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A Whole Transcriptome Profiling of Uterine Leiomyoma Cells under the influence of Phenolic Environmental Estrogen

ABSTRACT: Purpose:The study aimed to recognize potential molecular targets and signal pathways whereby phenolic environmental estrogen promotes the proliferation of uterine leiomyoma cells Methods:Primary cultured cell lines were treated with 0.1% DMSO, 10.0 μmol/L BPA, and 32.0 μmol/L NP for 48 h before RNA-seq was performed. Differentially expressed genes affected by BPA and NP were selected. Then, Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and Protein-protein Interaction (PPI) analysis were performed. Quantitative real-time polymerase chain reaction (q-PCR) was used to verify the differentially expressed genes Results:In comparison with the control group, 739 differentially expressed mRNAs were identified in the BPA intervention group and the NP intervention group. GO enrichment analysis results show that the most enriched GO terms were connective tissue development and G1/S transition of mitotic cell cycle, and extracellular matrix. The results of KEGG enrichment analysis showed that differentially expressed mRNA was enriched mainly in three primary pathways, including environmental information processing, human diseases, and cellular processes. The cell cycle, PI3K-Akt signaling pathway, pathways in cancer, and TGF-beta signaling pathway are significantly enriched. Conclusions:Phenolic environmental estrogens may promote the proliferation and cell cycle progression of uterine leiomyoma cells through rapid non-genomic ER signaling, which leads to disordered cell cycle regulation and accelerates the transition of the cell cycle from G0/G1 phase to S phase. In addition, as an external harmful stimulant, phenolic estrogen promotes the upregulation of inflammatory factors in uterine leiomyomas.

ORGANISM(S): Homo sapiens

PROVIDER: GSE173334 | GEO | 2021/04/27

REPOSITORIES: GEO

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Project description:Purpose:Our goal was to identify and characterize a new molecular target of Bisphenol A（BPA）in uterine leiomyoma cells to better understand how this compound may affect uterine leiomyomas growth and development. Methods: Primary cultured cell lines of uterine leiomyoma were treated with 0.1% DMSO or 10.0 μmol/L BPA for 48 h before RNA-seq and histone 3 lysine 27 acetylation (H3K27ac) ChIP-seq were performed. Integrative analysis of ChIP-seq and RNA-seq data identifies the key transcription factor (TF)，target gene and signaling pathway. To confirm the expression level of TF and target gene in uterine leiomyomas tissues, we analyzed 10 human uterine leiomyoma tissues and the matched adjacent uterine smooth muscle tissues using western blotting, and 96 paired paraffin-embedded human uterine samples by immunohistochemistry(IHC). The ChIP assay used to confirm the combination between the TF and target gene. In order to verify the functions of key TF, lentivirus was used to knock down the expression level and detect the effects on cell proliferation, cell cycle, and cell tumorigenicity. We further conducted Western blot analysis to confirm the whether the downstream signaling pathway is activated. RESULTS: Integrative Analysis of ChIP-seq and RNA-seq data identifies the key transcription factor XBP1and target gene ITGA2. The qPCR and ChIP- qPCR initially verified the sequencing results. XBP1 and ITGA2 were overexpressed in human uterine leiomyoma tissues. The IHC results confirmed that ITGA2 was significantly correlated with XBP1 expression (R = 0.6708, P < 0.001)， and the ChIP assay showed that XBP1 binds to the the ITGA2 predicted promoter region. BPA promoted uterine leiomyoma cells proliferation both in vitro and in vivo and that XBP1 expression levels modulated the cellular response to this endocrine disruptor. BPA upregulated ITGA2 through XBP1 and activated the downstream PI3K-AKT signaling pathway to promote the proliferation of human uterine leiomyoma cells. CONCLUSION: In conclusion, our current work reveals a novel mechanism by which BPA promotes the proliferation in uterine leiomyoma cells. The XBP1 transcription factor regulates and activates the downstream ITGA2/PI3K/AKT pathway. By defining XBP1 as an important regulatory role of BPA in uterine leiomyoma cell proliferation, they provide new insights into the pathogenesis related to the exposure to BPA and other endocrine disruptors acting similarly, and XBP1 may serve as a candidate molecular target for intervention and treatment of uterine leiomyomas.

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)

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.

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A Whole Transcriptome Profiling of Uterine Leiomyoma Cells under the influence of Phenolic Environmental Estrogen

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