Project Summary Pancreatic cancer arises from precancerous lesions that are curable if detected and treated early enough. Recent multi-region genomic analyses of one type of precancerous pancreatic lesion, intraductal papillary mucinous neoplasm (IPMN), suggest unique evolutionary and selective pressures in IPMNs compared to invasive cancers, underscoring the potential importance of selection in the progression of precancerous lesions. We propose to characterize the role of selective forces in IPMNs using comprehensive molecular analyses and computational data integration of both human IPMN tissue samples and organoid cultures. We will determine the molecular features of progressed subclones in human IPMN samples using multi-region whole genome sequencing and RNA-sequencing. In addition, we will develop and apply novel multi-omics computational methods to integrate DNA and RNA-sequencing data to delineate selective forces in human IPMNs. We will determine the function of progressed clones identified by whole genome DNA sequencing with gene signatures inferred from bulk transcriptional data in a new semi-supervised framework. We will then employ a three-dimensional in vitro organoid culture model of human IPMN cells to characterize the relative contributions of selective pressures over time. We will use combined DNA sequencing and single-cell RNA- sequencing to identify gene expression signatures of progressed subclones in our organoid model, further adapting our computational framework to single cell RNA-sequencing data. Taken together, the proposed studies combine direct analysis of human tissue samples and manipulation of human precancerous cells in three-dimensional culture with novel multi-omics computational integration to greatly expand our knowledge of the role of selection in pancreatic cancer precursor lesions.

Project Narrative Although pancreatic cancer is a deadly disease with a dismal prognosis, it arises through non-invasive precursor lesions that are curable if detected early enough. The goal of this project is to characterize the role of selective forces in the evolution of precancerous pancreatic neoplasms using genomic and transcriptomic analysis of human tissue samples and three-dimensional cultures, followed by novel computational approaches for data integration. The results will provide critical insights into premalignant pancreatic tumorigenesis, providing a rational foundation for the development of early detection and prevention approaches.