PROJECT SUMMARY/ABSTRACT Pancreatic Ductal Adenocarcinoma (PDAC) is on track to become the second leading cause of cancer related deaths in the United States. This dismal prognosis is in large part due to >80% of newly diagnosed cases being advanced in stage. For the rare patients diagnosed early, stage I, the 5-year survival rate reaches over 80%. Thus, for PDAC the mortality rates can be greatly impacted by the development of an earlier detection strategy. Even though PDAC is a major health issue, there are still no effective screening tests approved for the general population and only patients with family history and/or the presence of a pathogenic germline variants (PGVs) in relevant high-risk genes, referred to as high-risk individuals (HRIs), have published guidelines recommending cancer surveillance. PDAC arises predominantly from microscopic Pancreatic Intraepithelial Neoplasms (PanIN) lesions categorized based on their morphological features as low-grade (LG), which are common and have a very low probability of malignant transformation, or high-grade (HG), which are rare and are considered to be of high risk for progression to invasive carcinoma, but the diverse routes of progression from LG to HG PanIN are poorly understood. We hypothesize that the development of a comprehensive, molecular and cellular 3D atlas that depicts the key events in the progression of PanIN to PDAC will be the first step in identifying much needed early detection and interception strategies. Importantly, our pre-cancer atlas will focus on a common subset of HRI patients in surveillance programs who carry PGVs in canonical DNA repair genes, BRCA1, BRCA2 or PALB2 (referred to as gBRCA). This genetic subtype creates a genomic instability state that supports PDAC development, yet the exact mechanisms are unclear. Through deep genetics and three-dimensional spatial multi- omics mapping with computational modeling, we propose to create a 4D model of the molecular and cellular trajectories that underly the evolution of gBRCA-driven LG to HG PanINs to malignant PDAC through three integrated aims: 1) to design a gBRCA progression atlas; 2) to determine mechanisms underlying progression; and 3) to forecast progression toward translational impact, supported by three functional units: i) Biospecimen Unit: to collect, process and annotate biospecimens, ii) Characterization Unit: to perform molecular, cellular and spatial characterization, and iii) Data Science Unit: to process, analyze, computationally model and visualize data. We have assembled an exceptional team of experts (the BRCA Forecasting PDAC, BForePC team), with complimentary, multi-disciplinary expertise in PDAC clinical pathology, computational biology and model development, BRCA deficiency and DNA repair, cancer genetics, and tumor microenvironment, along with cutting edge technology experts. We are uniting three universities, Oregon Health & Science University, Johns Hopkins University, and Indiana University, all with strong ties to the PDAC research community, the HTAN, and multiple NCI consortia. Together, we will leverage the atlas for translational detection and interception use cases poised for clinical evaluation in HRIs and to inform future studies extending to all PDAC.

PROJECT NARRATIVE The dismal prognosis of pancreatic adenocarcinoma (PDAC) is in large part due to >80% of newly diagnosed cases being advanced in stage. Therefore, a better understanding of the progression of PDAC could inform earlier detection and interception strategies for PDAC. Herein, we will use a multi-disciplinary approach (the BForePC Team) to develop a 3D model of PDAC progression, focusing on a unique High-Risk population who carry mutations in relevant DNA repair genes (BRCA1, BRCA2, PALB2), as a first step, to understanding this heterogenous, complex devastating disease.