Development and first-in-human CAR T therapy against the pathognomonic MiT-fusion driven protein GPNMB
Bibliographic record
Abstract
Abstract CAR T therapy for solid tumors is limited by a lack of safe and uniformly expressed cell-surface targets. Here, we identify the MiT fusion-driven protein GPNMB as being highly, homogeneously, and stably expressed in primary and relapsed translocation-positive alveolar soft part sarcoma (ASPS) and renal cell carcinoma (tRCC). We developed a GPNMB-targeting CAR T therapy called GCAR1 that shows activity against patient-matched cells, organoids and xenograft models. First-in-human treatment of a patient with metastatic ASPS was well tolerated and generated stable disease until 6 months, with many non-target lesions resolving post-treatment. A polyclonal population of GCAR1 cells expanded in blood and were detectable until 6 months. Spatial transcriptomics revealed multiple immunosuppressive niches in proximity to T cells infiltrating a treatment-resistant lesion, and PDL1 blockade showed synergy with GCAR1 in a xenograft model. Our data provide clinical evidence for treating solid tumors with CAR T cells targeting a surface protein driven by an oncogenic gene fusion.
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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) | 0.002 | 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".