Fecal Streptococcus Alteration Is Associated with Gastric Cancer Occurrence and Liver Metastasis

The gut microbiome plays an indispensable role in the occurrence and progression of various diseases. However, its ability to predict gastric cancer (GC) and liver metastasis (GCLM) has not been fully identified. Fecal samples were collected from 49 GC patients (cancer group [group C]) and 49 healthy people (normal group [group N]) between 4 July 2020 and 9 March 2021. Furthermore, 26 patients with metastatic GC were divided into a liver metastatic group (group L) (n = 13) and a non-liver-metastatic group (group M) (n = 13). DNA was extracted, and 16S rRNA gene sequencing was performed. SPSS was used for statistical analyses, and all bioinformatics analyses were based on QIIME2. P values of <0.05 were considered statistically significant. The microbial richness and diversity in group C were higher than those in group N, and there were significant differences in species compositions between the two groups. Streptococcus, enriched in groups C and L by linear discriminant analysis (LDA) effect size (LEfSe) and further identified by a random forest (RF) model, enhances its potential as a biomarker for GC and GCLM. Functional gene and metabolic pathway analyses showed that d-galacturonate degradation pathway II was of great importance in the occurrence and development of GC. Streptococcus has the potential ability to predict GC and GCLM, which is critical for the early diagnosis of GC and GCLM. IMPORTANCE The gut microbiome plays an indispensable role in the occurrence and progression of various diseases. However, its ability to predict gastric cancer (GC) and liver metastasis (GCLM) has not been fully identified. We retrospectively analyzed 49 untreated GC patients and 49 matched healthy people between 4 July 2020 and 9 March 2021. By extracting DNA from their fecal samples and sequencing the 16S rRNA gene, we found that Streptococcus alteration was strongly associated with GC occurrence and liver metastasis, which might be a potential biomarker in predicting GC and GCLM, and the results of this study are helpful in providing ideas for the early diagnosis and treatment of GC.