Dataset Information

Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis.

ABSTRACT: Endometriosis has been associated with a high risk of infertility. However, the underlying molecular mechanism of infertility in endometriosis remains poorly understood. In our study, we aimed to discover topologically important genes related to infertility in endometriosis, based on the structure network mining. We used microarray data from the Gene Expression Omnibus (GEO) database to construct a weighted gene co-expression network for fertile and infertile women with endometriosis and to identify gene modules highly correlated with clinical features of infertility in endometriosis. Additionally, the protein-protein interaction network analysis was used to identify the potential 20 hub messenger RNAs (mRNAs) while the network topological analysis was used to identify nine candidate long non-coding RNAs (lncRNAs). Functional annotations of clinically significant modules and lncRNAs revealed that hub genes might be involved in infertility in endometriosis by regulating G protein-coupled receptor signaling (GPCR) activity. Gene Set Enrichment Analysis showed that the phospholipase C-activating GPCR signaling pathway is correlated with infertility in patients with endometriosis. Taken together, our analysis has identified 29 hub genes which might lead to infertility in endometriosis through the regulation of the GPCR network.

SUBMITTER: Wu J

PROVIDER: S-EPMC7887323 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis.

Wu Jingni J Xia Xiaomeng X Hu Ye Y Fang Xiaoling X Orsulic Sandra S

Frontiers in genetics 20210203

Endometriosis has been associated with a high risk of infertility. However, the underlying molecular mechanism of infertility in endometriosis remains poorly understood. In our study, we aimed to discover topologically important genes related to infertility in endometriosis, based on the structure network mining. We used microarray data from the Gene Expression Omnibus (GEO) database to construct a weighted gene co-expression network for fertile and infertile women with endometriosis and to iden ...[more]

PMID: 33613630

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Project description:Laryngeal squamous cell carcinoma (LSCC) is the most common malignant tumor in the head and neck, and can seriously affect the daily life of patients. To study the mechanisms of LSCC, the microarray of GSE51958 was analyzed in the present study. GSE51958 was downloaded from Gene Expression Omnibus, and included a collection of LSCC tissue samples and matched adjacent non-cancerous tissue samples from 10 patients. Differentially-expressed genes (DEGs) were identified using limma package. Next, a weighted co-expression network was constructed for the DEGs by WGCNA package in R. Modules of the weighted co-expression network were obtained through constructing a hierarchical clustering tree using the hybrid dynamic shear tree method. Using the clusterProfiler package, the potential functions of DEGs in the modules correlated with LSCC were predicted by pathway enrichment analysis. In total, 959 DEGs were screened from the LSCC samples compared with the adjacent non-cancerous samples, including 553 upregulated and 406 downregulated genes. The appointed black, brown, gray, pink and yellow modules were screened for the DEGs in the weighted co-expression network. For the DEGs in the brown and yellow modules, the enriched pathways were cytokine-cytokine receptor interaction and metabolic pathways, respectively. The DEGs in the pink module were involved in the majority of pathways. With high connectivity degrees in the pink module, TPX2, microtubule-associated (TPX2; degree, 25), minichromosome maintenance complex component 2 (MCM2; degree, 25), ubiquitin-like with PHD and ring finger domains 1 (UHRF1; degree, 22), cyclin-dependent kinase 2 (CDK2; degree, 20) and protein regulator of cytokinesis 1 (PRC1; degree, 20) may be involved in LSCC. Overall, In conclusion, from the integrated bioinformatics analysis of genes that may be associated with LSCC, 959 DEGs were obtained from LSCC samples compared with adjacent non-cancerous samples, and TPX2, MCM2, UHRF1, CDK2 and PRC1 were found to hold a possible association with the disease.

Project description:Background: The tumor microenvironment (TME) of human glioblastoma (GBM) exhibits considerable immune cell infiltration, and such cell types have been shown to be widely involved in the development of GBM. Here, weighted correlation network analysis (WGCNA) was performed on publicly available datasets to identify immune-related molecules that may contribute to the progression of GBM and thus be exploited as potential therapeutic targets. Methods: WGCNA was used to identify highly correlated gene clusters in Chinese Glioma Genome Atlas glioma dataset. Immune-related genes in significant modules were subsequently validated in the Cancer Genome Atlas (TCGA) and Rembrandt databases, and impact on GBM development was examined in migration and vascular mimicry assays in vitro and in an orthotopic xenograft model (GL261 luciferase-GFP cells) in mice. Results: WGCNA yielded 14 significant modules, one of which (black) contained genes involved in immune response and extracellular matrix formation. The intersection of these genes with a GO immune-related gene set yielded 47 immune-related genes, five of which exhibited increased expression and association with worse prognosis in GBM. One of these genes, TREM1, was highly expressed in areas of pseudopalisading cells around necrosis and associated with other proteins induced in angiogenesis/hypoxia. In macrophages induced from THP1 cells, TREM1 expression levels were increased under hypoxic conditions and associated with markers of macrophage M2 polarization. TREM1 siRNA knockdown in induced macrophages reduced their ability to promote migration and vascular mimicry in GBM cells in vitro, and treatment of mice with LP-17 peptide, which blocks TREM1, inhibited growth of GL261 orthotopic xenografts. Finally, blocking the cytokine receptor for CSF1 in induced macrophages also impeded their potential to promote tumor migration and vascular mimicry in GBM cells. Conclusions: Our results demonstrated that TREM1 could be used as a novel immunotherapy target for glioma patients.

Dataset Information

Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis.

Publications

Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis.

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