Polymerase θ Coordinates Multiple Intrinsic Enzymatic Activities during DNA Repair
Bibliographic record
Abstract
The POLQ gene encodes DNA polymerase θ, a 2590 amino acid protein product harboring DNA-dependent ATPase, template-dependent DNA polymerase, dNTP-dependent endonuclease, and 5′–dRP lyase functions. Polymerase θ participates at an essential step of a DNA double-strand break repair pathway able to join 5′-resected substrates by locating and pairing microhomologies present in 3′-overhanging single-stranded tails, cleaving the extraneous 3′-DNA by dNTP-dependent end-processing, before extending the nascent 3′ end from the microhomology annealing site. Metazoans require polymerase θ for full resistance to DNA double-strand break inducing agents but can survive knockout of the POLQ gene. Cancer cells with compromised homologous recombination, or other DNA repair defects, over-utilize end-joining by polymerase θ and often over-express the POLQ gene. This dependency points to polymerase θ as an ideal drug target candidate and multiple drug-development programs are now preparing to enter clinical trials with small-molecule inhibitors. Specific inhibitors of polymerase θ would not only be predicted to treat BRCA-mutant cancers, but could thwart accumulated resistance to current standard-of-care cancer therapies and overcome PARP-inhibitor resistance in patients. This article will discuss synthetic lethal strategies targeting polymerase θ in DNA damage-response-deficient cancers and summarize data, describing molecular structures and enzymatic functions.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".