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HMGA2 overexpression drives a leiomyoma-like phenotype by modulating the epigenomic environment in primary myometrial cells [ATAC-seq]

GSE276285 Homo sapiens Genome binding/occupancy profiling by high throughput sequencing 6 samples Submitted 2025/10/01 Platform GPL18573
Summary
With the utilization of advanced tools for genome-wide studies, the role of the epigenome in regulating gene expression is becoming more evident in both normal tissue development and disease states. Uterine fibroids, also known as leiomyomas, are a major reproductive disease that manifests as benign tumors and altered extracellular matrix composition leading to severe pathological symptoms. Several genomic alterations have been associated with leiomyoma. HMGA2 overexpression has been noted in approximately 10% of all patients with leiomyoma. HMGA2 is a chromatin-targeted protein and is therefore an important contributor to altered transcriptomic outcomes. However, due to a lack of specific antibodies against HMGA2 and appropriate in vitro cellular models, there is a lack in understanding of HMGA2 interaction with and regulation of chromatin in the context of leiomyoma. To address this gap, we engineered primary myometrial cells that express V5-tagged HMGA2 at levels comparable to those observed in leiomyoma. We observed transcriptomic and H3K27 acetylation changes that appeared to drive a leiomyoma-like phenotype in the engineered HMGA2v5 cells. HMGA2 was found to be diffusedly bound to chromatin, with most of the binding occurring at promoter- distal regions. Moreover, altered chromatin accessibility was observed in HMGA2v5 cells, with enrichment of AP-1 family transcription factor binding motifs at various sites. Thus, our study suggests that overexpression of HMGA2 modulates the genomic architecture of myometrial cells to cause leiomyoma-like gene expression and epigenomic changes.
Published in
Engineered uterine primary myometrial cells with high-mobility group AT-hook 2 overexpression display a leiomyoma-like transcriptional and epigenomic phenotype
Saini P, Holmes AG, Wei JJ et al. · F&S science 2024 · PMID 39074663 · doi:10.1016/j.xfss.2024.07.008
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Also filed as BioProject PRJNA1156537 and SRA study SRP530390. Searching any of these in the dataset finder brings you back here.

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