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Non-small cell lung cancer patients treated with Anti-PD1 immunotherapy show distinct microbial signatures and metabolic pathways according to progression-free survival and PD-L1 status

Due to the high variance in response rates concerning anti-PD1 immunotherapy (IT), there is an unmet need to discover innovative biomarkers to predict immune checkpoint inhibitor (ICI)-efficacy. Our study included 62 Caucasian advanced-stage non-small cell lung cancer (NSCLC) patients treated with a...

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Autores principales: Dora, David, Ligeti, Balazs, Kovacs, Tamas, Revisnyei, Peter, Galffy, Gabriella, Dulka, Edit, Krizsán, Dániel, Kalcsevszki, Regina, Megyesfalvi, Zsolt, Dome, Balazs, Weiss, Glen J., Lohinai, Zoltan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10184596/
https://www.ncbi.nlm.nih.gov/pubmed/37197440
http://dx.doi.org/10.1080/2162402X.2023.2204746
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author Dora, David
Ligeti, Balazs
Kovacs, Tamas
Revisnyei, Peter
Galffy, Gabriella
Dulka, Edit
Krizsán, Dániel
Kalcsevszki, Regina
Megyesfalvi, Zsolt
Dome, Balazs
Weiss, Glen J.
Lohinai, Zoltan
author_facet Dora, David
Ligeti, Balazs
Kovacs, Tamas
Revisnyei, Peter
Galffy, Gabriella
Dulka, Edit
Krizsán, Dániel
Kalcsevszki, Regina
Megyesfalvi, Zsolt
Dome, Balazs
Weiss, Glen J.
Lohinai, Zoltan
author_sort Dora, David
collection PubMed
description Due to the high variance in response rates concerning anti-PD1 immunotherapy (IT), there is an unmet need to discover innovative biomarkers to predict immune checkpoint inhibitor (ICI)-efficacy. Our study included 62 Caucasian advanced-stage non-small cell lung cancer (NSCLC) patients treated with anti-PD1 ICI. Gut bacterial signatures were evaluated by metagenomic sequencing and correlated with progression-free survival (PFS), PD-L1 expression and other clinicopathological parameters. We confirmed the predictive role of PFS-related key bacteria with multivariate statistical models (Lasso- and Cox-regression) and validated on an additional patient cohort (n = 60). We find that alpha-diversity showed no significant difference in any comparison. However, there was a significant difference in beta-diversity between patients with long- (>6 months) vs. short (≤6 months) PFS and between chemotherapy (CHT)-treated vs. CHT-naive cases. Short PFS was associated with increased abundance of Firmicutes (F) and Actinobacteria phyla, whereas elevated abundance of Euryarchaeota was specific for low PD-L1 expression. F/Bacteroides (F/B) ratio was significantly increased in patients with short PFS. Multivariate analysis revealed an association between Alistipes shahii, Alistipes finegoldii, Barnesiella visceriola, and long PFS. In contrast, Streptococcus salivarius, Streptococcus vestibularis, and Bifidobacterium breve were associated with short PFS. Using Random Forest machine learning approach, we find that taxonomic profiles performed superiorly in predicting PFS (AUC = 0.74), while metabolic pathways including Amino Acid Synthesis and Fermentation were better predictors of PD-L1 expression (AUC = 0.87). We conclude that specific metagenomic features of the gut microbiome, including bacterial taxonomy and metabolic pathways might be suggestive of ICI efficacy and PD-L1 expression in NSCLC patients.
