ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) is characterized by exceedingly high rates of metastatic progression, with the liver representing the most common site of distant spread. Here, we established a platform for multisite immune profiling of human PDAC encompassing the tumor, peripheral circulation, and premetastatic liver, to more comprehensively study how various immune subsets might contribute to patient outcomes. METHODS: Tumor, liver, and blood samples were obtained from patients undergoing resection for non-metastatic PDAC. Derived immune cells underwent paired single-cell RNA and TCR sequencing. Immune composition, cell type functional profiles, and T cell clonal expansion patterns were evaluated across tissue sites. RESULTS: In total, 106,539 immune cells were sequenced, of which 85,748 met criteria for analysis. We identified 32 cell populations, of which seven demonstrated significant enrichment within a particular tissue. Functional profiling revealed tissue-specific differences in cell phenotypes. This included terminally differentiated exhausted CD8 T cells within the tumor, highly active Tregs within the premetastatic liver and tumor, and M1 versus M2 polarization of liver and tumor macrophage populations, respectively. Clonal expansion of T cells was greatest in the liver, which comprised predominantly mature CD8 T cells and MAIT cells. Within the tumor, expanded Treg clones were uniquely abundant, and while expanded clones could be tracked to the blood and premetastatic liver, many of these mapped back to known viral antigens. Leveraging previously validated gene sets, we predicted the tumor reactivity of intratumoral T cells using transcriptional signatures. We demonstrated a high degree of concordance between multiple independent signatures and tracked high-priority TCRs within the blood and liver. CONCLUSION: This study provides a platform, which has already been implemented into ongoing clinical protocols, for immune profiling of human PDAC across the sites most relevant to metastatic progression. Future applications of this work can monitor immune populations throughout metastatic progression to build a temporal database of immune phenotypes and track association with clinical outcomes.
