Journal: Cell Death and Differentiation

Article Title: ABCC10-mediated cGAMP efflux drives cancer cell radiotherapy resistance

doi: 10.1038/s41418-025-01552-1

Figure Lengend Snippet: a Schematic of a metabolic in vitro CRISPR screen for identifying regulators of RT. b Scatter plot showing the top 10 negative regulatory genes in two rounds of the CRISPR-Cas9 screen using MAGeCK analysis. c Indication of the combined analysis of the two rounds of the functional screen. d Gene ontology (GO) analysis of molecular function (MF) for the intersection of 99 negative regulatory genes. e Survival analysis for BRCA patients was conducted separately within the high and low expression groups, comparing patients treated with RT and those who did not receive RT. f Immunoblot analysis of the protein expression levels of ABCC10 in parallel Patu8988T cells and radioresistant Patu8988T cells.

Article Snippet: Wild-type (WT) and mutant human ABCC10 constructs were generated using a human ABCC10 cDNA clone (Sino Biological HG19038-UT) as a template.

Techniques: In Vitro, CRISPR, Functional Assay, Expressing, Western Blot

Journal: Cell Death and Differentiation

Article Title: ABCC10-mediated cGAMP efflux drives cancer cell radiotherapy resistance

doi: 10.1038/s41418-025-01552-1

Figure Lengend Snippet: a Immunoblot analysis of the protein expression levels of ABCC10 in Patu8988T and Calu-1 cells treated with radiotherapy (RT) (8 Gy) at the indicated time points. b Cell viability in Patu8988T and Calu-1 ABCC10-knockout cells treated with RT (8 Gy). Representative images ( c ) and quantification ( d ) of clonogenic survival analysis of Patu8988T and Calu-1 ABCC10-knockout cells treated with the indicated dose of ionizing radiation. e Cell viability in WT cells, ABCC10-knockout cells and ABCC10-knockout cells with re-expression of ABCC10 treated with RT (8 Gy). Representative images ( f ) and quantification ( g ) of clonogenic survival analysis of WT cells, ABCC10-knockout cells and ABCC10-knockout cells with re-expression of ABCC10 treated with the indicated dose of ionizing radiation. h Cell viability in Patu8988T and Calu-1 ABCC10-overexpressing cells treated with RT (8 Gy). Representative images ( i ) and quantification ( j ) of clonogenic survival analysis of Patu8988T and Calu-1 ABCC10-overexpressing cells treated with the indicated dose of ionizing radiation. k–n NXG mice were transplanted subcutaneously with doxycycline (DOX)-inducible ABCC10-knockdown Patu8988T cells and treated as indicated. A diagram of tumor growth delay experiments performed in vivo and the ionizing radiation fractionated treatment protocol is shown in ( k ); tumor volumes were calculated ( l ); tumor images were acquired as shown in ( m ); tumor weights ( n ) were measured. Experiments were repeated three times, and data are expressed as mean ± SEM (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001).

Article Snippet: Wild-type (WT) and mutant human ABCC10 constructs were generated using a human ABCC10 cDNA clone (Sino Biological HG19038-UT) as a template.

Techniques: Western Blot, Expressing, Knock-Out, Knockdown, In Vivo

Journal: Cell Death and Differentiation

Article Title: ABCC10-mediated cGAMP efflux drives cancer cell radiotherapy resistance

doi: 10.1038/s41418-025-01552-1

Figure Lengend Snippet: a Immunoblot analysis of the protein expression levels of γ-H2A.X in Patu8988T and Calu-1 ABCC10-knockout cells at the indicated times after RT (8 Gy). b Immunoblot analysis of the protein expression levels of γ-H2A.X in Patu8988T and Calu-1 ABCC10-overexpressing cells at the indicated times after RT. c Protein levels of γ-H2A.X in tumor tissues were detected. d Quantification of γ-H2A.X protein levels in in tumor tissues. e Immunoblot analysis of the protein expression levels of ABCC10 and γ-H2A.X in WT cells, ABCC10-knockout cells and ABCC10-knockout cells with re-expression of ABCC10 treated with RT (8 Gy) after 6 h. f Quantification of flow cytometry-based analysis of ROS levels in Patu8988T WT and ABCC10 KO cells at 24 h after RT. g Quantification of flow cytometry-based analysis of ROS levels in Patu8988T vector and ABCC10-overexpressing cells at 24 h after RT. h Quantification of flow cytometry-based analysis of ROS levels in WT and ABCC10 KO1 Patu8988T cells pretreated with or without NAC (1 mM) at 24 h after RT. i Immunoblot analysis of the protein expression levels of γ-H2A.X in WT and ABCC10 KO1 Patu8988T cells pretreated with or without NAC (1 mM) at 6 h after RT. j Cell viability of Patu8988T WT and ABCC10-knockout cells pretreated with or without NAC (1 mM) at 72 h after RT. Experiments were repeated three times, and the data are expressed as mean ± SEM (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001).

