The leukemia inhibitory factor (LIF) and p21 mediate the TGFβ tumor suppressive effects in human cutaneous melanoma
Bibliographic record
Abstract
BACKGROUND: Cutaneous melanoma is the most lethal skin cancer and its incidence in developed countries has dramatically increased over the past decades. Localized tumors are easily treated by surgery, but advanced melanomas lack efficient treatment and are associated with very poor outcomes. Thus, understanding the processes underlying melanoma development and progression is critical. The Transforming Growth Factor beta (TGFβ) acts as a potent tumor suppressor in human melanoma, by inhibiting cell growth and preventing cellular migration and invasion. METHODS: In this study, we aimed at elucidating the molecular mechanisms underlying TGFβ-mediated tumor suppression. Human cutaneous melanoma cell lines, derived from different patients, were used to assess for cell cycle analysis, apoptosis/caspase activity and cell migration. Techniques involved immunoblotting, immunohistochemistry, real time PCR and luciferase reporter assays. RESULTS: We found the leukemia inhibitory factor (LIF) to be strongly up-regulated by TGFβ in melanoma cells, defining LIF as a novel TGFβ downstream target gene in cutaneous melanoma. Interestingly, we also showed that TGFβ-mediated LIF expression is required for TGFβ-induced cell cycle arrest and caspase-mediated apoptosis, as well as for TGFβ-mediated inhibition of cell migration. Moreover, we found that TGFβ-mediated LIF expression leads to activation of transcription of the cell cycle inhibitor p21 in a STAT3-dependent manner, and further showed that p21 is required for TGFβ/LIF-mediated cell cycle arrest and TGFβ-induced gene activation of several pro-apoptotic genes. CONCLUSIONS: Together, our results define the LIF/p21 signaling cascade as a novel tumor suppressive-like pathway in melanoma, acting downstream of TGFβ to regulate cell cycle arrest and cell death, further highlight new potential therapeutic strategies for the treatment of cutaneous melanoma.
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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".