Conventional DNA-Damaging Cancer Therapies and Emerging cGAS-STING Activation: A Review and Perspectives Regarding Immunotherapeutic Potential
Bibliographic record
Abstract
Many traditional cancer treatments such as radiation and chemotherapy are known to induce cellular DNA damage as part of their cytotoxic activity. The cGAS-STING signaling axis, a key member of the DNA damage response that acts as a sensor of foreign or aberrant cytosolic DNA, is helping to rationalize the DNA-damaging activity of these treatments and their emerging immunostimulatory capacity. Moreover, cGAS-STING, which is attracting considerable attention for its ability to promote antitumor immune responses, may fundamentally be able to address many of the barriers limiting the success of cancer immunotherapy strategies, including the immunosuppressive tumor microenvironment. Herein, we review the traditional cancer therapies that have been linked with cGAS-STING activation, highlighting their targets with respect to their role and function in the DNA damage response. As part of the review, an emerging "chemoimmunotherapy" concept whereby DNA-damaging agents are used for the indirect activation of STING is discussed as an alternative to the direct molecular agonism strategies that are in development, but have yet to achieve clinical approval. The potential of this approach to address some of the inherent and emerging limitations of cGAS-STING signaling in cancer immunotherapy is also discussed. Ultimately, it is becoming clear that in order to successfully employ the immunotherapeutic potential of the cGAS-STING axis, a balance between its contrasting antitumor and protumor/inflammatory activities will need to be achieved.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 teacher head, 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".