Cited by 254Gut microbiota and healthColorectal Cancer Treatments and StudiesColorectal Cancer Screening and Detection

Integrated metagenomic and metabolomic analysis reveals distinct gut-microbiome-derived phenotypes in early-onset colorectal cancer

Kong, Cheng, Liang, Lei, Liu, Guang, Du, Lutao, Yang, Yongzhi, Liu, Jianqiang, Shi, Debing, Li, Xinxiang +1 more·2023·Gut

Abstract

Objective: The incidence of early-onset colorectal cancer (EO-CRC) is steadily increasing. Here, we aimed to characterise the interactions between gut microbiome, metabolites and microbial enzymes in EO-CRC patients and evaluate their potential as non-invasive biomarkers for EO-CRC. Design: We performed metagenomic and metabolomic analyses, identified multiomics markers and constructed CRC classifiers for the discovery cohort with 130 late-onset CRC (LO-CRC), 114 EO-CRC subjects and age-matched healthy controls (97 LO-Control and 100 EO-Control). An independent cohort of 38 LO-CRC, 24 EO-CRC, 22 LO-Controls and 24 EO-Controls was analysed to validate the results. Results: Compared with controls, reduced alpha-diversity was apparent in both, LO-CRC and EO-CRC subjects. Although common variations existed, integrative analyses identified distinct microbiome–metabolome associations in LO-CRC and EO-CRC. Fusobacterium nucleatum enrichment and short-chain fatty acid depletion, including reduced microbial GABA biosynthesis and a shift in acetate/acetaldehyde metabolism towards acetyl-CoA production characterises LO-CRC. In comparison, multiomics signatures of EO-CRC tended to be associated with enriched Flavonifractor plauti and increased tryptophan, bile acid and choline metabolism. Notably, elevated red meat intake-related species, choline metabolites and KEGG orthology (KO) pldB and cbh gene axis may be potential tumour stimulators in EO-CRC. The predictive model based on metagenomic, metabolomic and KO gene markers achieved a powerful classification performance for distinguishing EO-CRC from controls. Conclusion: Our large-sample multiomics data suggest that altered microbiome–metabolome interplay helps explain the pathogenesis of EO-CRC and LO-CRC. The potential of microbiome-derived biomarkers as promising non-invasive tools could be used for the accurate detection and distinction of individuals with EO-CRC.

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Crossref · 10.1136/gutjnl-2022-327156

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Authors
Kong, C., Liang, L., Liu, G., Du, L., Yang, Y., Liu, J., Shi, D., Li, X., & Ma, Y.
Affiliations
  • Shanghai Medical College of Fudan University (CN)
  • Guangdong Hongyuan Pukang Medical Technology Co., Ltd, Guangdong, China
  • Second Hospital of Shandong University (CN)
  • Fudan University Shanghai Cancer Center (CN)
Corresponding author
Ma, Yanlei
Venue
Gut
Publisher
BMJ
Published
2022-08-11
Volume
72
Issue
6
Pages
1129-1142
ISSN
  • 0017-5749 (ISSN-L)
  • 1468-3288
OpenAlex
W4296580963
Cited by
254
References
60
Citations by year
2026: 50 · 2025: 79 · 2024: 79 · 2023: 41 · 2022: 5
FWCI
16.64
Type
journal article
Language
en
Open access
closed
Locations
  • Gut (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Fudan University Excellence 2025 Talent Cultivation Plan (for Dr. Yanlei Ma)
  • CSCO-Roche Tumor Research Fund (No. Y-2019Roche-079)
  • National Natural Science Foundation of China (81871964, 81920108026)
  • Science and Technology Development Fund (19410713300)
  • the Program of Shanghai Academic Research Leader (20XD1421200)
  • the National Ten Thousand Plan Young Top Talents (for Dr. Yanlei Ma)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Medicine › Oncology › Colorectal Cancer Treatments and Studies
  • Health Sciences › Medicine › Oncology › Colorectal Cancer Screening and Detection
Keywords
early-onset colorectal cancer, late-onset colorectal cancer, gut microbiota, gut metabolome, microbiome-metabolome interactions, non-invasive biomarkers, Fusobacterium nucleatum, short-chain fatty acids, GABA synthesis, Flavonifractor plautii, tryptophan metabolism, bile acid metabolism, choline metabolism, red meat consumption, microbial enzymes
MeSH terms
Gastrointestinal Microbiome, Choline, Humans, Phenotype, Colorectal Neoplasms, Microbiota

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