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BackgroundClinical outcomes of immune checkpoint inhibitor (ICI)-treated non-small cell lung cancer (NSCLC) patients might be associated with the gut metagenome.MethodsSixty-two Caucasian advanced-stage NSCLC patients treated with anti-PD1 immunotherapy were included. Gut bacterial signatures were evaluated by metagenomic sequencing and correlated with progression-free survival (PFS), PD-L1 expression defined by immunohistochemistry, and other clinicopathological parameters. The predictive role of PFS-related key bacteria was confirmed with multivariate statistical models and validated on an additional patient cohort (n=60). The functional microbial signature of distinct patient groups were determined by analyzing metabolic pathways. A random forest (RF) machine learning algorithm was used to assess the predictive power of taxonomic and metabolic microbial signatures.ResultsAlpha-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 Euryarcheota 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. 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).ConclusionThe specific metagenomic features of the gut microbiome including bacterial taxonomy and metabolic pathways are suggestive of ICI efficacy and PD-L1 expression in NSCLC patients. |
