Skip to main content
  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

AACR logo

  • Register
  • Log in
  • My Cart
Advertisement

Main menu

  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • Meeting Abstracts
    • Collections
      • COVID-19 & Cancer Resource Center
      • Focus on Computer Resources
      • Highly Cited Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Early Career Award
    • Best of: Author Profiles
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citations
    • Author/Keyword
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

User menu

  • Register
  • Log in
  • My Cart

Search

  • Advanced search
Cancer Research
Cancer Research
  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • Meeting Abstracts
    • Collections
      • COVID-19 & Cancer Resource Center
      • Focus on Computer Resources
      • Highly Cited Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Early Career Award
    • Best of: Author Profiles
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citations
    • Author/Keyword
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

Letters to the Editor

Comment on: A Validated Mathematical Model of Cell-Mediated Immune Response to Tumor Growth

Lisette G. de Pillis, Ami E. Radunskaya and Charles L. Wiseman
Lisette G. de Pillis
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ami E. Radunskaya
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Charles L. Wiseman
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI: 10.1158/0008-5472.CAN-07-1403 Published September 2007
  • Article
  • Info & Metrics
  • PDF
Loading
  • mathematical modeling
  • immune-tumor dynamics
  • NK cells
  • CD8+ T cells
  • vaccine therapy
  • Cancer vaccines
  • Cellular immunotherapy

In Response:

Gowal et al. erroneously surmise that in ref. 1, we assume “unrealistic” initial natural killer (NK) cell levels of zero in order to generate the simulations of Fig. 4, and they conclude from their own simulations that NK efficacy is stronger than we indicate. We do not draw conclusions about the efficiency of NK cells from our model. Rather, we use the model equations as a possible description of the different cytolytic mechanisms of NK cells versus CD8+ T cells. These mathematical descriptions of the immune cell dynamics are validated when we show that the simulations can reproduce experimentally observed differences in the efficacy of innate and the tumor-specific responses.

An explicit statement of the initial conditions used was omitted in ref. 1, so we state them here. Figure 4 (right) of ref. 1 is a simulation that captures the behavior shown in Fig. 3D (right-most panel) of ref. 2. The simulation employed a parameter set using a modified scaling of NK parameters from Table 1 of ref. 1 and non-zero NK initial conditions. The same qualitative simulation outcomes can be obtained using the NK parameters in Table 1, with j(ln) = 6j(nn), and with the initial NK count at its steady-state value: NK0 = σ/f = 3.16 × 105 cells. The initial CD8+ T count is zero, and the initial tumor challenge is T0 = 104 cells, with a re-challenge on day 10 of 104 live cells. We note that any values for j are rough estimates because precise values were not to be found in the literature.

We also point out that for the first 10 days of the simulation, the “ligand-transduced” parameter set for the NK cells was used, and from day 10 onward, the “control-transduced” parameter set was employed. This reflects the conditions of the laboratory experiment. We conjecture, based on their simulations, that Gowal et al. neglected to change the parameter set on day 10. We can only reproduce their results when the ligand-transduced parameter set is used for the entire simulation. This naturally results in a much stronger immune suppression of the tumor, but does not reflect the experiment reported in ref. 2.

The image on Fig. 4 (bottom left) of ref. 1 represents the outcomes of the experiments of Fig. 2A of ref. 2. In this case, only CD8+ T cells were targeted for deactivation. However, because of potential cross-reactions, including the loss of IL-2 production by the T cells, which in turn, could diminish NK differentiation and maturation, we assume that initial NK cell counts were lower than the steady state, but certainly not zero, as conjectured by Gowal and colleagues. Initial NK was NK0 = 104 cells, and initial CD8+ T count was zero. The NK source term and death term in our simulations are at the values stated in Table 1 of ref. 1.

The simulations of ref. 1 show that the new functional form for the interaction of the CD8+ T cells with tumor cells was sufficient to capture a range of behaviors observed experimentally, using a biologically reasonable set of initial conditions and system parameters.

  • ©2007 American Association for Cancer Research.

References

  1. 1.↵
    de Pillis L, Radunskaya A, Wiseman C. A validated mathematical model of cell-mediated immune response to tumor growth. Cancer Res 2005; 65: 7950–8.
    OpenUrlAbstract/FREE Full Text
  2. 2.↵
    Diefenbach A, Jensen E, Jamieson A, Raulet D. Rae1 and H60 ligands of the NKG2D receptor stimulate tumor immunity. Nature 2001; 413: 165–71.
    OpenUrlCrossRefPubMed
PreviousNext
Back to top
Cancer Research: 67 (17)
September 2007
Volume 67, Issue 17
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover

Sign up for alerts

View this article with LENS

Open full page PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for sharing this Cancer Research article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Comment on: A Validated Mathematical Model of Cell-Mediated Immune Response to Tumor Growth
(Your Name) has forwarded a page to you from Cancer Research
(Your Name) thought you would be interested in this article in Cancer Research.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Comment on: A Validated Mathematical Model of Cell-Mediated Immune Response to Tumor Growth
Lisette G. de Pillis, Ami E. Radunskaya and Charles L. Wiseman
Cancer Res September 1 2007 (67) (17) 8420; DOI: 10.1158/0008-5472.CAN-07-1403

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Comment on: A Validated Mathematical Model of Cell-Mediated Immune Response to Tumor Growth
Lisette G. de Pillis, Ami E. Radunskaya and Charles L. Wiseman
Cancer Res September 1 2007 (67) (17) 8420; DOI: 10.1158/0008-5472.CAN-07-1403
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • References
  • Info & Metrics
  • PDF
Advertisement

Related Articles

Cited By...

More in this TOC Section

  • Quantifying Preexisting Resistant and Persister Populations–Response
  • Quantifying Preexisting Resistant and Persister Populations–Letter
  • Tau Mutations as a Novel Risk Factor for Cancer—Response
Show more Letters to the Editor
  • Home
  • Alerts
  • Feedback
  • Privacy Policy
Facebook  Twitter  LinkedIn  YouTube  RSS

Articles

  • Online First
  • Current Issue
  • Past Issues
  • Meeting Abstracts

Info for

  • Authors
  • Subscribers
  • Advertisers
  • Librarians

About Cancer Research

  • About the Journal
  • Editorial Board
  • Permissions
  • Submit a Manuscript
AACR logo

Copyright © 2021 by the American Association for Cancer Research.

Cancer Research Online ISSN: 1538-7445
Cancer Research Print ISSN: 0008-5472
Journal of Cancer Research ISSN: 0099-7013
American Journal of Cancer ISSN: 0099-7374

Advertisement