HER2-low and Overexpression in Mucinous Ovarian Cancer: Analysis of ASCO/CAP and ToGA Immunohistochemical Scoring
Bibliographic record
Abstract
Mucinous ovarian carcinoma is an uncommon malignancy characterized by resistance to chemotherapy and poor survival in the metastatic setting. HER2 amplification is a frequent late event in carcinogenesis, yet the incidence of HER2-low in mucinous ovarian carcinoma is unknown. Further, the optimal method for determining overexpression in these tumors is not established. We sought to assess the ASCO/CAP and ToGA trial scoring methods for HER2 IHC with correlation to FISH, p53, and mismatch repair protein status and to determine the incidence of HER2-low in mucinous ovarian carcinoma. A total of 29 tumors from 23 patients were included. Immunohistochemistry for HER2, p53, MLH1, PMS2, MSH2, and MSH6 was performed. Scoring was performed according to the ASCO/CAP and ToGA trial criteria. HER2 FISH was performed and scored according to the ASCO/CAP criteria. The proportion of HER2-low, defined as 1+ or 2+ staining with negative FISH, was determined. Using ASCO/CAP, 26% demonstrated 3+ while 35% demonstrated 2+ staining. Using ToGA, 30% demonstrated 3+ while 57% demonstrated 2+ staining. By FISH, 26% were positive for HER2 amplification. Both systems captured all FISH-positive cases; the use of ASCO/CAP resulted in fewer equivocal and false-positive cases. Among HER2-negative cases, 88% were HER2-low. Aberrant p53 expression was detected in 55% of cases; mismatch repair deficiency was not identified in any cases. ASCO/CAP guidelines are accurate and resource-effective in determining HER2 overexpression in mucinous ovarian carcinoma. HER2-low is common in these tumors; further studies to determine the role of HER2-targeted therapy including antibody-drug conjugates are indicated.
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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 | 0.000 |
| 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) | 0.000 | 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".