Loss of the DNA repair protein, polynucleotide kinase/phosphatase, activates the type 1 interferon response independent of ionizing radiation
Bibliographic record
Abstract
DNA damage has been implicated in the stimulation of the type 1 interferon (T1IFN) response. Here, we show that downregulation of the DNA repair protein, polynucleotide kinase/phosphatase (PNKP), in a variety of cell lines causes robust phosphorylation of STAT1, upregulation of interferon-stimulated genes and persistent accumulation of cytosolic DNA, all of which are indicators for the activation of the T1IFN response. Furthermore, this did not require damage induction by ionizing radiation. Instead, our data revealed that production of reactive oxygen species (ROS) synergises with PNKP loss to potentiate the T1IFN response, and that loss of PNKP significantly compromises mitochondrial DNA (mtDNA) integrity. Depletion of mtDNA or treatment of PNKP-depleted cells with ROS scavengers abrogated the T1IFN response, implicating mtDNA as a significant source of the cytosolic DNA required to potentiate the T1IFN response. The STING signalling pathway is responsible for the observed increase in the pro-inflammatory gene signature in PNKP-depleted cells. While the response was dependent on ZBP1, cGAS only contributed to the response in some cell lines. Our data have implications for cancer therapy, since PNKP inhibitors would have the potential to stimulate the immune response, and also to the neurological disorders associated with PNKP mutation.
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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) | 0.001 | 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 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".