<scp>STING</scp> inhibition alleviates experimental peritoneal damage: potential therapeutic relevance for peritoneal dialysis
Bibliographic record
Abstract
Peritoneal dialysis (PD) is a widely used kidney replacement therapy for patients with end-stage kidney disease. Nevertheless, long-term exposure to PD fluid can damage the peritoneal membrane, leading to ultrafiltration failure and, ultimately, discontinuation of PD. Investigation of the molecular mechanisms underlying this damage is essential for identifying new therapeutic targets to mitigate peritoneal deterioration in PD patients. To this end, we employed RNA sequencing in a preclinical model of peritoneal injury, induced by prolonged chlorhexidine (CHX) exposure, which revealed cytosolic DNA-sensing signaling as a novel pathway. Next, we demonstrated that key players in this pathway, such as the stimulator of interferon genes (STING) and its downstream signaling effectors (interferon regulatory factor 3, interferon-stimulated genes, and nuclear factor-κB signaling), were upregulated in experimental peritoneal damage. Moreover, increased STING expression was observed in human peritoneal biopsies from patients with PD. Subsequent studies in STING-deficient mice showed reduced proinflammatory gene expression and immune cell infiltration, together with inhibited nuclear factor-κB pathway activation at both early (10 days) and late (30 days) stages of CHX-induced peritoneal injury. STING deficiency also reduced peritoneal membrane thickening, fibrosis, and mesothelial-to-mesenchymal transition (MMT)-related changes in advanced CHX-induced damage. Furthermore, pharmacological inhibition of STING with C-176 attenuated CHX-induced peritoneal inflammation. Macrophages were identified as one of the STING-expressing cell types in the injured peritoneum. Hence, in vitro STING blockade in activated macrophages inhibited MMT in cultured mesothelial cells, suggesting that STING activation in this population may drive peritoneal fibrosis. Additionally, STING deficiency reduced peritoneal inflammation in S. epidermidis-induced peritonitis and decreased adhesion scores in a postsurgical intra-abdominal adhesion model. These findings identify STING as a pivotal mediator of peritoneal injury and support its potential as a novel therapeutic target to prevent PD-associated ultrafiltration failure. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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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) | 0.002 | 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".