Cell cycle checkpoints cooperate to suppress DNA and RNA associated molecular pattern recognition and anti-tumor immune responses
Bibliographic record
Abstract
Summary The DNA dependent pattern recognition receptor, cGAS mediates communication between genotoxic stress and the immune system. Mitotic chromosome missegregation is an established stimulator of cGAS activity, however, it is unclear if progression through mitosis is required for cancer cell intrinsic activation of immune mediated anti-tumor responses. Moreover, it is unknown if disruption of cell cycle checkpoints can restore responses in cancer cells that are recalcitrant to DNA damage induced inflammation. Here we demonstrate that prolonged cell cycle arrest at the G2-mitosis boundary from either CDK1 inhibition or excessive DNA damage prevents inflammatory stimulated gene expression and immune mediated destruction of distal tumors. Remarkably, DNA damage induced inflammatory signaling is restored in a cGAS-and RIG-I-dependent manner upon concomitant disruption of p53 and the G2 checkpoint. These findings link aberrant cell progression and p53 loss to an expanded spectrum of damage associated molecular pattern recognition and have implications for the design of rational approaches to augment antitumor immune responses.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".