Complement Roles Revealed by Immune Gene Profiling in Endometriosis and Endometriosis-Associated Ovarian Cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE57545 | GEO | 2015/01/07
SECONDARY ACCESSION(S): PRJNA247492
REPOSITORIES: GEO
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Project description:Mechanisms of immune dysregulation against established tumors are relatively well understood. Much less is known about the role of immune effectors against cancer precursor lesions. Endometrioid and clear cell ovarian tumors may partly derive from endometriosis, a commonly diagnosed chronic inflammatory disease. We performed here the most comprehensive immune gene expression analysis of pelvic inflammation in endometriosis and endometriosis-associated ovarian cancer (EAOC). RNA was extracted from 120 paraffin tissue blocks comprising of normal endometrium (n=32), benign endometriosis (n=30), atypical endometriosis (n=15) and EAOC (n=43). Serous tumors (n=15) were included as non-endometriosis associated controls. The immune microenvironment was profiled using Nanostring and the nCounter® GX Human Immunology Kit, comprising probes for a total of 511 immune genes. Please note that 3 normal endometrium samples did not pass the array quality filtering and therefore excluded in the data analyses.
2015-01-07 | E-GEOD-57545 | biostudies-arrayexpress
Project description:This study aimed to identify an essential gene in the malignant transformation of endometriosis to clear cell ovarian carcinoma and endometrioid ovarian carcinoma.
2021-04-01 | GSE157153 | GEO
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.
2014-10-01 | E-GEOD-51981 | biostudies-arrayexpress
Project description:Endometriosis is a common disease seen by gynecologists. Clinical features involve pelvic pain and unexplained infertility. Although endometriosis is pathologically characterized by endometrial tissue outside the normal uterine location, endometriosis is otherwise not easily explained. Endometriomas, endometriotic cysts of the ovary, typically cause pain and distortion of pelvic anatomy. To begin to understand the pathogenesis of endometriomas, we carried out transcriptome:microRNAome analysis of endometriomas and eutopic endometrium, using gene expression arrays and next generation small RNA sequencing technology. Keywords: two group comparison Patients undergoing surgery for endometriomas, suspected endometriosis, pelvic pain, abnormal uterine bleeding, pelvic organ prolapse, or uterine leiomyomas were approached for participation. After informed consent, the patients underwent scheduled surgical procedure. Tissues were collected either as cyst wall of endometrioma or endometrial curettage of hysterectomy specimen and placed directly into RNALater (Ambion, Austin, TX) and eventually frozen at -80?C. Samples were designated as endometriomas or non-endometriosis control endometrium based on surgical pathology reports. Total RNA was isolated from frozen tissue. High quality RNA was subjected to Illumina’s Human WG-6 version 2.0 BeadChips (Illumina). . *** This Series represents the transcriptome component of the study. ***
2011-05-09 | E-GEOD-23339 | biostudies-arrayexpress
Project description:Endometriosis is a common disease seen by gynecologists. Clinical features involve pelvic pain and unexplained infertility. Although endometriosis is pathologically characterized by endometrial tissue outside the normal uterine location, endometriosis is otherwise not easily explained. Endometriomas, endometriotic cysts of the ovary, typically cause pain and distortion of pelvic anatomy. To begin to understand the pathogenesis of endometriomas, we carried out transcriptome:microRNAome analysis of endometriomas and eutopic endometrium, using gene expression arrays and next generation small RNA sequencing technology. Keywords: two group comparison
2011-05-09 | GSE23339 | GEO
Project description:Endometriosis is a complex pathological condition in which multiple components are involved in the disease development and clinical outcome. Endometriosis is mainly an inflammatory codition estrogen-dependent, with unknown pathogenesis, that is characterized by dissemination of edometrium tissue in ectopic position (ovary or pelvic peritoneum). Two main theories rise the pathologic onset: the presence of retrograde menstruation and celomic metaplasia in the pelvic peritoneum, that can occur for development defects. Endometriosis is related not only to genetic or immunological changes and to environmental pollution factors, as the endocrine interferents. The disease phenotype results from multiple events (genetics and enviromental), thus it is difficult to find a single gene as causative while is more probable that a gene network/s might involved in the onset and mantainement of the disease state. The peculiarity of endometriosis rely on the tissue speificity manteinance in the ectopic position, where it responds to the hormone stimuli as the tissue in the eutopic position. In order to identify genes potentially involved in growth and mainteinance of the ectopic endometrium, we have profiled ectopic (8 samples) and eutopic endometrium (8 samples) from several affected woman in the proliferative phase. As control we used endometrium from normal health donors in the same phase (6 samples).
2013-11-30 | E-GEOD-25628 | biostudies-arrayexpress
Project description:Endometriosis is associated with increased risk of epithelial ovarian cancers (EOCs). Using data from large endometriosis and EOC genome-wide association meta-analyses we estimate the genetic correlation and evaluate the causal relationship between genetic liability to endometriosis and EOC histotypes, and identify shared susceptibility loci. We estimate a significant genetic correlation (rg) between endometriosis and clear cell (rg=0.71), endometrioid (rg=0.48) and high-grade serous (rg=0.19) ovarian cancer, associations supported by Mendelian randomization analyses. Bivariate meta-analysis identify 28 loci associated with both endometriosis and EOC, including 19 with evidence for a shared underlying association signal. Differences in the shared risk suggest different underlying pathways may contribute to the relationship between endometriosis and the different histotypes. Functional annotation using transcriptomic and epigenomic profiles of relevant tissues/cells highlights several target genes. This comprehensive analysis reveals profound genetic overlap between endometriosis and EOC histotypes with valuable genomic targets for understanding the biological mechanisms linking the diseases.
2022-03-07 | GSE197928 | GEO
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.
2014-10-01 | GSE51981 | GEO
Project description:Endometriosis is a complex pathological condition in which multiple components are involved in the disease development and clinical outcome. Endometriosis is mainly an inflammatory codition estrogen-dependent, with unknown pathogenesis, that is characterized by dissemination of edometrium tissue in ectopic position (ovary or pelvic peritoneum). Two main theories rise the pathologic onset: the presence of retrograde menstruation and celomic metaplasia in the pelvic peritoneum, that can occur for development defects. Endometriosis is related not only to genetic or immunological changes and to environmental pollution factors, as the endocrine interferents. The disease phenotype results from multiple events (genetics and enviromental), thus it is difficult to find a single gene as causative while is more probable that a gene network/s might involved in the onset and mantainement of the disease state. The peculiarity of endometriosis rely on the tissue speificity manteinance in the ectopic position, where it responds to the hormone stimuli as the tissue in the eutopic position.
2013-11-30 | GSE25628 | GEO
Project description:Transcriptome-wide m6A methylome of endometrioid ovarian cancer and ovarian endometriosis
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