Molecular stratification of endometrioid ovarian carcinoma predicts clinical outcome
Bibliographic record
Abstract
Abstract Endometrioid ovarian carcinoma (EnOC) is an under-investigated type of ovarian carcinoma. Here, we report the largest genomic study of EnOCs to date, performing whole exome sequencing of 112 cases following rigorous pathological assessment. High frequencies of mutation were detected in CTNNB1 (43%), PIK3CA (43%), ARID1A (36%), PTEN (29%), TP53 (26%) and SOX8 (19%), a novel target of recurrent mutation in EnOC. POLE and mismatch repair protein-encoding genes were mutated at lower frequency (6%, 18%) with significant co-occurrence. A molecular taxonomy was constructed using a novel algorithm (PRISTINE), identifying clinically distinct EnOC subtypes: TP53 m cases demonstrated greater genomic complexity, were frequently FIGO stage III/IV at diagnosis (48%) and incompletely debulked (44%), and demonstrated inferior survival; conversely, CTNNB1 m cases demonstrated low complexity and excellent clinical outcome, were predominantly stage I/II at diagnosis (89%) and completely resected (87%). Tumour complexity provides further resolution within the TP53 wt/ CTNNB1 wt group. Moreover, we identify t he WNT, MAPK/RAS and PI3K pathways as good candidate targets for molecular therapeutics in EnOC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".