The predictive link between matrix and metastasis

• Published in: Current opinion in chemical engineering 2016-02, Vol.11, p.85-93
• Main Authors: Barney, LE, Jansen, LE, Polio, SR, Galarza, S, Lynch, ME, Peyton, SR
• Format: Article
• Language: English
• ISSN: 2211-3398; 2211-3398
• DOI: 10.1016/j.coche.2016.01.001

⿢In vitro systems are needed to predict if, when, and where a tumor will metastasize.⿢The ECM is a major driver of metastasis to specific tissue destinations.⿢Mechanical forces play a major role in driving invasion and metastatic outgrowth.⿢Predictive tools need to be moved toward clinical use, for example biomarkers. Cancer spread (metastasis) is responsible for 90% of cancer-related fatalities. Informing patient treatment to prevent metastasis, or kill all cancer cells in a patient's body before it becomes metastatic is extremely powerful. However, aggressive treatment for all non-metastatic patients is detrimental, both for quality of life concerns, and the risk of kidney or liver-related toxicity. Knowing when and where a patient has metastatic risk could revolutionize patient treatment and care. In this review, we attempt to summarize the key work of engineers and quantitative biologists in developing strategies and model systems to predict metastasis, with a particular focus on cell interactions with the extracellular matrix (ECM), as a tool to predict metastatic risk and tropism.