Abstract
BackgroundRecent evidence suggests that immunotherapy efficacy in melanoma is modulated by gut microbiota. Few studies have examined this phenomenon in humans, and none have incorporated metatranscriptomics, important for determining expression of metagenomic functions in the microbial community.MethodsIn melanoma patients undergoing immunotherapy, gut microbiome was characterized in pre-treatment stool using 16S rRNA gene and shotgun metagenome sequencing (n = 27). Transcriptional expression of metagenomic pathways was confirmed with metatranscriptome sequencing in a subset of 17. We examined associations of taxa and metagenomic pathways with progression-free survival (PFS) using 500 × 10-fold cross-validated elastic-net penalized Cox regression.ResultsHigher microbial community richness was associated with longer PFS in 16S and shotgun data (p < 0.05). Clustering based on overall microbiome composition divided patients into three groups with differing PFS; the low-risk group had 99% lower risk of progression than the high-risk group at any time during follow-up (p = 0.002). Among the species selected in regression, abundance of Bacteroides ovatus, Bacteroides dorei, Bacteroides massiliensis, Ruminococcus gnavus, and Blautia producta were related to shorter PFS, and Faecalibacterium prausnitzii, Coprococcus eutactus, Prevotella stercorea, Streptococcus sanguinis, Streptococcus anginosus, and Lachnospiraceae bacterium 3 1 46FAA to longer PFS. Metagenomic functions related to PFS that had correlated metatranscriptomic expression included risk-associated pathways of l-rhamnose degradation, guanosine nucleotide biosynthesis, and B vitamin biosynthesis.ConclusionsThis work adds to the growing evidence that gut microbiota are related to immunotherapy outcomes, and identifies, for the first time, transcriptionally expressed metagenomic pathways related to PFS. Further research is warranted on microbial therapeutic targets to improve immunotherapy outcomes.
Highlights
Recent evidence suggests that immunotherapy efficacy in melanoma is modulated by gut microbiota
In human melanoma patients undergoing immunotherapy, gut microbiome composition has been significantly associated with clinical response [9,10,11,12], and antitumor immunity was enhanced in germ-free mice receiving fecal transfer from the responding patients [9, 10]
We explored average species contributions to overall metagenome and metatranscriptome pathway abundances in this patient population (Fig. 5b); while multiple species are involved in each pathway, we noted that Bacteroides ovatus was a significant contributor to degradation of L-rhamnose and biosynthesis of pyridoxal 5-phosphate, 6-hydroxymethyldihydropterin diphosphate, and pantothenate and coenzyme A, while Bacteroides dorei was a significant contributor to guanosine nucleotides biosynthesis (Fig. 5b)
Summary
Recent evidence suggests that immunotherapy efficacy in melanoma is modulated by gut microbiota. Few studies have examined this phenomenon in humans, and none have incorporated metatranscriptomics, important for determining expression of metagenomic functions in the microbial community. Recent evidence suggests that immunotherapy efficacy may be impacted by the gut microbiota, which profoundly shape the human immune system [6] and may play a role in antitumor T cell responses. In human melanoma patients undergoing immunotherapy, gut microbiome composition has been significantly associated with clinical response [9,10,11,12], and antitumor immunity was enhanced in germ-free mice receiving fecal transfer from the responding patients [9, 10]. Published studies have not incorporated metatranscriptomic data into their analysis, which is crucial for understanding actual expression levels of metagenomic functions in the microbial community. We tested whether gut microbiome overall diversity and composition were related to progression-free survival using Cox proportional hazards models, and identified specific microbial taxa and functional pathways that were consistently related to progression-free survival in repeated cross-validation analyses
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