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Microbiota-based model improves the sensitivity of fecal immunochemical test for detecting colonic lesions.
Genome Med. 2016 Apr 06; 8(1):37.GM

Abstract

BACKGROUND

Colorectal cancer (CRC) is the second leading cause of death among cancers in the United States. Although individuals diagnosed early have a greater than 90% chance of survival, more than one-third of individuals do not adhere to screening recommendations partly because the standard diagnostics, colonoscopy and sigmoidoscopy, are expensive and invasive. Thus, there is a great need to improve the sensitivity of non-invasive tests to detect early stage cancers and adenomas. Numerous studies have identified shifts in the composition of the gut microbiota associated with the progression of CRC, suggesting that the gut microbiota may represent a reservoir of biomarkers that would complement existing non-invasive methods such as the widely used fecal immunochemical test (FIT).

METHODS

We sequenced the 16S rRNA genes from the stool samples of 490 patients. We used the relative abundances of the bacterial populations within each sample to develop a random forest classification model that detects colonic lesions using the relative abundance of gut microbiota and the concentration of hemoglobin in stool.

RESULTS

The microbiota-based random forest model detected 91.7% of cancers and 45.5% of adenomas while FIT alone detected 75.0% and 15.7%, respectively. Of the colonic lesions missed by FIT, the model detected 70.0% of cancers and 37.7% of adenomas. We confirmed known associations of Porphyromonas assaccharolytica, Peptostreptococcus stomatis, Parvimonas micra, and Fusobacterium nucleatum with CRC. Yet, we found that the loss of potentially beneficial organisms, such as members of the Lachnospiraceae, was more predictive for identifying patients with adenomas when used in combination with FIT.

CONCLUSIONS

These findings demonstrate the potential for microbiota analysis to complement existing screening methods to improve detection of colonic lesions.

Authors+Show Affiliations

Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, USA.Department of Family Medicine, University of Michigan, Ann Arbor, MI, USA.Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, USA. pschloss@umich.edu.

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural

Language

eng

PubMed ID

27056827

Citation

Baxter, Nielson T., et al. "Microbiota-based Model Improves the Sensitivity of Fecal Immunochemical Test for Detecting Colonic Lesions." Genome Medicine, vol. 8, no. 1, 2016, p. 37.
Baxter NT, Ruffin MT, Rogers MA, et al. Microbiota-based model improves the sensitivity of fecal immunochemical test for detecting colonic lesions. Genome Med. 2016;8(1):37.
Baxter, N. T., Ruffin, M. T., Rogers, M. A., & Schloss, P. D. (2016). Microbiota-based model improves the sensitivity of fecal immunochemical test for detecting colonic lesions. Genome Medicine, 8(1), 37. https://doi.org/10.1186/s13073-016-0290-3
Baxter NT, et al. Microbiota-based Model Improves the Sensitivity of Fecal Immunochemical Test for Detecting Colonic Lesions. Genome Med. 2016 Apr 6;8(1):37. PubMed PMID: 27056827.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Microbiota-based model improves the sensitivity of fecal immunochemical test for detecting colonic lesions. AU - Baxter,Nielson T, AU - Ruffin,Mack T,4th AU - Rogers,Mary A M, AU - Schloss,Patrick D, Y1 - 2016/04/06/ PY - 2015/10/13/received PY - 2016/03/16/accepted PY - 2016/4/9/entrez PY - 2016/4/9/pubmed PY - 2016/10/14/medline SP - 37 EP - 37 JF - Genome medicine JO - Genome Med VL - 8 IS - 1 N2 - BACKGROUND: Colorectal cancer (CRC) is the second leading cause of death among cancers in the United States. Although individuals diagnosed early have a greater than 90% chance of survival, more than one-third of individuals do not adhere to screening recommendations partly because the standard diagnostics, colonoscopy and sigmoidoscopy, are expensive and invasive. Thus, there is a great need to improve the sensitivity of non-invasive tests to detect early stage cancers and adenomas. Numerous studies have identified shifts in the composition of the gut microbiota associated with the progression of CRC, suggesting that the gut microbiota may represent a reservoir of biomarkers that would complement existing non-invasive methods such as the widely used fecal immunochemical test (FIT). METHODS: We sequenced the 16S rRNA genes from the stool samples of 490 patients. We used the relative abundances of the bacterial populations within each sample to develop a random forest classification model that detects colonic lesions using the relative abundance of gut microbiota and the concentration of hemoglobin in stool. RESULTS: The microbiota-based random forest model detected 91.7% of cancers and 45.5% of adenomas while FIT alone detected 75.0% and 15.7%, respectively. Of the colonic lesions missed by FIT, the model detected 70.0% of cancers and 37.7% of adenomas. We confirmed known associations of Porphyromonas assaccharolytica, Peptostreptococcus stomatis, Parvimonas micra, and Fusobacterium nucleatum with CRC. Yet, we found that the loss of potentially beneficial organisms, such as members of the Lachnospiraceae, was more predictive for identifying patients with adenomas when used in combination with FIT. CONCLUSIONS: These findings demonstrate the potential for microbiota analysis to complement existing screening methods to improve detection of colonic lesions. SN - 1756-994X UR - https://www.unboundmedicine.com/medline/citation/27056827/Microbiota_based_model_improves_the_sensitivity_of_fecal_immunochemical_test_for_detecting_colonic_lesions_ L2 - https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-016-0290-3 DB - PRIME DP - Unbound Medicine ER -