Immunotherapy has changed the landscape of oncology, improving survival rates for many patients across a variety of malignancies. Two antibody-based immunotherapies, immune checkpoint inhibitors (ICI) and targeted immunotherapy, are among the most successful clinical modalities. However, response rates remain incomplete with many patients exhibiting primary or acquired resistance. Our studies have identified host genetics as a contributor to response variation. Most preclinical research utilizes inbred mouse models, which fail to recapitulate the genetic diversity of humans. We have developed a unique approach utilizing F1 crosses of inbred mice with the genetically heterogeneous Diversity Outbred (DO) and Collaborative Cross (CC) mouse models, producing cohorts of mice with variable genetics that reliably accept tumor lines syngeneic to the inbred strain. In both ICI and targeted immunotherapy studies, we show that germline genetics influence anti-tumor immunity and response to immunotherapy against genetically identical tumors. Genetic linkage analysis pinpoints genomic loci that associate with response, revealing candidate causal genes. These loci are then validated in CC F1 models where the CC mice are selected for positive or negative driver genetics at our loci of interest. Single-cell RNA sequencing (scRNAseq) of tumor immune infiltrates is used to evaluate expression patterns of genes in each locus. Comparison to publicly available human scRNAseq datasets indicates similar expression patterns, supporting the translational potential of our findings. Additional work is underway to determine if our candidate genes/pathways contribute to cancer disparities. Collectively, our goal is to unveil novel actionable targets to improve immunotherapy outcomes, and to discover key biomarkers to guide clinical decision-making.

Learning Objectives:

• Discuss the role of host genetics in cancer immunotherapy
• Introduce new candidate mechanisms of cancer immunotherapy resistance
• Consider the choice of animal models for cancer immunology research