Yiwen Wang ^1,2 Yue Wang ^1,2 Wenjie Han ^1,2 Mengzhen Han ^1,2 Xiaolin Liu ³ Jianying Dai ⁴ Yuesheng Dong ⁴ Tao Sun ^1,5,6* Junnan Xu ^1,2,6*

• ¹ Department of Breast Medicine 1, Cancer Hospital of China Medical University, Liaoning Cancer Hospital, Shenyang, Liaoning Province, China
• ² Department of Pharmacology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital, Shenyang, China
• ³ Department of Bioinformatics, Kanghui Biotechnology Co., Ltd., Shenyang, China
• ⁴ School of Bioengineering, Dalian University of Technology, Dalian, China
• ⁵ Department of Oncology Medicine, Key Laboratory of Liaoning Breast Cancer Research, Shenyang, China
• ⁶ Department of Breast Medicine, Cancer Hospital of Dalian University of Technology, Liaoning Cancer Hospital, Shenyang, Liaoning Province, China

The relationship between dysbiosis of the gastrointestinal microbiota and gastric cancer (GC) has been extensively studied. However, microbiota alterations in GC patients vary widely across studies, and reproducible diagnostic biomarkers for early GC are still lacking in multiple populations. Thus, this study aimed to characterize the gastrointestinal microbial communities involved in gastric carcinogenesis through a meta-analysis of multiple published and open datasets. The α-diversity of results indicated significant differences in the intratumoral microbiota of cancer patients compared to non-cancer patients, while no significant differences were observed in the fecal microbiota. Network analysis showed that the positive correlation with GC-Microbiota in gastric cancer 2 enriched bacteria increased, and the positive correlation with GC-depleted bacteria decreased compared to healthy individuals. Functional analyses indicated that pathways related to carbohydrate metabolism were significantly enriched in GC, while biosynthesis of unsaturated fatty acids was diminished. Additionally, we investigated non-Helicobacter pylori (HP) commensals, which are crucial in both HP-negative and HP-positive GC. Random forest models, constructed using specific taxa associated with GC identified from the LEfSe analysis, revealed that the combination of Lactobacillus and Streptococcus included alone could effectively discriminate between GC patients and healthy individuals in fecal samples (area under the curve (AUC) = 0.7949). This finding was also validated in an independent cohort (AUC = 0.7712). This study confirms the validity of GC-specific microbial markers across multiple populations, which may aid in the early non-invasive diagnosis of GC.