Article Snippet: Wild-type (WT) and mutant human ABCC10 constructs were generated using a human ABCC10 cDNA clone (Sino Biological HG19038-UT) as a template.

Techniques: Western Blot, Expressing, Knock-Out, Flow Cytometry, Plasmid Preparation

Journal: Cell Death and Differentiation

Article Title: ABCC10-mediated cGAMP efflux drives cancer cell radiotherapy resistance

doi: 10.1038/s41418-025-01552-1

Figure Lengend Snippet: a A volcanic map was used to analyze differentially expressed transcriptome genes of ABCC10 KO1 cells treated with or without radiotherapy (RT) for 6 h. b Heatmap of STING pathway-related genes in ABCC10 KO1 cells compared to WT cells. c Gene Ontology (GO) molecular function enrichment analysis of upregulated genes from ABCC10 KO1 Patu8988T cells compared to WT cells treated with RT. d Western blot analysis of ABCC10, pTBK1, TBK1, pIRF3, and IRF3 protein levels in ABCC10 WT and KO Patu8988T cells. e Western blot analysis of FLAG, pTBK1, TBK1, pIRF3, IRF3, pSTING, and STING protein levels in vector and ABCC10-overexpressing Patu8988T STING-overexpression (OE) cells. f Quantification of flow cytometry-based analysis of reactive oxygen species (ROS) levels in Patu8988T WT and ABCC10 KO cells pretreated with H151 24 h after RT. g Western blot analysis of γ-H2A.X protein levels in Patu8988T and BxPC3 WT and ABCC10 KO cells pretreated with H151 (1 μM) 6 h after RT. h Quantification of clonogenic survival analysis of Patu8988T WT and ABCC10 KO cells pretreated with H151 (1 μM) after RT. Experiments were repeated at least three times, and the data are expressed as mean ± SEM (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001).

Article Snippet: Wild-type (WT) and mutant human ABCC10 constructs were generated using a human ABCC10 cDNA clone (Sino Biological HG19038-UT) as a template.

Techniques: Western Blot, Plasmid Preparation, Over Expression, Flow Cytometry

Journal: Cell Death and Differentiation

Article Title: ABCC10-mediated cGAMP efflux drives cancer cell radiotherapy resistance

doi: 10.1038/s41418-025-01552-1

Figure Lengend Snippet: a DNA was detected using PicoGreen dye in WT and ABCC10 KO1 cells. The nucleus was stained with DAPI dye. Fluorescence intensity of PicoGreen was calculated using ImageJ from three different areas, measuring the signal from PicoGreen in non-nuclear regions. b Cytoplasmic DNA from vector and ABCC10-overexpressing Patu8988T cell lysates was separated on an agarose gel. c Vector and ABCC10-overexpressing Patu8988T cells were treated with radiation (8 Gy) and measured for cGAMP in cell lysates and supernatants using an ELISA kit 8 h later. d WT and ABCC10-knockout Patu8988T cells were treated with radiation (8 Gy) and then measured for cGAMP in cell lysates and supernatants using an ELISA kit 8 h later. e 20-min vesicle transport assays using 293 T cell-derived vesicles expressing human ABCC10 or control vesicles with cGAMP (5 μM) in the presence of ATP or AMP. f Western blot analysis of vector and ABCC10-overexpressing cells treated with 2′3′-cGAMP after the indicated time points. g Western blot analysis of FLAG, ABCC10, pTBK1, TBK1, pIRF3, IRF3, pSTING, and STING expression in vector and ABCC10-overexpressing Patu8988T STING-OE cells. h qPCR analysis of IFNB1 mRNA expression in vector and ABCC10-overexpressing Patu8988T cells transfected with ctDNA at the indicated time points. i Western blot analysis of ABCC10 WT and KO Patu8988T cells transfected with ctDNA at the indicated time points. j qPCR analysis of IFNB1 mRNA expression in WT and ABCC10 KO1 Patu8988T cells transfected with ctDNA at the indicated time points. Experiments were repeated three times, and the data are expressed as mean ± SEM (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001).

