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Record W3024365161 · doi:10.1136/lba2019.17

P864 Combination of fecal microbiota transplantation from healthy donors with anti-PD1 immunotherapy in treatment-naïve advanced or metastatic melanoma patients

2020· article· en· W3024365161 on OpenAlexaff
Saman Maleki, John Lenehan, Jeremy P. Burton, Michael E. Silverman, Seema Nair Parvathy, Mikal El‐Hajjar, Mithunah Krishnamoorthy

Bibliographic record

VenuePoster presentations · 2020
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsSt Joseph's Health CareLawson Health Research InstituteWestern University
FundersMoffitt Cancer CenterRoyal Marsden NHS Foundation TrustUniversity of PittsburghNYU Langone Medical CenterFlorida Department of HealthMedical Center, University of PittsburghYale University
KeywordsMedicineMelanomaInternal medicineNauseaGastroenterologyRefractory (planetary science)ImmunotherapyAdverse effectTransplantationColorectal cancerCancerSurgeryOncology

Abstract

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Background Checkpoint inhibitors have changed the outcomes for patients with advanced melanoma. However, many patients still show primary resistance to single-agent therapy. Recently, the role of the gut microbiome in influencing antitumor immunity has been established. Currently, various methods of modifying the gut microbiome of cancer patients are being explored. We report the initial safety results of the first two patients treated on a phase I study combining Fecal Microbiota Transplantation (FMT) with single-agent anti-PD1 in treatment-naïve patients with advanced melanoma. Methods Two healthy donors were selected through our screening process and approximately 100 grams of fresh stool was processed and prepared for FMT as per our standardized protocol. FMT recipients were melanoma patients with unresectable or metastatic disease who were treatment naïve for their advanced disease. Bowel preparation was completed the day prior and FMT was performed using oral administration of approximately 40 capsules. Anti-PD1 was started at least 1 week after FMT to allow for microbiome engraftment. Blood and stool were analyzed at baseline (pre-FMT), before immunotherapy, and three weeks after it. Results Patient 1 was diagnosed with recurrent melanoma of the lower limb with multiple in-transit lesions refractory to control with surgery and a single intralesional injection of IL-2. Patient received stool from Donor 1 and did not experience any adverse effects from FMT. At the time of treatment #4, a solitary large cutaneous lesion stabilized but the patient experienced grade 1 diarrhoea, grade 2 nausea, and grade 2 fatigue, and grade 2 depression (NCI-CTCAE v5.0). Patient 2 was diagnosed with recurrent melanoma of the parotid gland with metastatic lesions in the lungs. Patient 2 received stool from Donor 2 and experienced only grade 1 flatus from FMT. At the time of treatment #3, the patient experienced grade 1 constipation. Both patients had a vigorous immune response to FMT measured by changes in the immune subpopulations in peripheral blood one week after FMT, including an increase in CD28+ CD8+ T cells and a decrease in PDL1+ CD3- cells. Following anti-PD1 therapy, both patients had an increase in CD39+ CD8+ T cell population. The PD1+ CD38+ CD8+ dysfunctional T cell levels decreased in both patients post-FMT and anti-PD1 therapy. Conclusions FMT combined with anti-PD1 therapy in patients with advanced melanoma appears to be safe. A measurable immune response was observed one week after FMT in both patients. One patient experienced several grade 2 toxicities with stabilization of a large cutaneous lesion. Acknowledgements This study is funded by a grant from The Lotte & John Hecht Memorial Foundation and a grant from The Medical Oncology Research Funds (MORF) from Western University. Trial Registration NCT03772899 Ethics Approval The study was approved by Western University Institutution‘s Ethics Board, approval number 113131, date of approval March 15, 2019.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.037
GPT teacher head0.319
Teacher spread0.282 · 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 designNon-randomized trial
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".

Quick stats

Citations12
Published2020
Admission routes1
Has abstractyes

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