Dataset Information

Immune-inflammation gene signatures in endometriosis patients.

ABSTRACT: To determine if the molecular profiles of endometriotic lesions contain informative measures of inflammation and immune dysfunction that may contribute to better understanding of the interplay between immune dysfunction and inflammation and their contribution to endometriosis pathogenesis.Immune and inflammation transcriptomic analysis with the use of the Nanostring nCounter GX Human Immunology V2 platform (579 human immune and inflammation-related genes and 15 housekeeping genes).Academic university and teaching hospital.None.Stage III-IV endometriosis patients with infertility (n = 8) and fertile disease-free control women undergoing tubal ligation (n = 8). Menstrual stage was matched to secretory phase in all participants.Immune and inflammation transcriptomics quantification from ectopic endometriotic lesions and matched eutopic endometrium from patients. Endometria of fertile women served as control subjects.Our results displayed endometriotic lesions as molecularly distinct entities compared with eutopic endometrium and endometrium of control samples; 396 out of 579 screened immune and inflammation-related genes were significantly different in ectopic tissues compared with control endometrium. Most importantly, eutopic endometrium of the patients displayed a unique molecular profile compared with the control endometrium (91/579 genes were significantly different), particularly of genes involved in regulation of cell apoptosis and decidualization.We characterize differential expression of immune-inflammation genes in endometriosis patients, and show molecular distinction of eutopic endometrium of patients compared with control fertile women.

SUBMITTER: Ahn SH

PROVIDER: S-EPMC5683404 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Immune-inflammation gene signatures in endometriosis patients.

Ahn Soo Hyun SH Khalaj Kasra K Young Steven L SL Lessey Bruce A BA Koti Madhuri M Tayade Chandrakant C

Fertility and sterility 20160727 6

<h4>Objective</h4>To determine if the molecular profiles of endometriotic lesions contain informative measures of inflammation and immune dysfunction that may contribute to better understanding of the interplay between immune dysfunction and inflammation and their contribution to endometriosis pathogenesis.<h4>Design</h4>Immune and inflammation transcriptomic analysis with the use of the Nanostring nCounter GX Human Immunology V2 platform (579 human immune and inflammation-related genes and 15 h ...[more]

PMID: 27475412

Similar Datasets

Project description:Aims:To identify the common and specific molecular mechanisms of three well-defined subtypes of endometriosis (EMs): ovarian endometriosis (OE), peritoneal endometriosis (PE), and deep infiltrating endometriosis (DIE). Methods:Four microarray datasets: GSE7305 and GSE7307 for OE, E-MTAB-694 for PE, and GSE25628 for DIE were downloaded from public databases and conducted to compare ectopic lesions (EC) with eutopic endometrium (EU) from EMs patients. Differentially expressed genes (DEGs) identified by limma package were divided into two parts: common DEGs among three subtypes and specific DEGs in each subtype, both of which were subsequently performed with the Kyoto Encyclopedia of Genes (KEGG) pathway enrichment analysis. The protein-protein interaction (PPI) network was constructed by common DEGs and five hub genes were screened out from the PPI network. Besides, these five hub genes together with selected interested pathway-related genes were further validated in an independent OE RNA-sequencing dataset GSE105764. Results:A total of 54 EC samples from three EMs subtypes (OE, PE, DIE) and 58 EU samples were analyzed, from which we obtained 148 common DEGs among three subtypes, and 729 specific DEGs in OE, 777 specific DEGs in PE and 36 specific DEGs in DIE. The most enriched pathway of 148 shared DEGs was arachidonic acid (AA) metabolism, in which most genes were up-regulated in EC, indicating inflammation was the most common pathogenesis of three subtypes. Besides, five hub genes AURKB, RRM2, DTL, CCNB1, CCNB2 identified from the PPI network constructed by 148 shared DEGs were all associated with cell cycle and mitosis, and down-regulated in EC, suggesting a slow and controlled proliferation in ectopic lesions. The KEGG pathway analysis of specific DEGs in each subtype revealed that abnormal ovarian steroidogenesis was a prominent feature in OE; OE and DIE seems to be at more risk of malignant development since both of their specific DEGs were enriched in the pathways in cancer, though enriched genes were different, while PE tended to be more associated with dysregulated peritoneal immune and inflammatory microenvironment. Conclusion:By integrated bioinformatic analysis, we explored common and specific molecular signatures among different subtypes of endometriosis: activated arachidonic acid (AA) metabolism-related inflammatory process and a slow and controlled proliferation in ectopic lesions were common features in OE, PE and DIE; OE and DIE seemed to be at more risk of malignant development while PE tended to be more associated with dysregulated peritoneal immune and inflammatory microenvironment, all of which could deepen our perception of endometriosis.

