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Meta-analysis of the gut microbiota in predicting response to cancer immunotherapy in metastatic melanoma
BACKGROUND: Identifying factors conferring responses to therapy in cancer is critical to select the best treatment for patients. For immune checkpoint inhibition (ICI) therapy, mounting evidence suggests that the gut microbiome can determine patient treatment outcomes. However, the extent to which g...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Clinical Investigation
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7714408/ https://www.ncbi.nlm.nih.gov/pubmed/33268597 http://dx.doi.org/10.1172/jci.insight.140940 |
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author | Limeta, Angelo Ji, Boyang Levin, Max Gatto, Francesco Nielsen, Jens |
author_facet | Limeta, Angelo Ji, Boyang Levin, Max Gatto, Francesco Nielsen, Jens |
author_sort | Limeta, Angelo |
collection | PubMed |
description | BACKGROUND: Identifying factors conferring responses to therapy in cancer is critical to select the best treatment for patients. For immune checkpoint inhibition (ICI) therapy, mounting evidence suggests that the gut microbiome can determine patient treatment outcomes. However, the extent to which gut microbial features are applicable across different patient cohorts has not been extensively explored. METHODS: We performed a meta-analysis of 4 published shotgun metagenomic studies (N(tot) = 130 patients) investigating differential microbiome composition and imputed metabolic function between responders and nonresponders to ICI. RESULTS: Our analysis identified both known microbial features enriched in responders, such as Faecalibacterium as the prevailing taxa, as well as additional features, including overrepresentation of Barnesiella intestinihominis and the components of vitamin B metabolism. A classifier designed to predict responders based on these features identified responders in an independent cohort of 27 patients with the area under the receiver operating characteristic curve of 0.625 (95% CI: 0.348–0.899) and was predictive of prognosis (HR = 0.35, P = 0.081). CONCLUSION: These results suggest the existence of a fecal microbiome signature inherent across responders that may be exploited for diagnostic or therapeutic purposes. FUNDING: This work was funded by the Knut and Alice Wallenberg Foundation, BioGaia AB, and Cancerfonden. |
format | Online Article Text |
id | pubmed-7714408 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Society for Clinical Investigation |
record_format | MEDLINE/PubMed |
spelling | pubmed-77144082020-12-08 Meta-analysis of the gut microbiota in predicting response to cancer immunotherapy in metastatic melanoma Limeta, Angelo Ji, Boyang Levin, Max Gatto, Francesco Nielsen, Jens JCI Insight Clinical Medicine BACKGROUND: Identifying factors conferring responses to therapy in cancer is critical to select the best treatment for patients. For immune checkpoint inhibition (ICI) therapy, mounting evidence suggests that the gut microbiome can determine patient treatment outcomes. However, the extent to which gut microbial features are applicable across different patient cohorts has not been extensively explored. METHODS: We performed a meta-analysis of 4 published shotgun metagenomic studies (N(tot) = 130 patients) investigating differential microbiome composition and imputed metabolic function between responders and nonresponders to ICI. RESULTS: Our analysis identified both known microbial features enriched in responders, such as Faecalibacterium as the prevailing taxa, as well as additional features, including overrepresentation of Barnesiella intestinihominis and the components of vitamin B metabolism. A classifier designed to predict responders based on these features identified responders in an independent cohort of 27 patients with the area under the receiver operating characteristic curve of 0.625 (95% CI: 0.348–0.899) and was predictive of prognosis (HR = 0.35, P = 0.081). CONCLUSION: These results suggest the existence of a fecal microbiome signature inherent across responders that may be exploited for diagnostic or therapeutic purposes. FUNDING: This work was funded by the Knut and Alice Wallenberg Foundation, BioGaia AB, and Cancerfonden. American Society for Clinical Investigation 2020-12-03 /pmc/articles/PMC7714408/ /pubmed/33268597 http://dx.doi.org/10.1172/jci.insight.140940 Text en © 2020 Limeta et al. http://creativecommons.org/licenses/by/4.0/ This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Clinical Medicine Limeta, Angelo Ji, Boyang Levin, Max Gatto, Francesco Nielsen, Jens Meta-analysis of the gut microbiota in predicting response to cancer immunotherapy in metastatic melanoma |
title | Meta-analysis of the gut microbiota in predicting response to cancer immunotherapy in metastatic melanoma |
title_full | Meta-analysis of the gut microbiota in predicting response to cancer immunotherapy in metastatic melanoma |
title_fullStr | Meta-analysis of the gut microbiota in predicting response to cancer immunotherapy in metastatic melanoma |
title_full_unstemmed | Meta-analysis of the gut microbiota in predicting response to cancer immunotherapy in metastatic melanoma |
title_short | Meta-analysis of the gut microbiota in predicting response to cancer immunotherapy in metastatic melanoma |
title_sort | meta-analysis of the gut microbiota in predicting response to cancer immunotherapy in metastatic melanoma |
topic | Clinical Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7714408/ https://www.ncbi.nlm.nih.gov/pubmed/33268597 http://dx.doi.org/10.1172/jci.insight.140940 |
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