Abstract 1074: CTCFDB: a systematic framework and comprehensive data resource for CTCF binding in the human genome

Abstract CCTCC-binding factor (CTCF), a highly conserved zinc finger protein, plays a crucial role in the three-dimensional (3D) genome organization by mediating DNA loops and topologically associating domains (TADs). Variations in CTCF binding across different cell types can lead to changes in cell type-specific chromatin conformation, altering gene expression and contributing to diseases such as cancer. Despite its importance, an up-to-date and comprehensive database for human CTCF binding sites has been lacking. To fill this gap, we developed CTCFDB, a curated data resource encompassing 2, 251 high-quality CTCF ChIP-seq datasets from NCBI GEO across 344 human cell types. We identified 510, 675 high-confidence CTCF binding sites in the human genome. Among those, 22, 722 were charactered as constitutive binding sites that are conserved across cell types. Using binding profiles across high-confidence CTCF binding sites, we performed unsupervised clustering analyses on all samples and found that the majority of cell types were clustered together, indicating cell type-specific binding patterns. Besides, we characterized 65, 697 cell type-specific gained and 18, 990 lost CTCF sites by focusing on individual union sites, further demonstrating the cell type specificity of CTCF binding. CTCFDB, with its systematic approach and user-friendly interface, provides an invaluable resource for advancing research on 3D genomics and gene regulation. This framework can be extended to generate similar data resources for other DNA-associating proteins, facilitating broader insights into functional genomics and cancer research. Citation Format: Shengyuan Wang, Zhenjia Wang, Grant Atwood, Yanbin Xu, Chongzhi Zang. CTCFDB: a systematic framework and comprehensive data resource for CTCF binding in the human genome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1074.

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Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-1074
Primary Topic
Growth Hormone and Insulin-like Growth Factors
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article
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article

Abstract 1074: CTCFDB: a systematic framework and comprehensive data resource for CTCF binding in the human genome

Chongzhi Zang, Yanbin Xu, Zhen Wang, Shengyuan Wang et al.
Cancer Research
Growth Hormone and Insulin-like Growth Factors
article

Abstract 1074: CTCFDB: a systematic framework and comprehensive data resource for CTCF binding in the human genome

Chongzhi Zang, Yanbin Xu, Zhen Wang, Shengyuan Wang, Grant Atwood
article en

Abstract

Abstract CCTCC-binding factor (CTCF), a highly conserved zinc finger protein, plays a crucial role in the three-dimensional (3D) genome organization by mediating DNA loops and topologically associating domains (TADs). Variations in CTCF binding across different cell types can lead to changes in cell type-specific chromatin conformation, altering gene expression and contributing to diseases such as cancer. Despite its importance, an up-to-date and comprehensive database for human CTCF binding sites has been lacking. To fill this gap, we developed CTCFDB, a curated data resource encompassing 2, 251 high-quality CTCF ChIP-seq datasets from NCBI GEO across 344 human cell types. We identified 510, 675 high-confidence CTCF binding sites in the human genome. Among those, 22, 722 were charactered as constitutive binding sites that are conserved across cell types. Using binding profiles across high-confidence CTCF binding sites, we performed unsupervised clustering analyses on all samples and found that the majority of cell types were clustered together, indicating cell type-specific binding patterns. Besides, we characterized 65, 697 cell type-specific gained and 18, 990 lost CTCF sites by focusing on individual union sites, further demonstrating the cell type specificity of CTCF binding. CTCFDB, with its systematic approach and user-friendly interface, provides an invaluable resource for advancing research on 3D genomics and gene regulation. This framework can be extended to generate similar data resources for other DNA-associating proteins, facilitating broader insights into functional genomics and cancer research. Citation Format: Shengyuan Wang, Zhenjia Wang, Grant Atwood, Yanbin Xu, Chongzhi Zang. CTCFDB: a systematic framework and comprehensive data resource for CTCF binding in the human genome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1074.

Cancer ResearchVol. 85(8_Supplement_1)
University of Virginia (US)
Openalex Percentile: Top 89%
Growth Hormone and Insulin-like Growth Factors
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