Modeling metastasis - leveraging novel tools to streamline discovery in advanced cancer.

Abstract

Metastasis remains a leading cause of morbidity and mortality in patients diagnosed with cancer. A variety of in vitro and in vivo approaches have been employed to study the individual steps of the metastatic cascade. However, these methodologies are sometimes limited in their ability to recapitulate the biological complexity and heterogeneity of human tumor biology. As a result, significant knowledge gaps still exist regarding the development, growth and evolution of treatment resistance in metastatic tumors. In this Perspective, we discuss the benefits and drawbacks of current, widely used techniques to model metastatic disease. We also highlight novel approaches utilized in recent studies to confront the limitations posed by classic modeling techniques. Ultimately, we provide suggestions for ensuring scientific rigor and reproducibility in metastasis studies, and we propose key areas of focus for developing next-generation models of metastasis.