Article Snippet: Wild-type (WT) and mutant human ABCC10 constructs were generated using a human ABCC10 cDNA clone (Sino Biological HG19038-UT) as a template.

Techniques: Staining, Fluorescence, Plasmid Preparation, Agarose Gel Electrophoresis, Enzyme-linked Immunosorbent Assay, Knock-Out, Derivative Assay, Expressing, Control, Western Blot, Transfection

Journal: Cell Death and Differentiation

Article Title: ABCC10-mediated cGAMP efflux drives cancer cell radiotherapy resistance

doi: 10.1038/s41418-025-01552-1

Figure Lengend Snippet: a Docking scores × (-1) of ABCC10 substrates. b 2′3′-cGAMP docked with the ABCC10-binding pocket. c Patu8988T cells transfected with empty vector, wild-type (WT), R545A, or R899A mutant ABCC10-overexpression lentivirus were harvested after stimulation with ctDNA for 4 h. The 2′3′-cGAMP level in cell lysates and supernatants were measured using an ELISA kit. d 20-min vesicle transport assays using 293 T cell-derived vesicles expressing human WT ABCC10, R545A mutant, R899A mutant or control vesicles with cGAMP in the presence of ATP. e Western blot analysis of Patu8988T cells transduced with WT, R545A, R899A mutant ABCC10, or control (empty vector) stimulated with ctDNA for 4 h. f Cell viability of Patu8988T cells transfected with empty vector, WT, R545A, or R899A mutant ABCC10-overexpression lentivirus was assessed 72 h after RT. g Quantification of clonogenic survival analysis of vector, WT, R545A, or R899A mutant ABCC10-overexpressing Patu8988T cells treated with RT. Experiments were repeated three times, and the data are expressed as mean ± SEM (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001).

Article Snippet: Wild-type (WT) and mutant human ABCC10 constructs were generated using a human ABCC10 cDNA clone (Sino Biological HG19038-UT) as a template.

Techniques: Binding Assay, Transfection, Plasmid Preparation, Mutagenesis, Over Expression, Enzyme-linked Immunosorbent Assay, Derivative Assay, Expressing, Control, Western Blot, Transduction

Journal: Cell Death and Differentiation

Article Title: ABCC10-mediated cGAMP efflux drives cancer cell radiotherapy resistance

doi: 10.1038/s41418-025-01552-1

Figure Lengend Snippet: a Docking scores × (-1) of ABCC10 inhibitors. b Nilotinib docked with the ABCC10-binding pocket. c 20-min vesicle transport assays using 293 T cell-derived vesicles expressing human WT ABCC10 and R545A mutant with cGAMP and nilotinib in the presence of ATP. d ELISA was performed to detect intracellular and extracellular cGAMP content in Patu8988T cells treated with nilotinib stimulated with ctDNA for 4 h. e Cell viability was assessed using CCK-8 in Patu8988T and KPC mouse cells treated with nilotinib at 72 h after RT. f Western blot analysis of γ-H2A.X in Patu8988T and KPC mouse cells pretreated with nilotinib at 6 h after RT. g Western blot analysis of pTBK1, TBK1, pIRF3, and IRF3 protein levels in Patu8988T and KPC cells pretreated with nilotinib at 24 h after RT. h Schematic diagram of in vivo tumor growth and fractionated treatment protocol with radiation. Tumor growth curves ( i ) and tumor weights ( j ) for tumors generated from KPC mouse cells implanted subcutaneously in C57BL/6 mice with the indicated treatments. k Representative photographs of isolated tumor tissues following the indicated treatments. l Immunohistochemical analysis of pSTING, ISG15, and γ-H2A.X protein levels in harvested tumor tissues. Experiments were repeated three times, and the data are expressed as mean ± SEM (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001). Data were analyzed using Student’s t-test or two-way analysis of variance. m A schematic model showing the role of ABCC10 in radioresistance. ABCC10 blocks the activation of the STING pathway by causing cGAMP efflux after RT. Moreover, nilotinib can overcome radioresistance by inhibiting ABCC10 activity, thereby activating the STING pathway and inducing DNA damage.

Article Snippet: Wild-type (WT) and mutant human ABCC10 constructs were generated using a human ABCC10 cDNA clone (Sino Biological HG19038-UT) as a template.

