Abstract B042: A screen to identify modifiers of BRCA1 protein level for cancer prevention and treatment
Bibliographic record
Abstract
Abstract The breast cancer susceptibility gene 1 (BRCA1) is a nuclear phosphoprotein involved in DNA double-strand break (DSB) repair and maintenance of genome stability. A single BRCA1 mutation leads to reduced levels of functional BRCA1 protein, such that DSB repair is compromised. It has been proposed that BRCA1 is a haploinsufficient tumor suppressor gene in some contexts, which when lost accelerates the mutation rate of other critical genes thus increasing neoplastic transformation. BRCA1 expression levels are modified through exogenous exposures, and modulating BRCA1 expression may alter tumour onset, progression, and treatment options. We hypothesize that compounds that increase BRCA1 expression and function may prevent the outgrowth of BRCA1-associated breast cancer. By contrast, compounds that reduce BRCA1 protein level could be used as combination therapries in conjunction with poly-ADP ribose polymerase (PARP) inhibitors. To achieve these goals, we generated BRCA1-reporter cell lines. Using CRISPR-assisted genome editing, we endogenously tagged the BRCA1 protein with HiBiT, an 11 amino acid luminescent tag. BRCA1-targeting was verified by sequencing and immunoblotting, and functional validation was performed with known modulators of BRCA1 expression. Our tests confirmed that HiBiT-tagging allows for sensitive measurement of BRCA1 protein levels, therefore permitting screenability. BRCA1-reporter cells were subsequently used to conduct a pilot screen (64 epigenetic-modifying drugs) and a high-content screen (6,000 compounds). We identified several compounds that modified BRCA1 protein expression (B-score >3*SD). The epigenetic drug library yielded five repressors and two activators, and the high-content screen identified 163 repressors and 12 activators. Validation studies have confirmed that the activator drug, aloxistatin can elevate BRCA1-HiBiT levels in a dose-dependent manner. Additionally, aloxistatin treatment increased BRCA1 expression and function in a panel of breast cells. We have also assessed 9 down-regulators of BRCA1 from the pilot and high-content screens. Each of these nine compounds reduced the expression of BRCA1 protein and synergized with the PARP inhibitor olaparib to inhibit cancer cell growth. Collectively, our ongoing studies suggest that BRCA1 activation may reduce cancer phenotypes and BRCA1 repression can sensitize breast cancer cells to PARP-inhibition and other chemotherapies. Overall, using our reporter cell lines we have identified a number of unique compounds that effectively modify BRCA1 expression and function that may have utility in the treatment and prevention of BRCA1-associated cancers. Citation Format: Erin Sellars, Margarita Savguira, Joanne Kotsopoulos, Leonardo Salmena. A screen to identify modifiers of BRCA1 protein level for cancer prevention and treatment [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr B042.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".