Finding Genes for Human Prostate Cancer

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Prostate Cancer Studies Prostate Cancer in Men of African Ancestry Although men of African ancestry have a high risk of prostate cancer (PCa), few genes or mutations have been identified that contribute to familial clustering of PCa in this population. This collaboration investigated whether the African ancestry-specific PCa risk variant at 8q24, rs72725854, is enriched in men with a PCa family history in 9052 cases, 143 cases from high-risk families, and 8595 controls of African ancestry. We found the risk allele to be significantly associated with earlier age at diagnosis, more aggressive disease, and enriched in men with a PCa family history (Darst et al., 2020). In men of African ancestry, the relevant variant accounts for 32% of the total familial risk explained by all known PCa risk variants, suggesting that African American men would benefit from guidance about prostate cancer screening and this variant. Prostate Cancer Risk and Prediction In this collaboration the role of DNA methylation in expression quantitative trail loci (eQTL) regulation was investigated (Dai et al., 2020). Specifically, this collaboration identifies and compares eQTLs and CpG methylation quantitative trait loci (meQTLs) among 147 established PrCa risk SNPs in primary prostate tumors (n = 355 from a Seattle-based study and n = 495 from The Cancer Genome Atlas, TCGA) and tumor-adjacent, histologically benign samples (n = 471 from a Mayo Clinic study). The study provides a comprehensive catalog of eQTLs, meQTLs and putative cancer genes for known PCa risk SNPs. We observe that a substantial portion of germline eQTL regulatory mechanisms are maintained in the tumor development, despite somatic alterations in the tumor genome. Finally, our analyses illuminates the likely intermediary role of CpG methylation in eQTL regulation of gene expression. In a separate collaboration (Schaid et al., 2020), we sought to understand the role of family history and more aggressive PCa. A two-stage design was used. In stage one, whole-exome sequencing was used to identify potential risk alleles among affected men with a strong family history of disease or with more aggressive disease (491 cases and 429 controls). Aggressive disease was based on a sum of scores for Gleason score, node status, metastasis, tumor stage, prostate-specific antigen at diagnosis, systemic recurrence, and time to PCa death. Genes identified in stage one were screened in stage two using a custom-capture design in an independent set of 2917 cases and 1899 controls. Frequencies of genetic variants were compared between cases and controls. Eleven genes previously reported to be associated with PCa were detected (ATM, BRCA2, HOXB13, FAM111A, EMSY, HNF1B, KLK3, MSMB, PCAT1, PRSS3, and TERT), as well as an additional 10 novel genes (PABPC1, QK1, FAM114A1, MUC6, MYCBP2, RAPGEF4, RNASEH2B, ULK4, XPO7, and THAP3). This approach demonstrates the advantage of gene sequencing in the search for genetic variants associated with PCa and the benefits of sampling patients with a strong family history of disease or an aggressive form of disease. Metastatic Lethal Prostate Cancer It is well know that, with the exception of Gleason score, few factors accurately identify the subset of prostate cancer (PCa) patients at high risk for metastatic progression (Wang et al., 2020). In this collaboration we tested if copy number alterations (CNAs), assessed using CpG methylation probes could identify primary prostate tumors with potential to develop metastatic progression. The study shows that CNAs can be reliably detected in tumor data. There are 11 recurrent CNAs showing association with metastatic-lethal events following radical prostatectomy, thus improving prediction over Gleason score. Genes affected by these CNAs may functionally relate to tumor aggressiveness and metastatic progression. An additional collaboration investigated if a four gene transcript score could be used to predict metastatic lethal progression in men original treated for localized disease (Cheng et al., 2019). Based on a previously published panel of 23 gene transcripts that distinguished patients with metastatic progression, the collaboration constructed a prediction model using independent training and testing datasets. Thirteen of 23 previously identified gene transcripts that stratified patients with aggressive PCa were validated in the training dataset. These biomarkers plus Gleason Score were used to develop a four-gene (CST2, FBLN1, TNFRSF19, and ZNF704) transcript (4GT) score that was significantly higher in patients who progressed to metastatic-lethal disease compared to those without recurrence. In aggregate, these studies show a role for transcript score in predicting which men originally treated for relatively moderate disease, will go on to get metastatic disease.