The Regulating Role of SB216763 in Pseudomonas aeruginosa Keratitis

The evaluation of six genes combined value in glioma diagnosis and prognosis

PURPOSE

Glioma is the most common and fatal type of brain tumour. Owing to its aggressiveness and lethality, early diagnosis and prediction of patient survival are very important. This study aimed to identify key genes and biomarkers for glioma that can guide clinicians in making rapid diagnosis and prognostication.

METHODS

Data mining of The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Repository of Molecular Brain Neoplasia Data, and Genotype-Tissue Expression Project brain expression data revealed significantly differentially expressed genes (DEGs), and the risk scores of individual patients were calculated. WGCNA was utilized to screen for genes most related to clinical diagnosis. Prognostic genes associated with glioma were selected via combining the LASSO regression with univariate and multivariate Cox regression and protein-protein interaction network analyses. Then, a nomogram was constructed. And CGGA dataset was utilized to validated. The protein expression levels of the signature were detected using the human protein atlas. Drug response prediction was carried out using the package "pRRophetic".

RESULTS

A six-gene signature (KLF6, CHI3L1, SERPINE1, ANGPT2, TGFBR1, and PTX3) was identified and used to stratify patients into low- and high-risk groups. Survival, ROC curve, and Cox analyses clarified that the six hub genes were a favourable independent prognostic factor for patients with glioma. A nomogram was set up by integrating clinical parameters with risk signatures, showing high precision for predicting 2-, 3-, 4-, 5-years survival. In addition, the expression of most genes was consistent with protein expression. Furthermore, the sensitivity to the top ten drugs in the GDSC database of the high-risk group was significantly higher than the low-risk group.

CONCLUSION

Based on genetic profiles and clinicopathological features, including age, grade, isocitrate dehydrogenase mutation status, we constructed a comprehensive prognostic model for patients with glioma. These signatures can be regarded as biomarkers to predict the prognosis of gliomas, possibly providing more therapeutic strategies for future clinical research.

Glycogen Synthase Kinase 3β Modulates the Inflammatory Response Activated by Bacteria, Viruses, and Parasites

Knowledge of glycogen synthase kinase 3β (GSK3β) activity and the molecules identified that regulate its function in infections caused by pathogenic microorganisms is crucial to understanding how the intensity of the inflammatory response can be controlled in the course of infections. In recent years many reports have described small molecular weight synthetic and natural compounds, proteins, and interference RNA with the potential to regulate the GSK3β activity and reduce the deleterious effects of the inflammatory response. Our goal in this review is to summarize the most recent advances on the role of GSK3β in the inflammatory response caused by bacteria, bacterial virulence factors (i.e. LPS and others), viruses, and parasites and how the regulation of its activity, mainly its inhibition by different type of molecules, modulates the inflammation.