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Engineered 3D ex vivo models to recapitulate the complex stromal and immune interactions within the tumor microenvironment

肿瘤微环境 离体 间质细胞 免疫系统 背景(考古学) 癌症 生物 计算生物学 癌症研究 体内 免疫学 遗传学 生物技术 古生物学
作者
Kalpana Ravi,Twinkle Jina Minette Manoharan,Kuei-Chun Wang,Barbara A. Pockaj,Mehdi Nikkhah
出处
期刊:Biomaterials [Elsevier]
卷期号:305: 122428-122428 被引量:20
标识
DOI:10.1016/j.biomaterials.2023.122428
摘要

Cancer thrives in a complex environment where interactions between cellular and acellular components, surrounding the tumor, play a crucial role in disease development and progression. Despite significant progress in cancer research, the mechanism driving tumor growth and therapeutic outcomes remains elusive. Two-dimensional (2D) cell culture assays and in vivo animal models are commonly used in cancer research and therapeutic testing. However, these models suffer from numerous shortcomings including lack of key features of the tumor microenvironment (TME) & cellular composition, cost, and ethical clearance. To that end, there is an increased interest in incorporating and elucidating the influence of TME. Advancements in 3D-engineered ex vivo models, leveraging biomaterials and microengineering technologies, have provided an unprecedented ability to reconstruct native-like bioengineered cancer models to study the heterotypic interactions of TME with a spatiotemporal organization. These bioengineered cancer models have shown excellent capabilities to bridge the gap between oversimplified 2D systems and animal models, which do not accurately represent the human context. In this review article, we primarily provide an overview of the immune and stromal cellular components of the TME and then discuss the latest state-of-the-art 3D-engineered ex vivo platforms aiming to recapitulate the complex TME features. The engineered TME model, discussed herein, are categorized into three sections according to the cellular interactions within TME: (i) Tumor-Stromal interactions, (ii) Tumor-Immune interactions, and (iii) Complex TME interactions. Finally, we will conclude the article with a perspective on how these models can be instrumental for cancer translational studies and therapeutic testing.
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