The DAV132 colon-targeted adsorbent does not interfere with plasma concentrations of antibiotics but prevents antibiotic-related dysbiosis: a randomized phase I trial in healthy volunteers.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
15 Sep 2024
15 Sep 2024
Historique:
received:
05
06
2024
accepted:
05
09
2024
medline:
16
9
2024
pubmed:
16
9
2024
entrez:
15
9
2024
Statut:
epublish
Résumé
The deleterious impact of antibiotics (ATB) on the microbiome negatively influences immune checkpoint inhibitors (ICI) response in patients with cancer. We conducted a randomized phase I study (EudraCT:2019-A00240-57) with 148 healthy volunteers (HV) to test two doses of DAV132, a colon-targeted adsorbent, alongside intravenous ceftazidime-avibactam (CZA), piperacillin-tazobactam (PTZ) or ceftriaxone (CRO) and a group without ATB. The primary objective of the study was to assess the effect of DAV132 on ATB plasma concentrations and both doses of DAV132 did not alter ATB levels. Secondary objectives included safety, darkening of the feces, and fecal ATB concentrations. DAV132 was well tolerated, with no severe toxicity and similar darkening at both DAV132 doses. DAV132 led to significant decrease in CZA or PTZ feces concentration. When co-administered with CZA or PTZ, DAV132 preserved microbiome diversity, accelerated recovery to baseline composition and protected key commensals. Fecal microbiota transplantation (FMT) in preclinical cancer models in female mice from HV treated with CZA or PTZ alone inhibited anti-PD-1 response, while transplanted samples from HV treated with ATB + DAV132 circumvented resistance to anti-PD-1. This effect was linked to activated CD8
Identifiants
pubmed: 39278946
doi: 10.1038/s41467-024-52373-8
pii: 10.1038/s41467-024-52373-8
doi:
Substances chimiques
Anti-Bacterial Agents
0
Immune Checkpoint Inhibitors
0
Types de publication
Journal Article
Clinical Trial, Phase I
Randomized Controlled Trial
Langues
eng
Sous-ensembles de citation
IM
Pagination
8083Informations de copyright
© 2024. The Author(s).
Références
Forde, P. M. et al. Neoadjuvant nivolumab plus chemotherapy in resectable lung cancer. N. Engl. J. Med. 386, 1973–1985 (2022).
pubmed: 35403841
pmcid: 9844511
doi: 10.1056/NEJMoa2202170
Haslam, A. & Prasad, V. Estimation of the percentage of US patients with cancer who are eligible for and respond to checkpoint inhibitor immunotherapy drugs. JAMA Netw. Open 2, e192535 (2019).
pubmed: 31050774
pmcid: 6503493
doi: 10.1001/jamanetworkopen.2019.2535
Derosa, L. et al. Microbiota-centered interventions: the next breakthrough in immuno-oncology? Cancer Discov. 11, 2396–2412 (2021).
pubmed: 34400407
doi: 10.1158/2159-8290.CD-21-0236
Sepich-Poore, G. D. et al. The microbiome and human cancer. Science 371, eabc4552 (2021).
pubmed: 33766858
pmcid: 8767999
doi: 10.1126/science.abc4552
Chen, D. S. & Mellman, I. Elements of cancer immunity and the cancer-immune set point. Nature 541, 321–330 (2017).
pubmed: 28102259
doi: 10.1038/nature21349
Hanahan, D. Hallmarks of cancer: new dimensions. Cancer Discov. 12, 31–46 (2022).
pubmed: 35022204
doi: 10.1158/2159-8290.CD-21-1059
Routy, B. et al. Melanoma and microbiota: Current understanding and future directions. Cancer Cell S1535-6108(23)00431–2. https://doi.org/10.1016/j.ccell.2023.12.003 (2023).
Elkrief, A. et al. Antibiotics are associated with worse outcomes in lung cancer patients treated with chemotherapy and immunotherapy. NPJ Precis. Oncol. 8, 143 (2024).
pubmed: 39014160
pmcid: 11252311
doi: 10.1038/s41698-024-00630-w
Routy, B. et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 359, 91–97 (2018).
pubmed: 29097494
doi: 10.1126/science.aan3706
Derosa, L. et al. Intestinal Akkermansia muciniphila predicts clinical response to PD-1 blockade in patients with advanced non-small-cell lung cancer. Nat. Med. 28, 315–324 (2022).
pubmed: 35115705
pmcid: 9330544
doi: 10.1038/s41591-021-01655-5
Spencer, C. N. et al. Dietary fiber and probiotics influence the gut microbiome and melanoma immunotherapy response. Science 374, 1632–1640 (2021).
pubmed: 34941392
pmcid: 8970537
doi: 10.1126/science.aaz7015
Lee, K. A. et al. Cross-cohort gut microbiome associations with immune checkpoint inhibitor response in advanced melanoma. Nat. Med. 28, 535–544 (2022).
