Stage-specific miRNA expression profiling during menstrual cycle in endometriosis and non-endometriosis patients
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA644187 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12147775.fastq.gz | Fastqsanger.gz | |||
| SRR12147776.fastq.gz | Fastqsanger.gz | |||
| SRR12147777.fastq.gz | Fastqsanger.gz | |||
| SRR12147778.fastq.gz | Fastqsanger.gz | |||
| SRR12147779.fastq.gz | Fastqsanger.gz |
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Project description:The aim of this research was to determined the plasma miRNA expresion profile in each stage of the endometriosis during menstrual cycle.
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Project description:The objectives of the study: 1. Does the phase of the menstrual cycle alter microRNA (miRNA) plasma profiles in healthy women of reproductive age and in women with endometriosis? 2. Does this alter prospects for development of a miRNA-based diagnostic test for endometriosis? Prospectively recruited asymptomatic control women and women with surgically diagnosed endometriosis (n = 8 in each group) were included. Each patient provided blood samples in the early proliferative, late proliferative and mid luteal phases of the menstrual cycle (n = 47 total plasma samples). The cycle phase was verified by hormonal profile. RNA was extracted from each sample and expression of microRNAs was assessed using TaqMan Low Density Human miRNA arrays.
2013-05-09 | E-GEOD-46735 | biostudies-arrayexpress
Project description:The objectives of the study: 1. Does the phase of the menstrual cycle alter microRNA (miRNA) plasma profiles in healthy women of reproductive age and in women with endometriosis? 2. Does this alter prospects for development of a miRNA-based diagnostic test for endometriosis?
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Project description:Endometriosis is a debilitating gynecological disorder affecting approximately 10% of the female population. Despite its prevalence, robust methods to classify and treat endometriosis remain elusive. Changes throughout the menstrual cycle in tissue size, architecture, cellular composition, and individual cell phenotypes make it extraordinarily challenging to identify markers or cell types associated with uterine pathologies since disease-state alterations in gene and protein expression are convoluted with cycle phase variations. Here, we developed an integrated workflow to generate both proteomic and single-cell RNA-sequencing (scRNA-seq) data sets using tissues and cells isolated from the uteri of control and endometriotic donors. Using a linear mixed effect model (LMM), we identified proteins associated with cycle stage and disease, revealing a set of genes that drive separation across these two biological variables. Further, we analyzed our scRNA-seq data to identify cell types expressing cycle and disease- associated genes identified in our proteomic data. A module scoring approach was used to identify cell types driving the enrichment of certain biological pathways, revealing several pathways of interest across different cell subpopulations. Finally, we identified ligand-receptor pairs including Axl/Tyro3 – Gas6, that may modulate interactions between endometrial macrophages and/or endometrial stromal/epithelial cells. Analysis of these signaling pathways in an independent cohort of endometrial biopsies revealed a significant decrease in Tyro3 expression in patients with endometriosis compared to controls, both transcriptionally and through histological staining. This measured decrease in Tryo3 in patients with disease could serve as a novel diagnostic biomarker or treatment avenue for patients with endometriosis. Taken together, this integrated approach provides a framework for integrating LMMs, proteomic and RNA-seq data to deconvolve the complexities of complex uterine diseases and identify novel genes and pathways underlying endometriosis.
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Project description:The transition of regularly cycling endometrium from the proliferative or Estrogen-dominant phase of the menstrual cycle to the Progesterone-dominant Early and Mid Secretory phases requires wide-spread changes in gene expression that shift the endometrium from a proliferative capacity to a differentiated 'decidual' phenotype in preparation for implantation. This process appears delayed in women with severe endometriosis, suggestive of a progesterone resistant endometrium in this disease. Experiment Overall Design: Endometrial biopsies were obtained from women both with normal endometrial pathologies and no history of endometriosis and from women with laporoscopy proven moderate-severe stage endometriosis. Samples were collected from the Proliferative(PE), Early Secretory (ESE) and Midsecretory (MSE) phases. Samples were then processed for Total RNA isolation and Affymetrix chip hybridization.
