Metagenomic Shotgun Sequencing and Unbiased Metabolomic Profiling Identify Specific Human Gut Microbiota and Metabolites Associated with Immune Checkpoint Therapy Efficacy in Melanoma Patients

Abstract

This is the first prospective study of the effects of human gut microbiota and metabolites on immune checkpoint inhibitor (ICT) response in metastatic melanoma patients. Whereas many melanoma patients exhibit profound response to ICT, there are fewer options for patients failing ICT-particularly with BRAF-wild-type disease. In preclinical studies, specific gut microbiota promotes regression of melanoma in mice. We therefore conducted a study of the effects of pretreatment gut microbiota and metabolites on ICT Response Evaluation Criteria in Solid Tumors response in 39 metastatic melanoma patients treated with ipilimumab, nivolumab, ipilimumab plus nivolumab (IN), or pembrolizumab (P). IN yielded 67% responses and 8% stable disease; P achieved 23% responses and 23% stable disease. ICT responders for all types of therapies were enriched for Bacteroides caccae. Among IN responders, the gut microbiome was enriched for Faecalibacterium prausnitzii, Bacteroides thetaiotamicron, and Holdemania filiformis. Among P responders, the microbiome was enriched for Dorea formicogenerans. Unbiased shotgun metabolomics revealed high levels of anacardic acid in ICT responders. Based on these pilot studies, both additional confirmatory clinical studies and preclinical testing of these bacterial species and metabolites are warranted to confirm their ICT enhancing activity.

Figure 1

Study schema.

Figure 2

MSS identifies specific bacterial species that are enriched in the gut microbiomes of melanoma patients who are responding to ICT therapy. Relative abundance of gut bacterial taxa as determined by MetaPhlAn analysis of MSS data generated from fecal specimens collected from melanoma patients prior to receiving ipilimumab/nivolumab, pembrolizumab, ipilimumab alone, or nivolumab alone. Differential taxonomic abundance was analyzed by linear discriminate analysis coupled with effect size measurements (LEfSe) projected as a histogram (A, C and E) or cladrogram (B, D and F). All listed bacterial groups were significantly (P < .05, Kruskal-Wallis test) enriched for their respective groups (responder versus progressive).

Figure 3

Unbiased metabolomics analysis of stool metabolites from adult melanoma patients prior to treatment with ICT. UPLC-MS–based global profiling of metabolites in feces of adult melanoma patients receiving immune checkpoint inhibitor therapy (n = 39). Data were log transformed and mean centered. Venn diagrams of metabolites (A) significantly increased or (B) decreased when comparing the ICT responder group versus the progressive group for all ICTs, IN only, and P only. The heat maps show the normalized relative abundances of stool metabolites comparing responders to those with progressive disease for (C) all ICTs, (D) IN only, and (E) P only (q < 0.05, unpaired t test with Welch's correction followed by false discovery rate correction). Orange colors indicate relative abundance increase, and blue indicates relative abundances decrease (responders:progressive, log₂ transformed).