pubmed: 35228751
pmcid: 8938272
doi: 10.1038/s41591-022-01695-5
Derosa, L. et al. Gut bacteria composition drives primary resistance to cancer immunotherapy in renal cell carcinoma patients. Eur. Urol. 78, 195–206 (2020).
pubmed: 32376136
doi: 10.1016/j.eururo.2020.04.044
Gopalakrishnan, V. et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science 359, 97–103 (2018).
pubmed: 29097493
doi: 10.1126/science.aan4236
Messaoudene, M. et al. A natural polyphenol exerts antitumor activity and circumvents anti-PD-1 resistance through effects on the gut microbiota. Cancer Discov. candisc.0808.2021 https://doi.org/10.1158/2159-8290.CD-21-0808 (2022).
Baruch, E. N. et al. Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients. Science 371, 602–609 (2021).
pubmed: 33303685
doi: 10.1126/science.abb5920
Davar, D. et al. Fecal microbiota transplant overcomes resistance to anti–PD-1 therapy in melanoma patients. Science 371, 595–602 (2021).
pubmed: 33542131
pmcid: 8097968
doi: 10.1126/science.abf3363
Routy, B. et al. Fecal microbiota transplantation plus anti-PD-1 immunotherapy in advanced melanoma: a phase I trial. Nat. Med. https://doi.org/10.1038/s41591-023-02453-x (2023).
Vétizou, M. et al. Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota. Science 350, 1079–1084 (2015).
pubmed: 26541610
pmcid: 4721659
doi: 10.1126/science.aad1329
Elkrief, A. et al. Antibiotics are associated with decreased progression-free survival of advanced melanoma patients treated with immune checkpoint inhibitors. Oncoimmunology 8, e1568812 (2019).
pubmed: 30906663
pmcid: 6422373
doi: 10.1080/2162402X.2019.1568812
Elkrief, A., Derosa, L., Kroemer, G., Zitvogel, L. & Routy, B. The negative impact of antibiotics on outcomes in cancer patients treated with immunotherapy: a new independent prognostic factor? Ann. Oncol. 30, 1572–1579 (2019).
pubmed: 31268133
doi: 10.1093/annonc/mdz206
Pinato, D. J. et al. Association of prior antibiotic treatment with survival and response to immune checkpoint inhibitor therapy in patients with cancer. JAMA Oncol. https://doi.org/10.1001/jamaoncol.2019.2785 (2019).
doi: 10.1001/jamaoncol.2019.2785
pubmed: 31513236
pmcid: 6743060
Hakozaki, T. et al. The gut microbiome associates with immune checkpoint inhibition outcomes in patients with advanced non-small cell lung cancer. Cancer Immunol. Res. https://doi.org/10.1158/2326-6066.CIR-20-0196 (2020).
doi: 10.1158/2326-6066.CIR-20-0196
pubmed: 32847937
Thomas, A. M. et al. Gut OncoMicrobiome Signatures (GOMS) as next-generation biomarkers for cancer immunotherapy. Nat. Rev. Clin. Oncol. https://doi.org/10.1038/s41571-023-00785-8 (2023).
Suez, J. et al. Post-antibiotic gut mucosal microbiome reconstitution is impaired by probiotics and improved by autologous FMT. Cell 174, 1406–1423.e16 (2018).
pubmed: 30193113
doi: 10.1016/j.cell.2018.08.047
de Gunzburg, J. et al. Targeted adsorption of molecules in the colon with the novel adsorbent-based medicinal product, DAV132: a proof of concept study in healthy subjects. J. Clin. Pharmacol. 55, 10–16 (2015).
pubmed: 25042595
doi: 10.1002/jcph.359
de Gunzburg, J. et al. Protection of the human gut microbiome from antibiotics. J. Infect. Dis. 217, 628–636 (2018).
pubmed: 29186529
doi: 10.1093/infdis/jix604
Burdet, C. et al. Protection of hamsters from mortality by reducing fecal moxifloxacin concentration with DAV131A in a model of moxifloxacin-induced clostridium difficile colitis. Antimicrob. Agents Chemother. 61, e00543–17 (2017).
pubmed: 28739791
pmcid: 5610506
doi: 10.1128/AAC.00543-17
Burdet, C. et al. Antibiotic-induced dysbiosis predicts mortality in an animal model of Clostridium difficile infection. Antimicrob. Agents Chemother. 62, e00925–18 (2018).
pubmed: 30061286
pmcid: 6153837
doi: 10.1128/AAC.00925-18
Saint-Lu, N. et al. DAV131A protects hamsters from lethal Clostridioides difficile infection induced by fluoroquinolones. Antimicrob. Agents Chemother. 64, e01196–19 (2019).
