De Ninno Adele, Bertani Francesca Romana, Gerardino Annamaria, Schiavoni Giovanna, Musella Martina, Galassi Claudia, Mattei Fabrizio, Sistigu Antonella, Businaro Luca
CNR Institute for Photonics and Nanotechnology;
CNR Institute for Photonics and Nanotechnology.
J Vis Exp. 2021 Apr 30(170). doi: 10.3791/61895.
Complex disease models demand cutting-edge tools able to deliver physiologically and pathologically relevant, actionable insights, and unveil otherwise invisible processes. Advanced cell assays closely mimicking in vivo scenery are establishing themselves as novel ways to visualize and measure the bidirectional tumor-host interplay influencing the progression of cancer. Here we describe two versatile protocols to recreate highly controllable 2D and 3D co-cultures in microdevices, mimicking the complexity of the tumor microenvironment (TME), under natural and therapy-induced immunosurveillance. In section 1, an experimental setting is provided to monitor crosstalk between adherent tumor cells and floating immune populations, by bright field time-lapse microscopy. As an applicative scenario, we analyze the effects of anti-cancer treatments, such as the so-called immunogenic cancer cell death inducers on the recruitment and activation of immune cells. In section 2, 3D tumor-immune microenvironments are assembled in a competitive layout. Differential immune infiltration is monitored by fluorescence snapshots up to 72 h, to evaluate combination therapeutic strategies. In both settings, image processing steps are illustrated to extract a plethora of immune cell parameters (e.g., immune cell migration and interaction, response to therapeutic agents). These simple and powerful methods can be further tailored to simulate the complexity of the TME encompassing the heterogeneity and plasticity of cancer, stromal and immune cells subtypes, as well as their reciprocal interactions as drivers of cancer evolution. The compliance of these rapidly evolving technologies with live-cell high-content imaging can lead to the generation of large informative datasets, bringing forth new challenges. Indeed, the triangle ''co-cultures/microscopy/advanced data analysis" sets the path towards a precise problem parametrization that may assist tailor-made therapeutic protocols. We expect that future integration of cancer-immune on-a-chip with artificial intelligence for high-throughput processing will synergize a large step forward in leveraging the capabilities as predictive and preclinical tools for precision and personalized oncology.
复杂疾病模型需要前沿工具，这些工具能够提供与生理和病理相关的、可采取行动的见解，并揭示其他不可见的过程。先进的细胞分析方法能够紧密模拟体内环境，正逐渐成为可视化和测量影响癌症进展的双向肿瘤-宿主相互作用的新方法。在这里，我们描述了两种通用方案，用于在微器件中创建高度可控的二维和三维共培养体系，模拟肿瘤微环境（TME）的复杂性，包括自然和治疗诱导的免疫监视。在第1节中，提供了一种实验设置，通过明场延时显微镜监测贴壁肿瘤细胞与悬浮免疫细胞群体之间的相互作用。作为一个应用场景，我们分析了抗癌治疗的效果，例如所谓的免疫原性癌细胞死亡诱导剂对免疫细胞募集和激活的影响。在第2节中，以竞争布局组装三维肿瘤-免疫微环境。通过长达72小时的荧光快照监测差异免疫浸润，以评估联合治疗策略。在这两种设置中，都说明了图像处理步骤，以提取大量免疫细胞参数（例如，免疫细胞迁移和相互作用、对治疗剂的反应）。这些简单而强大的方法可以进一步定制，以模拟TME的复杂性，包括癌症、基质和免疫细胞亚型的异质性和可塑性，以及它们作为癌症进化驱动因素的相互作用。这些快速发展的技术与活细胞高内涵成像的兼容性可能会产生大量信息丰富的数据集，带来新的挑战。事实上，“共培养/显微镜/高级数据分析”三角为精确的问题参数化设定了路径，这可能有助于制定量身定制的治疗方案。我们预计，未来将癌症免疫芯片与人工智能进行高通量处理的整合，将在利用其作为精准和个性化肿瘤学的预测和临床前工具的能力方面向前迈出一大步。