Project description:BackgroundPancreatic cancer is one of the most common malignant tumors of the digestive tract, and it has a poor prognosis. Traditional methods are not effective to accurately assess the prognosis of patients with pancreatic cancer. Immunotherapy is a new promising approach for the treatment of pancreatic cancer; however, some patients do not respond well to immunotherapy, which may be related to tumor microenvironment regulation. In this study, we use gene expression database to mine important immune genes and establish a prognostic prediction model for pancreatic cancer patients. We hope to provide a feasible method to evaluate the prognosis of pancreatic cancer and provide valuable targets for pancreatic cancer immunotherapy.ResultsWe used univariate COX proportional hazard regression analysis, the least absolute shrinkage and selection operator, and multivariate COX regression analysis to screen 8 genes related to prognosis from the 314 immune-related genes, and used them to construct a new clinical prediction model in the TCGA pancreatic cancer cohort. Subsequently, we evaluated the prognostic value of the model. The Kaplan-Meier cumulative curve showed that patients with low risk scores survived significantly longer than patients with high risk scores. The area under the ROC curve (AUC value) of the risk score was 0.755. The univariate COX analysis showed that the risk score was significantly related to overall survival (HR 1.406, 95% CI 1.237-1.598, P?<?0.001), and multivariate analysis showed that the risk score was an independent prognostic factor (HR 1.400, 95% CI 1.287-1.522, P?<?0.001). Correlation analysis found that immune genes are closely related to tumor immune microenvironment.ConclusionsBased on the TCGA-PAAD cohort, we identified immune-related markers with independent prognostic significance, validated, and analyzed their biological functions, to provide a feasible method for the prognosis of pancreatic cancer and provide potentially valuable targets for pancreatic cancer immunotherapy.

Project description:BackgroundEndometriosis (EMS) occurs when normal uterine tissue grows outside the uterus and causes chronic pelvic pain and infertility. Endometriosis-associated infertility is thought to be caused by unknown mechanisms. In this study, using necroptosis-related genes, we developed and validated multigene joint signatures to diagnose EMS and explored their biological roles.MethodsWe downloaded two databases (GSE7305 and GSE1169) from the Gene Expression Omnibus (GEO) database and 630 necroptosis-related genes from the GeneCards and GSEA databases. The limma package in Rsoftware was used to identify differentially expressed genes (DEGs). We interleaved common differentially expressed genes (co-DEGs) and necroptosis-related genes (NRDEGs) in the endometriosis dataset. The DEGs functions were reflected by gene ontology analysis (GO), pathway enrichment analysis, and gene set enrichment analysis (GSEA). We used CIBERSORT to analyze the immune microenvironment differences between EMS patients and controls. Furthermore, a correlation was found between necroptosis-related differentially expressed genes and infiltrating immune cells to better understand the molecular immune mechanism.ResultsCompared with the control group, this study revealed that 10 NRDEGs were identified in EMS. There were two types of immune cell infiltration abundance (activated NK cells and M2 macrophages) in these two datasets, and the correlation between different groups of samples was statistically significant (P < 0.05). MYO6 consistently correlated with activated NK cells in the two datasets. HOOK1 consistently demonstrated a high correlation with M2 Macrophages in two datasets. The immunohistochemical result indicated that the protein levels of MYO6 and HOOK1 were increased in patients with endometriosis, further suggesting that MYO6 and HOOK1 can be used as potential biomarkers for endometriosis.ConclusionsWe identified ten necroptosis-related genes in EMS and assessed their relationship with the immune microenvironment. MYO6 and HOOK1 may serve as novel biomarkers and treatment targets in the future.

