Harrison Karlsen (relishpeak9)

Oxidative stress triggered by the Fenton reaction (chemical) or UVR exposure (photo) can damage cellular biomolecules including RNA through oxidation of nucleotides. Besides such xenobiotic chemical modifications, RNA also contains several post-transcriptional nucleoside modifications that are installed by enzymes to modulate structure, RNA-protein interactions, and biochemical functions. We examined the extent of oxidative damage to naturally modified RNA which is required for cellular protein synthesis under two different contexts. The extent of oxidative damage is higher when RNA is not associated with proteins, but the degree of damage is lower when the RNA is presented in the form of a ribonucleoprotein complex, such as an intact ribosome. Our studies also indicate that absence of methylations in ribosomal RNA at specific positions could make it more susceptible to photooxidative stress. However, the extent of guanosine oxidation varied with the position at which the modification is deficient, indicating position-dependent structural effects. Further, an E. coli strain deficient in 5-methylaminomethyl-2-thiouridine (mnm5s2U) (found in lysine and glutamate tRNA anticodon) is more vulnerable to oxidative RNA damage compared to its wildtype strain suggesting an auxiliary function for the mnm5s2U modification. These studies indicate that oxidative damage to RNA is altered by the presence of enzymatic modified nucleosides or protein association inside the cell.Background Dysregulation of lipid metabolism plays important roles in the tumorigenesis and progression of gastric cancer (GC). The present study aimed to establish a prognostic model based on the lipid metabolism-related genes in GC patients. Materials and Methods Two GC datasets from the Gene Expression Atlas, GSE62254 (n = 300) and GSE26942 (n = 217), were used as training and validation cohorts to establish a risk predictive scoring model. The efficacy of this model was assessed by ROC analysis. The association of the risk predictive scores with patient characteristics and immune cell subtypes was evaluated. A nomogram was constructed based on the risk predictive score model and other prognostic factors. Results A risk predictive score model was established based on the expression of 19 lipid metabolism-related genes (LPL, IPMK, PLCB3, CDIPT, PIK3CA, DPM2, PIGZ, GPD2, GPX3, LTC4S, CYP1A2, GALC, SGMS1, SMPD2, SMPD3, FUT6, ST3GAL1, B4GALNT1, and ACADS). The time-dependent ROC analysis revealed that the risk predictive score model was stable and robust. Patients with high risk scores had significantly unfavorable overall survival compared with those with low risk scores in both the training and validation cohorts. A higher risk score was associated with more aggressive features, including a higher tumor grade, a more advanced TNM stage, and diffuse type of Lauren classification of GC. Moreover, distinct immune cell subtypes and signaling pathways were found between the high-risk and low-risk score groups. A nomogram containing patients' age, tumor stage, adjuvant chemotherapy, and the risk predictive score could accurately predict the survival probability of patients at 1, 3, and 5 years. Conclusion A novel 19-gene risk predictive score model was developed based on the lipid metabolism-related genes, which could be a potential prognostic indicator and therapeutic target of GC.Mitogen-activated protein kinases (MAPK) are important regulatory units in cells and they take part in the regulation of many cellular functions such as cell division, differentiation or apoptosis. All MAPKs have a shallow docking groove that interacts with linear binding motifs of their substrate proteins and their regulatory proteins such as kinases, phosphatases, scaffolds. Inhibition of these protein-protein interactions may reduce or abolish the activity of the targeted kinase. Based on the wide range of their biological activity, this kind of inhibition can be useful in the treatment of man