SNAP25/syntaxin4/VAMP2/Munc18-1 Complexes in Spinal Dorsal Horn Contributed to Inflammatory Pain

Screening and identification of key biomarkers associated with endometriosis using bioinformatics and next-generation sequencing data analysis

Background

Endometriosis is a common cause of endometrial-type mucosa outside the uterine cavity with symptoms such as painful periods, chronic pelvic pain, pain with intercourse and infertility. However, the early diagnosis of endometriosis is still restricted. The purpose of this investigation is to identify and validate the key biomarkers of endometriosis.

Methods

Next-generation sequencing dataset GSE243039 was obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) between endometriosis and normal control samples were identified. After screening of DEGs, gene ontology (GO) and REACTOME pathway enrichment analyses were performed. Furthermore, a protein–protein interaction (PPI) network was constructed and modules were analyzed using the Human Integrated Protein–Protein Interaction rEference database and Cytoscape software, and hub genes were identified. Subsequently, a network between miRNAs and hub genes, and network between TFs and hub genes were constructed using the miRNet and NetworkAnalyst tool, and possible key miRNAs and TFs were predicted. Finally, receiver operating characteristic curve analysis was used to validate the hub genes.

Results

A total of 958 DEGs, including 479 upregulated genes and 479 downregulated genes, were screened between endometriosis and normal control samples. GO and REACTOME pathway enrichment analyses of the 958 DEGs showed that they were mainly involved in multicellular organismal process, developmental process, signaling by GPCR and muscle contraction. Further analysis of the PPI network and modules identified 10 hub genes, including vcam1, snca, prkcb, adrb2, foxq1, mdfi, actbl2, prkd1, dapk1 and actc1. Possible target miRNAs, including hsa-mir-3143 and hsa-mir-2110, and target TFs, including tcf3 (transcription factor 3) and clock (clock circadian regulator), were predicted by constructing a miRNA-hub gene regulatory network and TF-hub gene regulatory network.

Conclusions

This investigation used bioinformatics techniques to explore the potential and novel biomarkers. These biomarkers might provide new ideas and methods for the early diagnosis, treatment and monitoring of endometriosis.

Prognostic signature construction of energy metabolism-related genes in pancreatic cancer

Pancreatic cancer is the 7th leading cause of cancer death worldwide, and its incidence and mortality rate have been on the rise in recent years in Western developed countries. The specificity of the disease and the lack of appropriate treatments have resulted in a 5-year overall survival rate of only 9%. In this study, we conducted a study based on the TCGA database and GEO database and analyzed using the energy metabolism gene set to establish a prognostic model with the least absolute shrinkage and selection operator to identify 7-genes prognostic signature, and the gene expression was verified by Real-time PCR. The model was validated using a risk score calculation, and the OS rates of the 7 genes were analyzed using one-way Cox regression. The prognostic relationship between vesicle-associated membrane protein 2 (VAMP2) and pancreatic cancer patients was analyzed by OS and progression-free survival, and the prognosis was found to be significantly worse in the high-expression group. A Nomogram showed that VAMP2 was an independent prognostic factor in pancreatic cancer. Gene set enrichment analysis showed that VAMP2 upregulation was enriched in pathways associated with immune response and that VAMP2 downregulation was enriched in metabolism-related pathways. The association of VAMP2 with immune cell infiltration was analyzed for the enrichment results, and VAMP2 was found to be positively associated with all 6 immune cells. The results of this study suggest that VAMP2 is an independent prognostic factor associated with energy metabolism in pancreatic cancer and may be involved in the immune response.

Cooperation of membrane-translocated syntaxin4 and basement membrane for dynamic mammary epithelial morphogenesis

Mammary epithelia undergo dramatic morphogenesis after puberty. During pregnancy, luminal epithelial cells in ductal trees are arranged to form well-polarized cystic structures surrounded by a myoepithelial cell layer, an active supplier of the basement membrane (BM). Here, we identified a novel regulatory mechanism involved in this process by using a reconstituted BM-based three-dimensional culture and aggregates of a model mouse cell line, EpH4, that had either been manipulated for inducible expression of the t-SNARE protein syntaxin4 in intact or signal peptide-connected forms, or that were genetically deficient in syntaxin4. We found that cells extruded syntaxin4 upon stimulation with the lactogenic hormone prolactin, which in turn accelerated the turnover of E-cadherin. In response to extracellular expression of syntaxin4, cell populations that were less affected by the BM actively migrated and integrated into the cell layer facing the BM. Concurrently, the BM-facing cells, which were simultaneously stimulated with syntaxin4 and BM, acquired unique epithelial characteristics to undergo dramatic cellular arrangement for cyst formation. These results highlight the importance of the concerted action of extracellular syntaxin4 extruded in response to the lactogenic hormone and BM components in epithelial morphogenesis.

STXBP1 encephalopathies: Clinical spectrum, disease mechanisms, and therapeutic strategies

Mutations in Munc18-1/STXBP1 (syntaxin-binding protein 1) are linked to various severe early epileptic encephalopathies and neurodevelopmental disorders. Heterozygous mutations in the STXBP1 gene include missense, nonsense, frameshift, and splice site mutations, as well as intragenic deletions and duplications and whole-gene deletions. No genotype-phenotype correlation has been identified so far, and patients are treated by anti-epileptic drugs because of the lack of a specific disease-modifying therapy. The molecular disease mechanisms underlying STXBP1-linked disorders are yet to be fully understood, but both haploinsufficiency and dominant-negative mechanisms have been proposed. This review focuses on the current understanding of the phenotypic spectrum of STXBP1-linked disorders, as well as discusses disease mechanisms in the context of the numerous pathways in which STXBP1 functions in the brain. We additionally evaluate the available animal models to study these disorders and highlight potential therapeutic approaches for treating these devastating diseases.