Diagnostic, prognostic, and immunological roles of CDSN in ovarian cancer.

Globally, ovarian cancer (OC) ranks as a principal cause of cancer-related mortality in females. Immunotherapy has revolutionized the treatment of OC, but the efficacy of immunotherapy is often limited by different immune microenvironments. The objective of this research was to pinpoint and validate candidate genes with potential value as diagnostic and prognostic biomarkers and therapeutic targets in OC. Data on genes associated with gene mutation, prognostic survival, and immune infiltration in OC were procured from the Cancer Genome Atlas (TCGA). Gene differential analysis, mutation site analysis, prognosis and survival analysis, and functional and signaling pathway enrichment analysis were conducted to identify and evaluate key genes. The genes were further investigated using immune infiltration analysis, receiver operating characteristic curves, and immunohistochemistry. The impact of CDSN on OC cell proliferation was investigated utilizing CCK-8, colony formation, and apoptosis detection assays. We identified a set of genes (CDSN, WARS, and CD38) that were highly expressed in OC and significantly associated with mutations and prognosis. Immune infiltration analysis and immunohistochemistry results indicated a correlation with immune infiltration in the tumor microenvironment, particularly in antigen-presenting cells. Receiver operating characteristic curve analysis demonstrated the diagnostic potential of these three genes in OC, with all three genes showing the area under the curve (AUC) above 0.8. In vitro studies suggested that knocked down CDSN expression resulted in a marked lower in the proliferative capacity of OC cells. The candidate gene CDSN identified through bioinformatics analysis and in vitro experiments is associated with mutation and immune infiltration, showing promise as a diagnostic and prognostic biomarker, as well as a therapeutic objective in OC.

Serum Hyaluronan as a Predictor of Severity in COVID-19: A Retrospective Study.

OBJECTIVE: We conducted this study to determine the impact of serum glycosaminoglycan hyaluronan (HA) on the prognosis of coronavirus disease 2019 (COVID-19). METHODS: A total of 497 hospitalized patients with COVID-19 were included. Patients were divided into two subgroups based on the severity of infection: mild (n=344) and severe (n=153). The levels of HA, lymphocyte count, C-reactive protein (CRP), ferritin, interleukin 6 (IL-6), and D-dimer were measured and the correlation of these parameters with the prognosis of COVID-19 was assessed. RESULTS: The mean HA level of the severe group was significantly higher than that of the mild group (204.4 ng/mL versus 850.6 ng/mL, P<0.01). In receiver operating characteristic curve analysis, an HA level ≥607.8 ng/mL predicted severe COVID-19 with a sensitivity of 62.3% and specificity of 88.6%. Multivariate regression analysis demonstrated that serum HA level was a significant predictor of disease severity (odds ratio=60.56, P<0.01). CONCLUSION: Our findings show that higher serum HA concentrations are associated with severe COVID-19 disease. Early analysis of HA level in patients with COVID-19 might effectively predict disease severity.

The deregulation of arachidonic acid metabolism in ovarian cancer.

Arachidonic acid (AA) is a crucial polyunsaturated fatty acid in the human body, metabolized through the pathways of COX, LOX, and cytochrome P450 oxidase to generate various metabolites. Recent studies have indicated that AA and its metabolites play significant regulatory roles in the onset and progression of ovarian cancer. This article examines the recent research advancements on the correlation between AA metabolites and ovarian cancer, both domestically and internationally, suggesting their potential use as biological markers for early diagnosis, targeted therapy, and prognosis monitoring.