The role of the microenvironment in tumor growth and invasion

Yangjin Kim, Magdalena A. Stolarska, Hans G. Othmer

Research output: Contribution to journalReview articlepeer-review

145 Scopus citations


Mathematical modeling and computational analysis are essential for understanding the dynamics of the complex gene networks that control normal development and homeostasis, and can help to understand how circumvention of that control leads to abnormal outcomes such as cancer. Our objectives here are to discuss the different mechanisms by which the local biochemical and mechanical microenvironment, which is comprised of various signaling molecules, cell types and the extracellular matrix (ECM), affects the progression of potentially-cancerous cells, and to present new results on two aspects of these effects. We first deal with the major processes involved in the progression from a normal cell to a cancerous cell at a level accessible to a general scientific readership, and we then outline a number of mathematical and computational issues that arise in cancer modeling. In Section 2 we present results from a model that deals with the effects of the mechanical properties of the environment on tumor growth, and in Section 3 we report results from a model of the signaling pathways and the tumor microenvironment (TME), and how their interactions affect the development of breast cancer. The results emphasize anew the complexities of the interactions within the TME and their effect on tumor growth, and show that tumor progression is not solely determined by the presence of a clone of mutated immortal cells, but rather that it can be 'community-controlled'.

Original languageEnglish (US)
Pages (from-to)353-379
Number of pages27
JournalProgress in Biophysics and Molecular Biology
Issue number2
StatePublished - Aug 2011

Bibliographical note

Funding Information:
Supported in part by NIH Grant GMS # 29123 , NSF Grants DMS # 0517884 and DMS # 0817529 to HGO, and the Minnesota Supercomputing Institute. Y. Kim is partially supported by an NSF grant to the Mathematical Biosciences Institute, OSU, and by a Rackham grant, University of Michigan-Ann Arbor.


  • Breast cancer
  • Hybrid model
  • Mechanical effects
  • Tumor progression


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