Emergent behaviors from a cellular automaton model for invasive tumor growth in heterogeneous microenvironments

Yang Jiao, Salvatore Torquato

Research output: Contribution to journalArticle

49 Citations (Scopus)

Abstract

Understanding tumor invasion and metastasis is of crucial importance for both fundamental cancer research and clinical practice. In vitro experiments have established that the invasive growth of malignant tumors is characterized by the dendritic invasive branches composed of chains of tumor cells emanating from the primary tumor mass. The preponderance of previous tumor simulations focused on non-invasive (or proliferative) growth. The formation of the invasive cell chains and their interactions with the primary tumor mass and host microenvironment are not well understood. Here, we present a novel cellular automaton (CA) model that enables one to efficiently simulate invasive tumor growth in a heterogeneous host microenvironment. By taking into account a variety of microscopic-scale tumor-host interactions, including the short-range mechanical interactions between tumor cells and tumor stroma, degradation of the extracellular matrix by the invasive cells and oxygen/nutrient gradient driven cell motions, our CA model predicts a rich spectrum of growth dynamics and emergent behaviors of invasive tumors. Besides robustly reproducing the salient features of dendritic invasive growth, such as least-resistance paths of cells and intrabranch homotype attraction, we also predict nontrivial coupling between the growth dynamics of the primary tumor mass and the invasive cells. In addition, we show that the properties of the host microenvironment can significantly affect tumor morphology and growth dynamics, emphasizing the importance of understanding the tumor-host interaction. The capability of our CA model suggests that sophisticated in silico tools could eventually be utilized in clinical situations to predict neoplastic progression and propose individualized optimal treatment strategies.

Original languageEnglish (US)
Article numbere1002314
JournalPLoS Computational Biology
Volume7
Issue number12
DOIs
StatePublished - Dec 2011
Externally publishedYes

Fingerprint

Emergent Behavior
Tumor Growth
cellular automaton
Cellular Automaton Model
Cellular automata
tumor
Tumors
Tumor
neoplasms
Growth
Neoplasms
Cell
Cells
Interaction
Predict
cells
Metastasis
Invasion
Nutrients
Progression

ASJC Scopus subject areas

  • Cellular and Molecular Neuroscience
  • Ecology
  • Molecular Biology
  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Computational Theory and Mathematics

Cite this

Emergent behaviors from a cellular automaton model for invasive tumor growth in heterogeneous microenvironments. / Jiao, Yang; Torquato, Salvatore.

In: PLoS Computational Biology, Vol. 7, No. 12, e1002314, 12.2011.

Research output: Contribution to journalArticle

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