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Record W4415896981 · doi:10.1136/jitc-2024-011382

Targeting the extracellular matrix with Tenascin-C-specific CAR T cells extends survival in preclinical models of glioblastoma

2025· article· en· W4415896981 on OpenAlexfundno aff
Jana de Sostoa, Eliana Marinari, Martin Pédard, Valérie Widmer, Suzel Davanture, Karl Schaller, Stéphanie Tissot, Michele De Palma, Benita Wolf, Gertraud Orend, Valérie Dutoit, Denis Migliorini

Bibliographic record

VenueJournal for ImmunoTherapy of Cancer · 2025
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsnot available
FundersInstitute of Genetics and Genomics of GenevaUniversité de GenèveLigue Genevoise Contre le CancerUniversity of PennsylvaniaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungFondation ISRECInstitut National Du CancerNational Science FoundationMcMaster UniversityFondation privée des Hôpitaux universitaires de Genève
KeywordsBystander effectGlioblastomaExtracellular matrixCytotoxic T cellDomain (mathematical analysis)T cellExtracellular

Abstract

fetched live from OpenAlex

BACKGROUND: Glioblastoma (GBM) is an aggressive brain tumor associated with poor outcome and limited treatment options. Chimeric antigen receptor (CAR) T cells targeting cell surface antigens were shown to induce tumor regression in patients with GBM, although efficacy was transient. To broaden the range of tumor-restricted antigens, we developed CAR T cells targeting Tenascin-C (TNC), a secreted extracellular matrix protein that is overexpressed in GBM and plays a critical role in tumor progression. METHODS: Second-generation CAR T cells were engineered to target the alternatively spliced fibronectin type III (FNIII)-D domain of TNC using a single-chain variable fragment isolated from the R6N antibody and coupled to a CD28 costimulatory domain. TNC-CAR T cells were evaluated in vitro for antigen specificity, activation, and cell proliferation using TNC-expressing patient-derived GBM cell lines cultured as adherent cells or as neurospheres. Reactivity toward purified TNC protein, tumor supernatant, and ex vivo patient tumor samples was also assessed. Cytotoxic CAR T-cell activity was tested against TNC-positive and TNC-negative GBM cell lines, including bystander effects mediated by secreted TNC. In vivo efficacy and safety were determined in NOD scid gamma mice bearing patient-derived GBM tumors. RESULTS: TNC-CAR T cells demonstrated activation when exposed to TNC-positive GBM cells, cell-derived supernatants, or purified TNC protein. They exhibited potent cytotoxicity against TNC-expressing, GBM-derived adherent cells and neurospheres, and induced bystander killing of TNC-negative cells in the presence of either TNC-secreting cells or purified TNC. In vivo, TNC-CAR T cells efficiently infiltrated tumors, triggered cancer cell apoptosis, and significantly extended survival of mice bearing patient-derived GBM, with no evidence of off-tumor toxicity. Notably, TNC-CAR T cells were activated exclusively in the presence of tumor samples and showed no reactivity toward patient-derived non-tumor tissues. CONCLUSIONS: Targeting the alternatively spliced FNIII-D domain of TNC with CAR T cells offers a promising therapeutic approach for GBM. TNC-CAR T cells demonstrated specific tumor recognition, robust antitumor activity and the ability to induce bystander effects mediated by secreted TNC. Their efficacy in preclinical models, combined with a favorable safety profile, underscores their potential for clinical translation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.378
Teacher spread0.341 · 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 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

Citations6
Published2025
Admission routes1
Has abstractyes

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