CHD1 is a synthetic lethal vulnerability in MYC-driven breast cancer
Bibliographic record
Abstract
ABSTRACT The MYC transcription factor is a key regulator of growth during development and a potent cancer driver when its expression is dysregulated. Strategies to inhibit MYC oncogenic activity would mark a significant advance, but decades of efforts to target MYC directly have not been fruitful. Understanding how MYC drives transformation and tumor growth may provide new therapeutic avenues in a variety of cancers. By intersecting two independent genome-wide screens, we identified loss of the chromatin remodeler Chromodomain-Helicase DNA-binding 1 (CHD1) as a potential synthetic lethal target in MYC-driven breast cancer. Knockdown of CHD1 in a xenograft model of MYC-driven breast cancer suppresses tumor growth in vivo. In tissue culture models, we found that knockdown of CHD1 suppresses cell proliferation and induces cell death, specifically when MYC is overexpressed. Mechanistically, we found that CHD1 is required to maintain an open chromatin landscape and a transcriptional program associated with cancer progression in MYC overexpressing breast cells. Follow-up experiments indicate that this synthetic lethality may arise from nucleolar stress and p53 activation. These findings provide new insights on the chromatin-level regulation of MYC-driven breast cancer and uncover CHD1 as a novel synthetic vulnerability and potential therapeutic target.
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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".