Abstract 1413: Chromosome arm aneuploidies as genetic vulnerabilities of triple-negative breast cancer
Bibliographic record
Abstract
Abstract Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. It has no approved targeted therapies due to the lack of the expression of key biomarkers, namely Estrogen and Progesterone receptors, and HER2 amplification. As a result, TNBC has the worst prognosis compared to other breast cancer subtypes. We previously showed that chromosome 4p (chr4p) loss is recurrent, correlates with poor prognosis, is an early event in tumor evolution, and confers a proliferative advantage. Here, we propose to leverage chr4p loss as a genetic vulnerability of TNBC by identifying its genetic interactions (GIs) with genes whose inactivation leads to synthetic lethality i.e. loss of viability of chr4p copy loss cells, but not of the chr4p copy neutral cells, or suppression i.e., positive GIs. We first classified breast cancer cell lines with TNBC enriched molecular subtype called basal-like, as chr4p copy loss (9) and chr4p copy neutral (7), using copy number data from CCLE. Associated with chr4p copy loss, the differential expression analysis carried out using CCLE data revealed transcriptomic changes that distinctly cluster the chr4p copy loss and chr4p copy neutral cell lines. We then used the publicly available CRISPR-based genome-wide gene inactivation data from the DepMap project and quantified chr4p loss-associated GIs using multiple scoring methods such as drugZ and MAGeCK. In total, we identified ~200 negative and ~70 positive statistically significant GIs involving genes annotated to biological processes such as translation, metabolism, and others. We have prioritized a subset of them for subsequent experimental validation using CRISPR-Cas9-based gene editing in TNBC cancer cell line models. Alongside, using the publicly available drug sensitivity data obtained from the PRISM project, we identified compounds that impair cell growth in a chr4p loss-specific manner, the strongest of which targeted redox balance. Collectively, the set of GIs, the compound sensitivities, and the computational methods we have generated are unique resources for developing precision oncology therapeutic strategies for TNBC, as well as for other cancers harboring chr4p loss. Citation Format: Rohan Dandage, Michael Schwartz, Lynn Karam, Alain Pacis, Traver Hart, Guillaume Bourque, Morag Park, Elena Kuzmin. Chromosome arm aneuploidies as genetic vulnerabilities of triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1413.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".