Modeling Tumor Immunology and Immunotherapy in Mice

Area of Science:

• Oncology
• Immunology
• Translational Research

Background:

• Immunodeficient mice xenografted with human cancer cell lines are foundational for drug approval but unsuitable for tumor immunology studies.
• Patient-derived xenografts (PDXs) in immunodeficient mice lack host immunosurveillance, though some transferred immune components may persist.
• Humanized mice and PDXs with patient immune cells are being developed to overcome limitations and aid therapeutic screening.

Purpose of the Study:

• To review the applications and limitations of various mouse models in tumor immunology and immunotherapy research.
• To highlight the importance of selecting appropriate mouse models based on specific research objectives.
• To discuss key features influencing model selection for studying cancer immunity and treatment responses.

Main Methods:

• Comparison of immunodeficient and immunocompetent mouse models, including xenografts, patient-derived xenografts (PDXs), and humanized mice.
• Analysis of carcinogen-driven and transgene-driven tumor models in different host environments.
• Evaluation of key parameters for model selection, such as host immunological competence, tumor mutational load, and microenvironment.

Main Results:

• Immunocompetent syngeneic models are vital for developing immunotherapeutics and understanding chemotherapy/radiation-induced immune responses.
• Carcinogen-driven tumors in immunocompetent hosts reveal natural immunosurveillance and allow evaluation of immunotherapies in complex settings.
• Transgene-driven tumors provide insights into oncogenic driver and tumor microenvironment interactions.

Conclusions:

• The choice of mouse model critically depends on the research question, balancing host immunity, tumor characteristics, and experimental goals.
• Each model offers distinct advantages and disadvantages for studying tumor immunology and immunotherapy.
• Careful consideration of host-pathogen compatibility, tumor mutational burden, and microenvironment is essential for successful research outcomes.