Gastric cancer (GC) is one of the most commonly occurring cancers, and metabolism-related genes (MRGs) are associated with its development. Transcriptome data and the relevant clinical data were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases, and we identified 194 MRGs differentially expressed between GC and adjacent nontumor tissues. Through univariate Cox and lasso regression analyses we identified 13 potential prognostic differentially expressed MRGs (PDEMRGs). These PDEMRGs (CKMT2, ME1, GSTA2, ASAH1, GGT5, RDH12, NNMT, POLR1A, ACYP1, GLA, OPLAH, DCK, and POLD3) were used to build a Cox regression risk model to predict the prognosis of GC patients. Further univariate and multivariate Cox regression analyses showed that this model could serve as an independent prognostic parameter. Gene Set Enrichment Analysis showed significant enrichment pathways that could potentially contribute to pathogenesis. This model also revealed the probability of genetic alterations of PDEMRGs. We have thus identified a valuable metabolic model for predicting the prognosis of GC patients. The PDEMRGs in this model reflect the dysregulated metabolic microenvironment of GC and provide useful noninvasive biomarkers.
Chemotherapy is the main clinical treatment method of gastric cancer. Multidrug resistance (MDR) has become a common phenomenon with the development of tumors, which alleviates the effect of chemotherapy and makes it difficult to break the bottleneck of survival rate of advanced gastric cancer. Therefore, the exploration of MDR reversal agents for gastric cancer is the focus and also the difficulty of current treatment. Currently, the researches on the mechanisms of drug resistance in gastric cancer have been continuously deepened, which reveal different pathways and targets of MDR, laying a solid foundation for studying reversal agents. As a kind of natural medicine, traditional Chinese medicine (TCM) owns the characteristics of low toxicity, high safety and effectiveness. It can inhibit the occurrence, growth and metastasis of tumors, and reverse MDR via multiple pathways and mechanisms, the pathological function of which has become a research hotspot in recent years. TCM reversers are mainly divided into Chinese medicine monomers, Chinese patent medicines, and Chinese herbal compounds. With certain quantity and advantage, TCM reversers for MDR play an important role in the clinical treatment and show great potential in gastric cancer.
Sparganii rhizoma (SL) has potential therapeutic effects on gastric cancer (GC), but its main active ingredients and possible anticancer mechanism are still unclear. In this study, we used HPLC-Q-TOF–MS/MS to comprehensively analyse the chemical components of the aqueous extract of SL. On this basis, a network pharmacology method incorporating target prediction, gene function annotation, and molecular docking was performed to analyse the identified compounds, thereby determining the main active ingredients and hub genes of SL in the treatment of GC. Finally, the mRNA and protein expression levels of the hub genes of GC patients were further analysed by the Oncomine, GEPIA, and HPA databases. A total of 41 compounds were identified from the aqueous extract of SL. Through network analysis, we identified seven main active ingredients and ten hub genes: acacetin, sanleng acid, ferulic acid, methyl 3,6-dihydroxy-2-[(2-hydroxyphenyl) ethynyl]benzoate, caffeic acid, adenine nucleoside, azelaic acid and PIK3R1, PIK3CA, SRC, MAPK1, AKT1, HSP90AA1, HRAS, STAT3, FYN, and RHOA. The results indicated that SL might play a role in GC treatment by controlling the PI3K-Akt and other signalling pathways to regulate biological processes such as proliferation, apoptosis, migration, and angiogenesis in tumour cells. In conclusion, this study used HPLC-Q-TOF–MS/MS combined with a network pharmacology approach to provide an essential reference for identifying the chemical components of SL and its mechanism of action in the treatment of GC.
BackgroundThe aim of this study was to systematically assess the efficacy and safety of mineralocorticoid receptor antagonists (MRAs) for patients with heart failure (HF) and diabetes mellitus (DM).MethodsWe conducted a comprehensive search for controlled studies that evaluated the efficacy and safety of MRAs in patients with DM and HF. Medline, Embase and Cochrane databases were searched. Two reviewers independently identified citations, extracted data and evaluated quality. Risk estimations were abstracted and pooled where appropriate.ResultsFour observational studies were included. MRAs use was associated with reduced mortality compared with controls (RR = 0.78; 95 % CI: 0.69–0.88; I 2 = 0 %; P < 0.001). Increased risk of developing hyperkalaemia was observed in those patients taking MRAs (RR = 1.74; 95 % CI: 1.27–2.38; I 2 = 0 %; P = 0.0005).ConclusionsThe current cumulative evidence suggests that MRAs can improve clinical outcomes but increase the risk of hyperkalaemia in patients with DM and HF.Trial registrationPROSPERO CRD42015025690.Electronic supplementary materialThe online version of this article (doi:10.1186/s12872-016-0198-2) contains supplementary material, which is available to authorized users.
The solute carrier family 30 member 8 (SLC30A8) gene may be involved in the development of type 2 diabetes mellitus (T2DM) through disrupting β-cell function. The aim of this study was to assess the association between SLC30A8 rs13266634 polymorphism and susceptibility to T2DM. We searched all reports regarding the association between SLC30A8 rs13266634 polymorphism and T2DM risk through Pubmed, Embase, and the Cochrane Library for English language reports and Chongqing VIP database, Wanfang data, CBMDisc, and CNKI for Chinese language studies. Allelic and genotype comparisons between cases and controls were evaluated, and odds ratios with 95 % confidence intervals were used to assess the strength of their association. A random effects model was selected. Publication bias was estimated using Begg's test. Forty-six studies were included in the analysis with a total of 71,890 cases and 96,753 controls. This meta-analysis suggests that SLC30A8 (rs13266634) polymorphism was associated with T2DM risk. Although previous meta-analyses have shown that this association was only found in Asian and European groups, and not in African populations, our analysis revealed the deleterious effect of SLC30A8 rs13266634 on T2DM in an African population when stratified by ethnicity under additive model even with a small number of studies.
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