{"doi":"10.1101/2022.04.11.487902","title":"Loss of the repressor REST affects progesterone receptor function and promotes uterine leiomyoma pathogenesis","abstract":"Abstract Uterine Leiomyomas (UL) are benign tumors that arise in the myometrial layer of the uterus. The standard treatment option for UL is hysterectomy, although hormonal therapies such as selective progesterone receptor modulators are often used as temporary treatment options to reduce symptoms or slow the growth of tumors. However, since the pathogenesis of UL is poorly understood and most hormonal therapies are not based on UL-specific, divergent hormone signaling pathways, hallmarks that predict long-term efficacy and safety of pharmacotherapies remain largely undefined. In a previous study, we reported aberrant expression of REST/NRSF target genes activate UL growth due to the near ubiquitous loss of REST. Here, we show that ablation of the Rest gene in mouse uterus leads to UL phenotype and gene expression patterns analogous to UL, including altered estrogen and progesterone signaling pathways. We demonstrate that many of the genes dysregulated in UL harbor cis-regulatory elements bound by REST and progesterone receptor (PGR) adjacent to each other. Crucially, we identify an interaction between REST and PGR in healthy myometrium and present a putative mechanism for the dysregulation of progesterone responsive genes in UL ensuing the loss of REST. Using three Rest conditional knockout mouse lines, we provide a comprehensive picture of the impact loss of REST has in UL pathogenesis and in altering the response of UL to steroid hormones. Significance statement Ablation of Rest gene in the mouse uterus, modelling the loss REST in uterine fibroids, results in tumor formation and gene expression patterns analogous to human UL, including altered estrogen and progesterone receptor (PGR) pathways. The current study provides a putative mechanism for the aberrant function of PGR in UL.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2022,"id":301123,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.956,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":879862,"name":"Faezeh Koohestani","orcid":"0000-0001-7777-6526","position":1,"is_corresponding":false},{"id":880362,"name":"Michelle M. McWilliams","orcid":null,"position":2,"is_corresponding":false},{"id":820019,"name":"Sornakala Ganeshkumar","orcid":"0000-0001-5840-5818","position":3,"is_corresponding":false},{"id":284304,"name":"Sumedha Gunewardena","orcid":"0000-0003-2097-135X","position":4,"is_corresponding":false},{"id":880363,"name":"Amanda Graham","orcid":null,"position":5,"is_corresponding":false},{"id":707979,"name":"Warren B. Nothnick","orcid":"0000-0002-2349-1880","position":6,"is_corresponding":false},{"id":820020,"name":"Vargheese M. Chennathukuzhi","orcid":"0000-0002-4178-146X","position":7,"is_corresponding":false},{"id":820018,"name":"Ashley S. Cloud","orcid":"0000-0002-1384-8778","position":0,"is_corresponding":true}],"reference_count":53,"raw_metadata":null,"created_at":"2026-07-19T00:31:57.812980Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}