Analysis of Circulating Cell-Free DNA Identifies Multiclonal Heterogeneity of <i>BRCA2</i> Reversion Mutations Associated with Resistance to PARP Inhibitors
Bibliographic record
Abstract
Abstract Approximately 20% of metastatic prostate cancers harbor mutations in genes required for DNA repair by homologous recombination repair (HRR) such as BRCA2. HRR defects confer synthetic lethality to PARP inhibitors (PARPi) such as olaparib and talazoparib. In ovarian or breast cancers, olaparib resistance has been associated with HRR restoration, including by BRCA2 mutation reversion. Whether similar mechanisms operate in prostate cancer, and could be detected in liquid biopsies, is unclear. Here, we identify BRCA2 reversion mutations associated with olaparib and talazoparib resistance in patients with prostate cancer. Analysis of circulating cell-free DNA (cfDNA) reveals reversion mutation heterogeneity not discernable from a single solid-tumor biopsy and potentially allows monitoring for the emergence of PARPi resistance. Significance: The mechanisms of clinical resistance to PARPi in DNA repair–deficient prostate cancer have not been described. Here, we show BRCA2 reversion mutations in patients with prostate cancer with metastatic disease who developed resistance to talazoparib and olaparib. Furthermore, we show that PARPi resistance is highly multiclonal and that cfDNA allows monitoring for PARPi resistance. Cancer Discov; 7(9); 999–1005. ©2017 AACR. See related commentary by Domchek, p. 937. See related article by Kondrashova et al., p. 984. See related article by Goodall et al., p. 1006. This article is highlighted in the In This Issue feature, p. 920
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".