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If  you’ve ever conducted experiments with compounds targeting tumor cells, you likely understand the disappointment of promising results in cell cultures not translating to success in live animal models. This disconnect can be a costly setback in the drug development process, emphasizing the importance of choosing the right models and techniques for preclinical testing.

At The Jackson Laboratory (JAX), our In Vivo Pharmacology Services group has conducted numerous efficacy studies using the JAX Onco-Hu™ Immuno-oncology platform. This platform, which involves co-engrafting human hematopoietic stem cells (HSC) and patient-derived xenografts (PDX) or cancer cell lines into severely immunodeficient mouse strains, has proven to be a valuable tool for testing novel immunotherapies and immune checkpoint inhibitors.

To ensure robust and reliable data from these studies, we have compiled several key tips for maximizing the effectiveness of Onco-Hu™ mice in immuno-oncology drug efficacy studies.

Know Thy Mouse and Pick the “Best” One(s)

Choosing the appropriate mouse model is critical for obtaining meaningful results. Each model serves a unique purpose, so it’s essential to select one that aligns with your study goals. For example, the Onco-Hu™ model can help determine optimal therapy combinations, mechanisms of tumor immune cell evasion, or the responsiveness of different tumor types to an immunotherapy.

Expect Variability in PDX Response and Use It to Your Advantage

PDX models are known for their heterogeneity, reflecting the variability observed in patients. Using multiple PDX samples can provide a more comprehensive understanding of how your compound may perform in different patient populations, potentially improving the predictability of clinical outcomes.

Expect Variability in CD34+ Response and Plan Accordingly

Similarly, CD34+ donors exhibit variability in their response to therapies, mirroring the diversity seen in clinical settings. Using multiple CD34+ donors in your experiments can help mitigate the risk of losing an entire study due to poor planning and provide a more accurate representation of clinical scenarios.

Be Careful: Level of T Cell Infiltration Isn’t Always a Good Predictor of Response

While high levels of T cell infiltration in tumors are often associated with a favorable response to immunotherapy, this isn’t always the case. Some tumors with high T cell infiltration may not respond to checkpoint inhibitors, highlighting the complexity of tumor biology and the need for comprehensive evaluation in preclinical studies.

In conclusion, maximizing the efficacy of immuno-oncology drug development requires careful consideration of the experimental models and techniques used. By understanding the strengths and limitations of these models and incorporating strategies to address variability, researchers can improve the translatability of preclinical data to clinical outcomes, ultimately advancing the field of immuno-

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Explore Immuno-oncology offerings at JAX www.jax.org.

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