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<p>The tumor microenvironment (TME) is a dynamic and multifaceted system that regulates cancer progression, metastasis, immune evasion, and therapeutic response through tightly coupled biochemical and biophysical interactions. Despite extensive advances, a central challenge in cancer research remains: how faithfully experimental models recapitulate the complex regulatory networks of the TME. Recent developments in three-dimensional (3D) tumor models, including multicellular spheroids, patient-derived organoids, and organ-on-chip systems, have provided powerful platforms for mimicking key structural and functional features of native tumors. However, current studies and existing reviews predominantly focus on individual model systems or specific cancer types, lacking a unifying framework to evaluate how these models reconstruct TME regulatory circuits across different biological dimensions. In this review, we present a comprehensive and integrative analysis of 3D tumor models across diverse cancer contexts, with a particular focus on their ability to recapitulate biochemical signaling and mechanotransduction pathways. Importantly, we propose a conceptual framework to assess the fidelity of 3D tumor models in reconstructing TME regulation, spanning biochemical cues, extracellular matrix dynamics, and mechanical signaling. We further discuss emerging applications of these models in studying tumor progression, immune modulation, and therapeutic response, highlighting their potential in precision oncology and drug discovery. Finally, we critically evaluate current limitations, including incomplete vascularization, insufficient immune complexity, and challenges in standardization and scalability. We also outline future directions, emphasizing the integration of bioengineering innovations and artificial intelligence for quantitative model evaluation and predictive modeling. By bridging model design with mechanistic insights and functional assessment, this review provides a framework for advancing 3D tumor models toward more faithful representation of in vivo tumor ecosystems.</p>

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From structure to function: 3D tumor models for reconstructing tumor microenvironment regulatory networks and mechanical properties

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月29日

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  • Mingke Wu,
  • Dingjie Xu,
  • Xuelin Dou,
  • Yihan Zhou,
  • Jin Lu,
  • Qing Ge

摘要

The tumor microenvironment (TME) is a dynamic and multifaceted system that regulates cancer progression, metastasis, immune evasion, and therapeutic response through tightly coupled biochemical and biophysical interactions. Despite extensive advances, a central challenge in cancer research remains: how faithfully experimental models recapitulate the complex regulatory networks of the TME. Recent developments in three-dimensional (3D) tumor models, including multicellular spheroids, patient-derived organoids, and organ-on-chip systems, have provided powerful platforms for mimicking key structural and functional features of native tumors. However, current studies and existing reviews predominantly focus on individual model systems or specific cancer types, lacking a unifying framework to evaluate how these models reconstruct TME regulatory circuits across different biological dimensions. In this review, we present a comprehensive and integrative analysis of 3D tumor models across diverse cancer contexts, with a particular focus on their ability to recapitulate biochemical signaling and mechanotransduction pathways. Importantly, we propose a conceptual framework to assess the fidelity of 3D tumor models in reconstructing TME regulation, spanning biochemical cues, extracellular matrix dynamics, and mechanical signaling. We further discuss emerging applications of these models in studying tumor progression, immune modulation, and therapeutic response, highlighting their potential in precision oncology and drug discovery. Finally, we critically evaluate current limitations, including incomplete vascularization, insufficient immune complexity, and challenges in standardization and scalability. We also outline future directions, emphasizing the integration of bioengineering innovations and artificial intelligence for quantitative model evaluation and predictive modeling. By bridging model design with mechanistic insights and functional assessment, this review provides a framework for advancing 3D tumor models toward more faithful representation of in vivo tumor ecosystems.