Abstract 5730: A new polyphenol prebiotic isolated from <i>Myrciaria dubia</i> improves gut microbiota composition and increases anti-PD-1 efficacy in murine cancer models
Bibliographic record
Abstract
Abstract Introduction The gut microbiota influences immune checkpoint inhibitors (ICI) efficacy, and immunogenic commensals bacteria such as Akkermansia muciniphila (AM) and Ruminoccocus are enriched in ICI responder patients. Therefore, strategies to beneficially shift microbiota composition represent a novel therapeutic avenue. Myrciaria dubia (MD) is a polyphenol-rich berry prebiotic that has been recently shown to improve the gut microbiota composition and dampen inflammation in metabolic diseases. Methods Daily oral administration of MD or water was performed in MCA-205 (PD-1 sensitive) and E0071 (PD-1 resistant) murine tumor models treated with iso-control or anti-PD-1. 16s rRNA gene sequencing and qPCR were used to profile the murine fecal microbiota. Tumor immune infiltration was analyzed by flow cytometry and RNA sequencing. Bile acid levels were measured using liquid chromatography coupled to tandem mass spectrometry in mouse feces and plasma at sacrifice. MD supplementation was also tested in antibiotic-treated mice that had undergone a fecal microbiota transplantation (FMT) using feces from non-responder (NR) and responder (R) non-small cell lung cancer (NSCLC) patients. Finally, to determine the bioactive compound, reverse-phase high performance liquid chromatography was used to isolate fractions that were tested in the MCA-205 tumor model. Results In MCA-205, MD gavage alone significantly reduced tumor size and in both tumor models MD increased the efficacy of anti-PD-1 compared to water + anti-PD-1. The activity of MD was inhibited upon antibiotics administration. FMT using mouse feces previously treated with MD recreated the effect in MD-naïve mice. Increases in alpha diversity, and AM and Ruminococcaceae were observed in the feces of MD supplemented mice. Serum and fecal CA, αMCA primary and HDCA and DCA secondary bile acids were upregulated in mice treated with MD. The combination of MD + anti-PD-1 increased the frequency of CD8+/CD4+ Treg and ICOS+ expression on CD8+ T cells, while the depletion of the CD8+ cells inhibited the anti-cancer activity. Next, we validated that FMT from NSCLC ICI patients recreated the patients' phenotypes in the MCA-205 tumor model (R vs NR). Treatment with MD resorted anti-PD-1 anti-tumor efficacy post FMT from NR patients. Lastly, we isolated the bioactive polyphenol molecule from MD and confirmed its anti-cancer effect in vivo. Supplementation of AM and ruminococcus further increased anti-PD1 activity. Conclusion We isolated the bioactive polyphenol molecule from the MD berry and demonstrated that its potent adjuvant effect on anti-PD-1 was associated with a beneficial shift in microbiome and bile acid composition in a CD8+ T cell dependent manner. The modification of the gut microbiota with polyphenol supplementation provides a new therapeutic approach in immuno-oncology. Citation Format: Meriem Messaoudene, Florent Cauchois, Reilly Piedgeon, Khoudia Diop, Corentin Richard, Thibault Varin, Jocelyn Trottier, Olivier Barbier, Geneviève Pilon, Simon Turcotte, André Marette, Bastien Castagner, Bertrand Routy. A new polyphenol prebiotic isolated from Myrciaria dubia improves gut microbiota composition and increases anti-PD-1 efficacy in murine cancer models [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5730.
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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) | 0.002 | 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".