IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v5y2014i1d10.1038_ncomms6870.html
   My bibliography  Save this article

Image-guided radiotherapy platform using single nodule conditional lung cancer mouse models

Author

Listed:
  • Grit S. Herter-Sprie

    (Harvard Medical School
    Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute
    Dana-Farber Cancer Institute)

  • Houari Korideck

    (Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, 450 Brookline Avenue)

  • Camilla L. Christensen

    (Harvard Medical School
    Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute
    Dana-Farber Cancer Institute)

  • Jan M. Herter

    (Center for Excellence in Vascular Biology, Brigham and Women’s Hospital, Harvard Medical School)

  • Kevin Rhee

    (Harvard Medical School
    Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute
    Dana-Farber Cancer Institute)

  • Ross I. Berbeco

    (Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, 450 Brookline Avenue)

  • David G. Bennett

    (Harvard Medical School, Beth Israel Deaconess Medical Center
    Present address: PAREXEL International Corp., 195 West Street, Waltham, Massachusetts, USA)

  • Esra A. Akbay

    (Harvard Medical School
    Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute
    Dana-Farber Cancer Institute)

  • David Kozono

    (Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School)

  • Raymond H. Mak

    (Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School)

  • G. Mike Makrigiorgos

    (Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, 450 Brookline Avenue)

  • Alec C. Kimmelman

    (Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, 450 Brookline Avenue)

  • Kwok-Kin Wong

    (Harvard Medical School
    Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute
    Dana-Farber Cancer Institute)

Abstract

Close resemblance of murine and human trials is essential to achieve the best predictive value of animal-based translational cancer research. Kras-driven genetically engineered mouse models of non-small-cell lung cancer faithfully predict the response of human lung cancers to systemic chemotherapy. Owing to development of multifocal disease, however, these models have not been usable in studies of outcomes following focal radiotherapy (RT). We report the development of a preclinical platform to deliver state-of-the-art image-guided RT in these models. Presence of a single tumour as usually diagnosed in patients is modelled by confined injection of adenoviral Cre recombinase. Furthermore, three-dimensional conformal planning and state-of-the-art image-guided dose delivery are performed as in humans. We evaluate treatment efficacies of two different radiation regimens and find that Kras-driven tumours can temporarily be stabilized upon RT, whereas additional loss of either Lkb1 or p53 renders these lesions less responsive to RT.

Suggested Citation

  • Grit S. Herter-Sprie & Houari Korideck & Camilla L. Christensen & Jan M. Herter & Kevin Rhee & Ross I. Berbeco & David G. Bennett & Esra A. Akbay & David Kozono & Raymond H. Mak & G. Mike Makrigiorgos, 2014. "Image-guided radiotherapy platform using single nodule conditional lung cancer mouse models," Nature Communications, Nature, vol. 5(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms6870
    DOI: 10.1038/ncomms6870
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms6870
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/ncomms6870?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Andreas Weigert & Xiang Zheng & Alina Nenzel & Kati Turkowski & Stefan Günther & Elisabeth Strack & Evelyn Sirait-Fischer & Eiman Elwakeel & Ivan M. Kur & Vandana S. Nikam & Chanil Valasarajan & Hauke, 2022. "Fibrocytes boost tumor-supportive phenotypic switches in the lung cancer niche via the endothelin system," Nature Communications, Nature, vol. 13(1), pages 1-21, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms6870. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.