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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

Dora, David ; Ligeti, Balazs ; Kovacs, Tamas ; Revisnyei, Peter ; Galffy, Gabriella ; Dulka, Edit ; Krizsán, Dániel ; Kalcsevszki, Regina ; Megyesfalvi, Zsolt and Dome, Balazs LU , et al. (2023) In OncoImmunology 12(1).
Abstract

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... (More)

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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publishing date
type
Contribution to journal
publication status
published
subject
keywords
Anti-PD1 immunotherapy, gut microbiome, metagenome pathways, NSCLC, PD-L1
in
OncoImmunology
volume
12
issue
1
article number
2204746
publisher
Landes Bioscience
external identifiers
  • pmid:37197440
  • scopus:85159176139
ISSN
2162-4011
DOI
10.1080/2162402X.2023.2204746
language
English
LU publication?
no
id
59505ddf-86f3-4db2-837b-83aff4fe503b
date added to LUP
2023-08-15 09:38:44
date last changed
2024-04-20 00:33:33
@article{59505ddf-86f3-4db2-837b-83aff4fe503b,
  abstract     = {{<p>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- (&gt;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.</p>}},
  author       = {{Dora, David and Ligeti, Balazs and Kovacs, Tamas and Revisnyei, Peter and Galffy, Gabriella and Dulka, Edit and Krizsán, Dániel and Kalcsevszki, Regina and Megyesfalvi, Zsolt and Dome, Balazs and Weiss, Glen J. and Lohinai, Zoltan}},
  issn         = {{2162-4011}},
  keywords     = {{Anti-PD1 immunotherapy; gut microbiome; metagenome pathways; NSCLC; PD-L1}},
  language     = {{eng}},
  number       = {{1}},
  publisher    = {{Landes Bioscience}},
  series       = {{OncoImmunology}},
  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}},
  url          = {{http://dx.doi.org/10.1080/2162402X.2023.2204746}},
  doi          = {{10.1080/2162402X.2023.2204746}},
  volume       = {{12}},
  year         = {{2023}},
}