Candidate biomarkers of PARP inhibitor sensitivity in ovarian cancer beyond the BRCA genes
Bibliographic record
Abstract
Olaparib (Lynparza™) is a PARP inhibitor approved for advanced BRCA -mutated ( BRCA m) ovarian cancer. PARP inhibitors may benefit patients whose tumours are dysfunctional in DNA repair mechanisms unrelated to BRCA1/2 . We report exploratory analyses, including the long-term outcome of candidate biomarkers of sensitivity to olaparib in BRCA wild-type ( BRCA wt) tumours. Tumour samples from an olaparib maintenance monotherapy trial (Study 19, D0810C00019; NCT00753545) were analysed. Analyses included classification of mutations in genes involved in homologous recombination repair (HRR), BRCA1 promoter methylation status, measurement of BRCA1 protein and Myriad HRD score. Patients with BRCA m tumours gained most benefit from olaparib; a similar treatment benefit was also observed in 21/95 patients whose tumours were BRCA wt but had loss-of-function HRR mutations compared to patients with no detectable HRR mutations (58/95). A higher median Myriad MyChoice ® HRD score was observed in BRCA m and BRCA wt tumours with BRCA1 methylation. Patients without BRCA m tumours derived benefit from olaparib treatment vs placebo although to a lesser extent than BRCA m patients. Ovarian cancer patients with tumours harbouring loss-of-function mutations in HRR genes other than BRCA1 / 2 may constitute a small, molecularly identifiable and clinically relevant population who derive treatment benefit from olaparib similar to patients with BRCA m.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".