Determining Dendritic Cell Responses to Vaccine-based Immunotherapy in PDAC at Single Cell Resolution.

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Project Summary Pancreatic ductal adenocarcinoma (PDAC), a traditionally non-immunogenic tumor type, has shown limited beneficial response to immunotherapy. We were the first to demonstrate that it is possible to convert PDAC to an immunogenic state following GM-CSF-secreting allogeneic vaccine (GVAX) treatment which promotes Dendritic Cell (DC) precursor expansion and formation of tertiary lymphoid aggregates (TLAs). However, immune regulatory mechanisms are preventing any significant clinical benefit. DC paucity gives rise to dysfunctional immune surveillance and can establish an immunosuppressive TME in PDAC that prevents lymphoid cell activation and immune invasion. With recently emerged single cell and spatial omics, we now have the ability to study cancer immunology at unprecedented scale and resolution. We propose to generate single cell and spatial transcriptomic and proteomic data to study systemic responses and local immunological activities in vaccine primed PDAC. Specifically, we hypothesize that DC state transitions and interactions with other TME cell types can delineate immunologic responses to immunotherapies in vaccine primed PDAC. To address this hypothesis, we propose two specific aims. We will first determine the distinct immunologic effects of vaccine and immune checkpoint inhibition combination regimens on peripheral DC state transitions in PDAC patients (Aim 1). To accomplish this we will develop a novel single cell proteomic trajectory analysis pipeline that computes cell phenotypes using continuous variables. This will allow us to study phenotypic transitions using unsupervised approaches that are less discernible in discrete cell type analyses (technological sub-aim). We will then apply our pipeline on DCs by implementing mass cytometry to capture DC state transitions in peripheral blood mononuclear cells (PBMCs) from vaccine clinical trials by assessing baseline and on-treatment samples (biological sub-aim). To delineate spatial factors influencing the immune dynamics of TLA formation after vaccine priming, we will evaluate the role of DCs in the formation and regulation of lymphoid aggregates in PDAC (Aim 2). To achieve this, we will spatially resolve TLAs in vaccine (GVAX) primed human PDAC tumors at the RNA and protein levels using Visium spatial transcriptomics and imaging mass cytometry (IMC). We will employ matrix factorization methods to learn gene and protein expression patterns in both of the spatial data modalities to discern gene expression patterns unique to TLAs and evaluate their expression of DC markers. By understanding DC state transitions directly within the TME, the findings from this Aim will synergize with Aim 1. Completion of these aims will deliver potential new immunotherapy strategies in PDAC patients, as well as develop novel open-source software for mass cytometry analysis. The skills I obtain from this work will prepare me to pursue a career as a cross-trained cancer immunologist and computational biologist, delineating immune responses to empower precision immunotherapy.