Reproduction of patterns in melanocytic proliferations by agent-based simulation and geometric modeling

Spatio-temporal patterns of melanocytic proliferations observed in vivo are important for diagnosis but the mechanisms that produce them are poorly understood. Here we present an agent-based model for simulating the emergence of the main biologic patterns found in melanocytic proliferations. Our model portrays the extracellular matrix of the dermo-epidermal junction as a two-dimensional manifold and we simulate cellular migration in terms of geometric translations driven by adhesive, repulsive and random forces. Abstracted cellular functions and melanocyte-matrix interactions are modeled as stochastic events. For identification and validation we use visual renderings of simulated cell populations in a horizontal perspective that reproduce growth patterns observed in vivo by sequential dermatoscopy and corresponding vertical views that reproduce the arrangement of melanocytes observed in histopathologic sections. Our results show that a balanced interplay of proliferation and migration produces the typical reticular pattern of nevi, whereas the globular pattern involves additional cellular mechanisms. We further demonstrate that slight variations in the three basic cellular properties proliferation, migration, and adhesion are sufficient to produce a large variety of morphological appearances of nevi. We anticipate our model to be a starting point for the reproduction of more complex scenarios that will help to establish functional connections between abstracted microscopic behavior and macroscopic patterns in all types of melanocytic proliferations including melanoma.
Author summary Clinicians and pathologists use pigmentation patterns to classify melanocytic nevi into subgroups and to differentiate nevi from melanoma. The mechanisms that produce these patterns are poorly understood. Here, we reproduce the main patterns of nevi in computer simulations using an abstracted model of individual cell behavior. We developed a novel geometric approach for reconstructing the microanatomy of the epidermis in silico and to model the interaction of cell-agents with the physiological environment. We generated visual representations of simulated populations of melanocytes and demonstrate that the interplay of the collective behavior of individual cells and the physiologic microenvironment is responsible for the typical patterns of melanocytic lesions. Further, we show that the variations of nevi observed in vivo can be reproduced by simple agent-based models that depend on a few key parameters that reflect basic cellular functions such as proliferation, migration, and adhesion. Our simulations confirm existing assumptions about nest formation in melanocytic lesions and offer new insights and testable hypotheses for important biologic phenomena such as senescence and tumor progression. Furthermore, synthetic nevi created by our model may serve as training cases for machine learning algorithms.