One cell, one cancer: a novel genetic approach to mouse models of human cancer initiation

Utah State Higher Education System--University Of Utah, Salt Lake City UT

Investigators

Abstract

The majority of human cancers arise from single cells, which reside within scattered, sporadic clones of mutant cells that harbor latent oncogenic potential. In the case of pancreatic ductal adenocarcinoma (PDAC), one of the deadliest human cancers, that oncogenic potential is conferred by driver mutations in genes including KRAS, TP53 and CDKN2A. As with many human cancers, genetically engineered mice have been generated to model the initiation and progression of PDAC, based on inducible mutations in these same genes. While highly reproducible and capable of mimicking many fundamental aspects of human PDAC, these models fall short with respect to the one cell-one cancer paradigm, as they develop multiple unique primary cancers that metastasize independently and cooperatively. This reflects the use of genetic models, primarily using the Cre-loxP system, in which oncogenic mutations are induced across the entire organ. This also creates a pro-inflammatory milieu that is not seen in human patients. Attempts to induce more discrete and sporadic mutations, using dose-dependent inducible Cre models, face inherent hurdles based on the biology of recombination, and cannot reliably induce cells with multiple genetic lesions in an otherwise wild-type tissue, as is seen in humans. These problems apply across mouse cancer models, and we propose to solve them for PDAC, using a novel dual- recombinase system termed “FLP-out.” This approach is designed for inducible, dose-dependent irreversible activation of Cre within single cells, which will then delete all copies of any floxed alleles in their genome, as well as become irreversibly marked by fluorescent protein expression. In Aim 1 of this limited, technology-oriented project, we will create the FLP-out mouse using a novel CRISPR-Cas9-based knock-in approach, and in Aim 2 we will validate its function for modeling PDAC initiation. This model will be of considerable use to the PDAC community, and we hope that our methodology will be adopted by researchers modeling other human cancers.