Smith Eric A, Hodges H Courtney
Department of Molecular and Cellular Biology and Center for Precision Environmental Health, Baylor College of Medicine, Houston, TX 77030, USA.
Department of Molecular and Cellular Biology and Center for Precision Environmental Health, Baylor College of Medicine, Houston, TX 77030, USA; Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA; Center for Cancer Epigenetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Bioengineering, Rice University, Houston, TX 77005, USA.
Trends Cancer. 2019 Jul;5(7):411-425. doi: 10.1016/j.trecan.2019.05.009. Epub 2019 Jun 18.
Many malignancies display heterogeneous features that support cancer progression. Emerging high-resolution methods provide a view of heterogeneity that recognizes the influence of diverse cell types and cell states of the tumor microenvironment. Here we outline a hierarchical organization of tumor heterogeneity from a genomic perspective, summarize the origins of spatially patterned metabolic features, and review recent developments in single-cell and spatially resolved techniques for genome-wide study of multicellular tissues. We also discuss how integrating these approaches can yield new insights into human cancer and emerging immune therapies. Applying these technologies for the analysis of primary tumors, patient-derived xenografts, and in vitro systems holds great promise for understanding the hierarchical structure and environmental influences that underlie tumor ecosystems.
许多恶性肿瘤表现出支持癌症进展的异质性特征。新兴的高分辨率方法提供了一种异质性视角,该视角认识到肿瘤微环境中不同细胞类型和细胞状态的影响。在这里,我们从基因组学角度概述肿瘤异质性的层次结构,总结空间模式化代谢特征的起源,并综述用于多细胞组织全基因组研究的单细胞和空间分辨技术的最新进展。我们还讨论了整合这些方法如何能够对人类癌症和新兴免疫疗法产生新的见解。将这些技术应用于原发性肿瘤、患者来源的异种移植和体外系统的分析,对于理解构成肿瘤生态系统基础的层次结构和环境影响具有巨大潜力。