Techniques: Binding Assay, Derivative Assay, Expressing, Mutagenesis, Enzyme-linked Immunosorbent Assay, CCK-8 Assay, Western Blot, In Vivo, Generated, Isolation, Immunohistochemical staining, Activation Assay, Activity Assay

Journal: Cancer Genomics & Proteomics

Article Title: Characterization of the Neoantigen Profile in a Tumor Mutation Burden-high Melanoma Patient With Multiple Metastases

doi: 10.21873/cgp.20517

Figure Lengend Snippet: A genomic analysis of mutational evolution in a metastatic melanoma case. The High-tech Omics-based Patient Evaluation (HOPE) project revealed that all metastatic sites, such as rib, intra-muscular, and brain lesions, had >1,500 SNVs, and 12 driver mutations (MPL, IDH1, CTNNB1, GATA2, PDGFRA, ARID1B, MET, ATM, ACVR1B, SMARCA4, GNAS, and AMER1) were common to all sites. New driver mutations were identified in intra-muscular (KMT2C: p.P3292S) and brain (JAK1: p.S404P) metastases. A functional analysis of these mutations was performed. The phylogenetic tree of mutation evolution in the metastatic melanoma case is shown on the right of the panel. PTR1: Primary tumor region 1.

Article Snippet: Briefly, JAK1 mutant ( p .S404P) gene cDNA was synthesized (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA), cloned into a vector, and transduced into three melanoma cells using the Neon TM Transfection System via electroporation (Invitrogen).

Techniques: Functional Assay, Mutagenesis

Journal: Cancer Genomics & Proteomics

Article Title: Characterization of the Neoantigen Profile in a Tumor Mutation Burden-high Melanoma Patient With Multiple Metastases

doi: 10.21873/cgp.20517

Figure Lengend Snippet: Effects of JAK1 mutant gene transduction on melanoma cell invasion activity. (A) Successful JAK1 mutant gene transduction confirmed by Sanger sequencing. JAK1 mutant (p.S404P) gene cDNA was synthesized and cloned into the vector. Mutant cDNA was then transduced into RPMI7951 melanoma cells using the Neon TM Transfection System via electroporation, and cells were seeded at a single-cell level. Proliferated clones were selected and JAK1 mutation-harboring clones were screened by Sanger sequencing. (B) The invasion activity of the JAK1 mutant gene-transduced melanoma cell line, RPMI7951. In the invasion assay, cells that invaded through the membrane were stained with the Differential Quik III stain kit and counted using microscopy. The significance of differences was evaluated by the Mann-Whitney U-test. **p<0.01.

Article Snippet: Briefly, JAK1 mutant ( p .S404P) gene cDNA was synthesized (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA), cloned into a vector, and transduced into three melanoma cells using the Neon TM Transfection System via electroporation (Invitrogen).

Techniques: Mutagenesis, Transduction, Activity Assay, Sequencing, Synthesized, Clone Assay, Plasmid Preparation, Transfection, Electroporation, Invasion Assay, Membrane, Staining, Microscopy, MANN-WHITNEY

Journal: Cell Genomics

Article Title: Binding domain mutations provide insight into CTCF’s relationship with chromatin and its contribution to gene regulation

doi: 10.1016/j.xgen.2025.100813

Figure Lengend Snippet: CTCF complementation system (A) Scheme of the CTCF doxycycline-inducible degron system. (B) Experimental strategy for the expression of WT and mutant transgenic CTCF. (C) Flow cytometry showing the level of GFP (endogenous CTCF) and mRuby (transgenic WT CTCF). (D) Left, scheme showing the locations of the different types of CTCF mutations within a ZF. Amino acids making contacts with the DNA are shown in shades of pink, residues that coordinate the zinc ion in red, boundary residues in purple, and residues that contact the sugar phosphate backbone of DNA in blue. Right, representation of CTCF showing the locations of each mutation under investigation. (E) Bar graph showing the expression levels (mean fluorescence intensity) of endogenous CTCF (GFP) and transgenic WT or mutant CTCF (mRuby2) after ID treatment. The error bars represent the standard deviation between the two replicates. (F) Western blot of endogenous CTCF (CTCF antibody) and transgenic CTCF (FLAG antibody) in untreated (WT-U), IAA, ID conditions. See also Figures S1–S5 .

Article Snippet: Construction of vector for cloning transgenic, doxycycline-inducible expression of WT and mutant mouse Ctcf cDNA were obtained from GenScript in pUC19 vectors.

