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Fecal microbiota transplantation followed by anti–PD-1 treatment in patients with advanced melanoma.

2022· article· en· W4281665305 on OpenAlexaffabout
Wilson H. Miller, Bertrand Routy, Rahima Jamal, D. Scott Ernst, Diane Logan, Khashayar Esfahani, Karl Bélanger, Arielle Elkrief, Réjean Lapointe, Paméla Thébault, Mayra Ponce, Seema Nair Parvathy, Meriem Messaoudene, Micheal Silverman, Saman Maleki, John Lenehan

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsLawson Health Research InstituteSt Joseph's Health CareWestern UniversityUniversité de MontréalLondon Health Sciences CentreCancer Care OntarioHôpital Notre-DameCentre Hospitalier de l’Université de MontréalMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineInternal medicineAdverse effectGastroenterologyTransplantationImmunosuppressionMelanomaDiarrheaPembrolizumabCancerImmunotherapy

Abstract

fetched live from OpenAlex

9533 Background: The gut microbiome has been shown to be a biomarker of response in patients (pts) with melanoma. Strategies to modify the microbiome are currently being investigated. We report the effects of Fecal Microbiota Transplantation (FMT) on safety and anti-PD-1 response in pts with melanoma from a phase I trial (NCT03772899). Methods: 20 pts with advanced melanoma with RECIST-evaluable disease, without prior anti-PD-1 treatment for advanced disease, were recruited from 3 Canadian academic centers. Pts with ECOG > 2, autoimmune diseases, immunosuppression or unstable brain metastases were excluded. Pts received 80-100 g of healthy donor stool via oral capsules and were treated with anti-PD-1 one week later. The primary objective was safety of combining FMT with anti-PD-1 therapy. Objective response rate (ORR) by RECIST 1.1 and correlative studies were secondary objectives. Flow cytometry and multiplex ELISA were performed on pts blood samples. Avatar mice were transplanted with stool samples obtained from participants on the trial before and after FMT. Mice were subsequently implanted with B-16 or MCA-205 tumors and received anti-PD-1 antibodies. Results: Median age was 75.5 years, 12 (60%) were male, 18 (90%) had stage 4 disease, and 5 (25%) pts harbored a BRAF mutation. Median follow-up was 11.2 months. FMT-related adverse events included grade 2 diarrhea (2 pts) and hypophosphatemia (1 pt), and 13 pts (65%) experienced grade 1 gastrointestinal toxicities. Grade 3 immune-related adverse events (irAE) were one each of myocarditis, nephritis, and fatigue. Anti-PD-1 therapy was discontinued for toxicity in 2 (10%) pts. No unexpected irAE or death on treatment occurred. ORR was 65% (13/20), of which 3 were CR. Clinical benefit rate (includes SD lasting > 6 months) was 75% (15/20). Median PFS was not reached, and one pt died from their disease. Translational analyses demonstrated upregulation of IL-17 post-FMT in responders, which correlated with upregulation of the frequency of Th17 cells in peripheral blood. In parallel, murine experiments showed that feces from pts pre-FMT did not sensitize tumors to anti-PD-1. In both tumor models, only feces obtained post-FMT from responders restored anti-PD-1 efficacy in mice, providing strong support that FMT contributed to the anti-tumor response observed in pts. Conclusions: FMT followed by anti-PD-1 treatment in melanoma pts undergoing therapy is safe and may lead to improved anti-tumor responses that can be reproduced in tumor mouse models. The gut microbiome plays an important role in responses to anti-PD-1 in patients with advanced melanoma, paving the way for future microbiome-based interventions. Clinical trial information: NCT03772899.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.043
GPT teacher head0.401
Teacher spread0.358 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations11
Published2022
Admission routes2
Has abstractyes

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