Abstract

Abstract The primary metastatic site of prostate cancer is the bone, which is associated with high morbidity and mortality. Despite this fact, very few genetically engineered mouse models recapitulate this phenotype, hindering our ability to model and understand the molecular drivers of bone metastasis. Our laboratory has generated a highly metastatic mouse model of castration-resistant prostate cancer based on the monoallelic loss of function of Nkx3.1, biallelic deletion of Pten, and oncogenic mutation of Kras in the prostate, termed the NPK model. By tracking these tumors with a bright fluorescent reporter, we now show that these tumors metastasize to bone with a penetrance of ~45% and display a bone distribution similar to that of human cancer. This model has thus allowed us to comprehensively profile the molecular alterations of bone metastatic lesions compared to the primary tumor and other metastatic sites. We found that differential gene expression profiles comparing bone metastases with primary tumors differ from those comparing lung metastases with primary tumors, suggesting that different biologic principles underlie metastasis to these two organ sites. Furthermore, gene-expression profiling demonstrated significant overlap with human bone metastases at the gene, master regulator, and pathway levels. Even though expression of the androgen receptor (AR) is maintained in the primary tumor and most lung metastases, bone lesions are AR-, without evidence of neuroendocrine (NE) differentiation, pointing to an AR-, NE- prostate cancer subtype, which is increasingly frequent in human prostate cancer. These results lay the groundwork for understanding the molecular drivers and pathways that are important for bone metastatic spread and may hopefully aid in selecting appropriate molecular targets to combat the metastatic disease. Citation Format: Juan Martin Arriaga, Cory Abate-Shen. A genetically engineered mouse model of de novo bone metastasis [abstract]. In: Proceedings of the AACR Special Conference: Advances in Modeling Cancer in Mice: Technology, Biology, and Beyond; 2017 Sep 24-27; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(10 Suppl):Abstract nr B01.

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