PDF(Pubmed)
Abstract：
Organ-on-chip (OOC) models can be useful tools for cancer drug discovery. Advances in OOC technology have led to the development of more complex assays, yet analysis of these systems does not always account for these advancements, resulting in technical challenges. A challenging task in the analysis of these two-channel microfluidic models is to define the boundary between the channels so objects moving within and between channels can be quantified. We propose a novel imaging-based application of a thin plate spline method - a generalized cubic spline that can be used to model coordinate transformations - to model a tissue boundary and define compartments for quantification of invaded objects, representing the early steps in cancer metastasis. To evaluate its performance, we applied our analytical approach to an adapted OOC developed by Emulate, Inc., utilizing a two-channel system with endothelial cells in the bottom channel and colorectal cancer (CRC) patient-derived organoids (PDOs) in the top channel. Initial application and visualization of this method revealed boundary variations due to microscope stage tilt and ridge and valley-like contours in the endothelial tissue surface. The method was functionalized into a reproducible analytical process and web tool - the Chip Invasion and Contour Analysis (ChICA) - to model the endothelial surface and quantify invading tumor cells across multiple chips. To illustrate applicability of the analytical method, we applied the tool to CRC organoid-chips seeded with two different endothelial cell types and measured distinct variations in endothelial surfaces and tumor cell invasion dynamics. Since ChICA utilizes only positional data output from imaging software, the method is applicable to and agnostic of the imaging tool and image analysis system used. The novel thin plate spline method developed in ChICA can account for variation introduced in OOC manufacturing or during the experimental workflow, can quickly and accurately measure tumor cell invasion, and can be used to explore biological mechanisms in drug discovery.
摘要：
芯片上器官（OOC）模型可能是癌症药物发现的有用工具。OOC技术的进步导致了更复杂的检测方法的发展，然而，对这些系统的分析并不总是解释这些进步，导致技术挑战。分析这些双通道微流体模型的一项具有挑战性的任务是定义通道之间的边界，以便可以量化在通道内和通道之间移动的对象。我们提出了一种新颖的基于成像的薄板样条方法的应用-可用于对坐标转换进行建模的广义三次样条-对组织边界进行建模并定义用于量化侵入物体的隔室，代表癌症转移的早期步骤。为了评估它的性能，我们将我们的分析方法应用于Emulate开发的适应性OOC，Inc.,利用双通道系统，底部通道中具有内皮细胞，顶部通道中具有结直肠癌（CRC）患者来源的类器官（PDO）。该方法的初始应用和可视化显示了由于显微镜载物台倾斜以及内皮组织表面的脊状和谷状轮廓而引起的边界变化。该方法被功能化为可再现的分析过程和网络工具-芯片侵入和轮廓分析（ChICA）-以模拟内皮表面并量化多个芯片上的侵入肿瘤细胞。为了说明分析方法的适用性，我们将该工具应用于接种了两种不同类型内皮细胞的CRC类器官芯片,并测量了内皮表面和肿瘤细胞侵袭动力学的不同变化.由于ChICA仅利用成像软件输出的位置数据，该方法适用于所使用的成像工具和图像分析系统并且是不可知的。ChICA中开发的新颖薄板样条方法可以解释OOC制造或实验工作流程中引入的变化，可以快速准确地测量肿瘤细胞的侵袭，并可用于探索药物发现的生物学机制。
