Abstract 2103: Reduced Tip60 expression as a predictive biomarker for advanced melanoma and patient outcome
Bibliographic record
Abstract
Abstract The tumor suppressor Tip60 plays a major role in transcription, DNA damage response, apoptosis and cancer development. We investigated the role of Tip60 in melanoma pathogenesis and assessed the prognostic value of Tip60 expression on melanoma patient survival. Two sets of tissue microarrays were constructed consisting of 448 cases of melanomas (201 for the training set and 247 for the validation set) and 105 cases of nevi. The TMA was assessed for Tip60 expression by immunohistochemistry. The Kaplan-Meier method was used to evaluate the patient survival, and univariate and multivariate Cox regression models were performed to estimate the harzard ratios (HR) at five-year follow-up. We found that Tip60 expression was significantly reduced in metastatic melanoma compared to normal nevi (P = 0.045), dysplastic nevi (P = 0.047) and primary melanoma (P = 0.001). Tip60 expression correlated with AJCC stages (I-II vs III-IV, P = 0.001) and tumor thickness (≤4.00 vs. >4.00 mm, P = 0.037). Reduced Tip60 expression was associated with a poor five-year disease-specific survival in primary melanoma (P = 0.016) and metastatic melanoma patients (P = 0.027). Furthermore, Cox regression analyses indicated that Tip60 expression was an independent prognostic marker for primary (P = 0.002) and metastatic melanomas (P = 0.035). In conclusion, reduced Tip60 expression is significantly associated with thick primary melanoma and metastatic melanoma, as well as poor patient prognosis, suggesting that Tip60 may serve as a potential biomarker for advanced melanoma and patient outcome. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2103. doi:10.1158/1538-7445.AM2011-2103
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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 | 0.000 | 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) | 0.003 | 0.001 |
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".