cells by luciferase report analysis. Luciferase activity was normalized by SEAP. Data are presented as mean ± SD. * p < 0.05, ** p < 0.01, *** p < 0.001. (E) Schematic representation of predicted transcription factor binding motifs within the ADAMTS14 promoter region. The experimentally identified IL‐6‐responsive region (−145/−43 bp) is highlighted in gray. In silico promoter analysis identified multiple putative NF‐κB, AP‐1, SMAD2‐associated binding motifs clustered within this region, suggesting a transcriptionally active regulatory hotspot potentially involved in IL‐6‐responsive ADAMTS14 regulation. IL‐6, Interleukin‐6; NF‐κB, Nuclear Factor Kappa B; SEAP, Secreted Alkaline Phosphatase.
Article Snippet: The human
Techniques: Sequencing, Activity Assay, Generated, Cloning, Plasmid Preparation, Luciferase, Binding Assay, In Silico
Journal: Journal of Cell Communication and Signaling
Article Title: Inflammatory cytokine IL‐6 regulates ADAMTS14 expression through MAPK and PI3K signaling in colorectal cancer
doi: 10.1002/ccs3.70092
Figure Lengend Snippet: Identification of signaling pathways involved in IL‐6‐mediated ADAMTS14 regulation. (A) SW480 cells were treated with 20 ng/mL IL‐6 alone or in combination with different signaling pathway inhibitors (PD98059: ERK inhibitor, PD169316 : p38 MAPK, SP600125: JNK inhibitor, Wortmannin: PI3K inhibitor). ADAMTS14 mRNA expression levels were analyzed by Quantitative real‐time PCR after treatment. (B) Under the same conditions, ADAMTS14 protein levels were analyzed by Western blot, and β‐actin was used as a loading control. Protein band densities were analyzed densitometrical, and fold change is shown in the graph. (C) Luciferase report gene analysis was performed using the ADAMTS14 promoter construction containing the −43/+297 promoter region, and the effect of inhibitor administration in combination with IL‐6 on promoter activity was determined. Luciferase activity was calculated as the Luc/SEAP ratio. All experiments were performed in triplicate, and data are presented as mean ± standard deviation. Western blot analysis was performed from a single experimental replicate. Statistical analysis was performed using ANOVA, with * p < 0.05, ** p < 0.01, and *** p < 0.001. ANOVA, Analysis of Variance; ERK, Extracellular Signal‐Regulated Kinase; IL‐6, Interleukin‐6; MAPK, Mitogen‐Activated Protein Kinase; PI3K, Phosphatidylinositol 3‐Kinase; SEAP, Secreted Alkaline Phosphatase.
Article Snippet: The human
Techniques: Protein-Protein interactions, Expressing, Real-time Polymerase Chain Reaction, Western Blot, Control, Luciferase, Activity Assay, Standard Deviation
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:
Techniques: Functional Assay, Expressing
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:
Techniques: Biomarker Discovery, Expressing, Reverse Transcription, Real-time Polymerase Chain Reaction, Quantitative RT-PCR, Immunohistochemical staining, Microarray, Gene Expression, Activity Assay
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:
Techniques: Functional Assay, Expressing, Activity Assay
Journal: Redox Biology
Article Title: Targeting HIF-1α promotes ferroptosis and boosts antitumor immunity in MSS colorectal cancer
doi: 10.1016/j.redox.2026.104151
Figure Lengend Snippet: A hypoxia-characteristic cluster identified by Microwell-seq exhibited pronounced ferroptosis resistance in MSS CRC cells. (A and B) t-distributed stochastic neighbor embedding (t-SNE) plot of Microwell-seq analysis based on gene expressions of SW480 and WiDr. (C and D) Comparative gene set enrichment analysis (GSEA) of signaling pathways in different clusters. The red color represents up-regulation and blue represents down-regulation, calculated with the formula: ± Log2|NES/p.adjust|. Grey color represents no enrichment in the indicated pathway. NES: normalized enrichment score. (E and F) GSEA analysis showed the indicated pathway activity between the hypoxia cluster and other clusters. (G and H) Correlation analysis of hypoxia scores, glycolysis scores, and ferroptosis suppressor scores in WiDr and SW480 cells was performed using Pearson's method. (I and J) The ferroptosis suppressor score of SW480 and WiDr with DMSO or RSL3 treatment was analyzed by AddModuleScore tool. P values were calculated by Wilcox.test. (K and L) The ferroptosis suppressor score of hypoxia cluster in SW480 and WiDr treated with DMSO or RSL3 was shown. P values were calculated by Wilcox.test.
