A high-throughput approach to identify BRCA1-downregulating compounds to enhance PARP inhibitor sensitivity
Bibliographic record
Abstract
PARP inhibitors (PARPi) are efficacious in BRCA1 -null tumors; however, their utility is limited in tumors with functional BRCA1. We hypothesized that pharmacologically reducing BRCA1 protein levels could enhance PARPi effectiveness in BRCA1 wild-type tumors. To identify BRCA1 downregulating agents, we generated reporter cell lines using CRISPR-mediated editing to tag endogenous BRCA1 protein with HiBiT. These reporter lines enable the sensitive measurement of BRCA1 protein levels by luminescence. Validated reporter cells were used in a pilot screen of epigenetic-modifying probes and a larger screen of more than 6,000 compounds. We identified 7 compounds that could downregulate BRCA1-HiBiT expression and synergize with olaparib. Three compounds, N-acetyl-N-acetoxy chlorobenzenesulfonamide (NANAC), A-443654, and CHIR-124, were validated to reduce BRCA1 protein levels and sensitize breast cancer cells to the toxic effects of olaparib. These results suggest that BRCA1-HiBiT reporter cells hold promise in developing agents to improve the clinical utility of PARPi.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".