Acquired <i>RAD51C</i> Promoter Methylation Loss Causes PARP Inhibitor Resistance in High-Grade Serous Ovarian Carcinoma
Bibliographic record
Abstract
ABSTRACT While loss of BRCA1 promoter methylation has been shown to cause PARP inhibitor (PARPi) resistance in high-grade serous ovarian carcinoma (HGSC), the impacts of RAD51C methylation (me RAD51C ) remain unresolved. In this study, three PARPi-responsive HGSC patient-derived xenografts (PDX) with RAD51C gene silencing and homologous recombination deficiency were found to have either homogeneous or heterogeneous patterns of me RAD51C . PDX could lose me RAD51C following PARPi treatment (rucaparib/niraparib), where a single unmethylated RAD51C copy was sufficient to drive PARPi-resistance. Genomic profiling revealed this resistance was acquired independently in two distinct PDX lineages. Furthermore, we describe a patient sample where 1/3 RAD51C gene copies lost methylation following neoadjuvant chemotherapy. We show me RAD51C is a positive predictive biomarker for PARPi response and should be screened for routinely in patients. However, methylation loss in a single gene copy is sufficient to cause PARPi resistance and should be carefully assessed in previously treated patients considering PARPi therapy.
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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 | 0.000 | 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) | 0.001 | 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".