Role of p53 Up-regulated Modulator of Apoptosis and Phosphorylated Akt in Melanoma Cell Growth, Apoptosis, and Patient Survival
Bibliographic record
Abstract
Malignant melanoma is an aggressive and chemoresistant form of skin cancer characterized by rapid metastasis and poor patient prognosis. The development of innovative therapies with improved efficacy is critical to treatment of this disease. Here, we show that aberrant expression of two proteins, p53 up-regulated modulator of apoptosis (PUMA) and phosphorylated Akt (p-Akt), is associated with poor patient survival. Using tissue microarray analysis, we found that patients exhibiting both weak PUMA expression and strong p-Akt expression in their melanoma tumor tissue had significantly worse 5-year survival than patients with either weak PUMA or strong p-Akt expression alone (P < 0.001). Strikingly, no patients exhibiting strong PUMA expression and weak p-Akt expression in primary tumor tissue died within 5 years of diagnosis. We propose a two-pronged therapeutic strategy of (a) boosting PUMA expression and (b) inhibiting Akt phosphorylation in melanoma tumor tissue. Here, we report that a recombinant adenovirus containing human PUMA cDNA (ad-PUMA) efficiently inhibits human melanoma cell survival in vitro, rapidly induces apoptosis, and dramatically suppresses human melanoma tumor growth in a severe combined immunodeficient mouse xenograft model. In melanoma cells strongly expressing p-Akt, we show that Akt/protein kinase B signaling inhibitor-2 (API-2; a small-molecule Akt inhibitor) reduces cell survival in a dose- and time-dependent manner and enhances ad-PUMA-mediated growth inhibition of melanoma cells. Finally, we show that, by combining ad-PUMA and API-2 treatments, human melanoma tumor growth can be inhibited by >80% in vivo compared with controls. Our results suggest that a strategy to correct dysregulated PUMA and p-Akt expression in malignant melanoma may be an effective therapeutic option.
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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".