ArticleNucleic acids research2024
Machine learning enables pan-cancer identification of mutational hotspots at persistent CTCF binding sites.
Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Therapy-associated mutagenesis at CTCF binding sites is shaped by chromatin context and DNA repair capacity.bioRxiv : the preprint server for biology · 2026Article
- Structural variants in the 3D genome as drivers of disease.Nature reviews. Genetics · 2025Review
- CanASM: a comprehensive database for genome-wide allele-specific DNA methylation identification and annotation in cancer.BMC genomics · 2025Article
- CTCF binding landscape is shaped by the epigenetic state of the N-terminal nucleosome in relation to CTCF motif orientation.Nucleic acids research · 2025Article
- Machine learning and single-cell analysis uncover distinctive characteristics of CD300LG within the TNBC immune microenvironment: experimental validation.Clinical and experimental medicine · 2025Article
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Authors and funding
8 authors.
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Abstract
CCCTC-binding factor (CTCF) is an insulator protein that binds to a highly conserved DNA motif and facilitates regulation of three-dimensional (3D) nuclear architecture and transcription. CTCF binding sites (CTCF-BSs) reside in non-coding DNA and are frequently mutated in cancer. Our previous study identified a small subclass of CTCF-BSs that are resistant to CTCF knock down, termed persistent CTCF binding sites (P-CTCF-BSs). P-CTCF-BSs show high binding conservation and potentially regulate cell-type constitutive 3D chromatin architecture. Here, using ICGC sequencing data we made the striking observation that P-CTCF-BSs display a highly elevated mutation rate in breast and prostate cancer when compared to all CTCF-BSs. To address whether P-CTCF-BS mutations are also enriched in other cell-types, we developed CTCF-INSITE-a tool utilising machine learning to predict persistence based on genetic and epigenetic features of experimentally-determined P-CTCF-BSs. Notably, predicted P-CTCF-BSs also show a significantly elevated mutational burden in all 12 cancer-types tested. Enrichment was even stronger for P-CTCF-BS mutations with predicted functional impact to CTCF binding and chromatin looping. Using in vitro binding assays we validated that P-CTCF-BS cancer mutations, predicted to be disruptive, indeed reduced CTCF binding. Together this study reveals a new subclass of cancer specific CTCF-BS DNA mutations and provides insights into their importance in genome organization in a pan-cancer setting.
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