Inherited duplications of PPP2R3B predispose to nevi and melanoma via a C21orf91-driven proliferative phenotype
Bibliographic record
Abstract
PURPOSE: Much of the heredity of melanoma remains unexplained. We sought predisposing germline copy-number variants using a rare disease approach. METHODS: Whole-genome copy-number findings in patients with melanoma predisposition syndrome congenital melanocytic nevus were extrapolated to a sporadic melanoma cohort. Functional effects of duplications in PPP2R3B were investigated using immunohistochemistry, transcriptomics, and stable inducible cellular models, themselves characterized using RNAseq, quantitative real-time polymerase chain reaction (qRT-PCR), reverse phase protein arrays, immunoblotting, RNA interference, immunocytochemistry, proliferation, and migration assays. RESULTS: We identify here a previously unreported genetic susceptibility to melanoma and melanocytic nevi, familial duplications of gene PPP2R3B. This encodes PR70, a regulatory unit of critical phosphatase PP2A. Duplications increase expression of PR70 in human nevus, and increased expression in melanoma tissue correlates with survival via a nonimmunological mechanism. PPP2R3B overexpression induces pigment cell switching toward proliferation and away from migration. Importantly, this is independent of the known microphthalmia-associated transcription factor (MITF)-controlled switch, instead driven by C21orf91. Finally, C21orf91 is demonstrated to be downstream of MITF as well as PR70. CONCLUSION: This work confirms the power of a rare disease approach, identifying a previously unreported copy-number change predisposing to melanocytic neoplasia, and discovers C21orf91 as a potentially targetable hub in the control of phenotype switching.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".