A cGAS-dependent response links DNA damage and senescence in alveolar epithelial cells: a potential drug target in IPF
Bibliographic record
Abstract
Alveolar epithelial cell (AEC) senescence is implicated in the pathogenesis of idiopathic pulmonary fibrosis (IPF). Mitochondrial dysfunction including release of mitochondrial DNA (mtDNA) is a feature of senescence, which led us to investigate the role of the DNA-sensing guanine monophosphate-adenine monophosphate (GMP-AMP) synthase (cGAS) in IPF, with a focus on AEC senescence. cGAS expression in fibrotic tissue from lungs of patients with IPF was detected within cells immunoreactive for epithelial cell adhesion molecule (EpCAM) and p21, epithelial and senescence markers, respectively. Submerged primary cultures of AECs isolated from lung tissue of patients with IPF (IPF-AECs, n = 5) exhibited higher baseline senescence than AECs from control donors (Ctrl-AECs, n = 5–7), as assessed by increased nuclear histone 2AXγ phosphorylation, p21 mRNA, and expression of senescence-associated secretory phenotype (SASP) cytokines. Pharmacological cGAS inhibition using RU.521 diminished IPF-AEC senescence in culture and attenuated induction of Ctrl-AEC senescence following etoposide-induced DNA damage. Short interfering RNA (siRNA) knockdown of cGAS also attenuated etoposide-induced senescence of the AEC line, A549. Higher levels of mtDNA were detected in the cytosol and culture supernatants of primary IPF- and etoposide-treated Ctrl-AECs when compared with Ctrl-AECs at baseline. Furthermore, ectopic mtDNA augmented cGAS-dependent senescence of Ctrl-AECs, whereas DNAse I treatment diminished IPF-AEC senescence. This study provides evidence that a self-DNA-driven, cGAS-dependent response augments AEC senescence, identifying cGAS as a potential therapeutic target for IPF.
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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".