Skip to main content Accessibility help
×
Hostname: page-component-7c8c6479df-5xszh Total loading time: 0 Render date: 2024-03-28T15:59:01.196Z Has data issue: false hasContentIssue false

11 - Conclusion

from Part II - Applications

Published online by Cambridge University Press:  05 October 2010

Vittorio Cristini
Affiliation:
University of Texas Health Science Center, Houston
John Lowengrub
Affiliation:
University of California, Irvine
Get access

Summary

Tumors are complex systems dominated by large numbers of processes with highly nonlinear dynamics spanning a wide range of dimensions. Typically, such complex systems can be understood only through complementary experimental investigation and mathematical modeling. New methodologies are needed to integrate and quantify the myriad variables and enable the prediction of outcomes, the selection of existing therapies, and the development of new treatments, possibly on a personalized, individual, basis. Mathematical modeling can provide a rigorous, precise, approach for quantifying correlations between tumor parameters, prognosis, and treatment outcomes. Integration of these elements into a multidisciplinary model of tumor progression would be an important tool to advance clinical decision-making. Thus, there is a critical need for biologically realistic and predictive multiscale and multivariate models of tumor growth and invasion and, as we have seen in this book, there has been much recent effort directed towards this goal.

The tumor models and simulation results that we have reviewed demonstrate that, while mathematical analyses still lag behind experimentation, significant progress has been made in providing important insights into the root causes of solid-tumor invasion and metastasis and in providing and assessing effective treatment strategies. For example, the results provide a means to associate quantitatively tumor growth and the effects of a limited supply of cell substrates. Inhomogeneities in the substrate availability and/or host tissue biomechanical properties can result in tumor morphological instability. These instabilities may allow a tumor to overcome diffusional limitations on growth and to grow to sizes larger than would be possible if it had a compact shape.

Type
Chapter
Information
Multiscale Modeling of Cancer
An Integrated Experimental and Mathematical Modeling Approach
, pp. 235 - 237
Publisher: Cambridge University Press
Print publication year: 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • Conclusion
  • Vittorio Cristini, University of Texas Health Science Center, Houston, John Lowengrub, University of California, Irvine
  • Book: Multiscale Modeling of Cancer
  • Online publication: 05 October 2010
  • Chapter DOI: https://doi.org/10.1017/CBO9780511781452.012
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • Conclusion
  • Vittorio Cristini, University of Texas Health Science Center, Houston, John Lowengrub, University of California, Irvine
  • Book: Multiscale Modeling of Cancer
  • Online publication: 05 October 2010
  • Chapter DOI: https://doi.org/10.1017/CBO9780511781452.012
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Conclusion
  • Vittorio Cristini, University of Texas Health Science Center, Houston, John Lowengrub, University of California, Irvine
  • Book: Multiscale Modeling of Cancer
  • Online publication: 05 October 2010
  • Chapter DOI: https://doi.org/10.1017/CBO9780511781452.012
Available formats
×