Investigating the Relationship between Genetics and Patient Response to Immunotherapy


ASPIRE II Award, (2019-Present)

Edison Liu, MD (Principal); Laura Reinholdt, PhD (Co-Principal); Lucas Chang, PhD; Daniel Skelly, PhD, The Jackson Laboratory

Edison Liu, MD

Laura Reinholdt, PhD

Immune checkpoint inhibitors (ICIs) are a class of anti-cancer drugs that increase the ability of the immune system to kill tumor cells. ICIs have significantly expanded the treatment options available to cancer patients, with more than a dozen ICI therapies approved by the FDA over the past 20 years. Despite the remarkable success of these immunotherapies in some patients, the overall response rate is low. Genetic differences between patients are thought to play an important role in determining who will respond to ICI-based therapy. However, scientists do not know exactly which genes contribute, their location within the genome, or how they affect factors such as the relative number of each type of immune cell. Researchers at the Jackson Laboratory are using specially bred mice with known and constant genetic diversity to systematically investigate the relationship between genetics and tumor response to ICI therapy. Using those mice for models of breast, colon, and skin cancer, the team will measure the rates of tumor growth both with and without treatment by an ICI. Genetic sequencing will be used to help identify the location within the genome of variations that affect immune response. To further develop the picture of factors that affect response to ICI therapy in these models, extensive cellular and chemical profiling of tumor and blood will be performed. The team expects that this research will ultimately allow them to determine which heritable traits affect response to ICI treatment. This may one day allow doctors to determine whether ICI therapy is the best course of treatment for individual cancer patients based on their genetic makeup.

PUBLISHED RESEARCH

Mayberry CL, Logan NA, Wilson JJ, Chang CH. Providing a Helping Hand: Metabolic Regulation of T Follicular Helper Cells and Their Association With Disease. Front Immunol. 2022.

Bosenberg M, Liu ET, Yu CI, Palucka K. Mouse models for immuno-oncology. Trends Cancer. 2023.

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