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Microbiome-based interventions: therapeutic strategies in cancer immunotherapy

The composition of the commensal microbiota has recently emerged as a key element influencing the efficacy of cancer treatments. It has become apparent that the interplay between the microbiome and immune system within the host influences the response to immunotherapy, particularly immune checkpoint...

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Detalles Bibliográficos
Autores principales: Soto Chervin, C., Gajewski, T.F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9216398/
https://www.ncbi.nlm.nih.gov/pubmed/35757563
http://dx.doi.org/10.1016/j.iotech.2020.11.001
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author Soto Chervin, C.
Gajewski, T.F.
author_facet Soto Chervin, C.
Gajewski, T.F.
author_sort Soto Chervin, C.
collection PubMed
description The composition of the commensal microbiota has recently emerged as a key element influencing the efficacy of cancer treatments. It has become apparent that the interplay between the microbiome and immune system within the host influences the response to immunotherapy, particularly immune checkpoint inhibitor therapy. Identifying the key components of the gut microbiota that influence this response is paramount for designing therapeutic interventions to enhance the response to cancer therapy. This review will discuss strategies being considered to modulate the gut microbiota, including fecal microbiota transplantation, administration of defined bacterial isolates as well as bacterial consortia, supplementation with probiotics, and lifestyle modifications such as dietary changes. Understanding the influence of the complex variables of the human microbiota on the effectiveness of cancer therapy will help drive the clinical design of microbial-based interventions in the field of oncology.
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spelling pubmed-92163982022-06-24 Microbiome-based interventions: therapeutic strategies in cancer immunotherapy Soto Chervin, C. Gajewski, T.F. Immunooncol Technol Review The composition of the commensal microbiota has recently emerged as a key element influencing the efficacy of cancer treatments. It has become apparent that the interplay between the microbiome and immune system within the host influences the response to immunotherapy, particularly immune checkpoint inhibitor therapy. Identifying the key components of the gut microbiota that influence this response is paramount for designing therapeutic interventions to enhance the response to cancer therapy. This review will discuss strategies being considered to modulate the gut microbiota, including fecal microbiota transplantation, administration of defined bacterial isolates as well as bacterial consortia, supplementation with probiotics, and lifestyle modifications such as dietary changes. Understanding the influence of the complex variables of the human microbiota on the effectiveness of cancer therapy will help drive the clinical design of microbial-based interventions in the field of oncology. Elsevier 2020-11-28 /pmc/articles/PMC9216398/ /pubmed/35757563 http://dx.doi.org/10.1016/j.iotech.2020.11.001 Text en © 2020 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review
Soto Chervin, C.
Gajewski, T.F.
Microbiome-based interventions: therapeutic strategies in cancer immunotherapy
title Microbiome-based interventions: therapeutic strategies in cancer immunotherapy
title_full Microbiome-based interventions: therapeutic strategies in cancer immunotherapy
title_fullStr Microbiome-based interventions: therapeutic strategies in cancer immunotherapy
title_full_unstemmed Microbiome-based interventions: therapeutic strategies in cancer immunotherapy
title_short Microbiome-based interventions: therapeutic strategies in cancer immunotherapy
title_sort microbiome-based interventions: therapeutic strategies in cancer immunotherapy
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9216398/
https://www.ncbi.nlm.nih.gov/pubmed/35757563
http://dx.doi.org/10.1016/j.iotech.2020.11.001
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