Development of Class II-agnostic CAR T Cell Therapy Targeting WT1 Peptide Presented by Diverse HLA class II Molecules
Bibliographic record
Abstract
The adoptive transfer of T cells redirected by antitumor T cell receptor (TCR) or chimeric antigen receptor (CAR) is a promising treatment against cancer. Most TCR genes currently tested in the clinic are HLA-class I-restricted, whereas CAR-T cells generally target surface molecules expressed on tumor cells independently of HLA. TCR-like CARs have been developed, but most of them target peptides presented by HLA class I molecules and bind to pHLA complexes instead of the peptides alone, which limits their applications to patients with the compatible HLA genotypes. HLA-class II molecules are expressed by multiple types of tumor cells in vivo, but their expression in normal tissues is limited, which potentially reduces the risk of off-tumor toxicities of class II-directed therapeutics. In contrast to class I-restricted peptides, many class II-restricted peptides can promiscuously bind to multiple different class II molecules. Wilms’ tumor protein (WT1) is an intracellular oncogenic protein highly expressed in various types of cancer. To develop therapeutics specific for class II-presented WT1 peptides, we first identified WT1328-348 as the natural WT1 epitope promiscuously presented by HLA-DP2 and HLA-DP4, in addition to class II proteins reported by others. T cells transduced with TCR specific for DP2/WT1328-348 and DP4/WT1328-348 were able to kill DP2+/WT1+ and DP4+/WT1+ tumor cells, highlighting the therapeutic potential of this TCR. Next, we developed a novel CAR-T therapy capable of specifically targeting WT1328-348 peptide presented by the 18 HLA-class II alleles tested, including 6 DPs, 8 DRs, and 4 DQs. We showed that second generation WT1/28z CAR-T cells recognized class II+/WT1+ leukemic cell lines and primary leukemic samples. These results suggest that our peptide-centric, class II-agnostic CAR-T therapy has the potential to benefit a broad population of cancer patients with diverse class II genotypes.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".