Leveraging Existing 16S rRNA Gene Surveys To Identify Reproducible Biomarkers in Individuals with Colorectal Tumors

ABSTRACT An increasing body of literature suggests that both individual and collections of bacteria are associated with the progression of colorectal cancer. As the number of studies investigating these associations increases and the number of subjects in each study increases, a meta-analysis to ide...

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Autores principales:	Marc A. Sze, Patrick D. Schloss
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2018
Materias:	16S rRNA adenoma biomarkers carcinoma colorectal cancer diagnostic Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/62e82a78deb34a7680dd0ffc683c76ac
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spelling	oai:doaj.org-article:62e82a78deb34a7680dd0ffc683c76ac2021-11-15T16:00:26ZLeveraging Existing 16S rRNA Gene Surveys To Identify Reproducible Biomarkers in Individuals with Colorectal Tumors10.1128/mBio.00630-182150-7511https://doaj.org/article/62e82a78deb34a7680dd0ffc683c76ac2018-07-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mBio.00630-18https://doaj.org/toc/2150-7511ABSTRACT An increasing body of literature suggests that both individual and collections of bacteria are associated with the progression of colorectal cancer. As the number of studies investigating these associations increases and the number of subjects in each study increases, a meta-analysis to identify the associations that are the most predictive of disease progression is warranted. We analyzed previously published 16S rRNA gene sequencing data collected from feces and colon tissue. We quantified the odds ratios (ORs) for individual bacterial taxa that were associated with an individual having tumors relative to a normal colon. Among the fecal samples, there were no taxa that had significant ORs associated with adenoma and there were 8 taxa with significant ORs associated with carcinoma. Similarly, among the tissue samples, there were no taxa that had a significant OR associated with adenoma and there were 3 taxa with significant ORs associated with carcinoma. Among the significant ORs, the association between individual taxa and tumor diagnosis was equal to or below 7.11. Because individual taxa had limited association with tumor diagnosis, we trained Random Forest classification models using only the taxa that had significant ORs, using the entire collection of taxa found in each study, and using operational taxonomic units defined based on a 97% similarity threshold. All training approaches yielded similar classification success as measured using the area under the curve. The ability to correctly classify individuals with adenomas was poor, and the ability to classify individuals with carcinomas was considerably better using sequences from feces or tissue. IMPORTANCE Colorectal cancer is a significant and growing health problem in which animal models and epidemiological data suggest that the colonic microbiota have a role in tumorigenesis. These observations indicate that the colonic microbiota is a reservoir of biomarkers that may improve our ability to detect colonic tumors using noninvasive approaches. This meta-analysis identifies and validates a set of 8 bacterial taxa that can be used within a Random Forest modeling framework to differentiate individuals as having normal colons or carcinomas. When models trained using one data set were tested on other data sets, the models performed well. These results lend support to the use of fecal biomarkers for the detection of tumors. Furthermore, these biomarkers are plausible candidates for further mechanistic studies into the role of the gut microbiota in tumorigenesis.Marc A. SzePatrick D. SchlossAmerican Society for Microbiologyarticle16S rRNAadenomabiomarkerscarcinomacolorectal cancerdiagnosticMicrobiologyQR1-502ENmBio, Vol 9, Iss 3 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	16S rRNA adenoma biomarkers carcinoma colorectal cancer diagnostic Microbiology QR1-502
spellingShingle	16S rRNA adenoma biomarkers carcinoma colorectal cancer diagnostic Microbiology QR1-502 Marc A. Sze Patrick D. Schloss Leveraging Existing 16S rRNA Gene Surveys To Identify Reproducible Biomarkers in Individuals with Colorectal Tumors
description	ABSTRACT An increasing body of literature suggests that both individual and collections of bacteria are associated with the progression of colorectal cancer. As the number of studies investigating these associations increases and the number of subjects in each study increases, a meta-analysis to identify the associations that are the most predictive of disease progression is warranted. We analyzed previously published 16S rRNA gene sequencing data collected from feces and colon tissue. We quantified the odds ratios (ORs) for individual bacterial taxa that were associated with an individual having tumors relative to a normal colon. Among the fecal samples, there were no taxa that had significant ORs associated with adenoma and there were 8 taxa with significant ORs associated with carcinoma. Similarly, among the tissue samples, there were no taxa that had a significant OR associated with adenoma and there were 3 taxa with significant ORs associated with carcinoma. Among the significant ORs, the association between individual taxa and tumor diagnosis was equal to or below 7.11. Because individual taxa had limited association with tumor diagnosis, we trained Random Forest classification models using only the taxa that had significant ORs, using the entire collection of taxa found in each study, and using operational taxonomic units defined based on a 97% similarity threshold. All training approaches yielded similar classification success as measured using the area under the curve. The ability to correctly classify individuals with adenomas was poor, and the ability to classify individuals with carcinomas was considerably better using sequences from feces or tissue. IMPORTANCE Colorectal cancer is a significant and growing health problem in which animal models and epidemiological data suggest that the colonic microbiota have a role in tumorigenesis. These observations indicate that the colonic microbiota is a reservoir of biomarkers that may improve our ability to detect colonic tumors using noninvasive approaches. This meta-analysis identifies and validates a set of 8 bacterial taxa that can be used within a Random Forest modeling framework to differentiate individuals as having normal colons or carcinomas. When models trained using one data set were tested on other data sets, the models performed well. These results lend support to the use of fecal biomarkers for the detection of tumors. Furthermore, these biomarkers are plausible candidates for further mechanistic studies into the role of the gut microbiota in tumorigenesis.
format	article
author	Marc A. Sze Patrick D. Schloss
author_facet	Marc A. Sze Patrick D. Schloss
author_sort	Marc A. Sze
title	Leveraging Existing 16S rRNA Gene Surveys To Identify Reproducible Biomarkers in Individuals with Colorectal Tumors
title_short	Leveraging Existing 16S rRNA Gene Surveys To Identify Reproducible Biomarkers in Individuals with Colorectal Tumors
title_full	Leveraging Existing 16S rRNA Gene Surveys To Identify Reproducible Biomarkers in Individuals with Colorectal Tumors
title_fullStr	Leveraging Existing 16S rRNA Gene Surveys To Identify Reproducible Biomarkers in Individuals with Colorectal Tumors
title_full_unstemmed	Leveraging Existing 16S rRNA Gene Surveys To Identify Reproducible Biomarkers in Individuals with Colorectal Tumors
title_sort	leveraging existing 16s rrna gene surveys to identify reproducible biomarkers in individuals with colorectal tumors
publisher	American Society for Microbiology
publishDate	2018
url	https://doaj.org/article/62e82a78deb34a7680dd0ffc683c76ac
work_keys_str_mv	AT marcasze leveragingexisting16srrnagenesurveystoidentifyreproduciblebiomarkersinindividualswithcolorectaltumors AT patrickdschloss leveragingexisting16srrnagenesurveystoidentifyreproduciblebiomarkersinindividualswithcolorectaltumors
_version_	1718426969537773568

Leveraging Existing 16S rRNA Gene Surveys To Identify Reproducible Biomarkers in Individuals with Colorectal Tumors

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