Abstract IA009: Single strand DNA GAP accumulation as a functional biomarker for DNA Repair Inhibitors
Bibliographic record
Abstract
Abstract Deficiency of homologous recombination (HR)-mediated DNA repair occurs through genetic or epigenetic inactivation of the BRCA1 and BRCA2 (BRCA1/2) genes. HR-deficiency also provides unique opportunities for targeted therapy, through the mechanism of synthetic lethality, as exemplified by the hypersensitivity of BRCA1/2-mutated tumors to PARP inhibitors (PARPi). To date, several PARP inhibitors have been approved for clinical use. The promising clinical response of patients with germline BRCA1/2-mutations prompted the use of PARPi for patients with somatic BRCA1/2 mutations as well. In addition, these results extended the use of PARPi for various types of ovarian, breast, pancreatic, and prostate tumors with HR defects. PARPi resistance is emerging as the major obstacle to clinical effectiveness in patients with HR-deficient tumors. PARPi resistance results from several independent mechanisms, leading to the restoration of Homologous Recombination and/or Replication Fork stabilization. The absence of alternative options for patients with tumors with innate or acquired resistance underlines the urgency to develop additional therapeutics. More recent studies have identified new synthetic lethal opportunities for BRCA1/2 deficient tumors. Knockout of the genes for POLQ (DNA polymerase theta) or for USP1 (Ubiquitin Specific Protease 1) results in killing of these tumors, and inhibitors of these enzymes are emerging as promising agents for HR-deficient tumors. POLQ and USP1 expression is particularly high in subtypes of breast and ovarian tumors with defects in HR. As a result, POLQi or USP1i in HR-deficient tumors induces cell death. POLQi or USP1i can synergize with PARPi in killing HR-deficient tumors or PARPi-resistant tumors. BRCA1/2 deficient tumors have an increase in single strand DNA gaps (ssGAPs) near replication forks. Treatment with PARPi results in an increase in the size and number for these ssGAPs, ultimately leading to DSBs and cell death. Interestingly, PARPi resistance results, at least in part, from the ability of resistant cells to close the ssGAPs through enhanced POLQ and USP1 activity, thereby providing a rationale for the combination of PARP1, POLQi, and USP1 in HR-deficient cancers. USP1 inhibition was synergistic with PARP and POLQ inhibition in BRCA1-mutant cells, with enhanced ssDNA gap accumulation. Moreover, this synergy was observed in a set of patient-derived ovarian cancer organoids (PDOs), thus confirming the sensitivity of BRCA1-deficient cells to inhibition by these agents. The accumulation of ssDNA gaps after treatment with a USP1i, PARP, or POLQi correlated with the sensitivity to these drugs in all models tested. Ovarian cancer PDOs provide a powerful tool for detecting drug synergy and for rapid in vitro sensitivity testing. The detection of ssDNA gap accumulation may be a useful predictive biomarker for response to DNA Repair inhibitors as monotherapy or in combination in ongoing clinical trials. Citation Format: Alan D. D'Andrea. Single strand DNA GAP accumulation as a functional biomarker for DNA Repair Inhibitors [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 IA009.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".