Epidemiological studies indicate that chemotherapy can increase the chance of metastasis in a subset patients, but the underlying mechanism remains unclear because of a lack of relevant experimental models. The goal of this proposal is to elucidate the impact of chemotherapy on metastatic relapse with a tissue-engineered metastasis model that can capture metastatic niche evolution with a high level of molecular and cellular detail. Inspired by the recent discovery of the pre-metastatic niche (PMN) in major metastatic organs, we have developed a bone marrow stromal cell–seeded microfabricated porous hydrogel scaffold that creates a richly vascularized proinflammatory microenvironment when it is subdermally implanted in a mouse. This implantable PMN model has been shown to attract and support the engraftment and growth of circulating tumor cells and can be serially implanted in syngeneic naive mice for long-term studies. The semitransparent materials of the implant are compatible with quantitative imaging analysis via multiple imaging modalities including multiplex immunohistostaining, CLARITY-based optical sectioning of entire scaffolds, and intravital imaging via a skinfold window chamber. Our central hypothesis is that tissue inflammation and remodeling induced by chemotherapy activates dormant disseminated tumor cells and causes them to migrate and form in situ clusters as a function of cell number. Forming clusters could allow the cells to overcome microenvironmental regulation and regain an aggressive phenotype. We propose three specific aims: In Aim 1, we will generate subcutaneous and hepatic PMN models in a MMTV-PyMT female mouse and demonstrate the long-term evolution of metastatic niche by serially transplanting early metastatic niche established in primary mice to secondary syngeneic FVB mice. For this purpose, we will generate MMTV-Luc2-PyMT mice that allow non-invasive long-term bioluminescent monitoring of metastatic relapse. In Aim 2, we will use the techniques verified in Aim 1 to observe the effect of chemotherapy with doxorubicin on the metastatic process in serially implanted bone marrow and liver PMN models. In Aim 3, we will apply the established algorithm to measure potency to determine if adjuvant therapy with anti-inflammatory (anakinra) or anti-macrophage (clodronate) drugs reduces doxorubicin-induced metastatic relapse and will look at the effect of adjuvant timing. The proposed research is significant because it has the potential to facilitate the development of better therapeutic regimens that can eliminate active residual tumor cells without activating dormant disseminated tumor cells, and this would significantly improve long-term metastasis prevention.