Literature DB >> 18524624

Invasion emerges from cancer cell adaptation to competitive microenvironments: quantitative predictions from multiscale mathematical models.

Vito Quaranta1, Katarzyna A Rejniak, Philip Gerlee, Alexander R A Anderson.   

Abstract

In this review we summarize our recent efforts using mathematical modeling and computation to simulate cancer invasion, with a special emphasis on the tumor microenvironment. We consider cancer progression as a complex multiscale process and approach it with three single-cell-based mathematical models that examine the interactions between tumor microenvironment and cancer cells at several scales. The models exploit distinct mathematical and computational techniques, yet they share core elements and can be compared and/or related to each other. The overall aim of using mathematical models is to uncover the fundamental mechanisms that lend cancer progression its direction towards invasion and metastasis. The models effectively simulate various modes of cancer cell adaptation to the microenvironment in a growing tumor. All three point to a general mechanism underlying cancer invasion: competition for adaptation between distinct cancer cell phenotypes, driven by a tumor microenvironment with scarce resources. These theoretical predictions pose an intriguing experimental challenge: test the hypothesis that invasion is an emergent property of cancer cell populations adapting to selective microenvironment pressure, rather than culmination of cancer progression producing cells with the "invasive phenotype". In broader terms, we propose that fundamental insights into cancer can be achieved by experimentation interacting with theoretical frameworks provided by computational and mathematical modeling.

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Year:  2008        PMID: 18524624      PMCID: PMC3789515          DOI: 10.1016/j.semcancer.2008.03.018

Source DB:  PubMed          Journal:  Semin Cancer Biol        ISSN: 1044-579X            Impact factor:   15.707


  37 in total

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  33 in total

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9.  Selection in spatial stochastic models of cancer: migration as a key modulator of fitness.

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