Genotype-Directed Synthetic Cytotoxicity of ATR Inhibition with Radiotherapy
Bibliographic record
Abstract
PURPOSE: The importance of the DNA damage response in mediating effects of radiotherapy (RT) has galvanized efforts to target this pathway with radiosensitizers. Yet early clinical trials of this approach have failed to yield a benefit in unselected populations. We hypothesized that ataxia-telangiectasia mutated (Atm)-null tumors would demonstrate genotype-specific synergy between RT and an inhibitor of the DNA damage response protein ataxia-telangiectasia and Rad3-related (ATR) kinase. EXPERIMENTAL DESIGN: We investigated the synergistic potential of the ATR inhibitor (ATRi) RP-3500 and RT in two Atm-null and isogenic murine models, both in vitro and in vivo. Staining of γ-H2AX foci, characterization of the immune response via flow cytometry, and tumor rechallenge experiments were performed to elucidate the mechanism of interaction. To examine genotype specificity, we tested the interaction of ATRi and RT in a Brca1-null model. Finally, patients with advanced cancer with ATM alterations were enrolled in a phase I/II clinical trial to validate preclinical findings. RESULTS: Synergy between RP-3500 and RT was confirmed in Atm-null lines in vitro, characterized by an accumulation of DNA double-strand breaks. In vivo, Atm-null tumor models had higher rates of durable control with RT and ATRi than controls. In contrast, there was no synergy in tumors lacking Brca1. Analysis of the immunologic response indicated that efficacy is largely mediated by cell-intrinsic mechanisms. Lastly, early results from our clinical trial showed complete responses in patients. CONCLUSIONS: Genotype-directed radiosensitization with ATRi and RT can unleash significant therapeutic benefit and could represent a novel approach to develop more effective combinatorial synthetic cytotoxic RT-based treatments. See related commentary by Schrank and Colbert, p. 5505.
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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".