The extracellular microenvironment plays a significant role in maintaining tissue homeostasis. Signals from the extracellular matrix (ECM) have been shown to regulate cell division, transcription, and apoptosis. We recently found that ECM also regulates DNA double-strand break repair in both human and mouse cell culture models. These results have potential implications for carcinogenesis and radiation therapy. Specifically, we found that ECM up- regulates homologous recombination in mammary epithelial cells in the right context (with correct cell-cell junctions) but downregulates it if the cells are single (aberrant context). Signaling through 21 integrin on the cell surface is necessary and sufficient for ECM to regulate repair, and kinetics of assembly of ionizing-radiation induced repair complexes on the double- strand breaks are altered by such signaling in cell culture. Given that context is so important for how ECM regulates DNA repair, here we propose to develop mouse models to examine this new pathway in the right context: the mouse mammary gland in vivo. This proposal aims to develop two sets of models to: 1. indirectly measure the effects of ECM on ionizing radiation- induced double-strand break repair in the mouse mammary gland, and 2. directly measure the effects of ECM on the homologous repair of an endonuclease-induced break in the mouse mammary gland, by developing the appropriate mouse models that will allow us to functionally downregulate or ablate 21 integrin and perform double-strand break repair assays in vivo. Developing mouse models is crucial for understanding this new pathway in the right context, as well as taking the next necessary step towards translating these findings to the clinic to affect radiation therapy.
Translating the findings on how the extracellular microenvironment regulates processes related to genome stability from cell culture models to mouse models is necessary for understanding a new pathway relevant to carcinogenesis and to ionizing-radiation based therapies used to treat cancers. The models developed here can be used to ask questions relevant to breast and other cancers and in determining tissue-specific markers that may predict responses to radiation therapy.
