A current perspective on the pathological assessment of <i><scp>FOXL</scp>2</i> in adult‐type granulosa cell tumours of the ovary
Bibliographic record
Abstract
AIMS: The diagnosis of adult-type granulosa cell tumours of the ovary (aGCT) is based on histomorphology aided by immunohistochemical staining for sex cord markers. Recently a single, recurrent somatic point mutation (402C→G) in FOXL2 was described in aGCT. We have investigated the impact of FOXL2 mutation testing in a large cohort of aGCT diagnosed previously by conventional histology and immunohistochemistry. METHODS AND RESULTS: Formalin-fixed, paraffin-embedded tissue cores from a cohort of 52 aGCT diagnosed previously by expert gynaecopathologists were analysed immunohistologically. FOXL2 mutation status was determined by Sanger sequencing and high-sensitivity TaqMan allelic discrimination assay. Histomorphology was reassessed by two expert gynaecopathologists. FOXL2 mutation analyses could be performed successfully in 46 cases, 40 of which were positive for the c.402C>G mutation, confirming a diagnosis of aGCT. In the six cases negative for the c.402C>G mutation, one case was confirmed on review as FOXL2 wild-type aGCT, whereas in the remaining five cases diagnoses other than aGCT were made. CONCLUSION: In cases where a diagnosis of aGCT is a consideration and unequivocal diagnosis is not possible based on morphology and routine immunostains, FOXL2 mutation testing can help to confirm the diagnosis. It is particularly relevant for accurate subclassification within the group of sex cord-stromal tumours.
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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 | 0.015 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| 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".