Techniques: Expressing, Mutagenesis, Transgenic Assay, Flow Cytometry, Fluorescence, Standard Deviation, Western Blot

Journal: Cell Genomics

Article Title: Binding domain mutations provide insight into CTCF’s relationship with chromatin and its contribution to gene regulation

doi: 10.1016/j.xgen.2025.100813

Figure Lengend Snippet: CTCF mutations have unique chromatin binding profiles (A) Scheme showing the locations of the CTCF mutations within the ZF. The consensus CTCF motif highlights the triplet to which each mutant ZF binds (top). The most common motif for the de novo binding sites is shown below. Each bar graph shows the percentage of WT-only, common, and mutant-only CTCF binding sites. The heatmaps show the profile of CTCF and ATAC-seq signal at those sites. The UN condition corresponds to the FLAG control. (B) Profiles of ATAC-seq in WT and mutants. Wilcoxon p values were coded as follow: NS, not significant, ∗5 × 10 −2 –5 × 10 −3 , ∗∗5 × 10 −3 –5 × 10 −4 , ∗∗∗5 × 10 −4 –5 × 10 −5 , ∗∗∗∗<5 × 10 −5 . Data were generated on 2 replicates. See also Figures S6–S9 .

Article Snippet: Construction of vector for cloning transgenic, doxycycline-inducible expression of WT and mutant mouse Ctcf cDNA were obtained from GenScript in pUC19 vectors.

Techniques: Binding Assay, Mutagenesis, Control, Generated

Journal: Cell Genomics

Article Title: Binding domain mutations provide insight into CTCF’s relationship with chromatin and its contribution to gene regulation

doi: 10.1016/j.xgen.2025.100813

Figure Lengend Snippet: Each mutation uniquely impacts CTCF’s chromatin bound fraction, residence time, and interaction with DNA (A) Plots of FRAP dynamics for WT and mutant CTCF. The bold lines show the fitted model of the average recovery, and the outlines give the 95% confidence intervals (95% CIs). (B) Violin plots of specific bound fractions. (C) Violin plots of specific residence times (min). p values were determined by bootstrapping ( n = 2,500). (D) Heatmaps show the proportion of CTCF-cohesin versus CTCF-only binding sites. UN corresponds to the FLAG control in untreated cells. (E) Correlation between residence time and the percentage of CTCF-cohesin overlap. (F) Correlation between the FRAP-specific bound fraction relative to WT and the fraction of common CTCF sites relative to all potential binding sites. (G) Correlation between the FRAP-specific bound fraction relative to WT and the effect of CTCF binding on ATAC-seq signal at CTCF-SMC3 sites ( Figure 2 B). For (E)–(G), data were generated in 2 replicates, the p values were calculated using linear regression, and the shaded area corresponds to the 95% CI. See also Figures S10–S14 .

Article Snippet: Construction of vector for cloning transgenic, doxycycline-inducible expression of WT and mutant mouse Ctcf cDNA were obtained from GenScript in pUC19 vectors.

Techniques: Mutagenesis, Binding Assay, Control, Generated

Journal: Cell Genomics

Article Title: Binding domain mutations provide insight into CTCF’s relationship with chromatin and its contribution to gene regulation

doi: 10.1016/j.xgen.2025.100813

Figure Lengend Snippet: Effect of CTCF binding and accessibility on SMC3 overlap (A) Bar graph showing the independent effect of CTCF (top) and ATAC-seq (bottom) signal on SMC3 enrichment in WT. The error bars correspond to the 95% CIs. The p values were calculated using a multivariate logistic model. (B) Percentage of SMC3 overlap in WT and CTCF mutants, stratified by ATAC-seq and CTCF signals. (C) SMC3 profiles in WT and mutant CTCF. p values were calculated using Wilcoxon tests. See also Figures S15 , , and Table S1 .

Article Snippet: Construction of vector for cloning transgenic, doxycycline-inducible expression of WT and mutant mouse Ctcf cDNA were obtained from GenScript in pUC19 vectors.

