APOBEC3A-Induced DNA Damage Drives Polymerase θ Dependency and Synthetic Lethality in Cancer
Bibliographic record
Abstract
Abstract APOBEC3 cytidine deaminases drive cancer evolution. There is an unmet need to target cancer cells with APOBEC3 activity. Here, we identify error-prone theta-mediated end joining (TMEJ) as the main pathway for repairing APOBEC3-induced double-strand breaks (DSBs). Using fluorescent DSB repair reporters and a novel biochemical assay, we demonstrate that APOBEC3A competes with replication protein A (RPA) for single-stranded DNA overhangs, exposing microhomologous sequences to shift DSB repair towards error-prone TMEJ. Genomic analysis of clinical tumor samples confirmed the co-occurrence and proximity between APOBEC3-induced mutational footprints, microhomology-mediated deletions (MMDs), and TMEJ-associated chromosomal instability signatures. Crucially, inhibition of DNA polymerase theta (Polθ) synergizes with APOBEC3A-induced DSBs to induce synthetic lethality in vitro and in vivo . Collectively, our findings identify TMEJ as the preferred mechanism for repairing APOBEC3A-induced DSBs and establish Polθ inhibition as a novel promising strategy to eliminate cancer cells with APOBEC3A activity.
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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 | 0.001 |
| 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".