4.4 Article

Advanced Animal Model of Colorectal Metastasis in Liver: Imaging Techniques and Properties of Metastatic Clones

Journal

JOVE-JOURNAL OF VISUALIZED EXPERIMENTS
Volume -, Issue 117, Pages -

Publisher

JOURNAL OF VISUALIZED EXPERIMENTS
DOI: 10.3791/54657

Keywords

Cancer Research; Issue 117; Oligometastases; heterogeneity; liver metastases; colorectal cancer; experimental model; spleen injection; in vivo imaging; ex vivo imaging; growth kinetics

Funding

  1. Virginia and D.K. Ludwig Fund for Cancer Research
  2. Lung Cancer Research Foundation (LCRF)
  3. Prostate Cancer Foundation (PCF)
  4. Cancer Center Support Grant [P30CA014599]

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Patients with a limited number of hepatic metastases and slow rates of progression can be successfully treated with local treatment approaches(1,2). However, little is known about the heterogeneity of liver metastases, and animal models capable of evaluating the development of individual metastatic colonies are needed. Here, we present an advanced model of hepatic metastases that provides the ability to quantitatively visualize the development of individual tumor clones in the liver and estimate their growth kinetics and colonization efficiency. We generated a panel of monoclonal derivatives of HCT116 human colorectal cancer cells stably labeled with luciferase and tdTomato and possessing different growth properties. With a splenic injection followed by a splenectomy, the majority of these clones are able to generate hepatic metastases, but with different frequencies of colonization and varying growth rates. Using the In Vivo Imaging System (IVIS), it is possible to visualize and quantify metastasis development with in vivo luminescent and ex vivo fluorescent imaging. In addition, Diffuse Luminescent Imaging Tomography (DLIT) provides a 3D distribution of liver metastases in vivo. Ex vivo fluorescent imaging of harvested livers provides quantitative measurements of individual hepatic metastatic colonies, allowing for the evaluation of the frequency of liver colonization and the growth kinetics of metastases. Since the model is similar to clinically observed liver metastases, it can serve as a modality for detecting genes associated with liver metastasis and for testing potential ablative or adjuvant treatments for liver metastatic disease.

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