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What is the best non-clinical liver cancer model with 100% cancer incidence rate and suitable for liver cancer assessment?

  • 2024.03.14
  • PRODUCTS AND SERVICES

If you are considering a drug evaluation study for liver cancer using a mouse model, our STAM™-HCC/IO⁺ model best replicates the pathology and characteristics seen in human patients with liver cancer, which allows for the optimal evaluation of your compound's efficacy.

 

In addition to molecular targeted drugs such as lenvatinib and sorafenib, immune checkpoint inhibitors such as atezolizumab + bevacizumab, nivolumab and pembrolizumab have recently been used clinically to treat HCC.

(Chen C et al, frontiers in Immunology, 14, 1133308, 2023)

 

When evaluating these types of compounds, it is important to be able to assess not only their tumor suppressive effect, but also the immune cells, the cancer microenvironment and the tumor heterogeneity. These are important factors of liver cancer in humans, and can be seen in our model.

 

Below is a table that compares four cancer models and the important differences between them.


As shown in the table, the STAM™-HCC/IO+ model shows an incidence rate of 100% liver cancer within a short period of 16-20 weeks. This allows for the assessment of tumor heterogeneity, the cancer microenvironment and the immune cells.

 

Our research has shown that our STAM™-HCC/IO+ mouse model has a high tumor mutation burden with the following features:

  • Tumor-infiltrating T cells (TILs), CD8+ cytotoxic T cells (CTLs)
  • ICI monotherapy and/or combination therapy
  • Tumor microenvironmental components
  • Changes from baseline [sum of the longest diameters of target lesions]

 

These characteristics are extremely useful when evaluating treatments based on tumor immune control in non-clinical studies, Since our STAM™-HCC/IO+ model has all of the above features, it is currently the most suitable non-clinical liver cancer mouse model for immuno-oncology research(Shalapour S et al, Nature, 551, 340-345, 2017, Dow M et al, PNAS, 115, E9879-E9888, 2018).

 

We are also able to provide any additional information regarding comparisons with cancer models other than those listed above as well as actual data showing the properties of our STAM™-HCC/IO+ model.
If you have any questions or requests for more information, please feel free to contact us.