Multiple Endocrine Neoplasia Type 1 Regulates TGFβ-Mediated Suppression of Tumor Formation and Metastasis in Melanoma
Bibliographic record
Abstract
Over the past few decades, the worldwide incidence of cutaneous melanoma, a malignant neoplasm arising from melanocytes, has been increasing markedly, leading to the highest rate of skin cancer-related deaths. While localized tumors are easily removed by excision surgery, late-stage metastatic melanomas are refractory to treatment and exhibit a poor prognosis. Consequently, unraveling the molecular mechanisms underlying melanoma tumorigenesis and metastasis is crucial for developing novel targeted therapies. We found that the multiple endocrine neoplasia type 1 (MEN1) gene product Menin is required for the transforming growth factor beta (TGFβ) signaling pathway to induce cell growth arrest and apoptosis in vitro and prevent tumorigenesis in vivo in preclinical xenograft models of melanoma. We further identified point mutations in two MEN1 family members affected by melanoma that led to proteasomal degradation of the MEN1 gene product and to a loss of TGFβ signaling. Interestingly, blocking the proteasome degradation pathway using an FDA-approved drug and RNAi targeting could efficiently restore MEN1 expression and TGFβ transcriptional responses. Together, these results provide new potential therapeutic strategies and patient stratification for the treatment of cutaneous melanoma.
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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".