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Project description:Alterations in endometrial DNA methylation profile have been proposed as one potential mechanism initiating the development of endometriosis. However, the normal endometrial methylome is influenced by the cyclic hormonal changes and the menstrual cycle phase-dependent epigenetic signature should be considered when studying endometrial disorders. So far, no studies have been performed to evaluate the menstrual cycle influences and endometriosis-specific endometrial methylation pattern at the same time. Therefore, we used Infinium HumanMethylation 450K BeadChip arrays to explore DNA methylation profiles of endometrial tissues from various menstrual cycle phases. Infinium HumanMethylation 450K BeadChip arrays were used to explore DNA methylation profiles of endometrial tissues from various menstrual cycle phases from 24 patients with endometriosis
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Project description:Alterations in endometrial DNA methylation profile have been proposed as one potential mechanism initiating the development of endometriosis. However, the normal endometrial methylome is influenced by the cyclic hormonal changes and the menstrual cycle phase-dependent epigenetic signature should be considered when studying endometrial disorders. So far, no studies have been performed to evaluate the menstrual cycle influences and endometriosis-specific endometrial methylation pattern at the same time. Therefore, we used Infinium HumanMethylation 450K BeadChip arrays to explore DNA methylation profiles of endometrial tissues from various menstrual cycle phases. Infinium HumanMethylation 450K BeadChip arrays were used to explore DNA methylation profiles of endometrial tissues from mid secretory cycle phase from 17 patients without endometriosis
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Project description:This project aims at comparing endometrium from women with and without endometriosis during the secretory phase of menstrual cycle. The present results constitute a first step towards identifying potential diagnosis biomarkers and may provide a better understanding of endometriosis especially the etiology of the disease.
2022-04-01 | PXD012981 | Pride
Project description:Endometriosis, an estrogen-dependent, progesterone-resistant, inflammatory disorder affects 10% of reproductive-age women. It is diagnosed and staged at surgery, resulting in an 11-year latency from symptom onset to diagnosis, underscoring the need for less invasive, less expensive approaches. Since the uterine lining (endometrium) in women with endometriosis has altered molecular profiles, we tested whether molecular classification of this tissue can distinguish and stage disease. We developed classifiers using genomic data from n=148 archived endometrial samples from women with endometriosis or without endometriosis (normal controls or with other common uterine/pelvic pathologies) across the menstrual cycle and evaluated their performance on independent sample sets. Classifiers were trained separately on samples in specific hormonal milieu, using margin tree classification, and accuracies were scored on independent validation samples. Classification of samples from women with endometriosis or no endometriosis involved two binary decisions each based on expression of specific genes. These first distinguished presence or absence of uterine/pelvic pathology and then no endometriosis from endometriosis, with the latter further classified according to severity (minimal/mild or moderate/severe). Best performing classifiers identified endometriosis with 90-100% accuracy, were cycle phase-specific or independent, and utilized relatively few genes to determine disease and severity. Differential gene expression and pathway analyses revealed immune activation, altered steroid and thyroid hormone signaling/metabolism and growth factor signaling in endometrium of women with endometriosis. Similar findings were observed with other disorders versus controls. Thus, classifier analysis of genomic data from endometrium can detect and stage pelvic endometriosis with high accuracy, dependent or independent of hormonal milieu. We propose that limited classifier candidate-genes are of high value in developing diagnostics and identifying therapeutic targets. Discovery of endometrial molecular differences in the presence of endometriosis and other uterine/pelvic pathologies raises the broader biological question of their impact on the steroid hormone response and normal functions of this tissue. We analyzed endometrial samples from n=148 women without or with endometriosis and/or other uterine/pelvic pathologies, using whole genome microarrays.
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Project description:Alterations in endometrial DNA methylation profile have been proposed as one potential mechanism initiating the development of endometriosis. However, the normal endometrial methylome is influenced by the cyclic hormonal changes and the menstrual cycle phase-dependent epigenetic signature should be considered when studying endometrial disorders. So far, no studies have been performed to evaluate the menstrual cycle influences and endometriosis-specific endometrial methylation pattern at the same time. Therefore, we used Infinium HumanMethylation 450K BeadChip arrays to explore DNA methylation profiles of endometrial tissues from various menstrual cycle phases.
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