ObjectiveProgrammed death 1 and its ligand 1 (PD-1/PD-L1) immunotherapy is promising for late-stage lung cancer treatment, however, the response rate needs to be improved. Gut microbiota plays a crucial role in immunotherapy sensitisation and Panax ginseng has been shown to possess immunomodulatory potential. In this study, we aimed to investigate whether the combination treatment of ginseng polysaccharides (GPs) and αPD-1 monoclonal antibody (mAb) could sensitise the response by modulating gut microbiota.DesignSyngeneic mouse models were administered GPs and αPD-1 mAb, the sensitising antitumour effects of the combination therapy on gut microbiota were assessed by faecal microbiota transplantation (FMT) and 16S PacBio single-molecule real-time (SMRT) sequencing. To assess the immune-related metabolites, metabolomics analysis of the plasma samples was performed.ResultsWe found GPs increased the antitumour response to αPD-1 mAb by increasing the microbial metabolites valeric acid and decreasing L-kynurenine, as well as the ratio of Kyn/Trp, which contributed to the suppression of regulatory T cells and induction of Teff cells after combination treatment. Besides, the microbial analysis indicated that the abundance of Parabacteroides distasonis and Bacteroides vulgatus was higher in responders to anti-PD-1 blockade than non-responders in the clinic. Furthermore, the combination therapy sensitised the response to PD-1 inhibitor in the mice receiving microbes by FMT from six non-responders by reshaping the gut microbiota from non-responders towards that of responders.ConclusionOur results demonstrate that GPs combined with αPD-1 mAb may be a new strategy to sensitise non-small cell lung cancer patients to anti-PD-1 immunotherapy. The gut microbiota can be used as a novel biomarker to predict the response to anti-PD-1 immunotherapy.

The present study aims to predict the regiospecific glucuronidation of three dihydroxyflavones and seven mono-hydroxyflavones in human liver and intestinal microsomes using recombinant UGT isoforms. Seven mono-hydroxyflavones (or HFs), 2′-, 3′-, 4′-, 3-, 5-, 6-, and 7-hydroxyflavone, and three di-hydroxyflavones (or diHFs), 3,7-dihydroxyflavone (3,7-diHF), 3,5-dihydroxyflavone (3,5-diHF) and 3,4′-dihydroxyflavone (3,4′-diHF) were chosen and rates were measured at 2.5, 10 and 35 μM. The results indicated that the position of glucuronidation of three diHFs could be determined by using the UV spectra of relevant HFs. The results also indicated that UGT1A1, UGT1A7, UGT1A8, UGT1A9, UGT1A10 and UGT2B7 are the most important six UGT isoforms for metabolizing the chosen flavones. Regardless of isoforms used, 3-HF was always metabolized the fastest whereas 5-HF was usually metabolized the slowest, probably due to the formation of an intra-molecular hydrogen bond between 4-carbonyl and 5-OH group. Relevant UGT isoformspecific metabolism rates generally correlated well with the rates of glucuronidation in human intestinal and liver microsomes at each of the three tested concentrations. In conclusion, the glucuronidation "fingerprint" of seven selected mono-hydroxyflavones was affected by UGT isoforms used, positions of the −OH group, and the substrate concentrations, and the rates of glucuronidation by important recombinant UGTs correlated well with those obtained using human liver and intestinal microsomes.

We characterized the isoform specific glucuronidation of six isoflavones genistein, daidzein, glycitein, formononetin, biochanin A and prunetin using 12 expressed human UGTs and human intestinal and liver microsomes. The results indicated that these isoflavones are metabolized most rapidly at three different concentrations by one of these four UGT isoforms: UGT1A1, UGT1A8, UGT1A9 and UGT1A10. Furthermore, glycitein was usually metabolized the fastest whereas prunetin the slowest. Using the rates of metabolism by 12 UGT isoforms as a means to establish the metabolic "fingerprint", we found that each isoflavone had distinctive concentration-dependent patterns. Determination of kinetic parameters of glucuronidation using genistein and prunetin indicated that the distinct concentration-dependent metabolic patterns were the result of differences in K m and V max values. We then measured how well metabolic "fingerprinting" predicted metabolism of these isoflavones by human intestinal and liver microsomes. We found that the prediction was rather successful for five isoflavones in the liver microsomes, but not successful in the intestinal microsomes. We propose that a newly discovered UGT3A1 isoform capable of metabolizing phenols and estrogens might be responsible for the metabolism of isoflavones such as formononetin in humans. In conclusion, the first systematic study of metabolic "fingerprinting" of six common isoflavones showed that each isoflavone has UGT isoform-specific metabolic patterns that are concentration-dependent and predictive of metabolism of the isoflavones in liver microsomes.