Determining Metastatic Drivers of Pten/p53-Loss-Driven Prostate Cancer Using Evolving DNA Barcodes
Abstract
Prostate cancer (PC) causes approximately 30,000 deaths in the United States each year, almost exclusively resulting from metastases. The substantial decrease in survival rate of metastatic patients underscores the urgency to delineate the changes that drive the transition between primary and specific metastatic sites to ensure optimal therapy for patients before the cancer advances to an incurable stage. Thus, the overarching goal of our research proposal is to define specific genetic vulnerabilities in primary tumors that may enable the interruption of metastases development and potentially target already existing metastases. We have designed a mouse model system (Evolution of Cancer in the Prostate, EvoCaP) that will enable us to detect metastasis-associated genes present in rare but aggressive cell populations. We will induce focal PC that efficiently proceeds toward metastases using the combined double knockout of Pten and Trp53, as previously validated in the RapidCaP model. Loss of Pten and Trp53 causes a robust Myc-dependent cancer phenotype that results in metastasis in up to one-half of mice. Tumorigenesis and metastatic dissemination will be followed using bioluminescence and tumor cells will be identified and sorted using fluorescence. Our EvoCAP model contains a synthetic target array (Barcode) with diminishing gene editing potential that is amenable to alteration by CRISPR/Cas9 technology. Using analysis of Barcode editing by Amplicon Sequencing, we will trace the lineages of metastatic lesions, generate phylogenetic trees, and identify additional potential drivers of metastasis present in these clones and identified upon sequencing the transcriptome and filtering for immune system relevance. Guides against these targets will be generated and used to test the roles of these specific immunomodulatory genes in cancer progression and metastatic dissemination. Detailed exploration of the molecular mechanisms underlying the evolution of metastasis through the use of our model will lead to the identification of metastasis-associated genes previously missed by conventional modeling systems. Successful completion of our project will reveal new therapeutic targets that may be applied to helping patients by treating: (1) primary diseases for early detection and interruption of metastases development, tested by gene knockout modeling and (2) already existing metastases, tested by drug therapy and inducible short hairpin RNA technology. Importantly, our injections-based EvoCaP model system can serve as a cost-effective and efficient tool for probing tumor evolution and metastasis in a wide range of cancer types, giving it a broad applicability and greatly expanding its therapeutic potential. Our goals satisfy two major overarching challenges of this Funding Opportunity Announcement: (1) to define the biology of lethal prostate cancer to reduce death and (2) to develop treatments that improve outcomes for men with lethal prostate cancer. The first challenge will be satisfied by the completion of the project, as understanding the evolutionary history of PC metastasis will allow us to define precise molecular signatures underlying prostate cancer biology and detect genes in rare but aggressive subclones that may potentially drive metastasis by affecting immune response mechanisms. The second challenge will be addressed by novel target identification that our model is uniquely equipped to satisfy by the testing of specific immunomodulating genes for their roles in cancer progression and metastasis. Importantly, we will simultaneously probe both tumor cells and cells in the microenvironmental niche. This may further lead to the identification of clinical therapeutics aimed against drivers of metastasis identified from our project that can be tested in subsequent studies over the following 3-6 years. Completion of this project will satisfy my personal goals of better understanding the biology of
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 28, 2022
- Source ID
- W81XWH2210068
Entities
People
- Ryan Serio
Organizations
- United States Army
- Weill Cornell Medicine