通过癌症活检组织的光谱空间分析来校准肿瘤生长和侵袭参数。
Calibrating tumor growth and invasion parameters with spectral spatial analysis of cancer biopsy tissues.
发表日期：2024 Oct 02
作者：
Stefano Pasetto, Michael Montejo, Mohammad U Zahid, Marilin Rosa, Robert Gatenby, Pirmin Schlicke, Roberto Diaz, Heiko Enderling
来源：
npj Systems Biology and Applications
摘要：
反应扩散方程广泛应用于癌症的数学模型中。基于有限临床数据的模型参数校准对于使用反应扩散方程模拟对每个患者进行可靠预测至关重要。在这里，我们重点关注用于临床癌症诊断的组织活检中常规获得的细胞水平数据。我们分析了多重免疫荧光染色的活检组织的空间结构。我们推导出两点相关函数和相应的空间功率谱分布。我们表明，这种数据推导的功率谱分布可以拟合反应扩散方程解的功率谱，从而可以识别患者特定的肿瘤生长和侵袭率。这种方法允许通过常规活检材料在单个快照中及时测量患者特定的关键肿瘤动力学特性。© 2024。作者。
The reaction-diffusion equation is widely used in mathematical models of cancer. The calibration of model parameters based on limited clinical data is critical to using reaction-diffusion equation simulations for reliable predictions on a per-patient basis. Here, we focus on cell-level data as routinely available from tissue biopsies used for clinical cancer diagnosis. We analyze the spatial architecture in biopsy tissues stained with multiplex immunofluorescence. We derive a two-point correlation function and the corresponding spatial power spectral distribution. We show that this data-deduced power spectral distribution can fit the power spectrum of the solution of reaction-diffusion equations that can then identify patient-specific tumor growth and invasion rates. This approach allows the measurement of patient-specific critical tumor dynamical properties from routinely available biopsy material at a single snapshot in time.© 2024. The Author(s).