The human gut microbiome as a screening tool for colorectal cancer
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Abstract
Recent studies have suggested that the gut microbiome may be an important factor in the development of colorectal cancer. Abnormalities in the gut microbiome have been reported in patients with colorectal cancer; however, this microbial community has not been explored as a potential screen for early-stage disease. We characterized the gut microbiome in patients from three clinical groups representing the stages of colorectal cancer development: healthy, adenoma, and carcinoma. Analysis of the gut microbiome from stool samples revealed both an enrichment and depletion of several bacterial populations associated with adenomas and carcinomas. Combined with known clinical risk factors of colorectal cancer (e.g., BMI, age, race), data from the gut microbiome significantly improved the ability to differentiate between healthy, adenoma, and carcinoma clinical groups relative to risk factors alone. Using Bayesian methods, we determined that using gut microbiome data as a screening tool improved the pretest to posttest probability of adenoma more than 50-fold. For example, the pretest probability in a 65-year-old was 0.17% and, after using the microbiome data, this increased to 10.67% (1 in 9 chance of having an adenoma). Taken together, the results of our study demonstrate the feasibility of using the composition of the gut microbiome to detect the presence of precancerous and cancerous lesions. Furthermore, these results support the need for more cross-sectional studies with diverse populations and linkage to other stool markers, dietary data, and personal health information.
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Fecal microbiome studies using 16S rRNA or shotgun metagenomic sequencing found Fusobacterium nucleatum increased in fecal samples from colorectal cancer or adenoma patients compared with controls.
“studies of fecal microbiomes that used either 16s rRNA or shotgun metagenomic sequencing found that F nucleatum to be increased in fecal samples from patients with CRC or adenoma compared with controls (Table 1).15, 18, 35–39”
From Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer (2020) · cites this paper as [35]
Enterotoxigenic Bacteroides fragilis is enriched in fecal samples of colorectal cancer patients compared with controls.
“However, ETBF was reported to be enriched in fecal samples of patients with CRC compared with controls.35, 44, 45”
From Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer (2020) · cites this paper as [35]
Besides Fusobacterium, other oral bacteria and periodontal disease markers are enriched in colorectal tumors and feces, including Porphyromonas, Peptostreptococcus, and Parvimonas micra.
“Besides Fusobacterium, other oral bacteria and markers of periodontal disease are enriched in colorectal tumors and feces of patients, including the genera of Porphyromonas and Peptostreptococcus, and Parvimonas micra.15, 35, 37, 38, 53”
From Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer (2020) · cites this paper as [35]
Compared with controls, colorectal cancer patients had lower abundances of Bifidobacterium and Lactobacillus spp. and other short-chain fatty acid-producing bacteria such as Clostridium, Roseburia, Lachnospiraceae, and Faecalibacterium prausnitzii.
“several studies have shown that compared with controls, patients with CRC had lower abundances of Bifidobacterium and Lactobacillus spp,16, 18 and other SCFA-producing bacteria, such as the genera Clostridium and Roseburia, the family Lachnospiraceae, and Faecalibacterium prausnitzii.15, 35, 37, 45, 53, 129”
From Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer (2020) · cites this paper as [35]
Adding stool microbiome data to risk-factor model scores or to screening tests like FOBT and FIT improves detection accuracy for advanced adenomas.
“Combining the fecal microbiome data with scores from risk factor-based models or results of screening tests (such as fecal occult blood test and fecal immunochemical test) increases the accuracy of detection for advanced adenomas.35, 186, 187”
From Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer (2020) · cites this paper as [35]
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- Authors
- Zackular, J. P., Rogers, M. A. M., Ruffin, M. T., & Schloss, P. D.
- Affiliations
- University of Michigan (US)
- Corresponding author
- Schloss, Patrick D.
- Venue
- Cancer Prevention Research
- Published
- 2014-11-01
- Volume
- 7
- Issue
- 11
- Pages
- 1112-1121
- ISSN
- 1940-6207 (ISSN-L)
- 1940-6215
- PMC
- PMC4221363
- OpenAlex
- W2096604969
- Cited by
- 551
- References
- 50
- Citations by year
- 2026: 21 · 2025: 36 · 2024: 49 · 2023: 44 · 2022: 51 · 2021: 65 · 2020: 55 · 2019: 45 · 2018: 60 · 2017: 58 · 2016: 40 · 2015: 23 · 2014: 4
- FWCI
- 17.10
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Cancer Prevention Research (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Human Genome Research Institute (R01HG005975)
- National Cancer Institute (5U01CA86400, U01CA086400)
- National Institute of General Medical Sciences (R01GM099514)
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK034933)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Medicine › Oncology › Colorectal Cancer Screening and Detection
- Health Sciences › Medicine › Pathology and Forensic Medicine › Genetic factors in colorectal cancer
- Keywords
- gut microbiota, colorectal cancer screening, colorectal adenoma, colorectal cancer, precancerous lesions, stool microbiome, Bayesian probability, risk factors, early cancer detection, bacterial community composition
- MeSH terms
- Adenoma, Aged, Bayes Theorem, Carcinoma, Feces, Female, Humans, Intestines, Male, Middle Aged, Occult Blood, Predictive Value of Tests, Probability, Risk Factors, RNA, Ribosomal, 16S, Colorectal Neoplasms, Biomarkers, Area Under Curve, Early Detection of Cancer, Microbiota
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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