Maintaining H. pylori Negativity After Eradication Can Consolidate Its Benefit in Gastric Cancer Prevention: A Meta-Analysis.

INTRODUCTION: Several studies have reported the role of Helicobacter pylori eradication in gastric cancer (GC) prevention. However, for individuals with unsatisfactory management of their H. pylori infection status after eradication, the risk of GC remains unclear. METHODS: An exhaustive search strategy of the incidence of GC (including primary gastric cancer and metachronous gastric cancer) incidence in patients with unsuccessful eradication or H. pylori reinfection was implemented in the PubMed, Embase, Cochrane Library, and Web of Science. The hazard ratios (HRs) and cumulative incidence of total GC in patients with failed eradication or H. pylori reinfection (FE-Hp (+)) group were compared with that in patients with successful eradication and no H. pylori reinfection (SE-Hp (-)) group and patients with noneradication (NE) group. RESULTS: Seven eligible studies (including 8,767 patients with H. pylori infection) were identified. In the FE-Hp (+) group, the total GC risk was 1.86-fold of that in the SE-Hp (-) group (HR = 1.86, 95% confidence interval [CI]: 1.14-3.04, P = 0.013). The total GC risk in the NE group was also higher than that in the FE-Hp (+) group (HR = 1.98, 95% CI: 1.11-3.52, P = 0.002). On further analysis with different end points showed that the pooled GC risk increased over time (5-year follow-up: HR = 2.92, 1.34-6.34; 10-year follow-up: HR = 4.04, 2.56-6.37). DISCUSSION: Compared with the SE-Hp (-) group, the FE-Hp (+) group had a higher risk of gastric carcinoma. Long-term monitoring of H. pylori infection status could consolidate the benefit of eradicating H. pylori for preventing GC prevention in patients after eradication.

Potential Mechanism of Tibetan Medicine Liuwei Muxiang Pills against Colorectal Cancer: Network Pharmacology and Bioinformatics Analyses.

This study aimed to explore the mechanism through which Tibetan medicine Liuwei Muxiang (LWMX) pills acts against colorectal cancer (CRC). We firstly retrieved the active ingredients and the correlated targets of LWMX pills from public databases. The CRC-related targets were determined through bioinformatic analysis of a public CRC dataset. By computing the intersection of the drug-specific and disease-related targets, LWMX pill-CRC interaction networks were constructed using the protein-protein interaction (PPI) method and functional enrichment analysis. Subsequently, we determined the hub genes using machine learning tools and further verified their critical roles in CRC treatment via immune infiltration analysis and molecular docking studies. We identified 81 active ingredients in LWMX pills with 614 correlated targets, 1877 differentially expressed genes, and 9534 coexpression module genes related to CRC. A total of 5 target hub genes were identified among the 108 intersecting genes using machine learning algorithms. The immune infiltration analysis results suggested that LWMX pills could affect the CRC immune infiltration microenvironment by regulating the expression of the target hub genes. Finally, the molecular docking outcomes revealed stable binding affinity between all target hub proteins and the primary active ingredients of LWMX pills. Our findings illustrate the anti-CRC potential and the mechanism of action of LWMX pills and provide novel insights into multitarget medication for CRC treatment.

A Novel Lipid Metabolism and Endoplasmic Reticulum Stress-Related Risk Model for Predicting Immune Infiltration and Prognosis in Colorectal Cancer.

Lipid metabolism and endoplasmic reticulum stress exhibit crosstalk in various cancer types, which are closely associated with the progression of colorectal cancer (CRC). This study constructs a prognostic signature based on lipid metabolism and endoplasmic reticulum stress-related genes (LERGs) for CRC patients, aiming to predict the prognosis and immune response. RNA sequencing and clinical data from the TCGA and GEO databases were analyzed to identify differentially expressed LERGs with prognostic relevance using univariate Cox regression. Subsequently, a risk model was developed using the LASSO regression. CRC patients were stratified into low-risk and high-risk groups based on risk scores, with the high-risk cohort demonstrating a poorer clinical prognosis in multiple databases. The risk model showed robust correlations with clinical features, gene mutations, and treatment sensitivity. Significant differences in immune cell infiltration and the expression of immune-related factors were also detected between risk groups, and elevated scores of cytokines and failure factors were detected in single-cell RNA sequencing analysis. This research indicates that lipid metabolism and endoplasmic reticulum stress in CRC are correlated with tumor progression, an immunosuppressive landscape, and alterations of drug sensitivity. The developed risk model can serve as a powerful prognostic tool, offering critical insights for refining clinical management and optimizing treatment in CRC patients.