Molecular alterations in indolent, aggressive and recurrent ovarian low‐grade serous carcinoma
Bibliographic record
Abstract
AIMS: The clinical courses of patients with low-grade serous carcinoma (LGSC) can be substantially different. The purpose of this study was to explore whether molecular or pathological features could identify patients who follow a more aggressive course. METHODS AND RESULTS: Twenty-six primary LGSCs (11 with an aggressive clinical course, and 15 with an indolent clinical course) and five paired recurrences were assessed for non-synonymous somatic mutations in 18 MAPK pathway genes and in 42 other classic cancer 'hotspot' genes by use of a custom-designed AmpliSeq panel based on the AmpliSeq Cancer hotspot panel v2. Copy number alterations for 94 target genes were assessed with the nCounter v2 Cancer CN assay. Immunohistochemistry for 12 proteins was performed. We detected 16 mutations in 13 of 26 cases (50%), affecting five genes that signal through the MAPK pathway, and one ESR1 mutation implicated in resistance to endocrine therapy in breast cancer. Recurrent samples were concordant with the primary tumour with respect to the mutational status, but all five cases showed additional alterations at the copy number or protein expression level. The absence of progesterone receptor (PR) expression and the presence of myometrial lymphovascular invasion were associated with an unfavourable outcome (log-rank P = 0.016 and P < 0.0001, respectively), but none of the other molecular features assessed showed an association. CONCLUSION: Despite limited case numbers, it appears that current molecular testing is inferior to a pathological parameter or protein expression in predicting the outcome of LGSCs. Prediction of outcome based on the primary tumour may be confounded by additional changes acquired over time.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".