We are continuing to make progress in our goal of defining germline modifiers of tumor progression and metastasis in prostate cancer. First, we are utilizing the well characterized C57BL/6-Tg(TRAMP)8247Ng/J (TRAMP) mouse model of aggressive neuroendocrine prostate cancer to investigate the role of hereditary factors in the development of aggressive disease with associated neuroendocrine differentiation (NED). Our earlier work conclusively proved that the introduction of germline polymorphism into this model by breeding significantly modulates tumor progression and metastasis. Specifically, by crossing TRAMP mice to the eight progenitor strains of the Collaborative Cross (CC) recombinant inbred panel we observed profound differences in tumor burden and metastasis frequencies in several TRAMP x CC progenitor F1 strains. In the last year, we have continued to use a modifier mapping approach to identify loci driving susceptibility to aggressive disease development in the TRAMP mouse model. Our approach centers on generating F2 intercross mapping populations using the TRAMP mouse and those CC progenitor strains that displayed the greatest phenotypic variation at the F1 generation. Additionally, we are performing high resolution mapping using TRAMP x Diversity Outbred (DO) F1 males. Regarding our TRAMP x CC progenitor F2 intercross experiments, three strains were chosen for these analyses: NOD/ShiLtJ, PWK/PhJ and WSB/EiJ. We have identified multiple loci driving susceptibility to aggressive disease development in these three crosses. However, the majority of our efforts to identify candidate modifier genes have focused on the TRAMP x NOD/ShiLtJ F2 cross. QTL mapping was performed in transgene-positive TRAMP x NOD/ShiLtJ F2 intercross males (n = 228), which facilitated identification of 11 loci associated with aggressive disease development. Microarray data derived from 126 (TRAMP x NOD/ShiLtJ) F2 primary tumors were used to prioritize candidate genes within pQTLs, with candidate genes deemed as being high priority when possessing both high levels of expression-trait correlation and a cis-expression QTL. This process enabled the identification of 27 aggressive prostate tumorigenesis candidate genes. The role of these genes in aggressive forms of human prostate cancer was investigated using two concurrent approaches. First, expression levels of two subsets of these genes, both of which included AKIRIN2, GZF1, HIST1H1A, and NSFL1C were consistently associated with patient outcome in human prostate cancer tumor gene expression datasets. Second, each of these four genes harbored polymorphisms associated with aggressive disease development in a human genome-wide association study (GWAS) cohort consisting of 1,172 prostate cancer patients. This study is the first example of using a systems genetics approach to successfully identify novel susceptibility genes for aggressive prostate cancer. Functional analysis of the four candidate genes identified in this study is currently ongoing in prostate cancer cell lines. A similar approach using data derived from the TRAMP x PWK/PhJ F2 intercross population has allowed for the identification of six novel germline metastasis susceptibility genes. As with the TRAMP x NOD/ShiLtJ F2 intercross, the role of each of these genes is being examined in aggressive human prostate cancer through a combination of expression profiling in human prostate tumors and analysis of human prostate cancer GWAS datasets. Functional analysis of these genes in prostate cancer cell lines is also ongoing. Finally, these F2 intercross experiments are complemented by our TRAMP x DO F1 cross, which utilizes the highly genetically diverse DO heterogeneous stock mapping population. Breeding, aging and phenotyping of a population of approximately 300 of these mice has been completed within the last year. Preliminary QTL analyses have identified multiple novel loci associated with aggressive disease development.
We aim to prioritize candidate genes initially through expression profiling of TRAMP x DO F1 tumors. Additionally, we will continue to accrue F1 mice in order to increase statistical power and identify modifiers that modulate prostate cancer aggressiveness through mechanisms unrelated to gene expression.
