Smolle J, Hofmann-Wellenhof R, Kofler R, Cerroni L, Haas J, Kerl H
Department of Dermatology, University of Graz, Austria.
J Invest Dermatol. 1995 Dec;105(6):797-801. doi: 10.1111/1523-1747.ep12326559.
Computer simulations have been used frequently in the life sciences to investigate the mechanisms of morphologic pattern formation. The cellular automaton program SMN5 is designed to simulate tumor growth and to estimate biologic properties by comparing real tumor patterns with computer-simulated reference patterns. This method was applied to 195 cases of primary melanoma of the skin. S-100-stained sections were evaluated by image analysis and compared statistically to a reference set of 4000 simulated patterns. Estimates of tumor cell proliferation, motility, cell loss, cohesion, stroma destruction, and intercellular signals (autocrine and paracrine factors affecting growth, motility, and cell loss) were calculated. Twelve of 18 estimated parameters correlated significantly with tumor progression, as indicated by vertical tumor thickness (linear regression analysis: p < or = 0.05), and 13 of 18 parameters carried prognostic significance (log rank test: p < or = 0.05). Poor prognosis was associated particularly with a pronounced increase in the estimates of proliferation, tumor cell motility, and stromal degradation. Poor prognosis was also associated with a decrease in the estimates of cell loss, tumor cell cohesion, and paracrine growth factor dependence. In multivariate analysis using Cox's proportional hazard model, stromal degradation and motility showed prognostic information in addition to conventional prognostic parameters. The study shows that analytical comparison of real tumors with computer-simulated patterns of a cellular automaton facilitates a functional interpretation of tumor morphology, which carries prognostic significance in cutaneous melanoma.
计算机模拟在生命科学中已被频繁用于研究形态模式形成的机制。细胞自动机程序SMN5旨在模拟肿瘤生长，并通过将真实肿瘤模式与计算机模拟的参考模式进行比较来估计生物学特性。该方法应用于195例原发性皮肤黑色素瘤。通过图像分析对S-100染色切片进行评估，并与4000个模拟模式的参考集进行统计学比较。计算肿瘤细胞增殖、运动性、细胞丢失、黏附、基质破坏以及细胞间信号（影响生长、运动性和细胞丢失的自分泌和旁分泌因子）的估计值。18个估计参数中的12个与肿瘤进展显著相关，如垂直肿瘤厚度所示（线性回归分析：p≤0.05），18个参数中的13个具有预后意义（对数秩检验：p≤0.05）。预后不良尤其与增殖、肿瘤细胞运动性和基质降解估计值的显著增加有关。预后不良还与细胞丢失、肿瘤细胞黏附以及旁分泌生长因子依赖性估计值的降低有关。在使用Cox比例风险模型的多变量分析中，除了传统的预后参数外，基质降解和运动性显示出预后信息。该研究表明，将真实肿瘤与细胞自动机的计算机模拟模式进行分析比较有助于对肿瘤形态进行功能解释，这在皮肤黑色素瘤中具有预后意义。
