Cytosolic DNA in radiotherapy: relevance, mechanisms, and detection
Bibliographic record
Abstract
Ionizing radiation (IR) is a cornerstone of cancer therapy, exerting cytotoxic effects primarily through the induction of DNA damage. Beyond direct tumor cell death, IR has been increasingly recognized for its capacity to modulate antitumor immune responses, in part through the accumulation of dispersed cytosolic double-stranded DNA (dsDNA) and micronuclei (MN) formation. These abnormally localized DNA structures are capable of engaging innate immune sensors such as the cGAS-STING pathway, linking IR and antitumor immune responses. This review highlights methodologies for the detection, quantification, and isolation of cytosolic DNA species, with a specific focus on dispersed cytosolic dsDNA and MN in the setting of IR. Together, these tools enhance our understanding of the role of MN and dispersed cytosolic dsDNA in IR-induced cellular responses and beyond. As the presence of MN and dispersed dsDNA in the cytosol act as interconnected but separate mediators of IR-induced immunogenicity, understanding their biology provides a foundation for optimizing combination therapies aimed at enhancing antitumor immunity. Modulating MN formation, MN rupture, and release of dispersed cytosolic dsDNA represents a promising avenue to enhance the efficacy of radiation-based cancer treatments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".