Background and Aims: Precancerous lesions of gastric cancer (PLGC) are the most important pathological phase with increased risk of gastric cancer (GC) and encompass the key stage in which the occurrence of GC can be prevented. In this study, we found that the gut microbiome changed significantly during the process of malignant transformation from chronic gastritis to GC in N-methyl-N'-nitro-N-nitrosoguanidine (MNNG) multiple factors-induced rat model. Accumulating evidence has shown that alterations in gut microbiota and metabolism are potentially linked to chronic inflammation and cancer of the gastrointestinal tract. However, the correlation of gut microbiota and metabolites, inflammatory factors, and the potential mechanism in the formation of PLGC have not yet been revealed. Methods: In this study, multiple factors including MNNG, sodium salicylate drinking, ranitidine feed, and irregular diet were used to establish a PLGC rat model. The pathological state of the gastric mucosa of rats was identified through HE staining and the main inflammatory cytokine levels in the serum were detected by the Luminex liquid suspension chip (Wayen Biotechnologies, Shanghai, China). The microbial composition and metabolites in the stool samples were tested by using 16S ribosomal RNA (rRNA) gene sequencing and non-targeted metabolomics. The correlation analysis of gut microbiota and inflammatory cytokines in the serum and gut microbiota and differential metabolites in feces was performed to clarify their biological function. Results: The results showed that compared to the control group, the gastric mucosa of the model rats had obvious morphological and pathological malignant changes and the serum levels of inflammatory cytokines including interleukin-1β (IL-1β), interleukin-4 (IL-4), interleukin-6 (IL-6), interleukin-10 (IL-10), interferon-γ (IFN-γ), tumor necrosis factor-α (TNF-α), and macrophage colony-stimulating factor (M-CSF) increased significantly, while the level of chemokine (C-X-C motif) ligand 1 (CXCL1) in serum reduced significantly. There were significant differences in the composition of the gut microbiota and fecal metabolic profiles between the model and control rats. Among them, Lactobacillus and Bifidobacterium increased significantly, while Turicibacter, Romboutsia, Ruminococcaceae_UCG-014, Ruminococcaceae_UCG-005, and Ruminococcus_1 reduced significantly in the model rats compared to the control rats. The metabolites related to the lipid metabolism and peroxisome proliferator-activated receptor (PPAR) signaling pathway have also undergone significant changes. In addition, there was a significant correlation between the changes of the differential inflammatory cytokines in the serum, fecal metabolic phenotypes, and gut microbial dysbiosis in model rats. Conclusion: The activation of the inflammatory response, disturbance of the gut microbiota, and changes in the fecal metabolic phenotype could be closely related to the occurrence of PLGC. This study provides a new idea to reveal the mechanism of risk factors of chronic gastritis and GC from the perspective of inflammation-immune homeostasis, gut microbiota, and metabolic function balance.

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