Dataset Information

MicroRNA 21: response to hormonal therapies and regulatory function in leiomyoma, transformed leiomyoma and leiomyosarcoma cells.

ABSTRACT: Aberrant expression of microRNAs (miRNAs), including miR-21, and alteration of their target genes stability have been associated with cellular transformation and tumorigenesis. We investigated the expression, regulation and function of miR-21 in leiomyomas which develop from myometrial cellular transformation. The results indicated that miR-21 is over-expressed in leiomyomas with specific elevation during the secretory phase of the menstrual cycle and in women who received Depo-Provera and oral contraceptives, but reduced due to GnRHa therapy (P < 0.05). Bioinformatic analysis of microarray gene expression profiles previously obtained from the above cohorts, and myometrial smooth muscle cells (MSMC) and leiomyoma smooth muscle cells (LSMC) treated with GnRHa, transforming growth factor (TGF)-beta and TGF-beta receptor type II (TGF-betaRII) antisense oligomer, indicated that a number of miR-21-predicted target genes were co-expressed and differentially regulated in these cohorts. Gain- and loss-of-function of miR-21 in MSMC, LSMC, transformed LSMC and leiomyosarcoma cell line (SKLM-S1) resulted in differential expression of many genes, including some of the miR-21-predicted/validated target genes, PTEN, PDCD4 and E2F1, and TGF-betaRII, in a cell-specific manner. Gain-of miR-21 function in MSMC and LSMC reduced TGF-beta-induced expression of fibromodulin and TGF-beta-induced factor (P < 0.05), and moderately altered the rate of cell growth and caspase-3/7 activity in these cells. We concluded that miR-21 is aberrantly expressed and hormonally regulated in leiomyomas where, through functional interaction with ovarian steroids and the TGF-beta signaling pathway, either directly or indirectly regulates a number of genes whose products are critical in leiomyoma growth and regression as well as their potential cellular transformation.

SUBMITTER: Pan Q

PROVIDER: S-EPMC2816170 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature

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microRNA 21: response to hormonal therapies and regulatory function in leiomyoma, transformed leiomyoma and leiomyosarcoma cells.

Pan Qun Q Luo Xiaoping X Chegini Nasser N

Molecular human reproduction 20091111 3

Aberrant expression of microRNAs (miRNAs), including miR-21, and alteration of their target genes stability have been associated with cellular transformation and tumorigenesis. We investigated the expression, regulation and function of miR-21 in leiomyomas which develop from myometrial cellular transformation. The results indicated that miR-21 is over-expressed in leiomyomas with specific elevation during the secretory phase of the menstrual cycle and in women who received Depo-Provera and oral ...[more]

PMID: 19906824

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Project description:Rationale & objectivePrevious studies have suggested that microRNA-21 (miR-21) plays an important role in kidney fibrosis. We examined the relationship between intrarenal miR-21 level and rate of kidney function loss in immunoglobulin A nephropathy (IgAN).Study designProspective cohort study.Setting & participants40 patients with IgAN and 10 with hypertensive nephrosclerosis as controls.PredictorsmiR-21 levels in kidney biopsy specimen and urinary sediment, quantified as ratio to the housekeeping gene.OutcomesKidney event-free survival and rate of kidney function decline.Analytic approachTime-to-event and correlation analysis.ResultsThe IgAN group had significantly higher intrarenal miR-21 expression compared with the hypertensive nephrosclerosis group (1.71 [IQR, 0.99-2.77] vs 0.31 [IQR, 0.25-1.32]; P < 0.0001), but urinary miR-21 levels were similar. Intrarenal miR-21 expression had significant but modest correlation with severity of glomerulosclerosis (r = 0.293; P = 0.05) and tubulointerstitial fibrosis (r = 0.341; P = 0.03). Patients with high intrarenal miR-21 expression had significantly higher risk for developing kidney end points compared with those with low expression (log-rank test, P = 0.017). Univariate Cox analysis showed that intrarenal miR-21 expression significantly predicted the development of kidney end points (unadjusted HR, 1.586; 95% CI, 1.179-2.134; P = 0.002). However, the result was just short of statistical significance after adjusting for the severity of histologic damage (P = 0.06). There was also a significant correlation between intrarenal miR-21 expression and the slope of kidney function decline by univariate analysis (r = -0.399; P = 0.02).LimitationsSmall sample size; uncertain cellular origin of miR-21.ConclusionsWe found that intrarenal miR-21 expression is increased in patients with IgAN, modestly correlated with the severity of histologic damage, and predictive of subsequent kidney function loss.

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.

Project description:ObjectiveUterine leiomyosarcoma (ULMS) is the most common subtype of uterine sarcoma and is difficult to discern from uterine leiomyoma (ULM) preoperatively. The aim of the study was to determine the potential and significance of immune-related diagnostic biomarkers in distinguishing ULMS from ULM.MethodsTwo public gene expression profiles (GSE36610 and GSE64763) from the GEO datasets containing ULMS and ULM samples were downloaded. Differentially expressed genes (DEGs) were selected and determined among 37 ULMS and 25 ULM control samples. The DEGs were used for Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Disease Ontology (DO) enrichment analyses as well as gene set enrichment analysis (GSEA). The candidate biomarkers were identified by least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) analyses. The receiver operating characteristic curve (ROC) was applied to evaluate diagnostic ability. For further confirmation, the biomarker expression levels and diagnostic value in ULMS were verified in the GSE9511 and GSE68295 datasets (12 ULMS and 10 ULM), and validated by immunohistochemistry (IHC). The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in ULMS.ResultIn total, 55 DEGs were recognized via GO analysis, and KEGG analyses revealed that the DEGs were enriched in nuclear division, and cell cycle. The recognized DEGs were primarily implicated in non-small cell lung carcinoma and breast carcinoma. Gene sets related to the cell cycle and DNA replication were activated in ULMS. DPP6 and MFAP5 were distinguished as diagnostic biomarkers of ULMS (AUC = 0.957, AUC = 0.899, respectively), and they were verified in the GSE9511 and GSE68295 datasets (AUC = 0.983, AUC = 0.942, respectively). The low expression of DPP6 and MFAP5 were associated with ULMS. In addition, the analysis of the immune microenvironment indicated that resting mast cells were positively correlated with DPP6 and MFAP5 expression and that eosinophils and M0 macrophages were negatively correlated with DPP6 expression (P<0.05).ConclusionThese findings indicated that DPP6 and MFAP5 are diagnostic biomarkers of ULMS, thereby offering a novel perspective for future studies on the occurrence, function and molecular mechanisms of ULMS.

Dataset Information

MicroRNA 21: response to hormonal therapies and regulatory function in leiomyoma, transformed leiomyoma and leiomyosarcoma cells.

Publications

microRNA 21: response to hormonal therapies and regulatory function in leiomyoma, transformed leiomyoma and leiomyosarcoma cells.

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