Comparative analysis of TCR and CAR signaling informs CAR designs with superior antigen sensitivity and in vivo function
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Chimeric antigen receptor (CAR)-modified T cell therapy is effective in treating lymphomas, leukemias, and multiple myeloma in which the tumor cells express high amounts of target antigen. However, achieving durable remission for these hematological malignancies and extending CAR T cell therapy to patients with solid tumors will require receptors that can recognize and eliminate tumor cells with a low density of target antigen. Although CARs were designed to mimic T cell receptor (TCR) signaling, TCRs are at least 100-fold more sensitive to antigen. To design a CAR with improved antigen sensitivity, we directly compared TCR and CAR signaling in primary human T cells. Global phosphoproteomic analysis revealed that key T cell signaling proteins-such as CD3δ, CD3ε, and CD3γ, which comprise a portion of the T cell co-receptor, as well as the TCR adaptor protein LAT-were either not phosphorylated or were only weakly phosphorylated by CAR stimulation. Modifying a commonplace 4-1BB/CD3ζ CAR sequence to better engage CD3ε and LAT using embedded CD3ε or GRB2 domains resulted in enhanced T cell activation in vitro in settings of a low density of antigen, and improved efficacy in in vivo models of lymphoma, leukemia, and breast cancer. These CARs represent examples of alterations in receptor design that were guided by in-depth interrogation of T cell signaling.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it