Bordel-Vozmediano Silvia, Sabir Soukaina, Benito-Barca Lucía, Weigelin Bettina, Pérez-García Víctor M
Mathematical Oncology Laboratory (MOLAB), Instituto de Matemática Aplicada a la Ciencia y la Ingeniería, Universidad de Castilla-La Mancha, Ciudad Real, 13005, Spain; Departamento de Matemáticas, Escuela Técnica Superior de Ingenieros Industriales, Universidad de Castilla-La Mancha, 13005, Ciudad Real, Spain.
Mathematical Oncology Laboratory (MOLAB), Instituto de Matemática Aplicada a la Ciencia y la Ingeniería, Universidad de Castilla-La Mancha, Ciudad Real, 13005, Spain; Departamento de Matemáticas, Escuela Técnica Superior de Ingenieros Industriales, Universidad de Castilla-La Mancha, 13005, Ciudad Real, Spain.
Comput Biol Med. 2025 Aug;194:110427. doi: 10.1016/j.compbiomed.2025.110427. Epub 2025 Jun 11.
Chimeric antigen receptor T (CAR T) cell therapy has emerged as a promising treatment for hematological malignancies, offering a targeted approach to cancer treatment. Understanding the complexities of CAR T-cell therapy within solid tumors poses challenges due to the intricate interactions within the tumor microenvironment. Mathematical modeling may serve as a valuable tool to unravel the dynamics of CAR T-cell therapy and improve its effectiveness in solid tumors. This study aimed to investigate the impact of spatial aspects in CAR T therapy of solid tumors, utilizing cellular automata for modeling purposes. Our main objective was to deepen our understanding of treatment effects by analyzing scenarios with different spatial distributions and varying the initial quantities of tumor and CAR T-cells. Tumor geometry significantly influenced treatment efficacy in-silico, with notable differences observed between tumors with block-like arrangements and those with sparse cell distributions, leading to the concept of immune suppression due to geometrical effects. This research delves into the intricate relationship between spatial dynamics and the effectiveness of CAR T therapy in solid tumors, highlighting the relevance of tumor geometry in the outcome of cellular immunotherapy treatments. Our results provide a basis for improving the efficacy of CAR T-cell treatments by combining them with other ones reducing the density of compact tumor areas and thus opening access ways for tumor killing T-cells.
嵌合抗原受体T(CAR T)细胞疗法已成为治疗血液系统恶性肿瘤的一种有前景的方法,为癌症治疗提供了一种靶向治疗途径。由于肿瘤微环境内复杂的相互作用,了解实体瘤中CAR T细胞疗法的复杂性具有挑战性。数学建模可能是揭示CAR T细胞疗法动态并提高其在实体瘤中有效性的宝贵工具。本研究旨在利用细胞自动机进行建模,探讨实体瘤CAR T治疗中空间因素的影响。我们的主要目标是通过分析不同空间分布以及改变肿瘤和CAR T细胞初始数量的情况,加深对治疗效果的理解。肿瘤几何形状在计算机模拟中显著影响治疗效果,块状排列的肿瘤与细胞分布稀疏的肿瘤之间观察到显著差异,从而引出了几何效应导致免疫抑制的概念。本研究深入探讨了实体瘤中空间动态与CAR T治疗有效性之间的复杂关系,突出了肿瘤几何形状在细胞免疫治疗结果中的相关性。我们的结果为通过将CAR T细胞治疗与其他降低致密肿瘤区域密度从而为杀伤肿瘤的T细胞开辟通路的治疗方法相结合来提高其疗效提供了依据。