Asbestos fibers persist in the lungs and cause chronic inflammation, pulmonary and pleural fibrosis, lung cancer, and malignant mesothelioma after latent periods of 20-40 years. Recent experimental evidence based on animal models using genetically engineered mice have provided new insight about the mechanistic links between chronic inflammation, fibrosis, and cancer. Recruitment and activation of inflammatory cells in response to biopersistent fibers is accompanied by release of reactive oxygen species leading to oxidant stress, DNA damage, and mutations. Inflammatory cells can release cytokines and growth factors that stimulate stromal remodeling and angiogenesis. It is hypothesized that reciprocal activation of tumor and stromal cells results in local release of matrix metalloproteinases that facilitate growth and invasion of diffuse malignant mesothelioma. In vitro, ex vivo, and in vivo assays using well characterized, transplantable murine mesothelial cell lines will be used to test this hypothesis.
The specific aims of the proposed research are: 1) To determine whether induction of matrix metalloproteinases in murine peritoneal macrophages is correlated with exposure to biopersistent, carcinogenic fibers; 2) To assess the contribution of macrophages to growth and invasion of neoplastic mesothelial cells in vivo; 3) To determine whether asbestos-activated macrophages stimulate invasion of preneoplastic and neoplastic mesothelial cells; 4) To determine whether overexpression of MMP9 leads to autonomous invasion of neoplastic mesothelial cells; and 5) To assess the contribution of stromal macrophages to growth and invasion of human neoplastic mesothelial cells. Newly developed technologies including laser capture microdissection and quantitative analysis of gene expression provide powerful tools for this experimental approach. Pharmacologic modulation of persistent inflammation triggered by biopersistent, carcinogenic fibers may provide a new strategy to prevent progression of malignant mesothelioma in exposed populations.
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