HER2 Overexpression in Retinoblastoma: A Potential Therapeutic Target
Bibliographic record
Abstract
BACKGROUND: Retinoblastoma (RB) is the most common primary intraocular malignancy. Current therapies are associated with high morbidity in the short- and long-term. Human epidermal growth factor receptor 2 (HER2) is a transmembrane protein detected in 15-30% of breast cancers, but it has also been described in other malignancies. Recently, it has been claimed that a truncated version of this protein is expressed in RB, responsive to directed therapies in vitro. We scored HER2 overexpression in RB tissue samples and discussed its potential clinical utility. METHODS: HER2 overexpression was investigated using immunohistochemistry; the overexpression was evaluated with a score ranging from 0 to 3+ according to the membranous staining pattern in archival formalin-fixed, paraffin-embedded RBs. RESULTS: A total of 60 RB cases and a RB cell line (Y79) were considered. The mean age at enucleation was 31.6 ± 31.5 months. The mean time from diagnosis to enucleation was 11.8 ± 11.2 months (range 1-44). Five (8%) cases were multifocal. HER2 overexpression was negative in all RB cases (49 cases scored 0 and 11 scored 1+) and in the Y79 cell line. CONCLUSIONS: Overall, we were not able to demonstrate the overexpression of HER2. Further studies should clarify and better elucidate the potential role of HER2-targeted therapies in RB.
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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 | 0.000 | 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) | 0.002 | 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".