Background: Gastric cancer (GC) is one of the most common solid malignant tumors worldwide with a high-recurrence-rate. Identifying the molecular signatures and specific biomarkers of GC might provide novel clues for GC prognosis and targeted therapy.Methods: Gene expression profiles were obtained from the ArrayExpress and Gene Expression Omnibus database. Differentially expressed genes (DEGs) were picked out by R software. The hub genes were screened by cytoHubba plugin. Their prognostic values were assessed by Kaplan–Meier survival analyses and the gene expression profiling interactive analysis (GEPIA). Finally, qRT-PCR in GC tissue samples was established to validate these DEGs. Results: Total of 295 DEGs were identified between GC and their corresponding normal adjacent tissue samples in E-MTAB-1440, GSE79973, GSE19826, GSE13911, GSE27342, GSE33335 and GSE56807 datasets, including 117 up-regulated and 178 down-regulated genes. Among them, 7 vital upregulated genes (HMMR, SPP1, FN1, CCNB1, CXCL8, MAD2L1 and CCNA2) were selected. Most of them had a significantly worse prognosis except SPP1. Using qRT-PCR, we validated that their transcriptions in our GC tumor tissue were upregulated except SPP1 and FN1, which correlated with tumor relapse and predicts poorer prognosis in GC patients.Discussion: We have identified 5 upregulated DEGs (HMMR, CCNB1, CXCL8, MAD2L1, and CCNA2) in GC patients with poor prognosis using integrated bioinformatical methods, which could be potential biomarkers and therapeutic targets for GC treatment.
Background: Most previous studies supported that the mammalian target of rapamycin (mTOR) is over-activated in Alzheimer’s disease (AD) and exacerbates the development of AD. It is unclear whether the causal associations between the mTOR signaling-related protein and the risk for AD exist. Objective: This study aims to investigate the causal effects of the mTOR signaling targets on AD. Methods: We explored whether the risk of AD varied with genetically predicted AKT, RP-S6K, EIF4E-BP, eIF4E, eIF4A, and eIF4 G circulating levels using a two-sample Mendelian randomization analysis. The summary data for targets of the mTOR signaling were acquired from published genome-wide association studies for the INTERVAL study. Genetic associations with AD were retrieved from the International Genomics of Alzheimer’s Project. We utilized the inverse variance weighted as the primary approach to calculate the effect estimates. Results: The elevated levels of AKT (OR = 0.910, 95% CI=0.840-0.986, p = 0.02) and RP-S6K (OR = 0.910, 95% CI=0.840-0.986, p = 0.02) may decrease the AD risk. In contrast, the elevated eIF4E levels (OR = 1.805, 95% CI=1.002-1.174, p = 0.045) may genetically increase the AD risk. No statistical significance was identified for levels of EIF4-BP, eIF4A, and eIF4 G with AD risk (p > 0.05). Conclusion: There was a causal relationship between the mTOR signaling and the risk for AD. Activating AKT and RP-S6K, or inhibiting eIF4E may be potentially beneficial to the prevention and treatment of AD.
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