Immune checkpoint therapy (ICT) is a front-line treatment for lung cancer; however, low mutational burden and ‘non-T cell inflamed’ signatures predict poor responses to ICT in ~50% of patients. Adoptive cellular therapy (ACT) with T cells engineered to express T cell receptors (TCRs) specific for tumor-associated antigens (TAAs; proteins overexpressed by cancers) is an approach that circumvents the need for endogenous T cell responses. TCR-ACT is effective against hematologic cancers, but ACT against solid tumors is in the early stages of exploration. A deeper understanding of complex interactions between therapeutic cells and the tumor microenvironment (TME) is crucial for identifying successful strategies to enhance function and mitigate toxicity. Genetically engineered mouse models (GEMMs) achieve in situ tumor development alongside competent immune systems, recapitulating the native TME over the full spectrum of disease progression in a preclinical setting. Kras and p53 mutant (KP) GEMM lung tumors harbor few mutations, are poorly infiltrated by T cells, and are refractory to ICT, modeling intractable patient disease. We show that TAA-specific T cells recognize KP lung cancer cells and efficiently home to tumors, but rapidly lose function in the lung TME (compared to KP pancreatic tumors). Repetitive TCR-ACT can extend survival of animals with lung tumors, but animals eventually succumb to disease. These results show promise for TCR-ACT against lung cancer but highlight tissue-specific obstacles that must be overcome to enhance efficacy. We are continuing to leverage these models to advance our understanding of tissue-specific effects on therapeutic outcomes, and strategies to improve them. These findings offer inroads to uncovering more effective therapies, with the ultimate goal of benefitting cancer patients.
1. Define engineered T cell therapy and its potential utility in checkpoint inhibitor-recalcitrant tumor settings.
2. Understand the advantages (and disadvantages) of using genetically engineered preclinical models for studying tumor immunotherapy.
3. Learn about tissue specific factors that can contribute to suppression of anti-tumor T cell responses.