Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States.
Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI 48109, United States.
Acta Biomater. 2021 Sep 15;132:401-420. doi: 10.1016/j.actbio.2021.04.041. Epub 2021 Apr 30.
Intractable human diseases such as cancers, are context dependent, unique to both the individual patient and to the specific tumor microenvironment. However, conventional cancer treatments are often nonspecific, targeting global similarities rather than unique drivers. This limits treatment efficacy across heterogeneous patient populations and even at different tumor locations within the same patient. Ultimately, this poor efficacy can lead to adverse clinical outcomes and the development of treatment-resistant relapse. To prevent this and improve outcomes, it is necessary to be selective when choosing a patient's optimal adjuvant treatment. In this review, we posit the use of personalized, tumor-specific models (TSM) as tools to achieve this remarkable feat. First, using ovarian cancer as a model disease, we outline the heterogeneity and complexity of both the cellular and extracellular components in the tumor microenvironment. Then we examine the advantages and disadvantages of contemporary cancer models and the rationale for personalized TSM. We discuss how to generate precision 3D models through careful and detailed analysis of patient biopsies. Finally, we provide clinically relevant applications of these versatile personalized cancer models to highlight their potential impact. These models are ideal for a myriad of fundamental cancer biology and translational studies. Importantly, these approaches can be extended to other carcinomas, facilitating the discovery of new therapeutics that more effectively target the unique aspects of each individual patient's TME. STATEMENT OF SIGNIFICANCE: In this article, we have presented the case for the application of biomaterials in developing personalized models of complex diseases such as cancers. TSM could bring about breakthroughs in the promise of precision medicine. The critical components of the diverse tumor microenvironments, that lead to treatment failures, include cellular- and extracellular matrix- heterogeneity, and biophysical signals to the cells. Therefore, we have described these dynamic components of the tumor microenvironments, and have highlighted how contemporary biomaterials can be utilized to create personalized in vitro models of cancers. We have also described the application of the TSM to predict the dynamic patterns of disease progression, and predict effective therapies that can produce durable responses, limit relapses, and treat any minimal residual disease.
难治性人类疾病，如癌症，是与个体患者和特定肿瘤微环境相关的、独特的。然而，传统的癌症治疗方法往往是非特异性的，针对的是全球相似之处，而不是独特的驱动因素。这限制了在异质患者群体中的治疗效果，甚至在同一患者的不同肿瘤部位也是如此。最终，这种疗效不佳会导致不良的临床结果和治疗抵抗的复发。为了防止这种情况发生并改善结果，在选择患者最佳辅助治疗时，有必要进行选择。在这篇综述中，我们提出使用个性化、肿瘤特异性模型（TSM）作为实现这一显著目标的工具。首先，我们以卵巢癌为例，概述了肿瘤微环境中细胞和细胞外成分的异质性和复杂性。然后，我们检查了当代癌症模型的优缺点和个性化 TSM 的基本原理。我们讨论了如何通过仔细和详细地分析患者活检来生成精确的 3D 模型。最后，我们提供了这些多功能个性化癌症模型的临床相关应用，以突出它们的潜在影响。这些模型非常适合进行癌症生物学和转化研究。重要的是，这些方法可以扩展到其他癌种，从而发现更有效地针对每个个体患者 TME 独特方面的新疗法。
