Ras–MEK Signaling Mediates a Critical Chk1-Dependent DNA Damage Response in Cancer Cells
Bibliographic record
Abstract
Abstract Cancer cell line profiling to identify previously unrecognized kinase dependencies revealed a novel nonmutational dependency on the DNA damage response checkpoint kinase Chk1. Although Chk1 is a promising therapeutic target in p53-deficient cancers, we found that Ras–MEK signaling engages Chk1 in a subset of osteosarcoma, ovarian, and breast cancer cells to enable their survival upon DNA damage, irrespective of p53 mutation status. Mechanistically, Ras–MEK signaling drives Chk1 expression and promotes cancer cell growth that produces genotoxic stress that requires Chk1 to mediate a response to the consequent DNA damage. Reciprocally, Chk1 engages a negative feedback loop to prevent hyperactivation of Ras–MEK signaling, thereby limiting DNA damage. Furthermore, exogenous DNA damage promotes Chk1 dependency, and pharmacologic Chk1 inhibition combined with genotoxic chemotherapy potentiates a DNA damage response and tumor cell killing. These findings reveal a mechanism-based diagnostic strategy to identify cancer patients that may benefit from Chk1-targeted therapy. Mol Cancer Ther; 16(4); 694–704. ©2017 AACR.
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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) | 0.003 | 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".