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spelling pubmed-101845962023-05-16 Non-small cell lung cancer patients treated with Anti-PD1 immunotherapy show distinct microbial signatures and metabolic pathways according to progression-free survival and PD-L1 status Dora, David Ligeti, Balazs Kovacs, Tamas Revisnyei, Peter Galffy, Gabriella Dulka, Edit Krizsán, Dániel Kalcsevszki, Regina Megyesfalvi, Zsolt Dome, Balazs Weiss, Glen J. Lohinai, Zoltan Oncoimmunology Original Research Due to the high variance in response rates concerning anti-PD1 immunotherapy (IT), there is an unmet need to discover innovative biomarkers to predict immune checkpoint inhibitor (ICI)-efficacy. Our study included 62 Caucasian advanced-stage non-small cell lung cancer (NSCLC) patients treated with anti-PD1 ICI. Gut bacterial signatures were evaluated by metagenomic sequencing and correlated with progression-free survival (PFS), PD-L1 expression and other clinicopathological parameters. We confirmed the predictive role of PFS-related key bacteria with multivariate statistical models (Lasso- and Cox-regression) and validated on an additional patient cohort (n = 60). We find that alpha-diversity showed no significant difference in any comparison. However, there was a significant difference in beta-diversity between patients with long- (>6 months) vs. short (≤6 months) PFS and between chemotherapy (CHT)-treated vs. CHT-naive cases. Short PFS was associated with increased abundance of Firmicutes (F) and Actinobacteria phyla, whereas elevated abundance of Euryarchaeota was specific for low PD-L1 expression. F/Bacteroides (F/B) ratio was significantly increased in patients with short PFS. Multivariate analysis revealed an association between Alistipes shahii, Alistipes finegoldii, Barnesiella visceriola, and long PFS. In contrast, Streptococcus salivarius, Streptococcus vestibularis, and Bifidobacterium breve were associated with short PFS. Using Random Forest machine learning approach, we find that taxonomic profiles performed superiorly in predicting PFS (AUC = 0.74), while metabolic pathways including Amino Acid Synthesis and Fermentation were better predictors of PD-L1 expression (AUC = 0.87). We conclude that specific metagenomic features of the gut microbiome, including bacterial taxonomy and metabolic pathways might be suggestive of ICI efficacy and PD-L1 expression in NSCLC patients. Taylor & Francis 2023-05-12 /pmc/articles/PMC10184596/ /pubmed/37197440 http://dx.doi.org/10.1080/2162402X.2023.2204746 Text en © 2023 The Author(s). Published with license by Taylor & Francis Group, LLC. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
spellingShingle Original Research
Dora, David
Ligeti, Balazs
Kovacs, Tamas
Revisnyei, Peter
Galffy, Gabriella
Dulka, Edit
Krizsán, Dániel
Kalcsevszki, Regina
Megyesfalvi, Zsolt
Dome, Balazs
Weiss, Glen J.
Lohinai, Zoltan
Non-small cell lung cancer patients treated with Anti-PD1 immunotherapy show distinct microbial signatures and metabolic pathways according to progression-free survival and PD-L1 status
title Non-small cell lung cancer patients treated with Anti-PD1 immunotherapy show distinct microbial signatures and metabolic pathways according to progression-free survival and PD-L1 status
title_full Non-small cell lung cancer patients treated with Anti-PD1 immunotherapy show distinct microbial signatures and metabolic pathways according to progression-free survival and PD-L1 status
title_fullStr Non-small cell lung cancer patients treated with Anti-PD1 immunotherapy show distinct microbial signatures and metabolic pathways according to progression-free survival and PD-L1 status
title_full_unstemmed Non-small cell lung cancer patients treated with Anti-PD1 immunotherapy show distinct microbial signatures and metabolic pathways according to progression-free survival and PD-L1 status
title_short Non-small cell lung cancer patients treated with Anti-PD1 immunotherapy show distinct microbial signatures and metabolic pathways according to progression-free survival and PD-L1 status
title_sort non-small cell lung cancer patients treated with anti-pd1 immunotherapy show distinct microbial signatures and metabolic pathways according to progression-free survival and pd-l1 status
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10184596/
https://www.ncbi.nlm.nih.gov/pubmed/37197440
http://dx.doi.org/10.1080/2162402X.2023.2204746
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