Development of a scoring function for comparing simulated and experimental tumor spheroids.
Development of a scoring function for comparing simulated and experimental tumor spheroids.
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开发用于比较模拟和实验性肿瘤球体的评分函数。
DOI：
10.1371/journal.pcbi.1010471
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发表时间：
2023-03
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
--
作者：
癌症生物学领域的进展仍在继续，但关于癌症侵袭的机制仍有许多有待揭示。特别是，复杂的生物物理机制使肿瘤能够重塑周围的细胞外基质（ECM），允许细胞单独或集体侵入。在胶原蛋白中培养的肿瘤球状体代表了简化的、可再现的3D模型系统，其足够复杂以概括在侵袭期间发生的细胞的演变组织和与ECM的相互作用。最近的实验方法使得能够对侵入的肿瘤球体的内部结构进行高分辨率成像和定量。同时，计算建模使得基于第一原理的复杂多细胞聚集体的模拟成为可能。真实的和模拟的球体之间的比较代表了一种充分利用这两种数据源的方法，但仍然是一个挑战。我们假设，比较任何两个球体首先需要从原始数据中提取基本特征，其次需要定义关键指标来匹配这些特征。在这里，我们提出了一种新的方法来比较三维球体的空间特征。为此，我们从球体点云数据中定义和提取特征，我们使用Cells in Silico（CiS）进行模拟，这是我们以前开发的用于大规模组织建模的高性能框架。然后，我们定义度量来比较各个球体之间的特征，并将所有度量联合收割机组合成总体偏差分数。最后，我们使用我们的功能来比较实验数据入侵球体在增加胶原蛋白密度。我们建议，我们的方法是定义改进的指标来比较大型3D数据集的基础。展望未来，这种方法将能够对任何来源的球状体进行详细分析，其中一个应用是基于其体外对应物的计算机模拟球状体。这将使基础和应用研究人员能够在癌症研究中关闭建模和实验之间的循环。肿瘤内的细胞使用各种方法逃逸，从而侵入身体的健康部位。这些方法是通过检查肿瘤球体，数百至数千个单个细胞的球形聚集体进行实验研究的。这样的球体也可以模拟，并比较模拟和实验是可取的。在这里，我们提出了一种分析策略，用于比较任何来源的肿瘤球体。使用这种策略，我们的目标是增加从数据中获得的信息，并提高实验学家和理论家之间的合作潜力。
Progress continues in the field of cancer biology, yet much remains to be unveiled regarding the mechanisms of cancer invasion. In particular, complex biophysical mechanisms enable a tumor to remodel the surrounding extracellular matrix (ECM), allowing cells to invade alone or collectively. Tumor spheroids cultured in collagen represent a simplified, reproducible 3D model system, which is sufficiently complex to recapitulate the evolving organization of cells and interaction with the ECM that occur during invasion. Recent experimental approaches enable high resolution imaging and quantification of the internal structure of invading tumor spheroids. Concurrently, computational modeling enables simulations of complex multicellular aggregates based on first principles. The comparison between real and simulated spheroids represents a way to fully exploit both data sources, but remains a challenge. We hypothesize that comparing any two spheroids requires first the extraction of basic features from the raw data, and second the definition of key metrics to match such features. Here, we present a novel method to compare spatial features of spheroids in 3D. To do so, we define and extract features from spheroid point cloud data, which we simulated using Cells in Silico (CiS), a high-performance framework for large-scale tissue modeling previously developed by us. We then define metrics to compare features between individual spheroids, and combine all metrics into an overall deviation score. Finally, we use our features to compare experimental data on invading spheroids in increasing collagen densities. We propose that our approach represents the basis for defining improved metrics to compare large 3D data sets. Moving forward, this approach will enable the detailed analysis of spheroids of any origin, one application of which is informing in silico spheroids based on their in vitro counterparts. This will enable both basic and applied researchers to close the loop between modeling and experiments in cancer research. Cells within a tumor use various methods to escape and thereby invade into healthy parts of the body. These methods are studied experimentally by examining tumor spheroids, spherical aggregates of hundreds to thousands of individual cells. Such spheroids can also be simulated, and the comparison of both simulations and experiments is desirable. Here, we present an analysis strategy for the comparison of tumor spheroids of any origin. Using this strategy, we aim to increase the information gained from the data and improve the collaborative potential between experimentalists and theorists.
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影响因子：
16.8
作者：
Fu X;Zhao Y;Lopez JI;Rowan A;Au L;Fendler A;Hazell S;Xu H;Horswell S;Shepherd STC;Spencer CE;Spain L;Byrne F;Stamp G;O'Brien T;Nicol D;Augustine M;Chandra A;Rudman S;Toncheva A;Furness AJS;Pickering L;Kumar S;Koh DM;Messiou C;Dafydd DA;Orton MR;Doran SJ;Larkin J;Swanton C;Sahai E;Litchfield K;Turajlic S;TRACERx Renal Consortium;Bates PA
通讯作者：
Bates PA
影响因子：
3
作者：
Berghoff M;Rosenbauer J;Hoffmann F;Schug A
通讯作者：
Schug A
肿瘤球体形成和生长的计算机模拟。
影响因子：
3.4
作者：
Amereh M;Edwards R;Akbari M;Nadler B
通讯作者：
Nadler B
影响因子：
2
作者：
Kursawe, Jochen;Baker, Ruth E.;Fletcher, Alexander G.
通讯作者：
Fletcher, Alexander G.
影响因子：
--
作者：
Ivascu, Andrea;Kubbies, Manfred
通讯作者：
Kubbies, Manfred