ArticleFrontiers in oncology2023
Taxonomic and functional profiling of fecal metagenomes for the early detection of colorectal cancer.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Gut microbiome biomarkers for colorectal cancer detection: a systematic review highlighting age as a key confounder.Frontiers in oncology · 2026Pooled it
- Integrative multicohort analysis reveals consistent sex differences in gut microbiota of multiple sclerosis patients.mSystems · 2026Article
- Gut fungal signatures in colorectal cancer and their potential for supporting diagnosis: a multi-cohort metagenomic analysis.Journal of translational medicine · 2026Article
- Virulome over taxonomy: refining the driver-passenger model in colorectal carcinogenesis.Frontiers in cellular and infection microbiology · 2026Review
- metadeconfoundR: Covariate analysis of high-dimensional cross-sectional omics data.Bioinformatics advances · 2026Article
- Gut Mucosal Microbiome of Patients With Low-Grade Adenomatous Bowel Polyps.Gastro hep advances · 2025Article
- Insights into the evolution and regulation of miRNAs from the view of their DNA replication temporal domains.Frontiers in genetics · 2025Article
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7 authors.
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Abstract
Objectives: This study aimed to identify colorectal cancer (CRC)-associated phylogenetic and functional bacterial features by a large-scale metagenomic sequencing and develop a binomial classifier to accurately distinguish between CRC patients and healthy individuals. Methods: We conducted shotgun metagenomic analyses of fecal samples from a ZhongShanMed discovery cohort of 121 CRC and 52 controls and SouthernMed validation cohort of 67 CRC and 44 controls. Taxonomic profiling and quantification were performed by direct sequence alignment against genome taxonomy database (GTDB). High-quality reads were also aligned to IGC datasets to obtain functional profiles defined by Kyoto Encyclopedia of Genes and Genomes (KEGG). A least absolute shrinkage and selection operator (LASSO) classifier was constructed to quantify risk scores of probability of disease and to discriminate CRC from normal for discovery, validation, Fudan, GloriousMed, and HongKong cohorts. Results: A diverse spectrum of bacterial and fungi species were found to be either enriched (368) or reduced (113) in CRC patients (q<0.05). Similarly, metabolic functions associated with biosynthesis and metabolism of amino acids and fatty acids were significantly altered (q<0.05). The LASSO regression analysis of significant changes in the abundance of microbial species in CRC achieved areas under the receiver operating characteristic curve (AUROCs) of 0.94 and 0.91 in the ZhongShanMed and SouthernMed cohorts, respectively. A further analysis of Fudan, GloriousMed, and HK cohorts using the same classification model also demonstrated AUROC of 0.80, 0.78, and 0.91, respectively. Moreover, major CRC-associated bacterial biomarkers identified in this study were found to be coherently enriched or depleted across 10 metagenomic sequencing studies of gut microbiota. Conclusion: A coherent signature of CRC-associated bacterial biomarkers modeled on LASSO binomial classifier maybe used accurately for early detection of CRC.
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