Multi-omics analysis reveals stage-associated differences in the gut microbiome ecosystem across stages of colorectal cancer in a cross-sectional cohort

The etiology of colorectal cancer (CRC) involves complex interactions among gut microbiota alterations, metabolic dysregulation, and disturbances in essential ions. The study aims to compare stage-associated differences in the gut microbiome ecosystem across CRC stages in a cross-sectional design, with no within-individual longitudinal sampling and therefore no direct observation of in-host progression. In this study, we performed comprehensive metagenomic, metabolomic, and ionomic analyses on 984 samples in a cross-sectional design to characterize gut microbiome‑associated signatures across different colorectal cancer (CRC) disease‑stage groups. Samples were categorized into six groups: low‑risk (individuals under 45 years of age with no intestinal lesions detected by colonoscopy), high‑risk (individuals ≥ 45 years of age with no intestinal lesions detected by colonoscopy), advanced adenoma (AA), stages I&II CRC, stage III CRC, and stage IV CRC. Metagenomic results showed that dominant genera including UBA7182 , Lachnoclostridium B. , Faecalibacillus , Fusicatenibacter , and Anaerobutyricum showed progressively lower relative abundance across more advanced CRC stage groups, whereas Intestinimonas and Bacteroides showed higher relative abundance. The comparison between high-risk and advanced-adenoma groups showed a marked decline in the detection rate of low-abundance taxa at the sequencing depth used in this study and reduced microbial diversity. Metabolomic analysis revealed age- and risk-group-associated differences between the low- and high-risk groups (< 45 vs. ≥ 45 years) that may largely reflect age and age-associated factors rather than early-disease biology, while putatively annotated metabolite features (MSI Level 2/3) mapped to eight candidate KEGG pathway modules. Elemental analysis indicated highest levels of strontium, iron, and phosphorus in CRC III, whereas beryllium predominated in low-risk individuals and sulfur was enriched in both low- and high-risk groups. Integrated multi-omics evidence indicates that microbiota, metabolites, and ionic profiles differ across CRC stage groups, including the earliest disease-stage groups. These cross-sectional, correlation-level findings are hypothesis-generating for further studies of CRC-stage-associated changes in the gut microbiome ecosystem and of its interplay with senescence; before any diagnostic application, the patterns described here would need to be validated in independent prospective cohorts. Two limitations warrant particular caution against over-interpretation: the low-risk and high-risk groups differ by age (< 45 vs. ≥ 45 years), so differences between them are confounded by age and cannot be fully adjusted; and no microbiome positive or negative controls (mock community, extraction blank, no-template) were included, so reagent and background contamination cannot be fully excluded and the low-abundance findings are exploratory.

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Publication Details

Journal
BMC Medicine
Published
2026-09-12
DOI
https://doi.org/10.1186/s12916-026-05218-8
Primary Topic
Gut microbiota and health
Type
article
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article

Multi-omics analysis reveals stage-associated differences in the gut microbiome ecosystem across stages of colorectal cancer in a cross-sectional cohort

Chu Caiyun, Xi Yang, Wei Wu, Qian Peng et al.
BMC Medicine
Gut microbiota and health
article

Multi-omics analysis reveals stage-associated differences in the gut microbiome ecosystem across stages of colorectal cancer in a cross-sectional cohort

Chu Caiyun, Xi Yang, Wei Wu, Qian Peng, Chu Jian, Wu Yinhang, Han Shuwen, Xu Yating, Li Shuwen, Wang Zefeng
article en

Abstract

The etiology of colorectal cancer (CRC) involves complex interactions among gut microbiota alterations, metabolic dysregulation, and disturbances in essential ions. The study aims to compare stage-associated differences in the gut microbiome ecosystem across CRC stages in a cross-sectional design, with no within-individual longitudinal sampling and therefore no direct observation of in-host progression. In this study, we performed comprehensive metagenomic, metabolomic, and ionomic analyses on 984 samples in a cross-sectional design to characterize gut microbiome‑associated signatures across different colorectal cancer (CRC) disease‑stage groups. Samples were categorized into six groups: low‑risk (individuals under 45 years of age with no intestinal lesions detected by colonoscopy), high‑risk (individuals ≥ 45 years of age with no intestinal lesions detected by colonoscopy), advanced adenoma (AA), stages I&II CRC, stage III CRC, and stage IV CRC. Metagenomic results showed that dominant genera including UBA7182 , Lachnoclostridium B. , Faecalibacillus , Fusicatenibacter , and Anaerobutyricum showed progressively lower relative abundance across more advanced CRC stage groups, whereas Intestinimonas and Bacteroides showed higher relative abundance. The comparison between high-risk and advanced-adenoma groups showed a marked decline in the detection rate of low-abundance taxa at the sequencing depth used in this study and reduced microbial diversity. Metabolomic analysis revealed age- and risk-group-associated differences between the low- and high-risk groups (< 45 vs. ≥ 45 years) that may largely reflect age and age-associated factors rather than early-disease biology, while putatively annotated metabolite features (MSI Level 2/3) mapped to eight candidate KEGG pathway modules. Elemental analysis indicated highest levels of strontium, iron, and phosphorus in CRC III, whereas beryllium predominated in low-risk individuals and sulfur was enriched in both low- and high-risk groups. Integrated multi-omics evidence indicates that microbiota, metabolites, and ionic profiles differ across CRC stage groups, including the earliest disease-stage groups. These cross-sectional, correlation-level findings are hypothesis-generating for further studies of CRC-stage-associated changes in the gut microbiome ecosystem and of its interplay with senescence; before any diagnostic application, the patterns described here would need to be validated in independent prospective cohorts. Two limitations warrant particular caution against over-interpretation: the low-risk and high-risk groups differ by age (< 45 vs. ≥ 45 years), so differences between them are confounded by age and cannot be fully adjusted; and no microbiome positive or negative controls (mock community, extraction blank, no-template) were included, so reagent and background contamination cannot be fully excluded and the low-abundance findings are exploratory.

BMC Medicine
Huzhou Normal University (CN), Tarim University (CN), Huzhou Central Hospital (CN), Institute of Modern Physics (CN), Hangzhou DAC Biotech (China) (CN), Institut Systèmes Intelligents et de Robotique (FR)
Life in Land
Openalex Percentile: Top 18%
Gut microbiota and health
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