Three-antibody classifier for muscle invasive urothelial carcinoma and its correlation with p53 expression
Bibliographic record
Abstract
AIMS: To assess the utility of a three-antibody immunohistochemistry panel to classify muscle invasive bladder cancers (MIBCs) in correlation with morphological features and p53 status. METHODS: A retrospective review of 243 chemotherapy naïve MIBC cystectomy specimens was performed to assess morphological features. A tissue microarray was sequentially stained with CK5/6, GATA-3 and p16. Subgroups were assigned as basal-like (CK5/6+, GATA3-) and luminal (CK5/6-, GATA3+), with the latter subdivided into genomically unstable (GU, p16+) and urothelial like (Uro, p16-) subgroups. p53 staining was assessed as abnormal/wild type. Cases from the The Cancer Genome Atlas (TCGA) portal were assessed as external validation. RESULTS: We identified 78.8% luminal, 21.2% basal cases within our cohort and 63.4% luminal, 36.6% basal in the TCGA dataset. Divergent differentiation (p<0.001) was significantly associated with basal-subtype cases in both cohorts. Within the luminal subgroup (n=186), 81 cases were classified as GU and 105 as Uro. Abnormal p53 staining was noted in 48.0% of basal, 80.2% GU and 38.1% Uro cases. Further, basal-subtype tumours significantly correlated with disease-specific death compared with Uro cases in multivariate survival analysis. CONCLUSIONS: This retrospective study demonstrates the potential utility of a three-antibody immunohistochemistry panel to differentiate luminal and basal MIBC.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| 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".