PD‐L1 (B7‐H1) expression by urothelial carcinoma of the bladder and BCG‐induced granulomata
Bibliographic record
Abstract
BACKGROUND: PD-L1 (programmed death ligand 1, B7-H1) is a cell surface glycoprotein that can impair T-cell function. PD-L1 is aberrantly expressed by multiple human malignancies and has been shown to carry a highly unfavorable prognosis in patients with kidney cancer. The role of PD-L1 was evaluated as a mechanism for local stage progression in urothelial carcinoma (UC) of the bladder. METHODS: Using immunohistochemistry, PD-L1 expression was evaluated in a cohort of 280 high-risk UCs of the bladder. PD-L1 was modeled as a predictor of bladder cancer stage using ordinal logistic regression. Other covariates evaluated as potential confounders included age, gender, tumor grade, and lymphocytic infiltration. Further, PD-L1 was evaluated as a potential mechanism of bacillus Calmette-Guerin (BCG) failure in the subset of high-risk nonmuscle-invasive tumors that received this treatment. RESULTS: PD-L1 expression was observed in 7% of pTa, 16% of pT1, 23% of pT2, 30% of pT3/4, and 45% of carcinoma in situ (CIS) tumors. PD-L1 expression was associated with high-grade tumors (odds ratio [OR] = 2.4, P = .009) and tumor infiltration by mononuclear cells (OR = 5.5, P = .004). We observed that the key determinants of stage progression in this cohort were World Health Organization/International Society of Urologic Pathology (WHO/ISUP) high-grade tumor pathology (OR = 4.77, 95% confidence interval [CI]: 2.73-8.34; P < .001) and PD-L1 expression (OR = 2.20, P = .012). PD-L1 expression was found to be extremely abundant in the BCG-induced bladder granulomata in 11 of 12 patients failing BCG treatment. CONCLUSIONS: Collectively, these data indicate that tumor PD-L1 may facilitate localized stage-advancement of UC and attenuate responses to BCG immunotherapy by neutralizing T cells that normally guard against cancer invasion from the epithelium into the bladder musculature.
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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) | 0.001 | 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".