Exploring gut microbiome markers in predicting efficacy of immunotherapy against lung cancer.

8525 Background: Immunotherapy has profoundly changed the treatment landscape for lung cancer (LC) due to its tolerable safety profile and longer sustained therapeutic response. However, only about 20% of patients with locally advanced and metastatic disease can derive long-term clinical benefit from ICIs. Previous studies have suggested that the microbiome is involved in the development of LC in some way. We aimed to use the gut microbiome (GM) to model the benefit of immunotherapy and to mine the biomarkers with a global impact on immune response. Methods: We performed human gut metagenomic analysis on the responder patients and non-responder patients with immunotherapy. A total of 296 fecal samples, including baseline samples (71 responders, 98 non-responders and 72 healthy controls), and 55 samples during treatment were enrolled in our study, the taxonomic and functional features of these samples also were excavated. A machine-learning model was developed to identify responders and non-responders. At the same time, we also explored the influence of antibiotic use on the above results. Results: Specific species, Bacteroides caccae and Bacteroides uniformis, were positively correlated with responders. In non-responders, Prevotella copri was the main enrichment species. The α diversity of microbiota in responding patients was significantly higher than that in non-responding groups, and antibiotic use increased this trend. There was no significant difference in β diversity between the two groups, but LEFSE analysis also could obtain biomarkers of biological significance between the two groups. We used the biomarkers from the above analysis to construct a random forest model, and the area under the receiver operating characteristic curve (AUC) (species level: 82.10%; genus level: 79.4%). In addition, our studies suggested that metabolism such as amino acid metabolism, valine, leucine might be important in regulating the immunotherapy response that warrants further investigation. Conclusions: Overall, our study explored the relationship between microbial composition and immunotherapy efficacy in LC patients and mined relevant markers, and further research is needed to investigate the mechanisms of action of these key strains in influencing immunotherapy in the future.