Switch ofHLA-G alternative splicing in a melanoma cell line causes loss of HLA-G1 expression and sensitivity to NK lysis
Bibliographic record
Abstract
Considerable information has been accumulated on HLA-G expression in tumor lesions in which HLA-G is viewed as a way to turn off anti-tumoral immunity. Nevertheless, there is little data concerning the mechanisms by which expression and function of HLA-G are regulated in malignant cells. Here, we have addressed these points by studying a melanoma cell line derived from a surgically-removed HLA-G-positive melanoma lesion. We show that HLA-G expression in melanoma cells can be regulated at the mRNA splicing level. Indeed, melanoma cells rapidly switched from cell-surface HLA-G1 to intra-cellular HLA-G2 expression. This mechanism restored tumor sensitivity to NK lysis. Moreover, switch from HLA-G1 to HLA-G2 was strong enough to prevent re-expression of immunoprotective HLA-G1 even following treatments with cytokines and DNA demethylating agent. Modulating HLA-G at the mRNA splicing level would be an efficient way of lifting in vivo HLA-G-mediated tumor immune escape.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".