Abstract 4369: Genome-wide copy number dependency analysis identifies partial copy loss of SF3B1 as a novel cancer vulnerability
Bibliographic record
Abstract
Abstract Genomic instability is a hallmark of cancer resulting in widespread somatic copy number alterations. We integrated a genome-scale shRNA viability screen and copy number profiles from 179 cancer cell lines to perform an unbiased analysis of copy-number associated gene-dependency interactions. We found most copy-number associated gene dependencies result from losses of genetic material rather than gains. Strikingly, the most enriched class of these dependencies was CYCLOPS (Copy-number alterations Yielding Cancer Liabilities Owing to Partial losS) genes. Hemizygous loss of CYCLOPS genes sensitizes cancer cells to their further suppression. One of the “top hits” from the analysis was the pre-mRNA splicing factor SF3B1, which is also frequently mutated in cancer. We then sought to evaluate SF3B1 as a CYCLOPS gene. Cancer cells with hemizygous SF3B1 copy-loss were uniquely sensitive to partial SF3B1 suppression by RNAi compared to cells with normal SF3B1 gene dosage. Mechanistically, cancer cells harboring partial SF3B1 copy-loss lack a reservoir of excess SF3b complex, a precursor complex of the U2 snRNP, which protects cells with normal SF3B1 copy number from cell death upon SF3B1 suppression. Our data highlight the prevalence of CYCLOPS dependencies in cancer and establish the spliceosome as a frequent CYCLOPS target. Further, these data indicate targeting wild-type SF3B1 as a novel cancer dependency in cells with hemizygous SF3B1 copy-loss. Citation Format: Brenton R. Paolella, William J. Gibson, Laura M. Urbanski, John A. Alberta, Travis I. Zack, Pratiti Bandopadhayay, Caitlin A. Nichols, Pankaj K. Agarwalla, Meredith S. Brown, Rebecca Lamothe, Yong Yu, Peter S. Choi, Esther A. Obeng, Dirk Heckl, Benjamin L. Ebert, Guo Wei, Belinda Wang, William C. Hahn, Francisca Vazquez, Barbara A. Weir, Charles D. Stiles, Robin Reed, Rameen Beroukhim. Genome-wide copy number dependency analysis identifies partial copy loss of SF3B1 as a novel cancer vulnerability. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4369.
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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 | 0.000 |
| 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".