STK11 (LKB1) immunohistochemistry is a sensitive and specific marker for <i>STK11</i> adnexal tumours
Bibliographic record
Abstract
AIMS: STK11 adnexal tumour is a rare, recently described malignant neoplasm that is associated with Peutz-Jeghers syndrome. [Correction added on 3 October 2024, after first online publication: 'ST11' in preceding sentence has been corrected to 'STK11' in this version.] It predominantly originates from the para-adnexal soft tissues and often shows secondary involvement of the fallopian tube and ovary. STK11 adnexal tumours have a broad differential diagnosis due to their variable morphology and non-specific immunoprofile, and diagnostic confirmation currently requires sequencing to identify an STK11 mutation. We investigate the diagnostic utility of STK11 (LKB1) immunohistochemistry (IHC) in a cohort of STK11 adnexal tumours and morphological mimics. METHODS AND RESULTS: IHC for STK11 was performed on 122 tumours, including 17 STK11 adnexal tumours and 105 morphological mimics (10 female adnexal tumours of Wolffian origin, 22 adult granulosa cell tumours, 10 juvenile granulosa cell tumours, four Sertoli-Leydig cell tumours, two Leydig cell tumours, one Sertoli cell tumour, one steroid cell tumour, four extra-ovarian sex cord-stromal tumours, 16 ovarian endometrioid carcinomas, eight tubo-ovarian high-grade serous carcinomas, five ovarian mesonephric-like adenocarcinomas, 14 ovarian carcinosarcomas, five peritoneal malignant mesotheliomas, two pelvic plexiform leiomyomata and one ovarian solid pseudopapillary tumour). All STK11 adnexal tumours showed complete loss of cytoplasmic staining for STK11. All other tumour types showed retained cytoplasmic staining, except for one endometrioid carcinoma with mucinous differentiation which showed complete loss of STK11 expression and a high-grade serous carcinoma with subclonal loss. CONCLUSIONS: STK11 is a highly sensitive and specific immunohistochemical marker for distinguishing STK11 adnexal tumour from its histological mimics, and can obviate the need for confirmatory molecular studies in the appropriate morphological context.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".