Abstract NTOC-093: SYNTHETIC LETHAL APPROACHES TO TARGET ARID1A DEFICIENT OVARIAN CANCERS
Bibliographic record
Abstract
Abstract Epithelial ovarian cancer (EOC) remains the most lethal gynaecological malignancy in the Western world. Ovarian clear cell carcinoma (OCCC), a distinct histological subtype, has a notably poor prognosis in the advanced setting compared to patients with high-grade serous ovarian cancer (HGSOC). Understanding why these patients have a poor outcome may be due to the underlying genetic drivers and their response to treatment. Dysregulation of the SWI/SNF complex is one of the most commonly occurring defects in solid cancers. Mutations in ARID1A (AT-rich interactive domain-containing protein 1A), a gene that encodes for BAF250A, forming part of the SWI/SNF chromatin remodeling complex, rarely occur in HGSOC but are common in ovarian clear cell carcinomas. The vast majority of these are loss of function frameshift or nonsense mutations, resulting in loss of protein function. In addition, loss of ARID1A expression in tumour specimens has been associated with a shorter progression free survival and chemoresistance in ovarian clear cell carcinoma (OCCC). Despite the understanding that ARID1A defects are associated with tumourigenesis, targeted therapy approaches that exploit this deficiency have not as yet been developed. Our aims were to identify ways of targeting ARID1A deficient tumours by performing a large-scale functional genomics screen to identify actionable synthetic lethal effects. Using a high-throughput combination drug screen with a plate library of 80 compounds and a phase 1 compound, in isogenic ARID1A null and wild type HCT116 cells, we have identified candidate therapeutic approaches to targeting ARID1A mutant tumours that could be assessed in proof of concept clinical trials. We have undertaken subsequent high throughput drug screens in isogenic ARID1A null and wild type MCF10A cells that in we have identified a series of novel synthetic lethal effects. Assessment of this combinatorial approach in in vivo models of ARID1A mutant cancers is now underway. In conclusion, we have identified clinically actionable combinatorial approaches that may provide additional therapeutic benefit for ARID1A deficient patients. Citation Format: Saira Khalique, Chris T. Williamson, Helen Pemberton, Patty T. Wai, Malini Menon, Rachel Brough, Andri Leonidou, Barrie Peck, Susana Banerjee, Rachael C. Natrajan and Christopher J. Lord,. SYNTHETIC LETHAL APPROACHES TO TARGET ARID1A DEFICIENT OVARIAN CANCERS [abstract]. In: Proceedings of the 11th Biennial Ovarian Cancer Research Symposium; Sep 12-13, 2016; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(11 Suppl):Abstract nr NTOC-093.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".