CUT Domain Proteins in DNA Repair and Cancer
Bibliographic record
Abstract
Recent studies revealed that CUT domains function as accessory factors that accelerate DNA repair by stimulating the enzymatic activities of the base excision repair enzymes OGG1, APE1, and DNA pol β. Strikingly, the role of CUT domain proteins in DNA repair is exploited by cancer cells to facilitate their survival. Cancer cells in which the RAS pathway is activated produce an excess of reactive oxygen species (ROS) which, if not counterbalanced by increased production of antioxidants, causes sustained oxidative DNA damage and, ultimately, cell senescence. These cancer cells can adapt by increasing their capacity to repair oxidative DNA damage in part through elevated expression of CUT domain proteins such as CUX1, CUX2, or SATB1. In particular, CUX1 overexpression was shown to cooperate with RAS in the formation of mammary and lung tumors in mice. Conversely, knockdown of CUX1, CUX2, or SATB1 was found to be synthetic lethal in cancer cells exhibiting high ROS levels as a consequence of activating mutations in KRAS, HRAS, BRAF, or EGFR. Importantly, as a byproduct of their adaptation, cancer cells that overexpress CUT domain proteins exhibit increased resistance to genotoxic treatments such as ionizing radiation, temozolomide, and cisplatin.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".