Prognostic significance of RUNX3 expression in human melanoma
Bibliographic record
Abstract
BACKGROUND: RUNX3 is a tumor suppressor that plays important roles in cell proliferation, apoptosis, and metastasis. The authors investigated the role of RUNX3 in melanoma pathogenesis and analyzed the prognostic impact of RUNX3 expression in a large series of melanoma patients. METHODS: Two sets of tissue microarrays were constructed, including 440 cases of melanomas (202 for the training set and 238 for the validation set) and 88 cases of nevi (25 normal nevi and 63 dysplastic nevi). RUNX3 expression was evaluated by immunohistochemistry. RESULTS: Positive RUNX3 expression was observed in 56%, 54%, 33%, and 24% of the biopsies in normal nevi, dysplastic nevi, primary melanoma, and melanoma metastases, respectively. Significant differences for positive nuclear RUNX3 staining were observed between dysplastic nevi and primary melanomas (P = .002, chi-square test), between dysplastic nevi and melanoma metastases (P < .001, chi-square test), and between primary melanoma and melanoma metastases (P = .045, chi-square test). Loss of RUNX3 expression was correlated with a worse 5-year survival of melanoma patients in both training and validation sets. Furthermore, loss of RUNX3 expression was also correlated with a poor 5-year disease-specific survival in primary melanoma (P = .001) and metastatic melanoma patients (P = .008). Multivariate Cox regression analysis revealed that positive RUNX3 expression is an independent prognostic factor to predict melanoma patient outcome. CONCLUSIONS: Our findings indicate that RUNX3 plays an important role in melanoma pathogenesis and may serve as a promising prognostic marker for 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".