Abstract B002: POLB knockout is synthetic lethal with PARP inhibition leading to complete and durable responses in BRCA-mutant tumor xenografts
Bibliographic record
Abstract
Abstract Despite the clinical benefit of PARP1/2 inhibitors (PARPi), which are FDA-approved for the treatment of certain BRCA-mutant cancers, many patients achieve incomplete disease control and develop progressive disease. Motivated by this clinical need, we utilized our CRISPR target discovery screening platform to identify novel targets that synergize with PARP inhibitor treatment. By conducting parallel screens in both BRCA-mutant and wildtype cells, we identified DNA polymerase beta (POLB) as a novel target that - when combined with PARPi - selectively kills BRCA-mutant lines while sparing normal cells. POLB knockout and cDNA rescue experiments using both BRCA1 and BRCA2-mutant isogenic cell lines further demonstrated that the catalytic activity of POLB is required for synthetic lethality with PARPi. Most strikingly, POLB knockout combined with sub-therapeutic doses of PARPi, led to profound tumor regression and prevented in vivo tumor regrowth, even after cessation of drug treatment. Mechanistically, POLB knockout is associated with increased single and double strand DNA breaks, accumulation of poly-ADP-ribose polymers, cell cycle arrest and apoptosis. Together, these results suggest that POLB inhibitors in combination with PARPi have the potential to drive deep and durable responses providing a novel therapeutic option for cancer patients with BRCA1/2-mutations. Citation Format: Madhavi Bandi. POLB knockout is synthetic lethal with PARP inhibition leading to complete and durable responses in BRCA-mutant tumor xenografts [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr B002.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".