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

期刊

SEMINARS IN CANCER BIOLOGY
卷 18, 期 5, 页码 338-348

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.semcancer.2008.03.018

关键词

cancer; invasion; mathematical modeling; adaptation; microenvironment; evolution; cancer progression; selection; computer simulations; cancer phenotypes; Darwinian selection

类别

资金

  1. Integrative Cancer Biology Program of the National Cancer Institute [U54-CA113007]
  2. NATIONAL CANCER INSTITUTE [U54CA113007, R01CA047858] Funding Source: NIH RePORTER

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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 microenviromment 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. (C) 2008 Elsevier Ltd. All rights reserved.

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