Multiparameter computational modeling of tumor invasion

Elaine L. Bearer, John S. Lowengrub, Hermann B. Frieboes, Yao Li Chuang, Fang Jin, Steven M. Wise, Mauro Ferrari, David B. Agus, Vittorio Cristini

Research output: Contribution to journalArticlepeer-review

101 Scopus citations


Clinical outcome prognostication in oncology is a guiding principle in therapeutic choice. A wealth of qualitative empirical evidence links disease progression with tumor morphology, histopathology, invasion, and associated molecular phenomena. However, the quantitative contribution of each of the known parameters in this progression remains elusive. Mathematical modeling can provide the capability to quantify the connection between variables governing growth, prognosis, and treatment outcome. By quantifying the link between the tumor boundary morphology and the invasive phenotype, this work provides a quantitative tool for the study of tumor progression and diagnostic/prognostic applications. This establishes a framework for monitoring system perturbation towards development of therapeutic strategies and correlation to clinical outcome for prognosis.

Original languageEnglish (US)
Pages (from-to)4493-4501
Number of pages9
JournalCancer research
Issue number10
StatePublished - May 15 2009

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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