Journal of Medical Molecular Biology ›› 2026, Vol. 23 ›› Issue (5): 502-513.doi: 10.3870/j.issn.1672-8009.2026.05.004

• Original Articles • Previous Articles     Next Articles

Metagenomic Meta-Analysis of Gut Microbiome in Different Primary Locations of Colorectal Cancer

LIAO Zhicheng, LONG Xiawei, LI Qian, WANG Zongjia, LIN Youzhi, LI Yongqiang, LIAO Xiaoli   

  1. Department of First Chemotherapy, Guangxi Medical University Cancer Hospital, Nanning, 530021, China
  • Received:2025-12-08 Online:2026-09-30 Published:2026-09-30
  • Contact: LIAO Xiaoli (E-mail:nllxl@163.com)
  • About author:#:These authors contributed equally as first author.
  • Supported by:
    Guangxi Key Research and Development Program(No. Gui Ke AB25069073), Natural Science Foundation of Guangxi Province(No. 2023GXNSFAA026156,No.2023GXNSFAA026145), Regional Fund of National Natural Science Foundation of China(No. 82060545)

Abstract: Objective The intestinal microbiota is related to the primary site of colorectal cancer (CRC). To explore the differences in the intestinal microbiome among different primary sites of colorectal cancer, this study conducted a meta-analysis using comprehensive genomic data. Methods Genomic data were collected from three studies and grouped according to three sites: right-sided colon cancer (RCC), left-sided colon cancer (LCC), and rectal cancer (RC). Firstly, confounding factors were identified through two-factor variance analysis and comparison of microbial diversity. Subsequently, a microbial co-occurrence network was constructed. A random forest algorithm was used to build a prediction model for the location of the primary tumor. Finally, tumor location and confounding factors were incorporated into the Maaslin2 (microbiome multivariable associations with linear models) model and linear discriminant analysis (LDA) was used to identify differentially expressed species. Results The sources of research and BMI are the main confounding factors. There is no significant difference in the α/β diversity of intestinal microbiota among different tumor sites. The Actinobacteria phylum, Firmicutes phylum, and Proteobacteria phylum all play key linking roles in the three microbial networks, and the Bacteroidetes phylum is more significant in the microbial network of RCC. There are both common key bacterial groups and their own unique key bacterial groups in the three networks. The random forest classification model performs well in predicting RC, but performs poorly in distinguishing RCC from LCC. By comparing CC with RC, and comparing RCC with LCC, some of the differential bacterial groups identified by Maaslin2 and LDA have been reported to be related to molecular and immune characteristics of CRC location. Conclusion This study elucidated the relationship between gut microbiome and CRC location and confirmed that RCC, LCC, and RC had different enrich patterns of microbiota.

Key words: metagenomic, microbiome, colorectal cancer, tumor location, meta-analysis

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