SummaryFibrosis in response to tissue damage or persistent inflammation is a pathological hallmark of many chronic degenerative diseases. By using a model of acute peritoneal inflammation, we have examined how repeated inflammatory activation promotes fibrotic tissue injury. In this context, fibrosis was strictly dependent on interleukin-6 (IL-6). Repeat inflammation induced IL-6-mediated T helper 1 (Th1) cell effector commitment and the emergence of STAT1 (signal transducer and activator of transcription-1) activity within the peritoneal membrane. Fibrosis was not observed in mice lacking interferon-γ (IFN-γ), STAT1, or RAG-1. Here, IFN-γ and STAT1 signaling disrupted the turnover of extracellular matrix by metalloproteases. Whereas IL-6-deficient mice resisted fibrosis, transfer of polarized Th1 cells or inhibition of MMP activity reversed this outcome. Thus, IL-6 causes compromised tissue repair by shifting acute inflammation into a more chronic profibrotic state through induction of Th1 cell responses as a consequence of recurrent inflammation.

Gastric cancer (GC) is associated with chronic inflammation; however, the molecular mechanisms promoting tumorigenesis remain ill defined. Using a GC mouse model driven by hyperactivation of the signal transducer and activator of transcription (STAT)3 oncogene, we show that STAT3 directly upregulates the epithelial expression of the inflammatory mediator Toll-like receptor (TLR)2 in gastric tumors. Genetic and therapeutic targeting of TLR2 inhibited gastric tumorigenesis, but not inflammation, characterized by reduced proliferation and increased apoptosis of the gastric epithelium. Increased STAT3 pathway activation and TLR2 expression were also associated with poor GC patient survival. Collectively, our data reveal an unexpected role for TLR2 in the oncogenic function of STAT3 that may represent a therapeutic target in GC.

Objective: To use information about prevalence, cost, and variation in resource utilization to prioritize comparative effectiveness research topics in hospital pediatrics.Design: Retrospective analysis of administrative and billing data for hospital encounters.