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Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications
BACKGROUND: The microbiome has been shown to affect the response to Immune Checkpoint Inhibitors (ICIs) in a small number of cancers and in preclinical models. Here, we sought to broadly survey cancers to identify those in which the microbiome may play a prognostic role using retrospective analyses...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7201618/ https://www.ncbi.nlm.nih.gov/pubmed/32375706 http://dx.doi.org/10.1186/s12885-020-06882-6 |
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author | Spakowicz, Daniel Hoyd, Rebecca Muniak, Mitchell Husain, Marium Bassett, James S. Wang, Lei Tinoco, Gabriel Patel, Sandip H. Burkart, Jarred Miah, Abdul Li, Mingjia Johns, Andrew Grogan, Madison Carbone, David P. Verschraegen, Claire F. Kendra, Kari L. Otterson, Gregory A. Li, Lang Presley, Carolyn J. Owen, Dwight H. |
author_facet | Spakowicz, Daniel Hoyd, Rebecca Muniak, Mitchell Husain, Marium Bassett, James S. Wang, Lei Tinoco, Gabriel Patel, Sandip H. Burkart, Jarred Miah, Abdul Li, Mingjia Johns, Andrew Grogan, Madison Carbone, David P. Verschraegen, Claire F. Kendra, Kari L. Otterson, Gregory A. Li, Lang Presley, Carolyn J. Owen, Dwight H. |
author_sort | Spakowicz, Daniel |
collection | PubMed |
description | BACKGROUND: The microbiome has been shown to affect the response to Immune Checkpoint Inhibitors (ICIs) in a small number of cancers and in preclinical models. Here, we sought to broadly survey cancers to identify those in which the microbiome may play a prognostic role using retrospective analyses of patients with advanced cancer treated with ICIs. METHODS: We conducted a retrospective analysis of 690 patients who received ICI therapy for advanced cancer. We used a literature review to define a causal model for the relationship between medications, the microbiome, and ICI response to guide the abstraction of electronic health records. Medications with precedent for changes to the microbiome included antibiotics, corticosteroids, proton pump inhibitors, histamine receptor blockers, non-steroid anti-inflammatories and statins. We tested the effect of medication timing on overall survival (OS) and evaluated the robustness of medication effects in each cancer. Finally, we compared the size of the effect observed for different classes of antibiotics to taxa that have been correlated to ICI response using a literature review of culture-based antibiotic susceptibilities. RESULTS: Of the medications assessed, only antibiotics and corticosteroids significantly associated with shorter OS. The hazard ratios (HRs) for antibiotics and corticosteroids were highest near the start of ICI treatment but remained significant when given prior to ICI. Antibiotics and corticosteroids remained significantly associated with OS even when controlling for multiple factors such as Eastern Cooperative Oncology Group performance status, Charlson Comorbidity Index score, and stage. When grouping antibiotics by class, β-lactams showed the strongest association with OS across all tested cancers. CONCLUSIONS: The timing and strength of the correlations with antibiotics and corticosteroids after controlling for confounding factors are consistent with the microbiome involvement with the response to ICIs across several cancers. |
format | Online Article Text |
id | pubmed-7201618 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72016182020-05-08 Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications Spakowicz, Daniel Hoyd, Rebecca Muniak, Mitchell Husain, Marium Bassett, James S. Wang, Lei Tinoco, Gabriel Patel, Sandip H. Burkart, Jarred Miah, Abdul Li, Mingjia Johns, Andrew Grogan, Madison Carbone, David P. Verschraegen, Claire F. Kendra, Kari L. Otterson, Gregory A. Li, Lang Presley, Carolyn J. Owen, Dwight H. BMC Cancer Research Article BACKGROUND: The microbiome has been shown to affect the response to Immune Checkpoint Inhibitors (ICIs) in a small number of cancers and in preclinical models. Here, we sought to broadly survey cancers to identify those in which the microbiome may play a prognostic role using retrospective analyses of patients with advanced cancer treated with ICIs. METHODS: We conducted a retrospective analysis of 690 patients who received ICI therapy for advanced cancer. We used a literature review to define a causal model for the relationship between medications, the microbiome, and ICI response to guide the abstraction of electronic health records. Medications with precedent for changes to the microbiome included antibiotics, corticosteroids, proton pump inhibitors, histamine receptor blockers, non-steroid anti-inflammatories and statins. We tested the effect of medication timing on overall survival (OS) and evaluated the robustness of medication effects in each cancer. Finally, we compared the size of the effect observed for different classes of antibiotics to taxa that have been correlated to ICI response using a literature review of culture-based antibiotic susceptibilities. RESULTS: Of the medications assessed, only antibiotics and corticosteroids significantly associated with shorter OS. The hazard ratios (HRs) for antibiotics and corticosteroids were highest near the start of ICI treatment but remained significant when given prior to ICI. Antibiotics and corticosteroids remained significantly associated with OS even when controlling for multiple factors such as Eastern Cooperative Oncology Group performance status, Charlson Comorbidity Index score, and stage. When grouping antibiotics by class, β-lactams showed the strongest association with OS across all tested cancers. CONCLUSIONS: The timing and strength of the correlations with antibiotics and corticosteroids after controlling for confounding factors are consistent with the microbiome involvement with the response to ICIs across several cancers. BioMed Central 2020-05-06 /pmc/articles/PMC7201618/ /pubmed/32375706 http://dx.doi.org/10.1186/s12885-020-06882-6 Text en © The Author(s) 2020 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Spakowicz, Daniel Hoyd, Rebecca Muniak, Mitchell Husain, Marium Bassett, James S. Wang, Lei Tinoco, Gabriel Patel, Sandip H. Burkart, Jarred Miah, Abdul Li, Mingjia Johns, Andrew Grogan, Madison Carbone, David P. Verschraegen, Claire F. Kendra, Kari L. Otterson, Gregory A. Li, Lang Presley, Carolyn J. Owen, Dwight H. Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications |
title | Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications |
title_full | Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications |
title_fullStr | Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications |
title_full_unstemmed | Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications |
title_short | Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications |
title_sort | inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7201618/ https://www.ncbi.nlm.nih.gov/pubmed/32375706 http://dx.doi.org/10.1186/s12885-020-06882-6 |
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