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Predicting cancer prognosis and drug response from the tumor microbiome

Tumor gene expression is predictive of patient prognosis in some cancers. However, RNA-seq and whole genome sequencing data contain not only reads from host tumor and normal tissue, but also reads from the tumor microbiome, which can be used to infer the microbial abundances in each tumor. Here, we...

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Autores principales: Hermida, Leandro C., Gertz, E. Michael, Ruppin, Eytan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9130323/
https://www.ncbi.nlm.nih.gov/pubmed/35610202
http://dx.doi.org/10.1038/s41467-022-30512-3
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author Hermida, Leandro C.
Gertz, E. Michael
Ruppin, Eytan
author_facet Hermida, Leandro C.
Gertz, E. Michael
Ruppin, Eytan
author_sort Hermida, Leandro C.
collection PubMed
description Tumor gene expression is predictive of patient prognosis in some cancers. However, RNA-seq and whole genome sequencing data contain not only reads from host tumor and normal tissue, but also reads from the tumor microbiome, which can be used to infer the microbial abundances in each tumor. Here, we show that tumor microbial abundances, alone or in combination with tumor gene expression, can predict cancer prognosis and drug response to some extent—microbial abundances are significantly less predictive of prognosis than gene expression, although similarly as predictive of drug response, but in mostly different cancer-drug combinations. Thus, it appears possible to leverage existing sequencing technology, or develop new protocols, to obtain more non-redundant information about prognosis and drug response from RNA-seq and whole genome sequencing experiments than could be obtained from tumor gene expression or genomic data alone.
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spelling pubmed-91303232022-05-26 Predicting cancer prognosis and drug response from the tumor microbiome Hermida, Leandro C. Gertz, E. Michael Ruppin, Eytan Nat Commun Article Tumor gene expression is predictive of patient prognosis in some cancers. However, RNA-seq and whole genome sequencing data contain not only reads from host tumor and normal tissue, but also reads from the tumor microbiome, which can be used to infer the microbial abundances in each tumor. Here, we show that tumor microbial abundances, alone or in combination with tumor gene expression, can predict cancer prognosis and drug response to some extent—microbial abundances are significantly less predictive of prognosis than gene expression, although similarly as predictive of drug response, but in mostly different cancer-drug combinations. Thus, it appears possible to leverage existing sequencing technology, or develop new protocols, to obtain more non-redundant information about prognosis and drug response from RNA-seq and whole genome sequencing experiments than could be obtained from tumor gene expression or genomic data alone. Nature Publishing Group UK 2022-05-24 /pmc/articles/PMC9130323/ /pubmed/35610202 http://dx.doi.org/10.1038/s41467-022-30512-3 Text en © This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Hermida, Leandro C.
Gertz, E. Michael
Ruppin, Eytan
Predicting cancer prognosis and drug response from the tumor microbiome
title Predicting cancer prognosis and drug response from the tumor microbiome
title_full Predicting cancer prognosis and drug response from the tumor microbiome
title_fullStr Predicting cancer prognosis and drug response from the tumor microbiome
title_full_unstemmed Predicting cancer prognosis and drug response from the tumor microbiome
title_short Predicting cancer prognosis and drug response from the tumor microbiome
title_sort predicting cancer prognosis and drug response from the tumor microbiome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9130323/
https://www.ncbi.nlm.nih.gov/pubmed/35610202
http://dx.doi.org/10.1038/s41467-022-30512-3
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