Expression patterns of the immune checkpoint ligand CD276 in urothelial carcinoma
Bibliographic record
Abstract
BACKGROUND: CD276 is an immune checkpoint molecule. Elevated CD276 expression by urothelial carcinoma is associated with poor prognosis, but little is known about its expression across different tumor stages. We therefore investigated CD276 expression in bladder cancer (BC) cells and in tissue samples of BC stages from pT2 to pT4. METHODS: CD276 expression was explored in 4 urothelial cancer cell lines and 4 primary normal urothelial cell populations by quantitative RT-PCR, Western blot and flow cytometry. CD276 was investigated in bladder tumors from 98 patients by immunohistochemistry using a score (0-300) incorporating both, staining intensity and area of CD276 staining. Normal appearing urothelium in the bladder of the same patients served as controls. RESULTS: The urothelial carcinoma cell lines expressed significantly higher levels of CD276 on transcript (p < 0.006), total protein levels (p < 0.005), and on the cell surface (p < 0.02) when compared to normal urothelial cells. In pT2-T4 tumor tissue samples, CD276 was overexpressed (median score 185) when compared to corresponding healthy tissues from the same patients (median score 50; p < 0.001). No significant differences in CD276 expression were recorded in late, locally advanced ≥ pT3a tumors (median score 185) versus organ-confined < pT3a tumors (median score 190), but it was significantly lower in the normal urothelial tissue associated with ≥ pT3a tumors (median score 40) versus < pT3a tumors (median score 80; p < 0.05). CONCLUSION: CD276 expression is significantly elevated in urothelial carcinoma cells in all stages but varies between individuals considerably. Reduced CD276 expression in normal urothelial cells may imply that these cells would be protected from CD276-mediated immuno therapies.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".