Advances in the study of gastric organoids as disease models.

Gastric organoids are models created in the laboratory using stem cells and sophisticated three-dimensional cell culture techniques. These models have shown great promise in providing valuable insights into gastric physiology and advanced disease research. This review comprehensively summarizes and analyzes the research advances in culture methods and techniques for adult stem cells and induced pluripotent stem cell-derived organoids, and patient-derived organoids. The potential value of gastric organoids in studying the pathogenesis of stomach-related diseases and facilitating drug screening is initially discussed. The construction of gastric organoids involves several key steps, including cell extraction and culture, three-dimensional structure formation, and functional expression. Simulating the structure and function of the human stomach by disease modeling with gastric organoids provides a platform to study the mechanism of gastric cancer induction by Helicobacter pylori. In addition, in drug screening and development, gastric organoids can be used as a key tool to evaluate drug efficacy and toxicity in preclinical trials. They can also be used for precision medicine according to the specific conditions of patients with gastric cancer, to assess drug resistance, and to predict the possibility of adverse reactions. However, despite the impressive progress in the field of gastric organoids, there are still many unknowns that need to be addressed, especially in the field of regenerative medicine. Meanwhile, the reproducibility and consistency of organoid cultures are major challenges that must be overcome. These challenges have had a significant impact on the development of gastric organoids. Nonetheless, as technology continues to advance, we can foresee more comprehensive research in the construction of gastric organoids. Such research will provide better solutions for the treatment of stomach-related diseases and personalized medicine.

A mechanistic study of Anwei decoction intervention in a rat model of gastric intestinal metaplasia through the endoplasmic reticulum stress - Autophagy pathway.

OBJECTIVE: To investigate the mechanism of Anwei decoction (AWD) intervention on gastric intestinal metaplasia (GIM) using a rat model through the endoplasmic reticulum stress-autophagy pathway. METHODS: Gastric intestinal metaplasia was induced in rats using 1-methyl-3-nitro-1-nitrosoguanidine. The experiment included a normal control group, a model group, and low-, medium- and high-dose AWD groups. The specificity of intestinal epithelial cells was determined for model establishment and drug efficacy by detecting the protein expression of markers such as MUC2, VILLIN and CDX2 through western blotting (WB). The effects of AWD on endoplasmic reticulum stress and autophagy were evaluated by measuring the mRNA and protein expression levels of endoplasmic reticulum stress markers (PEPK, ATF6, CHOP and caspase-12) and autophagy markers (LC3Ⅱ and Beclin-1) using reverse transcription polymerase chain reaction and the WB method. Furthermore, the ultrastructure of gastric mucosal cells and autophagosome status were observed using transmission electron microscopy. RESULTS: Compared with the model group, the AWD-treated rats exhibited significant improvement in body weight (P < 0.01), reduced protein expression of the intestine epithelial cell-specific markers MUC2, VILLIN, CDX2 and KLF4 (P < 0.01 for all) and increased SOX2 protein expression (P < 0.01). In addition, AWD suppressed the mRNA and protein expression of endoplasmic reticulum stress markers PEPK and ATF6 (P < 0.01 for all) and promoted the mRNA and protein expression of autophagy and apoptosis markers CHOP, caspase-12, LC3Ⅱ and Beclin-1 (P < 0.01 for all). CONCLUSION: Anwei decoction effectively inhibits the further progression of GIM and prevents the occurrence of gastric mucosal carcinogenesis.

A systematic review and network meta-analysis of single nucleotide polymorphisms associated with pancreatic cancer risk.

