  To elucidate the role of environmental conditions in molecular-level dynamics
and to study their impact on macroscopic brain tumor growth patterns, the
expression of the genes Tenascin C and PCNA in a 2D agent-based model for the
migratory trait is calibrated using experimental data from the literature,
while the expression of these genes for the proliferative trait is obtained as
the model output. Numerical results confirm that the gene expression of
Tenascin C is consistently higher in the migratory glioma cell phenotype and
show that the expression of PCNA is consistently higher among proliferating
tumor cells. Furthermore, detrended fluctuation analysis (DFA) suggests that
for prediction purposes, the simulated gene expression profiles of Tenascin C
and PCNA that were determined separately for the migrating and proliferating
phenotypes exhibit lesser predictability than those of the phenotypic mixture
combining all viable tumor cells typically found in clinical biopsies.
