Background: Glutathione peroxidase-1 (GPX1) is a member of the GPX family, which considered an enzyme that interacts with oxidative stress. GPX1 differential expression is closely correlated with carcinogenesis and disease progression. In this study, we used bioinformatics analysis to investigate GPX1 expression level and explore the prognostic information in different human cancers. Methods: Expression was analyzed via the Oncomine database and Gene Expression Profiling InteractiveAnalysis tool, and potential prognostic analysis was evaluated using the UALCAN, GEPIA, and DriverDBv3 databases. Then, the UALCAN database was used to find the promoter methylation of GPX1 in defied cancer types. While GPX1 related functional networks were found within the GeneMANIA interactive tool and Cytoscape software. Moreover, Metascape online website was used to analyze Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways.Results: We found that GPX1 was commonly overexpressed in most human cancers. High expression of GPX1 could lead to poor outcomes in Brain Lower Grade Glioma, while GPX1 over expression was correlated with better prognosis in Kidney renal papillary cell carcinoma (KIPP). High GPX1 expression was marginally associated with poor prognosis in acute myeloid leukemia (AML). Gene regulation network suggested that GPX1 mainly involved in pathways including the glutathione metabolism, ferroptosis, TP53 regulates metabolic genes, reactive oxygen species (ROS) metabolic process, and several other signaling pathways.Conclusions: Our findings revealed that GPX1 showed significant expression differences among cancers and served as a prognostic biomarker for defined cancer types. The data mining effectively revealed useful information about GPX1 expression, prognostic values, and potential functional networks in cancers, thus providing researchers with an available way to further explore the mechanism underlying carcinogenesis of genes of interest in different cancers.
The continued expand of the coronavirus disease 19 (COVID-19) pandemic, confinement measures and an urgent change in the education of nursing students from traditional education to distance learning throughout the country affect the mental health of university students. This study analyzed state-trait anxiety levels of nursing students because of e-Learning during two periods of the COVID-19 confinement. A mixed follow-up study was used, which evaluates the same cohort cross-sectionally but with a longitudinal component. A sample of 460 nursing students of the Nursing Degree at the University of Lorca (Murcia) and University of Almería (Spain) completed an online anxiety level questionnaire using the Spielberger State-Trait Anxiety Inventory (STAI) during the first and fourth weeks of the COVID-19 confinement. Total anxiety levels increased in the fourth week, as compared to the first week (first week: 50.4 ± 20.8 and fourth week: 59.9 ± 10.6 (p < 0.001)). The linear regression model showed that the significant predictors for STAI anxiety in nursing students were being in the last year of the degree program, being female, and spending confinement in a house without a garden. In general, most nursing students were emotionally affected by high levels of anxiety of state-trait during the COVID-19 outbreak.
Recent studies reported that long noncoding RNAs (LncRNAs) were involved in tumorigenesis of various human cancer types, including gastric cancer (GC) through targeting microRNAs (miRNAs/miRs). The present study investigated the biological functions of LncRNA SOX2 overlapping transcript (SOX2OT)/miR-194-5p axis and its underlying mechanism in the tumor progression of GC. The results showed that relative expression of LncRNA SOX2OT was highly upregulated while the expression of miR-194-5p was down-regulated in GC tissues and cell lines (MGC-803, SGC-7901, MKN-74). Knockdown of SOX2OT inhibited cell proliferation, invasion and migration of GC cells (MGC803, MKN-74) through reducing epithelial-mesenchymal transition (EMT). Moreover, miR-194-5p was predicted to be one of the targets of SOX2OT through bioinformatics analysis and was verified by luciferase reporter assay. miR-194-5p expression was negatively regulated by SOX2OT expression in GC cells and miR-194-5p inhibitor was found to counteract the inhibitory effects of SOX2OT short hairpin (sh)RNA on cell proliferation and mobility through enhancing EMT in GC cells. Taken together, the in vitro experiments revealed that knockdown of SOX2OT inhibited cell proliferation and mobility through suppressing EMT via targeting miR-194-5p in GC. In addition, results from in vivo experiments showed that knockdown of SOX2OT suppressed GC tumor growth and matrix metalloproteinase (MMP)-2 and MMP-9 expression through inhibiting EMT. Besides that, relative expression of miR-194-5p was increased in sh-SOX2OT group compared with sh-NC group. In summary, our study elucidated that the SOX2OT/miR-194-5p axis participated in the tumor progression of GC through regulation of EMT both in vitro and in vivo. Hence, targeting the SOX2OT/miR-194-5p axis may aid in establishing novel strategies for therapy of GC.
Background: The Dickkopf1 (DKK1) gene encodes a protein that belongs to the Dickkopf family. The protein can inhibit the Wnt signaling pathway which plays a key role in the carcinogenesis and progression of various types of cancers. Based on this, we hypothesized that the differential expression of DKK1 may figure significantly in cancers by regulating Wnt signaling pathway transduction. In this study, we conducted bioinformatics analysis to evaluate the prognostic and therapeutic value of DKK1 expression level in human cancers.Methods: The expression level was analyzed by using the Oncomine database and Gene Expression Profiling Interactive Analysis tool. The analysis of prognosis was conducted by using the UALCAN, Gene Expression Profiling Interactive Analysis (GEPIA), and DriverDBv3 databases. We also investigated using DKK1 promoter methylation to define cancer types through the UALCAN database. Meanwhile, the related functional networks of DKK1 were analyzed by using the GeneMANIA interactive tool and Cytoscape software. Furthermore, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis was conducted using the Metascape online website, and we used the cBioPotartal database to explored DKK1 expression, aberrant information, and the co-expression genes in the subgroups of lung cancer. Finally, we performed the overall survival (OS) meta-analysis of the DKK1 expression in lung squamous cell carcinoma (LUSC) via the Lung Cancer Explorer (LCE).Results: DKK1 was differentially expressed in different types of human cancers. DKK1 was overexpressed in human cancers including head and neck squamous cell carcinoma (HNSC), LUSC, and pancreatic adenocarcinoma (PAAD). Overexpression of DKK1 indicated adverse OS in bladder urothelial carcinoma (BLCA), HNSC, and PADD, but no difference in OS was found between the LUSC and healthy groups.The high expression of DKK1 was also associated with shorter disease-free survival (DFS) in HNSC, LUSC, and PAAD. Gene regulation network analysis indicated that DKK1 was mainly involved in Wnt signaling pathways and several other signaling pathways.Conclusions: Our findings showed that DKK1 is significantly expressed in various cancers and could be a biomarker for targeted therapy and a predictor for prognosis of these specific cancers. The bioinformatics analysis revealed a significant overexpression of DKK1 in HNSC, LUSC, and PAAD, with DKK1 overexpression being associated with adverse outcome in these patients, but how DKK1 expression levels relate to hematological malignancies and prognosis is still unclear. These new insights into the function of DKK1 may provide a basis for new targeted drug therapy and an avenue for further investigation into the mechanisms underlying carcinogenesis of DKK1 in different cancer types.
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