Excess Polθ functions in response to replicative stress in homologous recombination-proficient cancer cells
Bibliographic record
Abstract
DNA polymerase theta (Polθ) is a specialized A-family DNA polymerase that functions in processes such as translesion synthesis (TLS), DNA double-strand break repair and DNA replication timing. Overexpression of POLQ, the gene encoding Polθ, is a prognostic marker for an adverse outcome in a wide range of human cancers. While increased Polθ dosage was recently suggested to promote survival of homologous recombination (HR)-deficient cancer cells, it remains unclear whether POLQ overexpression could be also beneficial to HR-proficient cancer cells. By performing a short interfering (si)RNA screen in which genes encoding druggable proteins were knocked down in Polθ-overexpressing cells as a means to uncover genetic vulnerabilities associated with POLQ overexpression, we could not identify genes that were essential for viability in Polθ-overexpressing cells in normal growth conditions. We also showed that, upon external DNA replication stress, Polθ expression promotes cell survival and limits genetic instability. Finally, we report that POLQ expression correlates with the expression of a set of HR genes in breast, lung and colorectal cancers. Collectively, our data suggest that Polθ upregulation, besides its importance for survival of HR-deficient cancer cells, may be crucial also for HR-proficient cells to better tolerate DNA replication stress, as part of a global gene deregulation response, including HR genes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".