Selected aspects of avascular tumor growth reproduced by a hybrid model of cell dynamics and chemical kinetics

• Published in: Mathematical biosciences 2024-04, Vol.370, p.109168-109168, Article 109168
• Main Author: Scianna, Marco
• Format: Article
• Language: English
• Subjects: Hybrid model; Individual-based model; Tumor invasion; Tumor morphology
• ISSN: 0025-5564; 1879-3134
• DOI: 10.1016/j.mbs.2024.109168

We here propose a hybrid computational framework to reproduce and analyze aspects of the avascular progression of a generic solid tumor. Our method first employs an individual-based approach to represent the population of tumor cells, which are distinguished in viable and necrotic agents. The active part of the disease is in turn differentiated according to a set of metabolic states. We then describe the spatio-temporal evolution of the concentration of oxygen and of tumor-secreted proteolytic enzymes using partial differential equations (PDEs). A differential equation finally governs the local degradation of the extracellular matrix (ECM) by the malignant mass. Numerical realizations of the model are run to reproduce tumor growth and invasion in a number scenarios that differ for cell properties (adhesiveness, duplication potential, proteolytic activity) and/or environmental conditions (level of tissue oxygenation and matrix density pattern). In particular, our simulations suggest that tumor aggressiveness, in terms of invasive depth and extension of necrotic tissue, can be reduced by (i) stable cell–cell contact interactions, (ii) poor tendency of malignant agents to chemotactically move upon oxygen gradients, and (iii) presence of an overdense matrix, if coupled by a disrupted proteolytic activity of the disease. •The work presents a hybrid model to study the avascular growth of a generic tumor.•The model combines an individual-based approach and a system of RD equations.•Tumor progression is reproduced and quantified in different scenarios.•The computational results are compared to selected experiential evidence.