Abstract 5882: Prevention of antibiotic-induced dysbiosis in human volunteers by DAV132 and preservation of responsiveness to anti-PD-1 demonstrated by transplantation of human feces into tumor-bearing mice
Bibliographic record
Abstract
Abstract Background: Over the last decade, studies unraveled the cancer-immune dialogue in the setting of immune checkpoint inhibitors (ICI) and influenced by the gut microbiota. The first evidence of the key role of the microbiota in ICI modulation was observed during antibiotics (ATB) treatment, where altering the microbiota composition by ATB inhibited ICI responses. DAV132 (DAV) is an orally administered colon-targeted ATB adsorbent capsules designed to prevent ATB-induced dysbiosis. We investigated whether DAV co-administered with ATB could prevent ATB-related dysbiosis and ICI response. Methods: 72 human healthy volunteers (HV) were randomized to receive either IV ceftazidime-avibactam (CZA) or Piperacillin tazobactam (PTZ) alone or in combination with oral DAV. CZA and PTZ plasmatic and fecal pharmacodynamic levels were measured using HPLC-MS/MS. Microbiome was profiled with metagenomics at different timepoints. FMT experiments in germ-free mice were performed using fecal samples from HV from the trial, before (D1) or after 6 days (D6) of CZA or PTZ+/-DAV; subsequently mice were inoculated with MCA205 or B16 tumors and treated with anti-PD-1. Tumor infiltrating lymphocytes (TILs) were analyzed by flow cytometry. Results: DAV did not impact plasmatic CZA or PTZ concentrations, but significantly reduced ceftazidime and piperacillin concentrations in feces compared to ATB groups alone. DAV significantly prevented the reduction in microbiota alpha-diversity at D6 and was associated with a rapid return to baseline microbiota. 50 and 43 metagenomics species were preserved in the CZA+DAV vs CZA, or PTZ-DAV vs PTZ such as Faecalibacterium praunistzii, Alistipes Spp and Blautia obeum. FMT in germ-free mice using feces collected at D1 exhibited a significant anti-PD-1 activity. This anti-tumor response was inhibited in two tumors models in mice transplanted with D6 feces from patients in the CZA or PTZ alone groups. Conversely, the anti-tumor response was maintained in mice transplanted with D6 feces from HV treated with CZA+DAV or PTZ+DAV groups. Flow cytometry on TILs demonstrated that CZA decreased CD8+T cell and CD8+/Treg ratio compared to CZA+DAV. Conclusions: DAV prevented ATB-induced dysbiosis in HV treated with CZA or PTZ without influencing plasmatic concentrations. In avatar mice FMT from HV treated with CZA+DAV was able to preserve anti-PD-1 efficacy. These results provide rationale to launch clinical trials combining DAV in patients on ATB amenable to ICI. Citation Format: Meriem Messaoudene, Nathalie Saint-Lu, Frédérique Sablier-Gallis, Stéphanie Ferreira, Mayra Ponce, Clément Le Bescop, Thomas Loppinet, Tanguy Corbel, Céline Féger, Fabien Vitry, Antoine Andremont, Jean de Gunzburg, Bertrand Routy. Prevention of antibiotic-induced dysbiosis in human volunteers by DAV132 and preservation of responsiveness to anti-PD-1 demonstrated by transplantation of human feces into tumor-bearing mice [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5882.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".