Visualizing the Tumor Microenvironment of Liver Metastasis by Spinning Disk Confocal Microscopy

  • Liane Babes
  • Paul KubesEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1458)


Intravital microscopy has evolved into an invaluable technique to study the complexity of tumors by visualizing individual cells in live organisms. Here, we describe a method for employing intravital spinning disk confocal microscopy to picture high-resolution tumor–stroma interactions in real time. We depict in detail the surgical procedures to image various tumor microenvironments and different cellular components in the liver.

Key words

Spinning disk confocal microscopy Liver Intravital imaging Metastasis Mouse models Transgenic mice Imaging Tumor microenvironment 



This work was supported by the Alberta Innovates Health Solutions graduate studentship (201400345). We would like to acknowledge Caitlyn MacDonald for her assistance in acquiring images during surgical procedures.

Supplementary material

Movie 1:

3D reconstitution of liver metastasis. Melanoma cells (B16F10) were labeled in vitro with lipophilic membrane dye DiI (red) and intrasplenically transplanted into genetically engineered LysM-eGFP mice. Neutrophils (rounded cell morphology) are depicted in bright green and reside inside the vasculature (AF647-albumin, blue). Kupffer cells are located in the vasculature and labeled with anti-F4/80 (white). Hepatic stellate cells (bright green) can be distinguished from neutrophils by their elongated cell shape situated outside of hepatic vasculature. Autofluorescent hepatocytes are represented in dark green. 5 days after melanoma cell injection confocal z planes (20× lens) were recorded every 1 μm and reconstructed into a movie. Scale bar: 200 μm. Images were corrected for contrast and brightness (AVI 533220 kb)

Movie 2:

Visualizing immune cells in liver vasculature by spinning disk confocal microscopy. NKT cells (bright green) in the liver are visualized in CXCR6-GFP transgenic mice. Kupffer cells (red) are labeled with anti-F4/80. Autofluorescent hepatocytes are shown in dark green. Representative picture (20× lens) of a 30 min long image sequence with 10 s between frames. Scale bar: 68 μm. Images were corrected for contrast and brightness (AVI 41512 kb)

Movie 3:

Visualizing NKT cell dynamics in the liver tumor microenvironment. CXCR6-GFP transgenic mice were injected with colon adenocarcinoma cells (C26 cells labeled with DID membrane dye). 3 days later, metastases (blue) and NKT cells (bright green) are pictured in the liver. Autofluorescent hepatocytes are shown in dark green. The 1 h image sequence was recorded with 15 s between frames. Scale bar: 140 μm. Images were corrected for contrast and brightness (AVI 68992 kb)

Movie 4:

Long-term imaging of liver tumors. Neutrophils are visualized in LysM-eGFP transgenic mice. Image acquisition was performed right after tumor cells (B16F10 labeled with DID membrane dye (blue)) were intrasplenically injected. Dying tumor cells were detected with propidium iodide (red). Autofluorescent hepatocytes are shown in dark green. The movie over 3.5 h was recorded with 30 s between frames. Scale bar: 140 μm (MP4 26155 kb)


  1. 1.
    Ellenbroek SI, van Rheenen J (2014) Imaging hallmarks of cancer in living mice. Nat Rev Cancer 14:406–418CrossRefPubMedGoogle Scholar
  2. 2.
    Zomer A, Beerling E, Vlug EJ, van Rheenen J (2011) Real-time intravital imaging of cancer models. Clin Transl Oncol 13:848–854CrossRefPubMedGoogle Scholar
  3. 3.
    Lohela M, Werb Z (2010) Intravital imaging of stromal cell dynamics in tumors. Curr Opin Genet Dev 20:72–78CrossRefPubMedGoogle Scholar
  4. 4.
    Masedunskas A, Milberg O, Porat-Shliom N, Sramkova M, Wigand T, Amornphimoltham P, Weigert R (2012) Intravital microscopy: a practical guide on imaging intracellular structures in live animals. Bioarchitecture 2:143–157CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Dunn KW, Young PA (2006) Principles of multiphoton microscopy. Nephron Exp Nephrol 103:e33–e40CrossRefPubMedGoogle Scholar
  6. 6.
    Helmchen F, Denk W (2005) Deep tissue two-photon microscopy. Nat Methods 2:932–940CrossRefPubMedGoogle Scholar
  7. 7.
    Smith, C.L. (2008) Basic confocal microscopy. In: Ausubel FM et al (eds) Current protocol in molecular biology. Chapter 14:Unit 14.11Google Scholar
  8. 8.
    Tanaami T, Otsuki S, Tomosada N, Kosugi Y, Shimizu M, Ishida H (2002) High-speed 1-frame/ms scanning confocal microscope with a microlens and Nipkow disks. Appl Optics 41:4704–4708CrossRefGoogle Scholar
  9. 9.
    Ewald AJ, Werb Z, Egeblad M (2011) Dynamic, long-term in vivo imaging of tumor-stroma interactions in mouse models of breast cancer using spinning-disk confocal microscopy. Cold Spring Harbor Protocols 2011(2):pdb top97. doi: 10.1101/pdb.top97 Google Scholar
  10. 10.
    Nakasone ES, Askautrud HA, Kees T, Park JH, Plaks V, Ewald AJ et al (2012) Imaging tumor-stroma interactions during chemotherapy reveals contributions of the microenvironment to resistance. Cancer Cell 21:488–503CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Nakasone ES, Askautrud HA, Egeblad M (2013) Live imaging of drug responses in the tumor microenvironment in mouse models of breast cancer. J Vis Exp 73:e50088PubMedGoogle Scholar
  12. 12.
    Gul N, Babes L, Siegmund K, Korthouwer R, Bogels M, Braster R et al (2014) Macrophages eliminate circulating tumor cells after monoclonal antibody therapy. J Clin Invest 124:812–823CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Physiology and PharmacologyUniversity of CalgaryCalgaryCanada
  2. 2.Calvin, Phoebe & Joan Snyder Institute for Chronic Diseases, Snyder Institute for Chronic Diseases, Cumming School of MedicineUniversity of CalgaryCalgaryCanada

Personalised recommendations