Prognostic Significance of Activated Akt Expression in Melanoma: A Clinicopathologic Study of 292 Cases
Bibliographic record
Abstract
PURPOSE: Akt is a serine/threonine kinase that leads to stimulation of cell cycle progression, cell proliferation, and inhibition of apoptosis. To investigate the role of Akt in melanoma pathogenesis, we examined the expression of phospho-Akt (p-Akt; Ser-473) in melanocytic lesions at different stages and analyzed the correlations between the p-Akt expression level and clinicopathologic factors and patient survival. PATIENTS AND METHODS: We evaluated the p-Akt expression in 12 cases of normal nevi, 58 cases of dysplastic nevi, 170 cases of primary melanomas, and 52 cases of melanoma metastases using tissue microarray and immunohistochemistry. RESULTS: Strong p-Akt expression was observed in 17%, 43%, 49%, and 77% of the biopsies in normal nevi, dysplastic nevi, primary melanoma, and melanoma metastases, respectively. Significant differences for p-Akt staining pattern were observed between normal nevi and primary melanomas (P < .05), and between primary melanomas and melanoma metastases (P < .001). Furthermore, our Kaplan-Meier survival curves showed that strong p-Akt expression is inversely correlated with both overall and disease-specific 5-year survival of patients with primary melanoma (P < .05 for both). Strikingly, our multivariate Cox regression analysis revealed that p-Akt is an independent prognostic factor in low-risk melanomas (thickness < or = 1.5 mm; relative risk, 6.44; 95% CI, 1.28 to 32.55; P = .018). CONCLUSION: The expression of p-Akt increases dramatically with melanoma invasion and progression and is inversely correlated with patient survival. In addition, p-Akt may serve as an independent prognostic marker and help to identify those patients with low-risk melanomas who are at increased risk of death.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".