Identification of driver genes in uterine leiomyosarcoma: whole-genome sequencing (Complete Genomics)
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Complete Genomics
ORGANISM(S): Homo sapiens
SUBMITTER: Bram Boeckx
PROVIDER: E-MTAB-5902 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:Whole genome sequencing by Complete Genomics was performed on two leiomyosarcoma samples and their matched germline
2018-07-02 | E-MTAB-5764 | biostudies-arrayexpress
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2018-07-02 | E-MTAB-5773 | biostudies-arrayexpress
Project description:Low coverage whole-genome sequencing have been performed on uterine leiomyosarcoma to uncovered novel potential driver genes and recurrently affected pathways.
2018-07-02 | E-MTAB-5763 | biostudies-arrayexpress
Project description:RNA-sequencing was carried out on human leiomyosarcoma tissue. To uncover novel potential driver genes and recurrently affected pathways.
2018-07-02 | E-MTAB-5762 | 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:Leiomyosarcoma (LMS) is a malignant neoplasm of smooth muscle and is an aggressive soft tissue tumor, have complex genetic abnormalities and could be defined as three molecular subtypes. Since that the molecular heterogeneity of LMS, the pathogenesis analysis per subtype will be highly necessary and helpful to understand the etiology of this more common sarcoma. Within this study, we collected four Myometrium, three Leiomyoma, three LMS cell lines and 99 LMSs (GSE45510), performed the system-wide gene expression profiling by 3'end RNA Sequencing, and found that there are significant different molecular pathways along the pathogenesis for those three molecular subtypes.
2015-05-19 | E-GEOD-54511 | biostudies-arrayexpress
Project description:Background: Undifferentiated pleomorphic sarcoma (UPS), used to be called malignant fibrous histiocytoma (MFH), is a malignant soft tissue tumor of uncertain origin, and is characterized by morphology. UPS often share similar morphological characters with other sarcomas, especially Leiomyosarcoma. Leiomyosarcoma (LMS) is another malignant soft tissue sarcoma with complex genomic abnormalities, origin from smooth muscle. As a result, development of gene signature and/or biomarkers distinguishing UPS and LMS will definitely help the pathologist to precisely diagnose those patients. However, in the past, UPS was reported to be indistinguishable with LMS by genomic profiles. Methods and Results: In this study, 3’ end RNA Sequencing (3SEQ) was used to expression profile 6 UPS and 99 LMS cases. Overall, UPS was undistinguished with LMS by 3SEQ data, however, when we stratified LMS into three subtypes, UPS was shown to share similar expression pattern with Subtype II LMS, but had distinct molecular expression patterns with Subtype I and Subtype III LMS. Additional Immunohistochemistry staining by using LMS Subtype I and Subtype II markers validated that UPSs were positive for Subtype II marker ARL4C, but negative for Subtype I marker LMOD1. Furthermore, CD4 was shown to be significantly more highly expressed in UPS than LMS in both mRNA and protein levels. Conclusion: This study first reported that UPS shared similar gene expression pattern with subtype II LMS and UPS recapitulated the expression profiles of subtype II LMS. In this study, 3’ end RNA Sequencing (3SEQ) was used to expression profile 6 UPS and 99 LMS cases. In order to explore the molecular differences between UPS and LMS, We analyzed the expression data by SAMseq to identify the genes which were significantly differently expressed between UPS and LMS, between UPS and each LMS subtype.
2015-05-19 | E-GEOD-53844 | 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:Unexpected malignant tumors are a rare finding after surgery for symptomatic leiomyomas but there is little doubt that morcellation of these lesions is associated with a higher risk of iatrogenic peritoneal spread compared to women having surgery without morcellation. Thus, the FDA has issued a warning against the use of power morcellation in the majority of women undergoing myomectomy or hysterectomy for treatment of fibroids. We present a case report of 50 year old patient with intervertebral disc degeneration and multiple uterine fibroids decided to have laparoscopic supracervical hysterectomy. 28 months later the patient cystic adnexal mass removed by laparotomy and histologically, classified as leiomyosarcoma (sample H_12814-15). 19 months after this latter surgery MRI revealed a 10 x 8 x 6 cm abdominal mass attached to the liver and numerous other nodules attached to the abdominal wall. We investigated genomic profiles of four samples obtained from initial surgery and the malignant tumor that appeared 16 month later by molecular inversion probe (MIP) array hybridization. DNA was extracted from FFPE Tissue Samples using Covaris adaptive focused acoutics (AFATM) and truXTRACTM FFPE DNA kit and subjected to CGH analysis using the Affymetrix OncoScan platform according to the manufacturers protocol.
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Project description:Global gene expression analysis of inflammatory leiomyosarcoma (ILMS) and conventional leiomyosarcoma (LMS).
2013-05-22 | GSE37992 | GEO