PC-SYNERGY Project Summery

Prostate cancer (PC) is the most common noncutaneous malignancy diagnosed in men in the Western world and accounts for nearly 35,000 annual deaths in the United States alone. Unfortunately, the lethal form of PC, metastatic castration-resistant prostate cancer (mCRPC), is uncurable and represents a major healthcare and societal burden. It is clear that therapies do not work equally well across all lesions in a patient. While previous genomic efforts focused on grouping patients by subtypes of mCRPC, it is now clear that the heterogeneity of mCRPC results in multiple subtypes of disease existing within the same patient. This Tactical Proposal represents a first-in-field comprehensive effort to address the heath burden resulting from tumor heterogeneity by acquiring a detailed, quantitative and multidimensional view of tumor and host components. Studying metastases to different organs (liver vs lymph node vs bone) will define biological differences, as well as distinctions in potential therapeutic targets, between tumors at these different sites.

Tumor heterogeneity is more actionable than ever. We will assess heterogeneity at the level of DNA (single cell ATAC-seq), RNA (single cell RNA-seq and spatial transcriptomics) and protein (imaging mass cytometry). This project will establish the next-generation genomic atlas of mCRPC, using single-cell analysis approaches on multiple metastases per mCRPC patient. This program will leverage existing autopsy programs at the University of Washington and Wayne State, as well as matched pre- and post-treatment samples from 21 trials, creating comprehensive portraits of mCRPC that better represent the diverse backgrounds of prostate cancer patients. Given that therapies do not work equally well across each metastasis in a patient, studying metastases at a single cell level will identify biological differences within a single site of cancer as well as between different metastases in the same patient. Such knowledge would allow prioritization of potential therapies based on distribution of disease within a patient, as well as development of rational combination therapy approaches that may enable more effective co-targeting of metastases.