LAUSR

Simple Summary Metastatic prostate cancer (PC) is the second leading cause of cancer deaths in males. The lack of preclinical models and molecular characterization for advanced stage PC is a key barrier in understanding the aggressive subsets androgen receptor (AR) pathway active or AR-null castration-resistant prostate cancers (CRPC). Our study aimed to assess the potential of patient-derived xenograft (PDX) models and an approach integrating proteomic and transcriptomic techniques to explore the underlying drivers of metastatic PC. Transcriptomic and proteomic profiling of 42 PDX prostate tumors uncovered both previously established and unexpected molecular features of aggressive PC subsets. Of these, we confirmed the functional role of mitochondrial metabolism in AR-positive CRPC. Abstract Metastatic prostate cancer (PC) is the second leading cause of cancer deaths in males and has limited therapeutic options. The lack of preclinical models for advanced stage PC represents one of the primary barriers in understanding the key genetic drivers of aggressive subsets, including androgen receptor (AR) pathway active and AR-null castration-resistant prostate cancers (CRPC). In our studies, we described a series of LuCaP patient-derived xenograft (PDX) models representing the major genomic and phenotypic features of human disease. To fully exploit the potential of these preclinical models, we carried out a comprehensive transcriptomic and proteomic profiling of 42 LuCaP PDX prostate tumors. The collected proteomic data (~6000 data points) based on 71 antibodies revealed many of the previously known molecular markers associated with AR-positive and AR-null CRPC. Genomic analysis indicated subtype-specific activation of pathways such as Wnt/beta-catenin signaling, mTOR, and oxidative phosphorylation for AR-positive CRPC and upregulation of carbohydrate metabolism and glucose metabolism for AR-null CRPC. Of these, we functionally confirmed the role of mitochondrial metabolism in AR-positive CRPC cell lines. Our data highlight how the integration of transcriptomic and proteomic approaches and PDX systems as preclinical models can potentially map the connectivity of poorly understood signaling pathways in metastatic prostate cancer.