Article Snippet: The
Techniques: Protein-Protein interactions, Activity Assay
Journal: Redox Biology
Article Title: Targeting HIF-1α promotes ferroptosis and boosts antitumor immunity in MSS colorectal cancer
doi: 10.1016/j.redox.2026.104151
Figure Lengend Snippet: HIF-1α nuclear distribution increased in RSL3-resistant CT26 cells and significantly promoted tumourigenicity and metastasis. (A) The diagram demonstrated the procedure for sphere formation. (B and C) The representative images of sphere formation in MSS CRC cells and quantification analysis of sphere number derived from SW480, HT-29, and WiDr. (D) HIF-1α expression in WiDr was detected by western blotting. (E) qPCR analyzed the indicated gene expression involved in glycolysis in WiDr spheres. (F) Cell viability of parental CT26 and RSL3-resistant CT26 (Re-CT26). (G) Cytoplasm and nuclear HIF-1α expression in CT26. α-tubulin was used as an internal reference for the cytoplasm, and Histone 3 was used as a nuclear reference. (H) qPCR analyzed the indicated gene expression involved in glycolysis in CT26. (I) Image of subcutaneous tumors derived from parental CT26 and Re-CT26. (J) Tumor volume determined by formula: 0.52 × Long × width 2 . (K)Tumor weight of subcutaneous tumors. (L) Bioluminescent images in liver metastatic models. (M) Images of liver metastasis derived from parental CT26 and Re-CT26. (N) Number of liver nodules in liver metastasis models. (O) Representative hematoxylin and eosin (H&E) and immunohistochemical staining images from liver metastasis models. Scale bar: 25 μm. (P) Quantification of immunohistochemical staining results shown in (O). Data are shown as means ± SD. ∗ P < 0.05; ∗∗ P < 0.01; ∗∗∗ P < 0.001; ns: not significant. Two-way ANOVA in (J), others unpaired two-tailed Student's t -test.
Article Snippet: The
Techniques: Derivative Assay, Expressing, Western Blot, Gene Expression, Immunohistochemical staining, Staining, Two Tailed Test
Journal: Redox Biology
Article Title: Targeting HIF-1α promotes ferroptosis and boosts antitumor immunity in MSS colorectal cancer
doi: 10.1016/j.redox.2026.104151
Figure Lengend Snippet: P4HA1 was a major factor regulated by HIF-1α and was enriched in ferroptosis-resistant cells. (A) Venn diagram screening 10 genes commonly induced by hypoxia and the glycolysis pathway in SW480 and WiDr by single-cell sequencing. (B) Gene expression heatmap showed the distribution of genes in different clusters in the presence or absence of RSL3. D: DMSO, R: RSL3. (C) Correlation between ferroptosis suppressor score and P4HA1 in MSS CRC containing 119 patients using Pearson's method. (D) Kaplan-Meier plots of RFS in MSS colon cancer patients according to P4HA1 expression. (E) The correlation between HIF-1α and P4HA1 was evaluated by Spearman's analysis in a colon adenocarcinoma cohort of 457 patients. (F) Relative P4HA1 mRNA expression after HIF-1α knockdown, detected by qPCR. (G) Relative P4HA1 protein expression after HIF-1α knockdown, detected by Western blot. (H) Relative P4HA1 mRNA expression after HIF-1α overexpression, detected by qPCR. (I) Relative P4HA1 protein expression after HIF-1α overexpression, detected by Western blot. (J) Relative P4HA1 expression, detected by qPCR. (K) HIF-1α binding motif predicted from JASPAR. (L) The prospective binding site of HIF-1α on the promoter of P4HA1. (M) ChIP assay of HIF-1α and IgG in parental CT26 cells or Re-CT26 cells, followed by qPCR for the binding sequences.
Article Snippet: The
Techniques: Single Cell, Sequencing, Gene Expression, Expressing, Knockdown, Western Blot, Over Expression, Binding Assay
Journal: Redox Biology
Article Title: Targeting HIF-1α promotes ferroptosis and boosts antitumor immunity in MSS colorectal cancer
doi: 10.1016/j.redox.2026.104151
Figure Lengend Snippet: HIF-1α inhibition enhanced ferroptosis inducer sensitivity in MSS CRC cells. (A and B) Cell viability of HT-29 or SW480 treated with RSL3, BAY 87-2243 alone or in combination treatment. (C and D) DCFH-DA oxidation in HT-29 or SW480 treated with RSL3, BAY 87-2243 alone or in combination treatment were quantified using flow cytometry with DCFH-DA probe. (E and F) Lipid peroxidation levels of HT-29 or SW480 treated with RSL3, BAY 87-2243 alone or in combination treatment were detected using flow cytometry with C11-BODIPY 581/591 (FITC channel; excitation/emission: 488/510 nm). (G) MDA levels in cells subjected to the indicated treatment. (H) GSH levels in cells subjected to the indicated treatment. Results are shown as means ± SD. ∗ P < 0.05 ; ∗∗ P < 0.01 ; ∗∗∗ P < 0.001 ; ∗∗∗∗ P < 0.0001 . P values were calculated by one-way ANOVA.
Article Snippet: The
Techniques: Inhibition, Flow Cytometry