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.
