Engineering complexity in human tissue models of cancer

人体组织癌症模型中的工程复杂性

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Abstract

Major progress in the understanding and treatment of cancer have tremendously improved our knowledge of this complex disease and improved the length and quality of patients' lives. Still, major challenges remain, in particular with respect to cancer metastasis which still escapes effective treatment and remains responsible for 90% of cancer related deaths. In recent years, the advances in cancer cell biology, oncology and tissue engineering converged into the engineered human tissue models of cancer that are increasingly recapitulating many aspects of cancer progression and response to drugs, in a patient-specific context. The complexity and biological fidelity of these models, as well as the specific questions they aim to investigate, vary in a very broad range. When selecting and designing these experimental models, the fundamental question is "how simple is complex enough" to accomplish a specific goal of cancer research. Here we review the state of the art in developing and using the human tissue models in cancer research and developmental drug screening. We describe the main classes of models providing different levels of biological fidelity and complexity, discuss their advantages and limitations, and propose a framework for designing an appropriate model for a given study. We close by outlining some of the current needs, opportunities and challenges in this rapidly evolving field.

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