<i>FBXW7</i> -loss Sensitizes Cells to ATR Inhibition Through Induced Mitotic Catastrophe
Bibliographic record
Abstract
FBXW7 is a commonly mutated tumor suppressor gene that functions to regulate numerous oncogenes involved in cell-cycle regulation. Genome-wide CRISPR fitness screens identified a signature of DNA repair and DNA damage response genes as required for the growth of FBXW7-knockout cells. Guided by these findings, we show that FBXW7-mutant cells have high levels of replication stress, which results in a genotype-specific vulnerability to inhibition of the ATR signaling pathway, as these mutant cells become heavily reliant on a robust S-G2 checkpoint. ATR inhibition induces an accelerated S-phase, leading to mitotic catastrophe and cell death caused by the high replication stress present in FBXW7-/- cells. In addition, we provide evidence in cell and organoid studies, and mining of publicly available high-throughput drug screening efforts, that this genotype-specific vulnerability extends to multiple types of cancer, providing a rational means of identifying responsive patients for targeted therapy. SIGNIFICANCE: We have elucidated the synthetic lethal interactions between FBXW7 mutation and DNA damage response genes, and highlighted the potential of ATR inhibitors as targeted therapies for cancers harboring FBXW7 alterations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".