Project description:The immune system is crucial in regulating colorectal cancer (CRC) tumorigenesis. Identification of immune-related transcriptomic signatures derived from the peripheral blood of patients with CRC would provide insights into CRC pathogenesis, and suggest novel clues to potential immunotherapy strategies for the disease. The present study collected blood samples from 59 patients with CRC and 62 healthy control patients and performed whole blood gene expression profiling using microarray hybridization. Immune-related gene expression signatures for CRC were identified from immune gene datasets, and an algorithmic predictive model was constructed for distinguishing CRC from controls. Model performance was characterized using an area under the receiver operating characteristic curve (ROC AUC). Functional categories for CRC-specific gene expression signatures were determined using gene set enrichment analyses. A Kaplan-Meier plotter survival analysis was also performed for CRC-specific immune genes in order to characterize the association between gene expression and CRC prognosis. The present study identified five CRC-specific immune genes [protein phosphatase 3 regulatory subunit Bα (PPP3R1), amyloid β precursor protein, cathepsin H, proteasome activator subunit 4 and DEAD-Box Helicase 3 X-Linked]. A predictive model based on this five-gene panel showed good discriminatory power (independent test set sensitivity, 83.3%; specificity, 94.7%, accuracy, 89.2%; ROC AUC, 0.96). The candidate genes were involved in pathways associated with 'adaptive immune responses', 'innate immune responses' and 'cytokine signaling'. The survival analysis found that a high level of PPP3R1 expression was associated with a poor CRC prognosis. The present study identified five CRC-specific immune genes that were potential diagnostic biomarkers for CRC. The biological function analysis indicated a close association between CRC pathogenesis and the immune system, and may reveal more information about the immunogenic and pathogenic mechanisms driving CRC in the future. Overall, the association between PPP3R1 expression and survival of patients with CRC revealed potential new targets for CRC immunotherapy.

Project description:Endometriosis is an oestrogen-dependent chronic inflammatory process with primary symptoms including dysmenorrhea, chronic pelvic pain, and infertility. The immune environment of the endometrium is essential for successful embryo implantation and ongoing pregnancy. In this study, we assessed the composition, density, and distribution of infiltrating immune cells in the endometria of women with endometriosis. Gene expression profiles of endometrial samples were downloaded from the Gene Expression Omnibus (GEO) database. We found that the TNF signalling pathway, the IL-17 signalling pathway, and the MAPK signalling pathway were significantly enriched in the eutopic endometria of women with endometriosis. The fractions and proportion of infiltrating immune cells were estimated by the CIBERSORT, MCP-counter, and ImmuCellAI methods. We found that the proportions of CD8+ T cells, activated NK cells, and follicular helper T cells were significantly higher in the endometria of women with endometriosis than in the endometria of normal controls, while the proportions of M2 macrophages and resting mast cells were significantly lower in the eutopic endometria. In GSE120103 (n = 36), we found that elevated CD8+ T cells in endometriosis increased the risk of infertility (P = 0.0019). The area under the receiver operating characteristic (ROC) curve (AUC) of CD8+ T cells to distinguish fertile and infertile endometriosis was 0.914. In clinical samples (n = 40), we found that the proportions of CD8+ T cells and CD56+ NK cells were significantly higher in the eutopic endometria of women with endometriosis than in the endometria of normal controls, while the proportion of CD163+ macrophages were lower in the eutopic endometria. The AUCs of CD8+ T cells and CD163+ macrophages were 0.727 and 0.833, respectively, which indicated that CD8 and CD163 were potential diagnostic markers for endometriosis. In conclusion, our results demonstrated that increased CD8+ T cells and CD56+ NK cells and decreased CD163+ macrophages within the eutopic endometria of women with endometriosis reveal a proinflammatory feature in the endometrial immune environment and that elevated CD8+ T cells increase the risk of infertility in women with the disease.

Dataset Information

Immune-inflammation gene signatures in endometriosis patients.

Publications

Immune-inflammation gene signatures in endometriosis patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets