Evolution of a melanoma that escapes allogeneic rejection
Bibliographic record
Abstract
The histocompatibility barrier prevents the transfer of both normal and tumor cells between individuals; however, clonally transmissible cancers in dogs, Tasmanian devils, and soft-shell clams can naturally transmit as allografts. To understand if cancer cells can more generally evolve to escape the histocompatibility barrier, we have serially passaged a mouse melanoma into increasingly mismatched mouse strains until a transplantable tumor emerged. The transplantable melanoma cells are characterized by an antiviral immune signature and the upregulation of endogenous retrotransposable elements (RTEs), major histocompatibility complex class I (MHC class I), programmed cell death ligand-1 (PD-L1), and Qa-1 non-classical MHC molecules. Knockout of the RNA sensor retinoic acid-inducible gene I (RIG-I) reduces expression of PD-L1 and Qa-1, and antibody-mediated blockade of PD-L1 and Qa-1 induces tumor rejection. Thus, an immune antiviral signature linked to RTEs upregulation facilitates escape of the melanoma from allogeneic rejection, simultaneously making the tumor sensitive to PD-L1 and Qa-1 antagonism. A similar immune signature is found in human melanomas that respond to PD-L1 blockade.
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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".