Department of Physics, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0HE, UK.
Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.
Dis Model Mech. 2019 Jul 16;12(7):dmm039636. doi: 10.1242/dmm.039636.
The tumour microenvironment (TME) is a complex cellular ecosystem subjected to chemical and physical signals that play a role in shaping tumour heterogeneity, invasion and metastasis. Studying the roles of the TME in cancer progression would strongly benefit from non-invasive visualisation of the tumour as a whole organ , both preclinically in mouse models of the disease, as well as in patient tumours. Although imaging techniques exist that can probe different facets of the TME, they face several limitations, including limited spatial resolution, extended scan times and poor specificity from confounding signals. Photoacoustic imaging (PAI) is an emerging modality, currently in clinical trials, that has the potential to overcome these limitations. Here, we review the biological properties of the TME and potential of existing imaging methods that have been developed to analyse these properties non-invasively. We then introduce PAI and explore the preclinical and clinical evidence that support its use in probing multiple features of the TME simultaneously, including blood vessel architecture, blood oxygenation, acidity, extracellular matrix deposition, lipid concentration and immune cell infiltration. Finally, we highlight the future prospects and outstanding challenges in the application of PAI as a tool in cancer research and as part of a clinical oncologist's arsenal.
肿瘤微环境（TME）是一个复杂的细胞生态系统，受到化学和物理信号的影响，这些信号在塑造肿瘤异质性、侵袭和转移方面发挥着重要作用。研究 TME 在癌症进展中的作用将从对整个肿瘤的非侵入性可视化中受益良多，无论是在疾病的小鼠模型的临床前阶段，还是在患者的肿瘤中。尽管存在可以探测 TME 不同方面的成像技术，但它们面临着几个限制，包括有限的空间分辨率、延长的扫描时间和来自混杂信号的低特异性。光声成像（PAI）是一种新兴的模式，目前正在临床试验中，具有克服这些限制的潜力。在这里，我们回顾了 TME 的生物学特性和已经开发的潜在成像方法，这些方法可用于非侵入性地分析这些特性。然后，我们介绍 PAI 并探讨支持其用于同时探测 TME 多个特征的临床前和临床证据，包括血管结构、血氧、酸度、细胞外基质沉积、脂质浓度和免疫细胞浸润。最后，我们强调了 PAI 在癌症研究中作为一种工具以及作为临床肿瘤学家武器库的一部分的应用的未来前景和突出挑战。
