Mathematical and computational models have emerged as effective complements and, in some cases, alternatives to in vitro and in vivo research. Particularly in the area of cancer research, such models allow for testing of a diverse combination of parameters and variables via simulation, some of which would not be possible to examine experimentally. One of the most-common criticisms of mathematical and computational models is the extent to which they can accurately mimic, and subsequently predict, actual biological events. Given that many complex biological processes involve multiple independent but simultaneous events, portraying these processes computationally is difficult because they must be emulated sequentially in silico. Herein, we elaborate a nonlinear, dynamic, mathematical model for cancer growth, which involves iron requirements of cells. The model simulates malignant tumor growth, including cancerous cell diffusion and death (apoptosis), allowing for movement in all directions in two-dimensional space according to rule-based mathematical algorithms. To visualize the model, we developed a computer graphic simulation program and used it to demonstrate the effects of varying parameters and various diffusion patterns. We applied the Local Interaction Simulation Approach (LISA) and obtained graphical and numerical results using different diffusional neighborhoods. Our results show that the growth of a simulated tumor over time is dependent on the availability of its hypothetical nutrient source. Furthermore, we illustrate the effects of changing a variety of model parameters, and show the influence that is imparted by the diffusion process on the overall shape and growth of the tumor. Copyright © 2012 by the International Society for Computers and Their Applications (ISCA) All rights reserved.