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

Cheng Kong; Lei Liang; Guang Liu; Lutao Du; Yongzhi Yang; Jianqiang Liu; Debing Shi; Xinxiang Li; Yanlei Ma

doi:10.1136/gutjnl-2022-327156

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

Gut. 2023 Jun;72(6):1129-1142. doi: 10.1136/gutjnl-2022-327156. Epub 2022 Aug 11.

Authors

Cheng Kong^#^{1

2}, Lei Liang^#^{1

2}, Guang Liu^#³, Lutao Du^#⁴, Yongzhi Yang^#^{1

2}, Jianqiang Liu⁵, Debing Shi^{1

2}, Xinxiang Li^{1

2}, Yanlei Ma^{6

2}

Affiliations

¹ Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
² Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
³ Guangdong Hongyuan Pukang Medical Technology Co., Ltd, Guangdong, China.
⁴ Department of Clinical Laboratory, The Second Hospital of Shandong University, Jinan, Shandong province, China.
⁵ Department of Endoscopy, Fudan University Shanghai Cancer Center, Shanghai, China.
⁶ Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, Shanghai, China yanleima@fudan.edu.cn.

^# Contributed equally.

PMID: 35953094
DOI: 10.1136/gutjnl-2022-327156

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.

Keywords: COLORECTAL CANCER.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Choline
Colorectal Neoplasms* / diagnosis
Gastrointestinal Microbiome* / genetics
Humans
Microbiota*
Phenotype

Substances

Choline