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Record W4283662383 · doi:10.1080/2162402x.2022.2093426

Trogocytosis and fratricide killing impede MSLN-directed CAR T cell functionality

2022· article· en· W4283662383 on OpenAlexaff
Esther Schoutrop, Stefanie Renken, Isabella Micallef Nilsson, Paula Hahn, Thomas Poiret, Rolf Kiessling, Stina L. Wickström, Jonas Mattsson, Isabelle Magalhaes

Bibliographic record

VenueOncoImmunology · 2022
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersCancerföreningen i StockholmVetenskapsrådetKarolinska InstitutetCancerfonden
KeywordsMesothelinChimeric antigen receptorCancer researchT cellAntigenCD28Tumor microenvironmentImmunologyMedicineImmune systemTumor cells

Abstract

fetched live from OpenAlex

Successful translation of chimeric antigen receptor (CAR) T cell therapy for the treatment of solid tumors has proved to be troublesome, mainly due to the complex tumor microenvironment promoting T cell dysfunction and antigen heterogeneity. Mesothelin (MSLN) has emerged as an attractive target for CAR T cell therapy of several solid malignancies, including ovarian cancer. To improve clinical response rates with MSLN-CAR T cells, a better understanding of the mechanisms impacting CAR T cell functionality in vitro is crucial. Here, we demonstrated superior cytolytic capacity of CD28-costimulated MSLN-CAR T cells (M28z) relative to 4–1BB-costimulated MSLN-CAR T cells (MBBz). Furthermore, CD28-costimulated MSLN CAR T cells displayed enhanced cytolytic capacity against tumor spheroids with heterogeneous MSLN expression compared to MBBz CAR T cells. In this study, we identified CAR-mediated trogocytosis as a potential impeding factor for successful MSLN-CAR T cell therapy due to fratricide killing and contributing to tumor antigen heterogeneity. Moreover, we link antigen-dependent upregulation of LAG-3 with reduced CAR T cell functionality. Taken together, our study highlights the therapeutic potential and bottlenecks of MSLN-CAR T cells, providing a rationale for combinatorial treatment strategies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.886
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0110.000

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 head0.024
GPT teacher head0.292
Teacher spread0.267 · 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

Citations38
Published2022
Admission routes1
Has abstractyes

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