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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Main Authors: David Dora, Balazs Ligeti, Tamas Kovacs, Peter Revisnyei, Gabriella Galffy, Edit Dulka, Dániel Krizsán, Regina Kalcsevszki, Zsolt Megyesfalvi, Balazs Dome, Glen J. Weiss, Zoltan Lohinai
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:OncoImmunology
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Online Access:https://www.tandfonline.com/doi/10.1080/2162402X.2023.2204746
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author David Dora
Balazs Ligeti
Tamas Kovacs
Peter Revisnyei
Gabriella Galffy
Edit Dulka
Dániel Krizsán
Regina Kalcsevszki
Zsolt Megyesfalvi
Balazs Dome
Glen J. Weiss
Zoltan Lohinai
author_facet David Dora
Balazs Ligeti
Tamas Kovacs
Peter Revisnyei
Gabriella Galffy
Edit Dulka
Dániel Krizsán
Regina Kalcsevszki
Zsolt Megyesfalvi
Balazs Dome
Glen J. Weiss
Zoltan Lohinai
author_sort David Dora
collection DOAJ
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 doaj-art-3192af9b75d0451fa3c5111eb3db94712025-08-20T02:50:44ZengTaylor & Francis GroupOncoImmunology2162-402X2023-12-0112110.1080/2162402X.2023.2204746Non-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 statusDavid Dora0Balazs Ligeti1Tamas Kovacs2Peter Revisnyei3Gabriella Galffy4Edit Dulka5Dániel Krizsán6Regina Kalcsevszki7Zsolt Megyesfalvi8Balazs Dome9Glen J. Weiss10Zoltan Lohinai11Department of Anatomy, Histology and Embryology, Semmelweis University, Budapest, HungaryFaculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, HungaryDepartment of Anatomy, Histology and Embryology, Semmelweis University, Budapest, HungaryDepartment of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Budapest, HungaryCounty Hospital of Torokbalint, Torokbalint, HungaryCounty Hospital of Torokbalint, Torokbalint, HungaryFaculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, HungaryFaculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, HungaryNational Koranyi Institute of Pulmonology, Budapest, HungaryNational Koranyi Institute of Pulmonology, Budapest, HungaryUMass Chan Medical School, Department of Medicine, Worcester, MA, USACounty Hospital of Torokbalint, Torokbalint, HungaryDue 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.https://www.tandfonline.com/doi/10.1080/2162402X.2023.2204746Anti-PD1 immunotherapygut microbiomemetagenome pathwaysNSCLCPD-L1
spellingShingle David Dora
Balazs Ligeti
Tamas Kovacs
Peter Revisnyei
Gabriella Galffy
Edit Dulka
Dániel Krizsán
Regina Kalcsevszki
Zsolt Megyesfalvi
Balazs Dome
Glen J. Weiss
Zoltan Lohinai
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
OncoImmunology
Anti-PD1 immunotherapy
gut microbiome
metagenome pathways
NSCLC
PD-L1
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 Anti-PD1 immunotherapy
gut microbiome
metagenome pathways
NSCLC
PD-L1
url https://www.tandfonline.com/doi/10.1080/2162402X.2023.2204746
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