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Record W4409634212 · doi:10.1158/1538-7445.am2025-6114

Abstract 6114: Engineering novel synNotch CAR T cells to precisely and effectively target medulloblastoma

2025· article· en· W4409634212 on OpenAlexaff
Maggie Colton Cove, Senthilnath Lakshmanachetty, Milos Simic, Robert Zhu, Chanelle Shepherd, Lia Cardarelli, Sachdev S. Sidhu, Olga G. Troyanskaya, Wendell A. Lim, Hideho Okada

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedulloblastomaCancer researchNeuroscienceMedicineBiology

Abstract

fetched live from OpenAlex

Abstract Background: While clinical trials involving chimeric antigen receptor (CAR) T cells have shown promise for treating pediatric brain tumors, factors such as antigen heterogeneity, on-target, off-tumor toxicity and an immunosuppressive microenvironment limit the efficacy of these treatments. To overcome these challenges, we adopted synthetic notch receptor system and developed innovative synNotch-CAR T cell circuits. In this system, the first antigen which is expressed exclusively on the brain, primes the T cells to locally induce the expression of a CAR to completely kill the tumor cells. Here, we investigated the anti-tumor efficacy of synNotch CAR T cells in patient-derived models of Group 3 medulloblastoma, the deadliest subtype of medulloblastoma. Methods: We utilized a synNotch receptor specific to brevican, a proteoglycan expressed solely in the central nervous system, for brain-specific priming. Human CD3+ cells were stimulated with CD3/CD28 beads for 24 hours and lentivirally transduced to express the synNotch receptor (α-BCAN) and a α-B7H3/IL13Ra2 CAR payload. α-BCAN synNotch-α-B7H3/IL13Ra2 CAR (B-SYNC) T cells were co-cultured with mCherry+ D425 and D283 tumor cells for 4 days and real-time cell growth monitoring was performed using incucyte live imaging. Brevican-priming was accomplished either through brevican-expressing K562 cells or tissue culture plates coated with recombinant human brevican. Tumor cell growth was measured by mCherry fluorescent signal. Results: B-SYNC T cells completely killed the medulloblastoma cell line, D283, only when primed by K562 cells expressing BCAN. No killing was observed in the absence of priming cells. These cells also maintained killing of a more proliferative medulloblastoma cell line, D425, over an extended period than the constitutive -α-B7H3/IL13Ra2 CAR T cells. Furthermore, when cultured in brevican-coated plates, B-SYNC T cells killed D425 cells at a 17% faster rate than the constitutive -α-B7H3/IL13Ra2 CAR T cells. Conclusions: B-SYNC T cells show superior cell-killing to constitutive -α-B7H3/IL13Ra2 CAR T cells in in vitro models of Group 3 medulloblastoma. We are currently validating this finding in vivo using patient-derived xenografts. Future studies are aimed at elucidating the mechanisms by which synNotch CAR T cells outperform constitutive CAR T cells. Furthermore, we will investigate the anti-tumor efficacy of synNotch CAR T cells in the more resistant hypoxic medulloblastoma tumor microenvironment. Citation Format: Maggie Colton Cove, Senthilnath Lakshmanachetty, Milos Simic, Robert Zhu, Chanelle Shepherd, Lia Cardarelli, Sachdev Sidhu, Olga Troyanskaya, Wendell Lim, Hideho Okada. Engineering novel synNotch CAR T cells to precisely and effectively target medulloblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6114.

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)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.386
Teacher spread0.349 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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