Radiation and Chemo-Sensitizing Effects of DNA-PK Inhibitors Are Proportional in Tumors and Normal Tissues
Bibliographic record
Abstract
Inhibitors of DNA-dependent protein kinase (PRKDC; DNA-PK) sensitize cancers to radiotherapy and DNA-damaging chemotherapies, with candidates in clinical trials. However, the degree to which DNA-PK inhibitors also sensitize normal tissues remains poorly characterized. In this study, we compare tumor growth control and normal tissue sensitization following DNA-PK inhibitors in combination with radiation and etoposide. FaDu tumor xenografts implanted in mice were treated with 10 to 15 Gy irradiation ± 3 to 100 mg/kg AZD7648. A dose-dependent increase in time to tumor volume doubling following AZD7648 was proportional to an increase in toxicity scores of the overlying skin. Similar effects were seen in the intestinal jejunum, tongue, and FaDu tumor xenografts of mice assessed for proliferation rates at 3.5 days after treatment with etoposide or 5 Gy whole body irradiation ± DNA-PK inhibitors AZD7648 or peposertib (M3814). Additional organs were examined for sensitivity to DNA-PK inhibitor activity in ATM-deficient mice, where DNA-PK activity is indicated by surrogate marker γH2AX. Inhibition was observed in the heart, brain, pancreas, thymus, tongue, and salivary glands of ATM-deficient mice treated with the DNA-PK inhibitors relative to radiation alone. Similar reductions are also seen in ATM-deficient FaDu tumor xenografts where both pDNA-PK and γH2AX staining could be performed. DNA-PK inhibitor-mediated sensitization to radiation and DNA-damaging chemotherapy are not only limited to tumor tissues, but also extends to normal tissues sustaining DNA damage. These data are useful for interpretation of the sensitizing effects of DNA damage repair inhibitors, where a therapeutic index showing greater cell-killing effects on cancer cells is crucial for optimal clinical translation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".