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A phase 3 trial of IMC-F106C (PRAME x CD3) plus nivolumab versus standard nivolumab regimens in HLA-A*02:01+ patients with previously untreated advanced melanoma (PRISM-MEL-301).

2024· article· en· W4399570650 on OpenAlexaff
Georgina V. Long, Victoria Atkinson, Paolo A. Ascierto, Diwakar Davar, Omid Hamid, Caroline Robert, Marcus O. Butler, Reinhard Dummer, Christine Häfner, Muhammad Adnan Khattak, James Larkin, Paul Lorigan, Meredith McKean, Rino S. Seedor, Heather M. Shaw, Joe Stephenson, Yuan Yuan, Roma Patel, Piruntha Thiyagarajah, Dirk Schadendorf

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsNivolumabMedicineOncologyMelanomaInternal medicineHuman leukocyte antigenSurgeryImmunotherapyCancer researchImmunologyCancerAntigen

Abstract

fetched live from OpenAlex

TPS9602 Background: Current standard of care in newly diagnosed patients with metastatic cutaneous melanoma (CM) include anti-PD1 as monotherapy or in combination with other immune checkpoint inhibitors (ICI). However, most patients will eventually progress and the 5-year survival rate remains low, necessitating new therapies with novel mechanisms of action to combine with anti-PD1. T cell receptor (TCR) bispecifics have shown overall survival (OS) benefit with tebentafusp (gp100 ´ CD3) in a phase (Ph) 3 trial in metastatic uveal melanoma [1]. IMC-F106C is the first TCR bispecific protein targeting CD3 and PRAME (PRAME ´ CD3), redirecting T cells towards cancer cells presenting a PRAME peptide on the cell surface by HLA-A*02:01 proteins. PRAME is expressed in the vast majority of melanoma. In an ongoing Ph 1 study (NCT04262466), IMC-F106C monotherapy was well tolerated and demonstrated evidence of durable clinical activity in heavily pre-treated, advanced melanoma patients, including those who progressed on prior ICI and targeted therapy [2]. Two doses, 40 mcg and 160 mcg, were selected for further study based on exposure response modeling. Safety of combination TCR bispecifics with ICI has been demonstrated in the ongoing IMC-F106C Ph 1 study and in a prior study of tebentafusp + ICI [3]. Combining IMC-F106C with the anti-PD1 ICI nivolumab has the potential to improve progression free survival (PFS), OS, and response rate (RR). Methods: PRISM-MEL-301 is a randomized, global, open-label, Ph 3 study in previously untreated HLA-A*02:01+ patients with unresectable or metastatic non-uveal melanoma; up to 10% of patients can have a diagnosis of mucosal, acral, or other non-CM melanoma. The first 90 patients will be randomized 1:1:1 to receive IMC-F106C 40 mcg + nivolumab (Arm A), IMC-F106C 160 mcg + nivolumab (Arm B), or a nivolumab regimen (Arm C) from which a final IMC-F106C dose (Arm A or B) will be selected. Subsequently, approximately 590 additional patients will be randomized to Arm (A or B) vs. control Arm C, either nivolumab monotherapy or nivolumab + relatlimab, dependent on the country. Randomization will be stratified by 1) American Joint Committee on Cancer (8th Edition) M stage with lactate dehydrogenase (LDH; M0 or M1 with normal LDH vs M1 with elevated LDH); 2) prior anti-PD[L]1 adjuvant therapy (yes vs no); and 3) BRAF V600 mutation status (positive vs negative). Primary endpoint is PFS per RECIST 1.1 by blinded independent central review. Secondary endpoints include OS, ORR, and safety. Enrollment is ongoing globally. Clinical trial registration: NCT06112314 Nathan et al. N Engl J Med 2021; 385:1196 Hamid et al. Ann Oncol 2022; 33 (Supp7): S875 Hamid et al. J Immunother Cancer 2023; 11(6): e006747. Clinical trial information: NCT06112314 .

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)0.002
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.080
GPT teacher head0.473
Teacher spread0.394 · 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 designRandomized 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

Citations7
Published2024
Admission routes1
Has abstractyes

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