Oviduct-specific glycoprotein (OVGP1), a new serum biomarker for the detection of ovarian cancer
Bibliographic record
Abstract
4451 Ovarian carcinomas are the most lethal tumors of the female genital tract because most are detected late in the disease course. Our previous immunohistochemical study, using a polyclonal antibody, showed that oviduct-specific glycoprotein (OVGP1), normally a secreted and glycosylated protein of the oviduct, is aberrantly expressed and secreted in low grade ovarian epithelial neoplasias, suggesting that it may be detectable in the serum of women with such tumors. We generated a monoclonal antibody, clone OGP 7E10, to recombinant OVGP1, which recognizes the C-terminal region of the protein. It recognizes OVGP1 in conditioned medium at a molecular weight of 110-130 kDa and binds specifically to secretory epithelial cells of the mid- to late-proliferative phase oviduct. Immunohistochemical analysis of an ovarian tumor tissue array using OGP 7E10 demonstrated OVGP1 in 6/10 (60%) low grade serous carcinomas (LGSC), 168/185 (91%) high grade serous carcinomas (HGSC), 96/108 (89%) endometrioid carcinomas, 20/23 (87%) mucinous carcinomas and 102/116 (88%) clear cell carcinomas. Analysis with a Kaplan-Meier curve and log-rank statistics showed that positive OVGP1 staining in HGSCs was associated with a more favorable outcome (p
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".