Nearly 70% of Uterine fibroid (UF) tumors are driven by recurrent MED12 hotspot mutations. Unfortunately, no cellular models could be generated because the mutant cells have lower fitness in 2D culture conditions. To address this, we employ CRISPR to precisely engineer MED12 Gly44 mutations in UF-relevant myometrial smooth muscle cells. The engineered mutant cells recapitulate several UF-like cellular, transcriptional, and metabolic alterations, including altered Tryptophan/kynurenine metabolism. The aberrant gene expression program in the mutant cells is, in part, driven by a substantial 3D genome compartmentalization switch. At the cellular level, the mutant cells gain enhanced proliferation rates in 3D spheres and form larger lesions in vivo with elevated production of collagen and extracellular matrix deposition. These findings indicate that the engineered cellular model faithfully models key features of UF tumors and provides a platform for the broader scientific community to characterize genomics of recurrent MED12 mutations.
Uterine fibroid (UF) tumors originate from a mutated smooth muscle cell (SMC). Nearly 70% of these tumors are driven by hotspot recurrent somatic mutations in the MED12 gene; however, there are no tractable genetic models to study the biology of UF tumors because, under culture conditions, the non-mutant fibroblasts outgrow the mutant SMC cells, resulting in the conversion of the population to WT phenotype. The lack of faithful cellular models hampered our ability to delineate the molecular pathways downstream of MED12 mutations and identify therapeutics that may selectively target the mutant cells. To overcome this challenge, we employed CRISPR knock-in with a sensitive PCR-based screening strategy to precisely engineer cells with mutant MED12 Gly44, which constitutes 50% of MED12 exon two mutations. Critically, the engineered myometrial SMC cells recapitulate several UF-like cellular, transcriptional and metabolic alterations, including enhanced proliferation rates in 3D spheres and altered Tryptophan/kynurenine metabolism. Our transcriptomic analysis supported by DNA synthesis tracking reveals that MED12 mutant cells, like UF tumors, have heightened expression of DNA repair genes but reduced DNA synthesis rates. Consequently, these cells accumulate significantly higher rates of DNA damage and are selectively more sensitive to common DNA-damaging chemotherapy, indicating mutation-specific and therapeutically relevant vulnerabilities. Our high-resolution 3D chromatin interaction analysis demonstrates that the engineered MED12 mutations drive aberrant genomic activity due to a genome-wide chromatin compartmentalization switch. These findings indicate that the engineered cellular model faithfully models key features of UF tumors and provides a novel platform for the broader scientific community to characterize genomics of recurrent MED12 mutations and discover potential therapeutic targets.
Uterine fibroids (UF), also called leiomyomas, are observed in nearly 70% of women of reproductive age. These tumors disrupt normal uterine function and cause significant physical and psychological health problems. Although heritable genetics is a significant risk factor, specific genetic variations and gene targets causally associated with UL are poorly understood. We performed a meta-analysis on existing fibroid genome-wide association studies (GWAS) and integrated the identified risk loci and potentially causal single nucleotide polymorphisms (SNPs) with epigenomics (H3K27me3), transcriptomics (RNA-Seq), 3D chromatin organization (Hi-C) and single-cell atlas (scRNA-Seq) of primary samples from UF patients. The integrative analysis identified 24 risk loci and 394 potential gene targets associated with UF. Among these, 106 of them were differentially expressed in UF tumors. Critically, the integrative analysis with single-cell RNA sequencing revealed the cell types with aberrant expression of these target genes in normal and UF tissue. Finally, CRISPR-based epigenetic manipulation (dCas9-KRAB) of two risk loci in a disease-relevant cell type fine-mapped the gene targets. These findings and the methodological approach indicate the effectiveness of integrative multi-omics data combined with locus-specific epigenetic editing approaches to identify disease-relevant risk loci and their target genes.
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