Pickled Vegetables Intake Impacts the Metabolites for Gastric Cancer

Multi-omics Combined with Machine Learning Facilitating the Diagnosis of Gastric Cancer

Gastric cancer (GC) is a highly intricate gastrointestinal malignancy. Early detection of gastric cancer forms the cornerstone of precision medicine. Several studies have been conducted to investigate early biomarkers of gastric cancer using genomics, transcriptomics, proteomics, and metabolomics, respectively. However, endogenous substances associated with various omics are concurrently altered during gastric cancer development. Furthermore, environmental exposures and family history can also induce modifications in endogenous substances. Therefore, in this study, we primarily investigated alterations in DNA mutation, DNA methylation, mRNA, lncRNA, miRNA, circRNA, and protein, as well as glucose, amino acid, nucleotide, and lipid metabolism levels in the context of GC development, employing genomics, transcriptomics, proteomics, and metabolomics. Additionally, we elucidate the impact of exposure factors, including HP, EBV, nitrosamines, smoking, alcohol consumption, and family history, on diagnostic biomarkers of gastric cancer. Lastly, we provide a summary of the application of machine learning in integrating multi-omics data. Thus, this review aims to elucidate: i) the biomarkers of gastric cancer related to genomics, transcriptomics, proteomics, and metabolomics; ii) the influence of environmental exposure and family history on multiomics data; iii) the integrated analysis of multi-omics data using machine learning techniques.

Fermented Vegetables: Health Benefits, Defects, and Current Technological Solutions

This review summarizes current studies on fermented vegetables, analyzing the changes in nutritional components during pickling, the health benefits of fermented vegetables, and their safety concerns. Additionally, the review provides an overview of the applications of emergent non-thermal technologies for addressing these safety concerns during the production and processing of fermented vegetables. It was found that vitamin C would commonly be lost, the soluble protein would degrade into free amino acids, new nutrient compositions would be produced, and the flavor correlated with the chemical changes. These changes would be influenced by the variety/location of raw materials, the original bacterial population, starter cultures, fermentation conditions, seasoning additions, and post-fermentation processing. Consuming fermented vegetables benefits human health, including antibacterial effects, regulating intestinal bacterial populations, and promoting health (anti-cancer effects, anti-diabetes effects, and immune regulation). However, fermented vegetables have chemical and biological safety concerns, such as biogenic amines and the formation of nitrites, as well as the existence of pathogenic microorganisms. To reduce hazardous components and control the quality of fermented vegetables, unique starter cultures, high pressure, ultrasound, cold plasma, photodynamic, and other technologies can be used to solve these problems.

Prognostic Implication of Plasma Metabolites in Gastric Cancer

Gastric cancer (GC) typically carries a poor prognosis as it is often diagnosed at a late stage. Altered metabolism has been found to impact cancer outcomes and affect patients' quality of life, and the role of metabolites in gastric cancer prognosis has not been sufficiently understood. We aimed to establish a prognostic prediction model for GC patients based on a metabolism-associated signature and identify the unique role of metabolites in the prognosis of GC. Thus, we conducted untargeted metabolomics to detect the plasma metabolites of 218 patients with gastric adenocarcinoma and explored the metabolites related to the survival of patients with gastric cancer. Firstly, we divided patients into two groups based on the cutoff value of the abundance of each of the 60 metabolites and compared the differences using Kaplan-Meier (K-M) survival analysis. As a result, 23 metabolites associated with gastric cancer survival were identified. To establish a risk score model, we performed LASSO regression and Cox regression analysis on the 60 metabolites and identified 8 metabolites as an independent prognostic factor. Furthermore, a nomogram incorporating clinical parameters and the metabolic signature was constructed to help individualize outcome predictions. The results of the ROC curve and nomogram plot showed good predictive performance of metabolic risk features. Finally, we performed pathway analysis on the 24 metabolites identified in the two parts, and the results indicated that purine metabolism and arachidonic acid metabolism play important roles in gastric cancer prognosis. Our study highlights the important role of metabolites in the progression of gastric cancer and newly identified metabolites could be potential biomarkers or therapeutic targets for gastric cancer patients.

Association of single nucleotide polymorphisms (SNPs) with gastric cancer susceptibility and prognosis in population in Wuwei, Gansu, China

BACKGROUND

Gastric cancer (GC) is the sixth most common cancer. China is one of the most frequent GC occurred countries, and Wuwei, Gansu, is one of the highest incidence area in China. Possible biomarkers of GC susceptibility and prognosis among the population in Wuwei are urgently needed.

METHODS

All participants in this study were recruited from the Wuwei Cancer Hospital in Gansu, including 303 patients diagnosed with GC and 200 non-cancer controls. DNA was extracted for further single nucleotide polymorphisms (SNP) genotyping. All SNPs were firstly screened by additive logistic regression model then selected SNPs were subjected to univariate Cox regression analysis and multivariate Cox regression analysis for their associations with GC occurrence.

RESULTS

The results showed that 31 SNPs were significantly related to the incidence of GC in Wuwei, Gansu, China. Genotype rs4823921 was significantly related to the overall survival of GC patients and AC/AA genotype of rs4823921 polymorphism was significantly associated with an increased risk of GC in Wuwei population.

CONCLUSIONS

Thirty-one SNPs were significantly related to the incidence of GC in Wuwei and rs4823921 genotype AC/AA was significantly associated with poor prognosis of GC patients in Wuwei, Gansu.

mGWAS identification of six novel single nucleotide polymorphism loci with strong correlation to gastric cancer

BACKGROUND

Metabolite genome-wide association studies (mGWAS) are key for understanding the genetic regulation of metabolites in complex diseases including cancers. Although mGWAS has revealed hundreds of metabolomics quantitative trait loci (mQTLs) in the general population, data relating to gastric cancer (GC) are still incomplete.

METHODS

We identified mQTLs associated with GC by analyzing genome-wide and metabolome-wide datasets generated from 233 GC patients and 233 healthy controls.

RESULTS

Twenty-two metabolites were statistically different between GC cases and healthy controls, and all of them were associated with the risk of gastric cancer. mGWAS analyses further revealed that 9 single nucleotide polymorphisms (SNPs) were significantly associated with 3 metabolites. Of these 9 SNPs, 6 loci were never reported in the previous mGWAS studies. Surprisingly, 4 of 9 SNPs were significantly enriched in genes involved in the T cell receptor signaling pathway.

CONCLUSIONS

Our study unveiled several novel GC metabolite and genetic biomarkers, which may be implicated in the prevention and diagnosis of gastric cancer.