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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...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
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.
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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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