p53 immunohistochemistry in high‐grade urothelial carcinoma of the bladder is prognostically significant
Bibliographic record
Abstract
AIMS: TP53 mutations are characteristic of the high-grade pathway in the dual pathway of urothelial carcinogenesis. These mutations have been correlated with aberrant accumulation of p53 protein; however the definition and significance of this vary in the literature. The aim of this study was to assess p53 immunostaining in a cohort of high-grade urothelial carcinomas by using standard published cut-offs and a novel binarized method that included assessment of the null phenotype. Each scoring method was correlated with oncological outcome. METHODS AND RESULTS: A triplicate core tissue microarray was constructed from 207 cases of high-grade urothelial carcinoma treated by cystectomy, and was stained with p53. The percentage nuclear staining was recorded for each core and averaged for every case (206 cases were evaluable). Cases were categorized as positive/negative according to published cut-offs (10%, 40%) or by binarizing them as abnormal (null phenotype or >50% positivity) and wild type (1-49% positivity). Correlation with disease-specific survival was not significant according to standard definitions of p53 positivity. When a 40% cut-off was used, a correlation with relapse-free survival was significant on univariate analysis (P = 0.038) but not on multivariate analysis (P = 0.079). Abnormal p53 expression showed a near-significant trend for association with disease-specific survival (P = 0.052) and was a significant predictor for relapse-free survival on both univariate analysis (P = 0.047) and multivariate analysis (P = 0.035). CONCLUSIONS: Prior to this study, the p53 null phenotype was not well described in urothelial carcinoma of the bladder. Abnormal p53 immunoexpression (null staining pattern or staining in >50% of cells) is prognostic in terms of oncological outcome.
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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 | 0.002 |
| 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".