In this meta-analysis, we systematically investigated the correlation between single nucleotide polymorphisms (SNPs) and pancreatic cancer (PC) risk. We searched PubMed, Network Science, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Science and Technology Periodical Database (VIP), and Wanfang databases up to January 2020 for studies on PC risk-associated SNPs. We identified 45 case-control studies (36,360 PC patients and 54,752 non-cancer individuals) relating to investigations of 27 genes and 54 SNPs for this meta-analysis. Direct meta-analysis followed by network meta-analysis and Thakkinstian algorithm analysis showed that homozygous genetic models for CTLA-4 rs231775 (OR =0.326; 95% CI: 0.218-0.488) and VDR rs2228570 (OR = 1.976; 95% CI: 1.496-2.611) and additive gene model for TP53 rs9895829 (OR = 1.231; 95% CI: 1.143-1.326) were significantly associated with PC risk. TP53 rs9895829 was the most optimal SNP for diagnosing PC susceptibility with a false positive report probability < 0.2 at a stringent prior probability value of 0.00001. This systematic review and meta-analysis suggest that TP53 rs9895829, VDR rs2228570, and CTLA-4 rs231775 are significantly associated with PC risk. We also demonstrate that TP53 rs9895829 is a potential diagnostic biomarker for estimating PC risk.

A comprehensive evaluation of single nucleotide polymorphisms associated with atrophic gastritis risk: A protocol for systematic review and network meta-analysis.

BACKGROUND: Single nucleotide polymorphisms (SNPs) have been inconsistently associated with atrophic gastritis (AG) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with AG. METHODS: To identify all associated studies of SNPs and AG published, databases had been searched through January 2020 from the databases of PubMed, China National Knowledge Infrastructure (CNKI), Web of Science, Embase, the Chinese Science and Technology Periodical Database (VIP), Cochrane Library, and Wanfang databases. With the help of network meta-analysis and Thakkinstian algorithm, the best genetic model with the strongest correlation with AG was selected, the final result - matching to the noteworthy correlation - was obtained by referring to the false positive reporting rate (false positive report probability, FPRP). Based on STREGA's stated criteria, the methodological quality of the data we collected was valued. Both Stata 14.0 and GeMTC will be used for a comprehensive review of the system and will be used in our meta-analysis. RESULTS: This study will provide a high-quality evidence to find the SNP most associated with AG susceptibility and the best genetic model. CONCLUSIONS: This study will explore which SNP is most associated with AG susceptibility. REGISTRATION: INPLASY202050016.

A comprehensive evaluation of single nucleotide polymorphisms associated with gastric cancer risk: A protocol for systematic review and network meta-analysis.

BACKGROUND: Single nucleotide polymorphisms (SNPs) have been inconsistently associated with gastric cancer (GC) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with GC. METHODS: Databases were searched to identify association studies of SNPs and GC published through January 2020 from the databases of PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, the Chinese Science and Technology Periodical Database, and Wan fang databases. Network meta-analysis and Thakkinstian algorithm were used to select the most appropriate genetic model, along with false positive report probability for noteworthy associations. The methodological quality of data was assessed based on the STrengthening the REporting of Genetic Association Studies statement Stata 14.0 will be used for systematic review and meta-analysis. RESULTS: This study will provide a high-quality evidence to find the SNP most associated with GC susceptibility and the best genetic model. CONCLUSIONS: This study will explore which SNP is most associated with GC susceptibility. REGISTRATION: INPLASY202040132.

A comprehensive evaluation of single nucleotide polymorphisms associated with osteosarcoma risk: A protocol for systematic review and network meta-analysis.

BACKGROUND: Single nucleotide polymorphisms (SNPs) have been inconsistently associated with osteosarcoma (OS) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with OS. METHODS: Databases were searched to identify association studies of SNPs and OS published through January 2020 from the databases of PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, the Chinese Science and Technology Periodical Database, and Wan fang databases. Network meta-analysis and Thakkinstian algorithm were used to select the most appropriate genetic model, along with false positive report probability for noteworthy associations. The methodological quality of data was assessed based on the STrengthening the REporting of Genetic Association Studies statement Stata 14.0 will be used for systematic review and meta-analysis. RESULTS: This study will provide a high-quality evidence to find the SNP most associated with OS susceptibility and the best genetic model. CONCLUSIONS: This study will explore which SNP is most associated with OS susceptibility. REGISTRATION: INPLASY202040023.