Tumor and germline testing with next generation sequencing in epithelial ovarian cancer: a prospective paired comparison using an 18‐gene panel
Bibliographic record
Abstract
Genetic testing in epithelial ovarian cancer (EOC) in Ontario includes germline next-generation sequencing (NGS) for 19 genes. Additionally, tumor tissue undergoes reflex NGS testing for BRCA1/2 to assess eligibility for PARPi. Although parallel testing confers advantages, this model duplicates healthcare resources. Here, we prospectively assessed the feasibility of tumor-first multigene testing by comparing tumor tissue with germline testing of peripheral blood. An 18-gene NGS panel was used to test tumor and germline DNA (n = 106 patients). In 26 patients, 27 tumor Tier I or II variants were identified, with 16/27 (59%) being germline pathogenic variants (PV) (13 BRCA1/2; 3 other genes) and 11/27 (41%) somatic variants (9 BRCA1/2; 2 other). In 51/106 patients, there were no tumor variants (excluding TP53), of which one patient had a germline BRCA1 copy number variant deletion in exon 12. Tumor-first testing detected variant-positive and variant-negative germline cases in 105/106 patients (99.1%). Among 50 BRCA-negative patients, 14/50 (28%) were homologous recombination deficiency (HRD)-positive. Therefore, we demonstrate that multigene NGS tumor-testing is effective in identifying germline variants in EOC with a < 1% false-negative rate.
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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".