Determinants of toxicity and response to immune checkpoint blockade through integrative profiling of T cell clonal dynamics and plasma cell- free DNA

PROJECT SUMMARY Severe immune-related adverse events (irAEs) occur in up to ~60% of melanoma patients treated with combination (anti-PD1 / anti-CTLA4) immune checkpoint inhibitors (ICIs), and cause treatment- related morbidity and mortality. However, the pathophysiology underlying severe irAE development remains unclear and there is no way in clinical practice to predict who will develop severe toxicities and who will not. Based on our preliminary data, we hypothesize that clonally diverse activated CD4 memory T cells, and more specifically CXCR5–PD1hi peripheral helper T (Tph) cells, specifically underpin ICI-mediated toxicity in melanoma patients. To address this hypothesis, we will perform flow cytometry, CyTOF, scRNA-seq, scV(D)J-seq and immunoSEQ® to broadly assess T and B cell states in peripheral blood to 1) determine whether Tph levels in pretreatment blood are predictive of severe irAE development in melanoma patients treated with combination immunotherapy (Aim 1), and 2) determine whether Tph clonotypes preferentially expand in on-treatment blood and are enriched in irAE skin lesions during combination immunotherapy in patients who develop severe toxicity (Aim 2). While the prediction of severe irAEs from peripheral blood will be important clinically, patients who experience some degree of toxicity have also been shown to have better durable immunotherapy response rates. Therefore, it will be challenging to make clinical decisions regarding immunotherapy without also considering the probability of durable response. We will thus utilize cell-free DNA methylation sequencing to predict 1) immunotherapy toxicity and 2) durable immunotherapy response concurrently from pre-treatment plasma using both cell-state signatures and an agnostic machine learning approach, which we will validate in held-out cohorts (Aim 3). By doing so, we will lay the foundation for future clinical trials where immunotherapy decision-making is guided by the risk versus benefit of combination immunotherapy using the liquid biopsy biomarkers defined here. In summary, this study will reveal determinants of irAE development which will form the basis for liquid biopsy technology to predict both immunotherapy response and toxicity to make treatment safer and more personalized in the future.