Telomere Dysfunction and DNA-PKcs Deficiency: Characterization and Consequence
Bibliographic record
Abstract
The mechanisms by which cells accurately distinguish between DNA double-strand break (DSB) ends and telomeric DNA ends remain poorly defined. Recent investigations have revealed intriguing interactions between DNA repair and telomeres. We were the first to report a requirement for the nonhomologous end-joining (NHEJ) protein DNA-dependent protein kinase (DNA-PK) in the effective end-capping of mammalian telomeres. Here, we report our continued characterization of uncapped (as opposed to shortened) dysfunctional telomeres in cells deficient for the catalytic subunit of DNA-PK (DNA-PKcs) and shed light on their consequence. We present evidence in support of our model that uncapped telomeres in this repair-deficient background are inappropriately detected and processed as DSBs and thus participate not only in spontaneous telomere-telomere fusion but, importantly, also in ionizing radiation-induced telomere-DSB fusion events. We show that phosphorylation of DNA-PKcs itself (Thr-2609 cluster) is a critical event for proper telomere end-processing and that ligase IV (NHEJ) is required for uncapped telomere fusion. We also find uncapped telomeres in cells from the BALB/c mouse, which harbors two single-nucleotide polymorphisms that result in reduced DNA-PKcs abundance and activity, most markedly in mammary tissue, and are both radiosensitive and susceptible to radiogenic mammary cancer. Our results suggest mechanistic links between uncapped/dysfunctional telomeres in DNA-PKcs-deficient backgrounds, radiation-induced instability, and breast cancer. These studies provide the first direct evidence of genetic susceptibility and environmental insult interactions leading to a unique and ongoing form of genomic instability capable of driving carcinogenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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".