Evaluation of PUMA and NOXA expression as predictive biomarkers in prostate cancer.
Bibliographic record
Abstract
28 Background: PUMA and NOXA are two pro-apoptotic members of the BH3-only subgroup of the BCL-2 family. These two proteins play a role in the initiation of apoptosis. The objective of this study is to analyse their expression by immunofluorescence, alone or in combination, in benign and tumor prostate tissues to determine if there is a correlation between their expression and patient biochemical recurrence (BCR). Methods: Biomarker antibodies were verified for specificity and optimized by western blot and with tissue microarrays (TMA) containing prostate cancer cell lines and cell line derived xenograft tissues. Subsequently, quantification of expression for both biomarkers was performed on six TMA generated from radical prostatectomy samples (285 patients). The TMA were constructed using two cores of benign adjacent to the tumor and two cores of tumor tissue from each patient. Analysis of biomarker expression was semi-automated using the VisiomorphDP software. To optimize the analysis, we developed 2 different immunofluorescence masks: a cocktail of anti-cytokeratin-8 and -18 antibodies to identify epithelial cells and a combination of anti-p63 and anti-cytokeratin high marker weight to discriminate benign glands within tumor cores. Correlation with patient clinical outcome was determined with SPSS V20 software. Results: There was no correlation of PUMA and NOXA expression and BCR in tumor cores and stroma. In contrast, in benign epithelial cells Kaplan-Meier analysis showed a significant association between an extreme (low or high) PUMA expression and BCR (Log rank = 11.349, p = 0.001). Further analysis revealed a significant association between high NOXA expression in benign epithelial cells and BCR (Log rank = 6.133, p = 0.013). The combination of extreme PUMA and high NOXA identified patients with a poor prognosis (Log rank = 16.041, p = 0.000). In a multivariate Cox regression model, PUMA and NOXA proteins were also identified as independent predictive biomarkers of BCR. Conclusions: By studying benign epithelial cells adjacent to the tumor we identified two potential biomarkers that discriminate high-risk patients, independent of Gleason score or pathologic stage.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".