Prevalence of Loss of Expression of DNA Mismatch Repair Proteins in Primary Epithelial Ovarian Tumors
Bibliographic record
Abstract
Although different histologic subtypes of epithelial ovarian tumors have long been recognized, their molecular abnormalities have not been fully defined. We examined the prevalence of DNA mismatch repair (MMR) protein loss in these tumors. Tissue microarrays (TMA) of suspected ovarian carcinomas were stained for hMLH1, hMSH2, hMSH6, and hPMS2 and scored separately by 2 groups of investigators. Loss of staining (negative) or discrepant staining results on TMA were verified on whole-section slides. Intact (positive) staining results were also verified for an additional 25 randomly selected cases. Clinical data for cases demonstrating MMR protein loss were collected. A second set of TMA composed purely of mucinous tumors was also stained for antibodies to MMR proteins and scored by 1 group of investigators. TMA was an effective method for screening a large number of ovarian tumors for MMR protein expression, with a sensitivity of 100% for all 4 MMR proteins, and a specificity of 22.2%-53.8% for different MMR proteins. Of the primary epithelial tumors of the ovary, loss of expression of MMR proteins was significantly more common in the endometriosis-associated carcinomas (7/69; 10.1%) than in high-grade serous carcinomas (2/182; 1.1%): P=0.0021. The former group also showed more frequent loss of MMR proteins compared with mucinous intestinal-type carcinomas (0/32; P=0.0940). Cases within the group of endometriosis-associated carcinomas were endometrioid (2/29 cases), clear cell (1/27 cases), undifferentiated (1/8 cases), and mixed carcinomas with an endometrioid, clear cell, and/or undifferentiated component (3/5 cases). No loss of MMR protein expression was identified in epithelial tumors of other histologic subtypes. Our study demonstrated the loss of MMR protein expression in 10.1% of endometriosis-associated ovarian carcinomas. These results raise the possibility of selective screening for Lynch syndrome in patients with these types of ovarian carcinoma.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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 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".