Genome-wide prgesterone receptor binding profile in human uterine leiomyoma tissue
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA574344 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10189640.fastq.gz | Fastqsanger.gz | |||
| SRR10189641.fastq.gz | Fastqsanger.gz | |||
| SRR10189642.fastq.gz | Fastqsanger.gz | |||
| SRR10189643.fastq.gz | Fastqsanger.gz | |||
| SRR10189644.fastq.gz | Fastqsanger.gz |
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Project description:Uterine leiomyomas (LM) affect up to 80% of all reproductive-age women. LM growth requires progesterone, progesterone receptor (PGR), and the maintenance and proliferation of a small (5%) stem cell population. Stem cell activation and differentiation are driven by DNA methylation and nuclear hormone receptor action, but crosstalk between these mechanisms remains unclear. We performed an integrated analysis of the transcriptome and epigenetic landscape of LM cells at three differentiation stages and the PGR cistrome of whole LM tissue. The PGR-deficient stem cell population harbored a unique methylation landscape, with hypermethylation at the PGR gene locus and PGR-binding regions, which suppressed stem cell responsiveness to progesterone. The DNA methylation inhibitor 5’-Aza upregulated the expression of PGR and its target genes by stimulating PGR recruitment to the targeted gene loci, and significantly depleted the LM stem cell population and its tumor-initiating capacity. We herein provided mechanistic insights via therapeutically accelerating the stem cell differentiation process of a hormone-sensitive tumor.
2021-08-01 | GSE138049 | GEO
Project description:Global protein coding gene and miRNA expression profiling studies in uterine leiomyoma showed their aberrant expression and involvement in the pathogenesis of uterine leiomyoma. But the global expression patterns and potential clinical value of long noncoding RNA (lncRNA) in uterine leiomyoma have not been explored.In this study, we performed lncRNA expression profiles analysis of uterine leiomyoma using microarray(Arraystar Human LncRNA Array v2.0) to evaluate the genome-wide expression of lncRNAs and mRNAs and their potential role in the pathogenesis of uterine leiomyoma.
2014-08-14 | GSE52618 | GEO
Project description:Global protein coding gene and miRNA expression profiling studies in uterine leiomyoma showed their aberrant expression and involvement in the pathogenesis of uterine leiomyoma. But the global expression patterns and potential clinical value of long noncoding RNA (lncRNA) in uterine leiomyoma have not been explored.In this study, we performed lncRNA expression profiles analysis of uterine leiomyoma using microarray(Arraystar Human LncRNA Array v2.0) to evaluate the genome-wide expression of lncRNAs and mRNAs and their potential role in the pathogenesis of uterine leiomyoma. Expression profiling analysis of the 15 samples including 5 large fibroids, 5 small fibroids and 5 matched myometrium by Arraystar Human LncRNA Array v2.0.
2014-08-14 | E-GEOD-52618 | biostudies-arrayexpress
Project description:Objective: The objective of this study was to estimate the accuracy of transcriptome-based classifier in differential diagnosis of uterine leiomyoma and leiomyosarcoma. Methods: We manually selected 114 normal uterine tissue and 31 leiomyosarcoma samples from publicly available transcriptome data in UCSC Xena as training/validation sets. We developed pre-processing procedure and gene selection method to sensitively find genes of larger variance in leiomyosarcoma than normal uterine tissues. Through our method, twenty genes were selected to build transcriptome-based classifier. The prediction accuracies of deep feedforward neural network (DNN), support vector machine (SVM), Random Forest (RF), and Gradient Boosting (GB) models were examined. We interpret the biological functionality of selected genes via network-based analysis using Gene-Mania. To validate the performance of trained model, we additionally collected 35 clinical samples of leiomyosarcoma and leiomyoma as a test set (18 + 17 as 1st and 2nd test sets). Results: We discovered genes expressed in a highly variable way in leiomyosarcoma while these genes are expressed in a conserved way in normal uterine samples. These genes were mainly associated with DNA replication, cell cycle, and DNA damage checkpoint. Among evaluated machine learning classifiers, the DNN had the highest accuracy and average AUC value in training data set. As gene selection and model training were made in leiomyosarcoma and uterine normal tissue, proving discriminant of ability between leiomyosarcoma and leiomyoma is necessary. Thus, further validation of trained model was conducted in newly collected clinical samples of leiomyosarcoma and leiomyoma. The DNN classifier performed AUC of 0.917 and 0.914 supporting that the selected genes in conjunction with DNN classifier are well discriminating the difference between leiomyosarcoma and leiomyoma in clinical sample. Conclusion: The transcriptome-based classifier accurately distinguished uterine leiomyoma from leiomyosarcoma.
