Treatment of colorectal liver metastasis with cabazitaxel containing biodegradable nanoparticles in combination with acoustic cluster therapy

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Liver metastasis is the most common metastatic site for colorectal cancer and relevant in vivo models are important to find novel treatment options for liver metastasis. Tumor colonization in the liver can be achieved by injection of human colorectal tumor cells into the spleen of mice. Cabazitaxel is a semi-synthetic taxane derivative that is used in the clinic and has been shown to be effective against subcutaneous colorectal cancer in mice. In this study we want to investigate if incorporation of cabazitaxel into biodegradable polycyanoacrylate nanoparticles can inhibit liver metastasis tumor growth and reduce adverse effects in healthy tissue when compared to the drug alone. In addition we want to test if the ultrasound method of Acoustic Cluster Therapy™ (ACT) can further increase the delivery of the nanoparticles to the tumor cells and thereby enhance the anti-tumor effect of cabazitaxel.

The combination of two tumor targeting approaches with nanoparticles and ACT has a high potential to improve the treatment of metastatic colorectal cancer. These experiments might provide the basis for future clinical applications.

The mice will get tumors in their liver and get anticancer drug treatment, and this can result in loss of body weight, or lead to swollen abdominal region because of high tumor burden in the liver. If we observe any signs of these severe symptoms, we will limit the harm to the animals to as short as possible. Previous experiments have been shown that the treatment with ultrasound and the imaging is well tolerated.

We apply for a total of 312 athymic nude mice. We aim to replace and reduce the number of animals and try to refine the procedures. The mechanisms of cancer metastasis are very complex and up-to-date there are no cell culture or other techniques that can mimic the effects of drugs and nanoparticles in an organism completely. The number of mice is as low as possible, but high enough so that it is still possible to find significant differences.