Techniques: Binding Assay, Mutagenesis

Journal: Cell Genomics

Article Title: Binding domain mutations provide insight into CTCF’s relationship with chromatin and its contribution to gene regulation

doi: 10.1016/j.xgen.2025.100813

Figure Lengend Snippet: CTCF mutations alter gene expression, cellular reprogramming, and TF binding (A) Heatmap showing supervised clustering of the cell lines based on the expression levels of DEGs identified across the comparisons to WT. (B) Gene set enrichment analysis of DEGs in IAA condition and in H455R. The volcano plots below highlight the DEGs belonging to these enriched pathways. (C) Radar plots showing the averaged expression of developmental germ layer genes in WT and mutant mESCs cultured in LIF and no LIF conditions. (D) Heatmap showing predicted differentially bound TFs in WT, mutants and IAA. CTCF is highlighted with an asterisk (∗). (E) Volcano plots highlighting the differentially expressed target genes of CTCF and MBD2 in IAA and CTCF mutants. The metrics for enrichment of the target genes among the DEGs are reported on top on the volcanos (ORs and logistic p values). (F) Examples of altered CTCF binding and footprinting at the Rerg promoter (left) and altered MYC footprinting at the Brdt promoter (right). All data in this figure were generated on 2 replicates. See also Figures S17–S20 and Table S2. Differentially expressed genes (DEGs) identified using DE-seq. DEGs were defined as adjusted genes with p-value<0.05 and absolute log2 fold change > log2(1.5) compared to WT , Table S3. CTCF mutations altered cell differentiation , Table S4. CTCF mutations altered TF binding .

Article Snippet: Construction of vector for cloning transgenic, doxycycline-inducible expression of WT and mutant mouse Ctcf cDNA were obtained from GenScript in pUC19 vectors.

Techniques: Gene Expression, Binding Assay, Expressing, Mutagenesis, Cell Culture, Footprinting, Generated, Cell Differentiation

Journal: Cell Genomics

Article Title: Binding domain mutations provide insight into CTCF’s relationship with chromatin and its contribution to gene regulation

doi: 10.1016/j.xgen.2025.100813

Figure Lengend Snippet: CTCF mutations alter chromatin interactivity (A) The top panels show the aggregated differential TAD analysis between mutants and WT. In the first panel, (a) indicates the intra-TAD interaction, (b) and (c) the inter-TAD interactions. The lower panels show the aggregated differential peak analysis. The data were generated by Hi-C on 2 replicates. (B) Correlation between the interaction counts and the FRAP residence times. (C) Correlation between the insulation score at CTCF peaks and the FRAP residence times. (D) Correlation between the loop extrusion length and the FRAP bound fractions. (E) Example of differential interactions between mutants and WT (right). The left matrix shows interactions in WT within a 10 Mb region (40 kb resolution) with the insulation score on the side. (F) Profiles show the averaged insulation score at WT-only, common, and mutant-only binding sites. (G) Profiles show the insulation score at CTCF binding sites stratified by CTCF signals. The bar graph shows the independent effect of CTCF signal on insulation score. (H) Profiles show the insulation score at CTCF binding sites stratified by ATAC signals. The bar graph shows the independent effect of ATAC signal on insulation score. For (F)–(H), p values reported in the profiles were calculated using Kruskal-Wallis tests. The fitted estimates for the bar graphs in (G) and (H) were obtained using a mixed multivariate model. The error bars correspond to the 95% CI. See also Figures S21–S24 .

Article Snippet: Construction of vector for cloning transgenic, doxycycline-inducible expression of WT and mutant mouse Ctcf cDNA were obtained from GenScript in pUC19 vectors.

Techniques: Generated, Hi-C, Insulation, Mutagenesis, Binding Assay

Journal: Cell Genomics

Article Title: Binding domain mutations provide insight into CTCF’s relationship with chromatin and its contribution to gene regulation

doi: 10.1016/j.xgen.2025.100813

Figure Lengend Snippet: Changes in gene expression are linked to changes in chromatin interactivity but to a lesser extent than changes in TF binding at gene promoters (A) Bar graphs showing the enrichment of over-expressed (top) or under-expressed (bottom) genes in gained (top) or lost (bottom) loops in IAA and mutants compared to WT. ORs and p values were calculated using logistic models. (B) Example of 2 loci (blue and red rectangles) with a direct effect of gain in CTCF binding and chromatin interactivity. The interaction matrices (left) show gain of both intra- and inter-TAD interactions in some mutants compared to WT. The left panels show the zoom-in tracks of these loci. Only significant differential chromatin loops are shown. Overexpressed genes are highlighted in red. (C) Bar graph showing the percentage of DEGs resulting from direct or indirect effect of CTCF binding distinguishing loop dependent and independent effect.

Article Snippet: Construction of vector for cloning transgenic, doxycycline-inducible expression of WT and mutant mouse Ctcf cDNA were obtained from GenScript in pUC19 vectors.

Techniques: Gene Expression, Binding Assay