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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.

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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.

Background Observational studies have reported an association between circulating levels of mammalian target of rapamycin (mTOR)-dependent circulating proteins and multiple sclerosis (MS). However, the casual association has not been fully elucidated. Mendelian randomization (MR) is used to overcome limitations inherent to observational studies and assess the causal association. Methods To explore the causal association between mTOR-dependent proteins (AKT, RP-S6K, eIF4E-BP, eIF4A, eIF4E, eIF4G, and PKC-α) and MS, summary statistics were obtained from GWAS meta-analysis of the International Multiple Sclerosis Genetics Consortium (47429 patients and 68374 controls) and the INTERVAL study (genetic associations with 2994 plasma proteins from 3301 healthy individuals). MR analysis and sensitivity analyses were conducted. Results Among seven selected mTOR-dependent proteins, the circulating level of PKC-α (OR = 0.90, 95%CI 0.82–0.98, P = 0.017) and RP-S6K (OR = 1.12, 95%CI 1.00-1.25, P = 0.045) were associated with MS risk, while no significant causation was found between other proteins (AKT, eIF4E-BP, eIF4A, eIF4E, eIF4G) and MS. Conclusion Molecules in the mTOR signaling pathway may bidirectionally regulate the occurrence and development of MS. PKC-α is a protective factor, while RP-S6K is a risk factor. They might be used as future therapeutic targets for screening high-risk individuals.

Background and Aims Ulcerative colitis [UC] is a complex heterogeneous disease. This study aims to reveal the underlying molecular features of UC using genome-scale transcriptomes of patients with UC and develop and validate a novel stratification scheme. Methods A normalized compendium was created using colon tissue samples [455 patients with UC and 147 healthy controls [HCs]], covering genes from 10 microarray datasets. Up-regulated differentially expressed genes [DEGs] were subjected to functional network analysis, wherein samples were grouped using unsupervised clustering. Additionally, the robustness of subclustering was further assessed by two RNA sequencing datasets [100 patients with UC and 16 HCs]. Finally, the Xgboost classifier was applied to the independent datasets to evaluate the efficacy of different biologics in patients with UC. Results Based on 267 up-regulated DEGs of the transcript profiles, UC patients were classified into three subtypes [subtype A-C] with distinct molecular and cellular signatures. Epithelial activation-related pathways were significantly enriched in subtype A [named epithelial proliferation], whereas subtype C was characterized as the immune activation subtype with prominent immune cells and proinflammatory signatures. Subtype B [named mixed] was modestly activated in all the signalling pathways. Notably, subtype A showed a stronger association with the superior response of biologics such as golimumab, infliximab, vedolizumab and ustekinumab compared to subtype C. Conclusions We conducted a deep stratification of mucosal tissue using the most comprehensive microarray and RNA sequencing data, providing critical insights into pathophysiological features of UC, which could serve as a template for stratified treatment approaches.

Background: This study investigated gut microbiota characteristics and their associations with lymphocyte subsets, cytokines, and disease activity in patients with ankylosing spondylitis (AS). Fecal DNA from 62 AS patients and 62 healthy controls (HCs) was subjected to 16S rRNA gene sequencing. The absolute numbers of peripheral lymphocyte subsets were detected by flow cytometry, while the serum levels of cytokines were tested by cytokine bead arrays. Results: The gut microbiota diversity was significantly decreased in AS patients, compared to HCs. Proteobacteria and Patescibacteria were more abundant in AS patients than in HCs; Firmicutes, Fusobacteriota, Verrucomicrobiota, Synergistota, and Campilobacterota were less abundant in AS patients than in HCs. At the genus level, the abundances of Escherichia–Shigella were increased in AS patients compared to HCs; in contrast, the abundances of Faecalibacterium, Prevotella, Agathobacter, Roseburia, and Dialister were decreased in AS patients. The linear discriminant analysis effect size indicated that Enterobacterales was the most significant order in AS patients. The relative abundances of Agathobacter, Ruminococcus, Prevotella, and CAG–352 were correlated with lymphocyte subsets and cytokine levels; the relative abundances of Faecalibacterium, Klebsiella, and Roseburia were correlated with disease activity. In addition, specific gut microbiota were significantly correlated with peripheral blood cell count, age, and body mass index. Conclusions: The gut microbiota in AS patients differed from the gut microbiota in HCs; changes in bacterial communities were associated with the immune profile that contributes to AS pathogenesis.