pubmed: 31636067
pmcid: 7187614
doi: 10.1128/AAC.01196-19
Shirley, M. Ceftazidime-avibactam: a review in the treatment of serious gram-negative bacterial infections. Drugs 78, 675–692 (2018).
pubmed: 29671219
doi: 10.1007/s40265-018-0902-x
Perry, C. M. & Markham, A. Piperacillin/tazobactam: an updated review of its use in the treatment of bacterial infections. Drugs 57, 805–843 (1999).
pubmed: 10353303
doi: 10.2165/00003495-199957050-00017
Vehreschild, M. J. G. T. et al. An open randomized multicentre Phase 2 trial to assess the safety of DAV132 and its efficacy to protect gut microbiota diversity in hospitalized patients treated with fluoroquinolones. J. Antimicrob. Chemother. 77, 1155–1165 (2022).
pubmed: 35016205
pmcid: 8969469
doi: 10.1093/jac/dkab474
Kaleko, M. et al. Development of SYN-004, an oral beta-lactamase treatment to protect the gut microbiome from antibiotic-mediated damage and prevent Clostridium difficile infection. Anaerobe 41, 58–67 (2016).
pubmed: 27262694
doi: 10.1016/j.anaerobe.2016.05.015
Klastersky, J. et al. Management of febrile neutropaenia: ESMO Clinical Practice Guidelines. Ann. Oncol. J. Eur. Soc. Med. Oncol. 27, v111–v118 (2016).
doi: 10.1093/annonc/mdw325
Wendt, S., Ranft, D., Rodloff, A. C., Lippmann, N. & Lübbert, C. Switching from ceftriaxone to cefotaxime significantly contributes to reducing the burden of Clostridioides difficile infections. Open Forum Infect. Dis. 7, ofaa312 (2020).
pubmed: 33005693
pmcid: 7518363
doi: 10.1093/ofid/ofaa312
Costello, S. P., Tucker, E. C., La Brooy, J., Schoeman, M. N. & Andrews, J. M. Establishing a fecal microbiota transplant service for the treatment of Clostridium difficile infection. Clin. Infect. Dis. Publ. Infect. Dis. Soc. Am. 62, 908–914 (2016).
doi: 10.1093/cid/civ994
Harris, H. C. et al. Optimization of an assay to determine colonization resistance to Clostridioides difficile in fecal samples from healthy subjects and those treated with antibiotics. Antimicrob. Agents Chemother. 65, e01401–20 (2020).
pubmed: 33139292
pmcid: 7927831
doi: 10.1128/AAC.01401-20
Yonekura, S. et al. Cancer induces a stress ileopathy depending on β-adrenergic receptors and promoting dysbiosis that contributes to carcinogenesis. Cancer Discov. 12, 1128–1151 (2022).
pubmed: 34930787
doi: 10.1158/2159-8290.CD-21-0999
Fidelle, M. et al. A microbiota-modulated checkpoint directs immunosuppressive intestinal T cells into cancers. Science 380, eabo2296 (2023).
pubmed: 37289890
doi: 10.1126/science.abo2296
Vehreschild, M. J. G. T. et al. An obituary on DAV-132—authors’ viewpoint on the current limits of pivotal trials in clinical microbiome research. J. Antimicrob. Chemother. 78, 1551–1553 (2023).
doi: 10.1093/jac/dkad123
Schulz, K. F., Altman, D. G., Moher, D. & CONSORT Group. CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. J. Clin. Epidemiol. 63, 834–840 (2010).
pubmed: 20346629
doi: 10.1016/j.jclinepi.2010.02.005
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
pubmed: 22388286
pmcid: 3322381
doi: 10.1038/nmeth.1923
Schubert, M., Lindgreen, S. & Orlando, L. AdapterRemoval v2: rapid adapter trimming, identification, and read merging. BMC Res. Notes 9, 88 (2016).
pubmed: 26868221
pmcid: 4751634
doi: 10.1186/s13104-016-1900-2
Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinforma. Oxf. Engl. 26, 589–595 (2010).
doi: 10.1093/bioinformatics/btp698
Nielsen, H. B. et al. Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes. Nat. Biotechnol. 32, 822–828 (2014).
pubmed: 24997787
doi: 10.1038/nbt.2939
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
pubmed: 25516281
pmcid: 4302049
doi: 10.1186/s13059-014-0550-8
Lê, S., Josse, J. & Husson, F. FactoMineR: an R package for multivariate analysis. J. Stat. Softw. 25, 1–18 (2008).
doi: 10.18637/jss.v025.i01
Kolde, R. pheatmap: Pretty Heatmaps (2019).
Miao, Y.-R. et al. ImmuCellAI-mouse: a tool for comprehensive prediction of mouse immune cell abundance and immune microenvironment depiction. Bioinforma. Oxf. Engl. 38, 785–791 (2022).
doi: 10.1093/bioinformatics/btab711