ORIGINAL RESEARCH article
Front. Cell Dev. Biol.
Sec. Epigenomics and Epigenetics
Volume 13 - 2025 | doi: 10.3389/fcell.2025.1597245
This article is part of the Research TopicChromatin Modifications and Gene Expression: From Mechanisms to Therapeutic Implications in DiseaseView all 3 articles
Integration of Chromosome Conformation and Gene Expression Networks Reveal Regulatory Mechanisms in Triple Negative Breast Cancer
Provisionally accepted
- 1Feinstein Institute for Medical Research, New York, New York, United States
- 2Computational Genomics, National Institute of Genomic Medicine (INMEGEN), Mexico City, Mexico
- 3Weill Cornell Medicine, Cornell University, New York, New York, United States
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Triple-negative breast cancer (TNBC) accounts for twelve percent of all breast cancer cases, with a survival rate around ten percent lower than ER+/PR+ positive breast cancers. There are limited therapeutic options as these tumors do not respond to hormonal therapy or HER2-targeted treatments. We hypothesized that new insights into pathogenic mechanisms in TNBC could be obtained from the study of epigenetic alterations, by analyzing Hi-C (a genome-wide chromosome conformation capture technique) data. Hi-C data can distinguish interaction patterns related to diseased phenotypes or interaction patterns with potential to exert regulatory effects instead of incidental contacts, but some apparently random interactions may also support important genome regulatory activities. Key factors in Hi-C data, including the distance-decay effect, correcting for technical biases inherited from the experimental procedures, and the equal visibility principle, they may not capture the genome-wide complexity of chromatin interactions. In this study, we developed a computational model that captured key properties of chromatin conformation while incorporating statistical measures of interaction significance. We then tested this model on Hi-C and RNA-seq data from patients with TNBC and healthy controls. We represented the data as networks and identified genome-wide properties of the TNBC 3D genome. Finally, we integrated these networks with transcriptional data to examine how chromatin organization relates to gene expression, demonstrating the power of network-based Hi-C analysis to perform integrative analysis.
Keywords: Triple negative breast cancer, chromosome conformation capture, Hi-C, complex networks, regulatory genomics
Received: 20 Mar 2025; Accepted: 16 Jun 2025.
Copyright: © 2025 Reyes-Gopar, Pérez-Fuentes, Bendall and Hernandez-Lemus. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Enrique Hernandez-Lemus, Computational Genomics, National Institute of Genomic Medicine (INMEGEN), Mexico City, Mexico
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