Composition of the Gut Microbiota Associated with the Response to Immunotherapy in Advanced Cancer Patients: A Chinese Real-World Pilot Study

Background: The composition of the gut microbiota is associated with the response to immunotherapy for different cancers. However, the majority of previous studies have focused on a single cancer and a single immune checkpoint inhibitor. Here, we investigated the relationship between the gut microbiota and the clinical response to anti-programmed cell death protein 1 (PD-1) immunotherapy in patients with advanced cancers. Method: In this comprehensive study, 16S rRNA sequencing was performed on the gut microbiota of pre-immunotherapy and post-immunotherapy, of 72 advanced cancer patients in China. Results: At the phylum level, Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria were the main components of the microbiota in the 72 advanced cancer patients. At the genus level, Bacteroides and Prevotella were the dominant microbiota among these 72 patients. The PD_whole_tree, Chao1, Observed_species and Shannon indices of R.0 and R.T were higher than those of NR.0 and NR.T. The results of LEfSe showed that Archaea, Lentisphaerae, Victivallaceae, Victivallales, Lentisphaeria, Methanobacteriaceae, Methanobacteria, Euryarchaeota, Methanobrevibacter, and Methanobacteriales were significantly enriched in the response group before immunotherapy (R.0), and the Clostridiaceae was significantly enriched in the non-response group before immunotherapy (NR.0) (p < 0.05). Lachnospiraceae and Thermus were significantly enriched in the response group after immunotherapy (R.T), and Leuconostoc was significantly enriched in R.0 (p < 0.05). ROC analysis showed that the microbiota of R.T (AUC = 0.70) had obvious diagnostic value in differentiating Chinese cancer patients based on their response to immunotherapy. Conclusions: We demonstrated that the gut microbiota was associated with the clinical response to anti-PD-1 immunotherapy in cancer patients. Taxonomic signatures enriched in responders were effective biomarkers to predict the clinical response. Our findings provide a new strategy to improve the efficiency of responses to immunotherapy among cancer patients.