Relationship between histopathological features of chemotherapy treated retinoblastoma and P‐glycoprotein expression
Bibliographic record
Abstract
BACKGROUND: P-glycoprotein (P-gp) has been identified as a possible mediator of chemoresistance in retinoblastoma. The aim of this study was to determine the expression of P-gp in retinoblastoma treated with chemotherapy prior to enucleation. METHODS: Seventeen enucleated specimens of retinoblastoma from 16 patients were studied. Nine had been treated with chemotherapy alone, and eight had been treated with chemotherapy and other forms of local treatment. Tumour differentiation as well as choroidal and optic nerve invasion were assessed. P-gp immunohistochemical staining was performed and evaluated as negative, low or high. RESULTS: Histopathological assessment of the cases showed that 14 of 17 eyes (82.3%) had viable retinoblastoma cells. Nine retinoblastomas were considered regressed with a well-differentiated component, five regressed retinoblastomas had viable cells with poor differentiation and three retinoblastomas had regressed leaving no viable cells. Sixteen of 17 retinoblastomas were P-gp positive. In the one case with optic nerve invasion and the three cases with massive choroidal invasion, P-gp expression was found in invading retinoblastoma cells. CONCLUSION: Almost all retinoblastomas expressed P-gp. High levels of P-gp expression might play a role in chemotherapy resistance of retinoblastoma or, conversely, chemotherapy might induce P-gp expression. These results might have an impact on management of bilateral retinoblastoma.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".