Wilms Tumor Gene Product
Bibliographic record
Abstract
Carcinomas of ovarian surface epithelial origin can arise from, and often present at, extraovarian sites. There are few available markers for the positive identification of carcinomas of ovarian surface epithelial origin, which might aid in distinguishing them from metastatic carcinomas, such as of breast, colon, or lung origin. Recently, the Wilms tumor gene product (WT-1) has been shown to be expressed in ovarian surface and mesothelial epithelium. We tested the hypothesis that WT-1 would be a sensitive and specific marker of ovarian surface epithelium carcinomas. An archived series of 116 ovarian carcinomas (57 serous [43 ovarian, 14 extraovarian], 31 mucinous, 15 clear cell, 13 endometrioid), 118 breast carcinomas, 46 colonic carcinomas, and 45 nonsmall cell lung cancers were selected. A polyclonal antibody to the WT-1 gene product was applied to deparaffinized, formalin-fixed tissue sections after epitope retrieval. Fifty-two of 57 (93%) serous carcinomas of ovarian surface epithelial origin were WT-1-positive, in a nuclear pattern, with virtually all the tumor cell population positive in the majority of cases. None of the mucinous, clear cell, or endometrioid ovarian cancers were positive, and only 8 of 118 breast, 0 of 46 colonic, and 0 of 45 lung nonsmall cell carcinomas were WT-1-positive. These findings demonstrate that WT-1 is a highly sensitive and specific marker of serous carcinomas of ovarian surface epithelial origin (both ovarian and extraovarian). These results also contradict recent reports demonstrating WT-1 expression in both breast and lung carcinomas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.022 | 0.013 |
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".