A comparison of p53 and <scp>WT</scp>1 immunohistochemical expression patterns in tubo‐ovarian high‐grade serous carcinoma before and after neoadjuvant chemotherapy
Bibliographic record
Abstract
AIMS: The treatment of patients with tubo-ovarian high-grade serous carcinoma (HGSC) is increasingly based on diagnosis on small biopsy samples, and the first surgical sample is often taken post-chemotherapy. p53 and WT1 are important diagnostic markers for HGSC. The effect of neoadjuvant chemotherapy on p53 and WT1 expression has not been widely studied. We aimed to compare p53 and WT1 expression in paired pre-chemotherapy and post-chemotherapy samples of HGSC. METHODS AND RESULTS: Immunohistochemistry (IHC) was carried out for p53 and WT1 on paired omental HGSC samples pre-chemotherapy and post-chemotherapy. p53 IHC was recorded as normal (wild-type) or abnormal (mutation-type), and was further classified as overexpression, complete absence, or cytoplasmic. WT1 IHC was classified as positive or negative. A subset of cases were further assessed for the extent of nuclear immunoreactivity of WT1 by use of the H-score. Fifty-seven paired samples were stained with p53. Fifty-six of 57 (98%) cases showed mutation-type p53 staining. Pre-chemotherapy and post-chemotherapy IHC results were concordant in 55 of 57 (96%) cases. For WT1, pre-chemotherapy and post-chemotherapy IHC results were concordant in 56 of 58 (97%) cases. In 23 paired WT1 cases, the mean post-treatment H-score decreased from 227 [range 20-298, standard deviation (SD) 64] to 151 (range 0-288, SD 78) (P = 0.0008). CONCLUSIONS: Immunohistochemical expression of p53 (abnormal/mutation-type pattern) and WT1 in HGSC is almost universal and is largely concordant before and after chemotherapy. This finding underscores the reliability of these diagnostic markers in small samples and in surgical samples following neoadjuvant chemotherapy, with very few exceptions. A novel finding was the significant diminution in intensity of WT1 staining following chemotherapy.
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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) | 0.001 | 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".