Differentially regulated targets in the fast-acting antidepressant effect of (R)-ketamine: A systems biology approach.

Approximately two-thirds of patients with major depressive disorder (MDD) fail to respond to conventional antidepressants, suggesting that additional mechanisms are involved in the MDD pathophysiology. In this scenario, the glutamatergic system represents a promising therapeutic target for treatment-resistant depression. To our knowledge, this is the first study using semantic approach with systems biology to identify potential targets involved in the fast-acting antidepressant effects of ketamine and its enantiomers as well as identifying specific targets of (R)-ketamine. We performed a systematic review, followed by a semantic analysis and functional gene enrichment to identify the main biological processes involved in the therapeutic effects of these agents. Protein-protein interaction networks were constructed, and the genes exclusively regulated by (R)-ketamine were explored. We found that the regulation of α-Amino-3-Hydroxy-5-Methyl-4-Isoxazolepropionic Acid (AMPA) receptor and N-methyl-d-aspartate (NMDA) receptor subunits-Postsynaptic Protein 95 (PSD-95), Brain Derived Neurotrophic Factor (BDNF), and Tyrosine Receptor Kinase B (TrkB) are shared by the three-antidepressant agents, reinforcing the central role of the glutamatergic system and neurogenesis on its therapeutic effects. Differential regulation of Transforming Growth Factor Beta 1 (TGF-ß1) receptors-Mitogen-Activated Protein Kinases (MAPK's), Receptor Activator of Nuclear Factor-Kappa Beta Ligand (RANKL), and Serotonin Transporter (SERT) seems to be particularly involved in (R)-ketamine antidepressant effects. Our data helps further studies investigating the relationship between these targets and the mechanisms of (R)-ketamine and searching for other therapeutic compounds that share the regulation of these specific biomolecules. Ultimately, this study could contribute to improve the fast management of depressive-like symptoms with less detrimental side effects than ketamine and (S)-ketamine.

Identification of novel biomarkers with potential for diagnosis and prognosis of gastric cancer: a bioinformatics approach

INTRODUCTION: Gastric cancer (GC) is the fifth most diagnosed neoplasia and the third leading cause of cancer-related deaths. A substantial number of patients exhibit an advanced GC stage once diagnosed. Therefore, the search for biomarkers contributes to the improvement and development of therapies. OBJECTIVE: This study aimed to identify potential GC biomarkers making use of in silico tools. METHODS: Gastric tissue microarray data available in Gene Expression Omnibus and The Cancer Genome Atlas Program was extracted. We applied statistical tests in the search for differentially expressed genes between tumoral and non-tumoral adjacent tissue samples. The selected genes were submitted to an in-house tool for analyses of functional enrichment, survival rate, histological and molecular classifications, and clinical follow-up data. A decision tree analysis was performed to evaluate the predictive power of the potential biomarkers. RESULTS: In total, 39 differentially expressed genes were found, mostly involved in extracellular structure organization, extracellular matrix organization, and angiogenesis. The genes SLC7A8, LY6E, and SIDT2 showed potential as diagnostic biomarkers considering the differential expression results coupled with the high predictive power of the decision tree models. Moreover, GC samples showed lower SLC7A8 and SIDT2 expression, whereas LY6E was higher. SIDT2 demonstrated a potential prognostic role for the diffuse type of GC, given the higher patient survival rate for lower gene expression. CONCLUSION: Our study outlines novel biomarkers for GC that may have a key role in tumor progression. Nevertheless, complementary in vitro analyses are still needed to further support their potential.