The NF1 tumor suppressor regulates PD-L1 and immune evasion in melanoma
Bibliographic record
Abstract
Hotspot BRAF, hotspot NRAS, and NF1 loss-of-function mutations are found in approximately 50%, 25%, and 15% of cutaneous melanomas, respectively. Compared to mutant BRAF and NRAS, the role of NF1 loss in melanoma remains understudied. NF1 has a RAS GTPase-activating protein (GAP) function; however, studies also support NF1 RAS-independent tumor-suppressor functions. Recent reports indicate that patients with NF1 mutant melanoma have high response rates to anti-PD-1 immune checkpoint inhibitors (ICIs) for reasons that are not entirely clear. Here, we present data demonstrating that NF1 interacts with PD-L1. Furthermore, NF1 loss in melanoma lines increases PD-L1 cell surface expression through a RAS-GAP-independent mechanism. Co-culture experiments demonstrate that NF1 depletion in melanoma increases resistance to T cell killing, which can be abrogated with anti-PD-1/PD-L1 ICIs. These results support a model whereby NF1 loss leads to immune evasion through the PD-L1/PD-1 axis, providing support for the examination of anti-PD-1 therapies in other NF1 mutant cancers.
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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 | 0.000 |
| 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".