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Clinical reports suggest a potential link between excess retinoids and development of depression. Although it has been shown that all-trans retinoic acid (ATRA) administration induces behavioral changes, further insight into how ATRA is involved is lacking. The hippocampus seems to be a major target of retinoids, and abnormal synaptic plasticity of the hippocampus is involved in depression. We examined two genes associated with synaptic function, discs large homolog 2 (DLG2), and synapse differentiation-inducing gene protein 1 (SynDIG1) in terms of hippocampal expression and correlation with behavior. Three different doses of ATRA were injected into young mice and 10 mg/kg ATRA was found to induce depression-like behavior. In the hippocampus, DLG2 mRNA was significantly decreased by ATRA. mRNA levels were positively correlated with central area duration and distance in the open-field test. Increased SynDIG1 mRNA levels were observed. There was a negative correlation between SynDIG1 mRNA levels and mobility time in the forced swimming test. Retinoic acid receptor γ mRNA was significantly positively correlated with DLG2 and negatively correlated with SynDIG1. To summarize, ATRA administration induced anxiety- and depression-like behavior accompanied by a decreased expression of DLG2 and an increased expression of SynDIG1. Moreover, DLG2 was correlated with anxiety-like behavior and SynDIG1 was correlated with depression-like behavior. These results might constitute a novel target underlying ATRA-induced anxiety- and depression-like behavior. Full article

Background and objectives: Bladder urothelial carcinoma is the most common type of genitourinary cancer. Patients with bladder cancer may have limited treatment efficacy related to drug toxicity, resistance or adverse effects, and novel therapeutic strategies to enhance treatment efficacy or increase sensitivity to drugs are of high clinical importance. Epigallocatechin gallate (EGCG) is a polyphenolic compound found in green tea leaves, and a potential anti-cancer agent in various cancer types through modulating and regulating multiple signaling pathways. The current study aimed to explore the role and novel therapeutic targets of EGCG on bladder urothelial carcinoma. Materials and Methods: The BFTC-905 cells, human urinary bladder transitional cell carcinoma (TCC) cell line, were treated with EGCG or water for 24 hours, and the expression profiles of mRNAs and microRNAs were analyzed using next generation sequencing (NGS). The enriched biological functions were determined using different bioinformatics databases. Results: A total of 108 differentially expressed genes in EGCG-treated bladder TCC cells were identified, which were mainly involved in nicotinamide adenine dinucleotide (NAD) biogenesis, inflammatory response and oxidation-reduction metabolism. Moreover, several microRNA-mRNA interactions that potentially participated in the response of bladder TCC to EGCG treatment, including miR-185-3p- ARRB1 (arrestin beta 1), miR-3116- MGAT5B (alpha-1,6-mannosylglycoprotein 6-beta-N-acetylglucosaminyltransferase B), miR-31-5p-TNS1 (tensin 1), miR-642a-5p-TNS1, miR-1226-3p- DLG2 (discs large homolog 2), miR-484-DLG2, and miR-22-3p- PPM1K (protein phosphatase 1K). Conclusions: The current findings provide insights into novel therapeutic targets and underlying mechanisms of action of EGCG treatment in bladder cancer. Full article

Insulin resistance is present in the majority of patients with non-insulin-dependent diabetes mellitus (NIDDM) and obesity. In this study, we aimed to investigate the key genes and potential molecular mechanism in insulin resistance. Expression profiles of the genes were extracted from the Gene Expression Omnibus (GEO) database. Pathway and Gene Ontology (GO) enrichment analyses were conducted at Enrichr. The protein–protein interaction (PPI) network was settled and analyzed using the Search Tool for the Retrieval of Interacting Genes (STRING) database constructed by Cytoscape software. Modules were extracted and identified by the PEWCC1 plugin. The microRNAs (miRNAs) and transcription factors (TFs) which control the expression of differentially expressed genes (DEGs) were analyzed using the NetworkAnalyst algorithm. A database (GSE73108) was downloaded from the GEO databases. Our results identified 873 DEGs (435 up-regulated and 438 down-regulated) genetically associated with insulin resistance. The pathways which were enriched were pathways in complement and coagulation cascades and complement activation for up-regulated DEGs, while biosynthesis of amino acids and the Notch signaling pathway were among the down-regulated DEGs. Showing GO enrichment were cardiac muscle cell–cardiac muscle cell adhesion and microvillus membrane for up-regulated DEGs and negative regulation of osteoblast differentiation and dendrites for down-regulated DEGs. Subsequently, myosin VB (MYO5B), discs, large homolog 2(DLG2), axin 2 (AXIN2), protein tyrosine kinase 7 (PTK7), Notch homolog 1 (NOTCH1), androgen receptor (AR), cyclin D1 (CCND1) and Rho family GTPase 3 (RND3) were diagnosed as the top hub genes in the up- and down-regulated PPI network and modules. In addition, GATA binding protein 6 (GATA6), ectonucleotide pyrophosphatase/phosphodiesterase 5 (ENPP5), cyclin D1 (CCND1) and tubulin, beta 2A (TUBB2A) were diagnosed as the top hub genes in the up- and down-regulated target gene–miRNA network, while tubulin, beta 2A (TUBB2A), olfactomedin-like 1 (OLFML1), prostate adrogen-regulated mucin-like protein 1 (PARM1) and aldehyde dehydrogenase 4 family, member A1 (ALDH4A1)were diagnosed as the top hub genes in the up- and down-regulated target gene–TF network. The current study based on the GEO database provides a novel understanding regarding the mechanism of insulin resistance and may provide novel therapeutic targets. Full article