Human microbiome signatures of differential colorectal cancer drug metabolism

Abstract

It is well appreciated that microbial metabolism of drugs can influence treatment efficacy. Microbial β-glucuronidases in the gut can reactivate the excreted, inactive metabolite of irinotecan, a first-line chemotherapeutic for metastatic colorectal cancer. Reactivation causes adverse drug responses, including severe diarrhea. However, a direct connection between irinotecan metabolism and the composition of an individual’s gut microbiota has not previously been made. Here, we report quantitative evidence of inter-individual variability in microbiome metabolism of the inactive metabolite of irinotecan to its active form. We identify a high turnover microbiota metabotype with potentially elevated risk for irinotecan-dependent adverse drug responses. We link the high turnover metabotype to unreported microbial β-glucuronidases; inhibiting these enzymes may decrease irinotecan-dependent adverse drug responses in targeted subsets of patients. In total, this study reveals metagenomic mining of the microbiome, combined with metabolomics, as a non-invasive approach to develop biomarkers for colorectal cancer treatment outcomes.

Harnessing the Microbiome to Improve Drug Therapy

“…In the case of specific drug modifications, such as glucuronidation, there may be a diverse set of microbial enzymes that can catalyze the modification and, due to horizontal gene transfer between microbes, it may not be possible to link a specific microbe to a drug-metabolizing function. 8 Given all these complications, it is not surprising that translating basic research on microbiome drug metabolism into clinical practice has been slow. Improved communication between pharmacologists and microbiome scientists is crucial to overcome this gap.…”

“…Once in the gut, bacterial β‐glucuronidase enzymes recognize the glucuronide moiety as a carbon source and remove it, leading to reactivation and downstream adverse events, such as severe diarrhea, in patients. The capacity for a given microbiome to perform this deconjugation reaction varies between people and may be dependent on the presence of specific bacterial β‐glucuronidase and transport genes rather than specific species of bacteria . Other characterized microbial enzyme–drug interactions include the cardiac glycoside digoxin and related plant compounds, and the antiviral nucleoside drug brivudine …”

“…In addition to the limitations in model systems described above, the extraordinary diversity of microbial populations in individual human bodies makes it difficult to design cohorts that will identify general features of the microbiome that have the strongest influence on drug metabolism and are applicable to broad sets of patients. In the case of specific drug modifications, such as glucuronidation, there may be a diverse set of microbial enzymes that can catalyze the modification and, due to horizontal gene transfer between microbes, it may not be possible to link a specific microbe to a drug‐metabolizing function …”

“…The capacity for a given microbiome to perform this deconjugation reaction varies between people and may be dependent on the presence of specific bacterial βglucuronidase and transport genes rather than specific species of bacteria. 8 Other characterized microbial enzyme-drug interactions include the cardiac glycoside digoxin and related plant compounds, 9 and the antiviral nucleoside drug brivudine. 10 There are parallels between pharmacogenetics studies, which attempt to assess the role human genetic variation plays in drug metabolism, and microbiome studies of drug metabolism; both must contend with a vast quantity of uncharacterized and often unstructured genetic diversity.…”

How to Determine the Role of the Microbiome in Drug Disposition

“…The link between patient quantified by Guthrie and colleagues. Utilizing healthy stool sample incubations with irinotecan they identified highly-efficient or non-drug metabolizers based on quantities of irinotecan derived from the glucoronated metabolite, then used a metagenomics approach to identify β-glucuronidases gene abundance as the driving distinction between these two groups (Guthrie et al, 2017).…”