Crosstalk with keratinocytes causes GNAQ oncogene specificity in melanoma
Bibliographic record
Abstract
ABSTRACT Different melanoma subtypes exhibit specific and non-overlapping sets of oncogene and tumor suppressor mutations, despite a common cell of origin in melanocytes. For example, activation of the Gα q/11 signaling pathway is a characteristic initiating event in primary melanomas that arise in the dermis, uveal tract or central nervous system. It is rare in melanomas arising in the epidermis. Here, we present evidence that in the mouse, crosstalk with the epidermal microenvironment actively impairs the survival of melanocytes expressing the GNAQ Q209L oncogene, providing a new model for oncogene specificity in cancer. The presence of epidermal cells inhibited cell division and fragmented dendrites of melanocytes expressing GNAQ Q209L in culture, while they promoted the growth of normal melanocytes. Differential gene expression analysis of FACS sorted epidermal melanocytes showed that cells expressing GNAQ Q209L exhibit an oxidative stress and apoptosis signature previously linked to vitiligo. Furthermore, PLCB4, the direct downstream effector of Gα q/11 signaling, is frequently mutated in cutaneous melanoma alongside P53 and NF1. Our results suggest that a deficiency of PLCB4 promotes cutaneous melanomagenesis by reducing GNAQ driven signaling. Hence, our studies reveal the flip side of the GNAQ/PLCB4 signaling pathway, which was hitherto unsuspected. In the future, understanding how epidermal crosstalk restrains the GNAQ Q209L oncogene could suggest novel melanoma therapies.
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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) | 0.002 | 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".