Abstract CT258: Phase II trial of fecal microbiota transplantation in combination with ipilimumab and nivolumab in patients with advanced cutaneous melanoma (FMT-LUMINate trial)
Bibliographic record
Abstract
Abstract Background: Several trials combining microbiome-based interventions with immune checkpoints inhibitors (ICI) are currently underway. Previous studies showed the potential of fecal microbiota transplant (FMT) to circumvent secondary anti-PD-1 resistance or improve first-line anti-PD-1 response in patients with advanced melanoma. Whether FMT can be used safely in combination with anti-PD-1/anti-CTLA-4 (dual ICI) and its impact on the microbiome composition remain unknown. Here, we report results from combining FMT with dual ICI in previously untreated patients (pts) with advanced melanoma (NCT04951583). Methods: 20 pts with previously untreated advanced melanoma were included. FMT from healthy donors was administered in oral capsules after bowel preparation 1 week prior to start of dual ICI. A total of 6 different donors were used. The primary endpoint was safety. Secondary endpoints included objective response rate (ORR) and microbiome shift using shotgun metagenomic sequencing. Longitudinal serum Il1rl1 gene product (sST2) epithelial integrity marker was measured. Stool from pts before and after FMT were transplanted into avatar mice (MCA-205 or B16 OVA) and then treated with dual ICI. Results: In the 20 pts enrolled, 13 (65%) were male and median age was 56. Median follow-up was 6 months (range (IQR) 3.23; 12.33). FMT alone resulted in grade 1 toxicities. Grade 1-2 immune related adverse event (irAE) occurred in 80% of pts and 65% developed grade >3 irAE. Diarrhea or colitis was the most frequent grade 3 irAE occurring in 4 (20%). 2 pts developed myocarditis (grade 3 and grade 4, respectively). 6 (30%) pts completed all 4 cycles of dual ICI. 6 (43%) pts that developed irAE grade 3 received FMT from the same donor. ORR was 70% (2 complete responses (CR) and 12 partial responses (PR)). Two pts died; one from unknown cause in PR and one from disease progression. Microbiome profiling beta-diversity analyses revealed separate clustering of responders (R) and non-responders (NR) post-FMT (p=0.024). We observed an enrichment of Prevotella copri, Ruminoccocaceae and Eubacterium in R pts post-FMT. Pts who developed colitis were found to have a higher level of sST2 in plasma 1 week after FMT in comparison to those who did not develop colitis (p<0.05). In both avatar murine tumor models, microbiome composition with R pts’ feces (without ICI) 1 month post-FMT had reduced tumor growth compared to those treated with respective NR pt feces. Additionally, dual ICI led to significantly improved tumor control in mice treated with R pts’ feces post-FMT(p<0.005). Conclusions: The addition of FMT to dual ICI resulted in significant irAEs that occurred earlier, although the proportion was similar to previously described literature, with encouraging ORR. Metagenomic analysis depicted differences in the microbiome profiles of R compared to NR pts post FMT. These results support the study of FMT and immunotherapy in the randomized setting. Citation Format: Sreya Duttagupta, Meriem Messaoudene, Rahima Jamal, Catalin Mihalcioiu, Karl Belanger, John Lenehan, Wiam Belkaid, Seema Nair Parvathy, Jade Maillou, Yongjia Hu, Mayra Ponce, Taiki Hakozaki, Eder Mendez Salazar, Michael Silverman, Saman Maleki Vareki, Arielle Elkrief, Bertrand Routy. Phase II trial of fecal microbiota transplantation in combination with ipilimumab and nivolumab in patients with advanced cutaneous melanoma (FMT-LUMINate trial) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr CT258.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".