Identification and validation of shared inflammatory transcriptomic signatures across multiple tissues in severe acute pancreatitis
TL;DR
A systems-level framework for understanding systemic inflammation in SAP is provided and supports future mechanistic and translational investigations and defines a conserved inflammatory transcriptomic program shared across multiple SAP-affected tissues and identifies PROK2 and VCAN as candidate biomarkers reflecting disease severity.
Abstract
Severe acute pancreatitis (SAP) is frequently accompanied by systemic inflammatory responses and multi-organ injury; however, the shared transcriptomic programs underlying its systemic progression remain incompletely defined. This study aimed to identify conserved inflammatory signatures across SAP-affected tissues using an integrative cross-tissue transcriptomic framework. Six independent transcriptomic datasets encompassing pancreatic and extra-pancreatic tissues were analyzed using differential expression analysis and robust rank aggregation. To reduce potential bias from immune-cell composition, neutrophil infiltration was computationally estimated and incorporated into adjusted differential expression analyses. A total of 16 hub genes, including S100A8, S100A9, VCAN, and PROK2, were consistently dysregulated across multiple tissues. Although adjustment for neutrophil abundance reduced the overall number of differentially expressed genes, key cross-tissue inflammatory signals remained largely preserved. Functional enrichment analysis indicated that these genes were mainly involved in neutrophil activation, inflammatory responses, and IL-17 signaling pathways. External validation further showed that 11 hub genes were significantly associated with disease severity. In clinical validation, serum levels of PROK2 and VCAN were significantly elevated in SAP patients and correlated with disease severity. In silico perturbation analysis further suggested that VCAN may be associated with leukocyte migration-related transcriptional networks. Collectively, these findings define a conserved inflammatory transcriptomic program shared across multiple SAP-affected tissues and identify PROK2 and VCAN as candidate biomarkers reflecting disease severity. This study provides a systems-level framework for understanding systemic inflammation in SAP and supports future mechanistic and translational investigations.