Abstract PR17: The transcriptional repressor Slug promotes the DNA damage response
Bibliographic record
Abstract
Abstract The transcriptional repressor Slug/SNAI2 orchestrates epigenetic programs indispensable for tissue self-renewal and tumorigenesis. Although Slug-deficient animals are highly sensitive to lethal irradiation, the direct biological relationship between Slug and the DNA damage response remains largely unexplored. Here we report that Slug interacts with DNA repair proteins, including FANCI, BCCIP and PARP1, in a mass spectrometry screen for Slug binding partners. In response to double-strand breaks (DSBs) induced by irradiation, Slug-deficient cells exhibited a marked delay in the resolution of γH2ax foci. Furthermore, we showed that Slug inhibition significantly impaired DSBs repair that is mediated by homologous recombination. Accordingly, Slug-deficient mouse tissue accumulates DNA damage markers and showed altered nuclear morphology. Mechanistically, Slug interacts with and is stabilized by ATM upon DNA damage. Finally, we demonstrated that Slug depletion sensitizes aggressive triple-negative breast cancer cells to irradiation and chemotherapy. These findings suggest that Slug may be an important regulator of the DNA damage response and an attractive therapeutic target for aggressive cancer types. This abstract is also being presented as Poster B16. Citation Format: Wenhui Zhou, Jian Ouyang, Kathryn Huber, Charlotte Kuperwasser. The transcriptional repressor Slug promotes the DNA damage response [abstract]. In: Proceedings of the AACR Special Conference on DNA Repair: Tumor Development and Therapeutic Response; 2016 Nov 2-5; Montreal, QC, Canada. Philadelphia (PA): AACR; Mol Cancer Res 2017;15(4_Suppl):Abstract nr PR17.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".