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Computational Modelling Identifies Morphologic Predictors of Tumor Invasion
Author(s) -
Bearer Elaine,
Cristini Vittorio
Publication year - 2008
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.22.1_supplement.321.7
Subject(s) - in vivo , biology , pathology , tumor microenvironment , carcinogenesis , tumor cells , glioma , brain tumor , infiltration (hvac) , cancer research , cancer , medicine , genetics , microbiology and biotechnology , physics , thermodynamics
We hypothesize that tumor morphology can be derived from first principles of physics: conservation of mass, energy and momentum. With a series of interdependent partial differential equations describing diffusion gradients of metabolites, cell division, adhesion and migration, we have designed a computational model that produces three‐dimensional architecture of tumor growth as a function of these variables. Through “constitutive” laws, these parameters are dictated in turn by a mutation array describing alterations of key cellular pathways in carcinogenesis. We calculated parameters from 36 human glioblastoma samples. Parameters affecting tumor growth in silica were compared statistically to behavior present in biopsy samples. Computer simulations demonstrate that morphological instability drives increased nutrient demand, introducing hypoxic diffusion gradients in the microenvironment. This results in nutrient gradients within the tumor that either cause necrosis or provoke hypoxic tumor cells to infiltrate adjacent tumor and/or brain. This invasive pattern is consistent with our experiments and with other in‐vitro and in‐vivo observations. We predict that increase in distance between capillaries at tumor margins is evidence of invading malignant cells and serves as a previously unrecognized histological marker of tumor‐brain margin. Supported by NINDS NS046810 and NIGMS GM47368.