2023-12-13 | GSE222045 | GEO
Project description:Uterine leiomyomas, or fibroids, represent the most common benign tumor of the female reproductive tract. Fibroids become symptomatic in 30% of all women and up to 70% of African American women of reproductive age. Epigenetic dysregulation of individual genes has been demonstrated in leiomyoma cells; however, the in vivo genome-wide distribution of such epigenetic abnormalities, however, remains unknown. Principal Findings: We characterized and compared genome-wide DNA methylation and mRNA expression profiles in uterine leiomyoma and matched adjacent normal myometrial tissues from 18 African-American women. We found 55 genes with differential promoter methylation and concominant differences in mRNA expression in uterine leiomyoma versus normal myometrium. Eighty percent of the identified genes showed an inverse relationship DNA methylation status and mRNA expression in uterine leiomyoma tissues, and the majority of genes (62%) displayed hypermethylation associated with gene silencing. We selected two genes, the known tumor suppressors KLF11 and DLEC1, and verified promoter hypermethylation and mRNA repression using bisulfite sequencing and real-time PCR. Incubation of primary leiomyoma smooth muscle cells with a DNA methyltransferase inhibitor restored KLF11 and DLEC1 mRNA levels. paired LM and MM tissue samples
2012-04-29 | E-GEOD-31699 | biostudies-arrayexpress
Project description:Uterine leiomyomas, or fibroids, represent the most common benign tumor of the female reproductive tract. Fibroids become symptomatic in 30% of all women and up to 70% of African American women of reproductive age. Epigenetic dysregulation of individual genes has been demonstrated in leiomyoma cells; however, the in vivo genome-wide distribution of such epigenetic abnormalities, however, remains unknown. Principal Findings: We characterized and compared genome-wide DNA methylation and mRNA expression profiles in uterine leiomyoma and matched adjacent normal myometrial tissues from 18 African-American women. We found 55 genes with differential promoter methylation and concominant differences in mRNA expression in uterine leiomyoma versus normal myometrium. Eighty percent of the identified genes showed an inverse relationship DNA methylation status and mRNA expression in uterine leiomyoma tissues, and the majority of genes (62%) displayed hypermethylation associated with gene silencing. We selected two genes, the known tumor suppressors KLF11 and DLEC1, and verified promoter hypermethylation and mRNA repression using bisulfite sequencing and real-time PCR. Incubation of primary leiomyoma smooth muscle cells with a DNA methyltransferase inhibitor restored KLF11 and DLEC1 mRNA levels.
2012-04-30 | GSE31699 | GEO
Project description:Uterine leiomyomata, or fibroids, are benign tumors of the uterine myometrium that significantly affect up to 30% of reproductive-age women. Despite being the primary cause of hysterectomy in the United States, accounting for up to 200,000 procedures annually, the etiology of leiomyoma remains largely unknown. Due to the lack of an effective medicinal therapy for these tumors, this disease continues to have a tremendous negative impact on women’s health. As a basis for understanding leiomyoma pathogenesis and identifying targets for pharmacotherapy, we conducted transcriptional profiling of leiomyoma and unaffected myometrium from humans and Eker rats, the best characterized preclinical model of leiomyoma. A global comparison of mRNA from leiomyoma versus myometrium in human and rat identified a highly significant overlap of dysregulated gene expression in leiomyoma. An unbiased pathway analysis using a method of gene set enrichment based on the Sigpathway algorithm detected the mammalian target of rapamycin (mTOR) pathway as one of the most highly upregulated pathways in both human and rat tumors. Activation of this pathway was confirmed in both human and rat leiomyomata at the protein level via Western. Inhibition of mTOR in female Eker rats with the rapamycin analog WAY-129327 for 2 weeks decreased mTOR signaling and cell proliferation in tumors, and treatment for 4 months significantly decreased tumor incidence, multiplicity and size. These results identify dysregulated mTOR signaling as a component of leiomyoma etiology across species and directly demonstrate the dependence of these tumors on mTOR signaling for growth in the Eker rat. Modulation of this pathway warrants additional investigation as a potential therapy for uterine leiomyoma. Experiment Overall Design: We analyzed 1-3 leiomyoma or normal myometrium biopsies from each 23 woman undergoing hysterectomy for the treatment of uterine fibroids. tment and compared it leiomyoma and normal myometrium from the Eker rat model of uterine fibroids (N=14-15)
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Project description:Comparison of Gene Expression in Uterine Smooth Muscle Tumors (including normal myometrium, benign uterine leiomyoma, malignant uterine and extra-uterine leiomyosarcoma). Total RNA was isolated with Trizol and converted to labeled cRNA by standard Affymetrix protocols. Before analysis, Avg Diff values were normalized to a sum of 3 million for each probe set on the chip and values less than 20 were adjusted to 20 to allow log scaling in subsequent analysis.
2007-09-25 | E-GEOD-764 | biostudies-arrayexpress
Project description:Analysis of genes regulated by RU486 (an progesterone antagonist) in human breast cancer T47D cells and human uterine leiomyoma smooth muscle cells. The hypothesis is that RU486 inhibits tumor growth by inactivating the transcription of multiple genes which trigger critical signaling pathways to induce tumorigenesis in both breast caner and uterine leomyoma. Tissue-specific and common patterns of gene regulation may determine the therapeutic effects of antiprogestins in uterine leiomyoma and breast cancer. We applied ChIP-seq to identify PR-interaction sites in T47D breast cancer cells and primary uterine leiomyoma cells treated with RU486.
2012-09-11 | E-GEOD-40724 | biostudies-arrayexpress
Project description:Analysis of genes regulated by RU486 (an progesterone antagonist) in human breast cancer T47D cells and human uterine leiomyoma smooth muscle cells. The hypothesis is that RU486 inhibits tumor growth by inactivating the transcription of multiple genes which trigger critical signaling pathways to induce tumorigenesis in both breast caner and uterine leomyoma. Tissue-specific and common patterns of gene regulation may determine the therapeutic effects of antiprogestins in uterine leiomyoma and breast cancer. Total RNA isolated from T47D cells subjected to RU486 treatment for 6 hours compared to vehicle (ethanol) treated cells. Total RNA isolated from uterine leiomyoma cells subjected to RU486 treatment for 6 hours compared to vehicle (ethanol) treated cells.
2011-07-22 | E-GEOD-30871 | biostudies-arrayexpress