Comparison of Gene Expression in Uterine Smooth Muscle Tumors
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE764 | GEO | 2004/01/01
SECONDARY ACCESSION(S): PRJNA87717
REPOSITORIES: GEO
Similar Datasets
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:Uterine leiomyosarcoma (ULMS) is a poorly understood gynecologic cancer with few effective treatments. This study explores molecular events involved in ULMS with the goal of identifying strategies. Genome-wide transcriptional profiling were used to compare clinically well-annotated specimens of myometrium, leiomyoma and leiomyosarcoma.
2012-04-26 | E-GEOD-36610 | 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:Our study seeks to identify genes differentially expressed between uterine leiomyomas and normal myometrial tissue. This series consists of samples derived from normal myometrium and uterine leiomyomas obtained from fibroid afflicted patients.Total RNA was extracted from samples, converted to biotin-labeled cRNA, hybridized to oligonucleotide arrays, and followed by model based expression analysis. In order to select differentially expressed genes of interest, dChip model-based expression analysis was employed. Significant genes were identified, utilizing the dChip software, as having an average fold change of > +1.5 or < -1.5 between leiomyoma and normal myometrium and p < 0.05. Under these conditions the 226 genes in the following list were identified. Keywords: other
2003-10-17 | GSE593 | GEO
Project description:Uterine leiomyosarcoma is a most aggressive gynecological malignancy, and uterine leiomyoma is a benign tumor. Here, we performed bulk RNA-seq using archival fresh-frozen tumor samples stored at the National Cancer Center Biobank.
2022-06-30 | GSE185543 | 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)
2009-09-05 | E-GEOD-13319 | biostudies-arrayexpress
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:Our study seeks to identify genes differentially expressed between uterine leiomyomas and normal myometrial tissue. This series consists of samples derived from normal myometrium and uterine leiomyomas obtained from fibroid afflicted patients.Total RNA was extracted from samples, converted to biotin-labeled cRNA, hybridized to oligonucleotide arrays, and followed by model based expression analysis.,In order to select differentially expressed genes of interest, dChip model-based expression analysis was employed. Significant genes were identified, utilizing the dChip software, as having an average fold change of > +1.5 or < -1.5 between leiomyoma and normal myometrium and p < 0.05. Under these conditions the 226 genes in the following list were identified.
2007-09-28 | E-GEOD-593 | biostudies-arrayexpress
Project description:Transcriptional profiling of uterine leiomyoma tumor samples for integrative analysis with copy number alterations data. Goal was to identify up- and/or down-expressed genes associated with genomic gains and/or losses, respectively. After, it was applied to GSEA and CONEXIC algorithm to integrate the data. Protein-protein interactions also was building and the data were validated using qRT-PCR and IHC techniques. Experiment condition, 51 uterine leiomyoma samples from patients at the secretory or proliferative menstrual cycle phases were labeled with Cy3 and adjacent normal myometrium reference samples were labeled with Cy5. Each uterine leiomyoma and adjacent normal myometrium sample were obtained from the same patient and were mixed and hybridized on a glass slide Agilent 4x44 platform.
2012-12-16 | E-GEOD-42939 | biostudies-arrayexpress
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. Keywords: Disease State Analysis: Animal Model Validation
2009-08-20 | GSE13319 | GEO