Article

Solving the Puzzle of Metastasis: The Evolution of Cell Migration in Neoplasms

Genomics and Computational Biology Program, School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
PLoS ONE (Impact Factor: 3.23). 04/2011; 6(4):e17933. DOI: 10.1371/journal.pone.0017933
Source: PubMed

ABSTRACT

Metastasis represents one of the most clinically important transitions in neoplastic progression. The evolution of metastasis is a puzzle because a metastatic clone is at a disadvantage in competition for space and resources with non-metastatic clones in the primary tumor. Metastatic clones waste some of their reproductive potential on emigrating cells with little chance of establishing metastases. We suggest that resource heterogeneity within primary tumors selects for cell migration, and that cell emigration is a by-product of that selection.
We developed an agent-based model to simulate the evolution of neoplastic cell migration. We simulated the essential dynamics of neoangiogenesis and blood vessel occlusion that lead to resource heterogeneity in neoplasms. We observed the probability and speed of cell migration that evolves with changes in parameters that control the degree of spatial and temporal resource heterogeneity. Across a broad range of realistic parameter values, increasing degrees of spatial and temporal heterogeneity select for the evolution of increased cell migration and emigration.
We showed that variability in resources within a neoplasm (e.g. oxygen and nutrients provided by angiogenesis) is sufficient to select for cells with high motility. These cells are also more likely to emigrate from the tumor, which is the first step in metastasis and the key to the puzzle of metastasis. Thus, we have identified a novel potential solution to the puzzle of metastasis.

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Available from: Carlo Maley, Mar 24, 2015
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    • "Our model showed that high cell metabolism leads to the evolution of higher cell motility (Aktipis et al. 2012). More generally, our model and other models suggest that dispersal evolution may play an important role in invasion and metastasis in cancer (Chen et al. 2011;Aktipis et al. 2012). Walk Away dynamics may also help to illuminate other aspects of cancer biology that are poorly understood. "
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    • "Others use mathematical models of cell growth and specific biologic processes such as matrix modeling and migration to predict metastasis growth over time [77-80]. Agent-based modeling of metastases has been employed to characterize the selective forces involved in the generation of circulating, potentially metastatic tumor cells [81,82], implicate the role of host immunity in the generation of satellite metastases [1,2,4,10-14], and examine the interactions of metastatic tumor cells with the host immune system for optimizing tumor vaccine delivery [15-18]. Other models of individual tumor cell interactions with host environment, employing knowledge of biomechanics and enzyme kinetics in a system of differential equations that describe integrin interactions and tumor cell growth patterns [83,84]. "
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