GPC2-CAR T cells tuned for low antigen density mediate potent activity against neuroblastoma without toxicity
Bibliographic record
Abstract
Pediatric cancers often mimic fetal tissues and express proteins normally silenced postnatally that could serve as immune targets. We developed T cells expressing chimeric antigen receptors (CARs) targeting glypican-2 (GPC2), a fetal antigen expressed on neuroblastoma (NB) and several other solid tumors. CARs engineered using standard designs control NBs with transgenic GPC2 overexpression, but not those expressing clinically relevant GPC2 site density (∼5,000 molecules/cell, range 1–6 × 10 3 ). Iterative engineering of transmembrane (TM) and co-stimulatory domains plus overexpression of c-Jun lowered the GPC2-CAR antigen density threshold, enabling potent and durable eradication of NBs expressing clinically relevant GPC2 antigen density, without toxicity. These studies highlight the critical interplay between CAR design and antigen density threshold, demonstrate potent efficacy and safety of a lead GPC2-CAR candidate suitable for clinical testing, and credential oncofetal antigens as a promising class of targets for CAR T cell therapy of solid tumors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".