Understanding the History of Mutations and Cancer Cells
Understanding the history of mutations that transform a normal cell to a cancer cell can have profound impact on early detection of tumors and optimizing for more effective treatments for patients. This team has previously shown that chromatin accessibility of originating normal tissue shapes the landscape of passenger mutations in eight tumor types.
This project will leverage single-cell resolution openly available chromatin data from more than 220 cell types and whole genome sequencing from over 6,450 patients to more comprehensively and accurately model the link between cell-of-origin chromatin accessibility and passenger mutation footprints. The team will develop a probabilistic model to decompose the contribution of different cell type epigenomes to the observed passenger mutations landscape and apply this model to assess the contribution of acinar, ductal, and other unexpected cell types to the origin of pancreatic ductal adenocarcinoma.
This framework and analysis will be extended to predict the cell-of-origin across 38 tumor types, including histological and molecular subtypes that are thought to derive from different normal cell types, as well as rare cancers with unknown origins. This project anticipates that this work will establish improved tools for learning the history of cancer progression and deepen our understanding of the cells-of-origin across multiple cancer types that can ultimately improve clinical management and treatment for patients.