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Record W4409446817 · doi:10.1016/j.xcrm.2025.102076

Evolution of the tumor immune landscape during treatment with tebentafusp, a T cell receptor-CD3 bispecific

2025· article· en· W4409446817 on OpenAlexaff
Joseph J. Sacco, Peter Kirk, Emma Leach, Alexander N. Shoushtari, Richard D. Carvajal, Camille Britton-Rivet, Sophie Khakoo, Laura C. Collins, Luis de la Cruz‐Merino, Zeynep Eroglu, Alexandra P. Ikeguchi, Paul Nathan, Omid Hamid, Marcus O. Butler, Sarah Stanhope, Koustubh Ranade, Takami Sato

Bibliographic record

VenueCell Reports Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsPrincess Margaret Cancer Centre
FundersNational Cancer Institute
KeywordsImmune systemCD3T-cell receptorReceptorT cellBiologyCancer researchMedicineImmunologyInternal medicineCD8

Abstract

fetched live from OpenAlex

Metastatic uveal melanoma is an aggressive disease with poor outcome, which is refractory to immune checkpoint inhibitors. A T cell receptor (TCR)-based CD3 bispecific, tebentafusp, delivers clinical benefit in patients with metastatic uveal melanoma. Understanding the molecular basis for the anti-tumor activity of tebentafusp in an indication where checkpoint inhibitors are ineffective could aid in identification of other solid tumor indications where CD3 bispecifics may serve an unmet need. By analyzing tumor biopsies taken prior to treatment, early on-treatment, and at progression (NCT02570308), using RNA sequencing (RNA-seq) and immunohistochemistry (IHC), we show that expression of interferon-related genes in the tumor prior to treatment is associated with improved overall survival and tumor reduction on tebentafusp, that T cell recruitment occurs even in tumors with a low baseline level of T cell infiltration, and that durability of changes induced in the tumor microenvironment is key for survival duration.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.256
Teacher spread0.246 · 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 teacher head, not a consensus.

Study designBench or experimental
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
Published2025
Admission routes1
Has abstractyes

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