ARID1B Immunohistochemistry Is an Important Test for the Diagnosis of Dedifferentiated and Undifferentiated Gynecologic Malignancies
Bibliographic record
Abstract
Dedifferentiated and undifferentiated endometrial and ovarian carcinomas (DDC/UDC) are aggressive malignancies defined by morphologic and molecular undifferentiation, and associated with core SWI/SNF deficiency. Their main differential diagnoses include high-grade endometrial and ovarian carcinomas that often show overlapping morphologic and molecular profiles. Loss of cell lineage markers expression by immunohistochemistry (IHC) is commonly used to assist diagnosis, but it has poor specificity, while core SWI/SNF deficiency is much more specific. Approximately half of SWI/SNF-deficient DDC/UDC are associated with loss of ARID1B expression, yet, unlike the other core SWI/SNF proteins (SMARCA4 and SMARCB1), this test is rarely available, even in tertiary centers. Mutational testing for ARID1B is increasingly common among targeted DNA sequencing panels, but it is difficult to interpret in the absence of IHC results. Overall, the importance of including ARID1B IHC as part of the routine panel for undifferentiated gynecologic malignancies should be emphasized, especially as SWI/SNF inactivation is becoming a necessary biomarker for diagnostics, clinical management, and clinical trial enrollment.
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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 | 0.002 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".