Prostate cancer is the second most common cancer in men worldwide and causes over 250,000 deaths each year1. Overtreatment of indolent disease also results in significant morbidity2. Common genetic alterations in prostate cancer include losses of NKX3.1 (8p21)3,4 and PTEN (10q23)5,6, gains of the androgen receptor gene (AR)7,8 and fusion of ETS-family transcription factor genes with androgen-responsive promoters9–11. Recurrent somatic base-pair substitutions are believed to be less contributory in prostate tumorigenesis12,13 but have not been systematically analyzed in large cohorts. Here we sequenced the exomes of 112 prostate tumor/normal pairs. Novel recurrent mutations were identified in multiple genes, including MED12 and FOXA1. SPOP was the most frequently mutated gene, with mutations involving the SPOP substrate binding cleft in 6–15% of tumors across multiple independent cohorts. SPOP-mutant prostate cancers lacked ETS rearrangements and exhibited a distinct pattern of genomic alterations. Thus, SPOP mutations may define a new molecular subtype of prostate cancer.

Genome-wide association studies (GWAS) have identified numerous prostate cancer-associated risk loci. Some variants at these loci may be regulatory and influence expression of nearby genes. Such loci are known as cis-expression quantitative trait loci (cis-eQTL). As cis-eQTLs are highly tissue-specific, we asked if GWAS-identified prostate cancer risk loci are cis-eQTLs in human prostate tumor tissues. We investigated 50 prostate cancer samples for their genotype at 59 prostate cancer riskassociated single-nucleotide polymorphisms (SNPs) and performed cis-eQTL analysis of transcripts from paired primary tumors within two megabase windows. We tested 586 transcript-genotype associations, of which 27 were significant (false discovery rate r10%). An equivalent eQTL analysis of the same prostate cancer risk loci in lymphoblastoid cell lines did not result in any significant associations. The top-ranked cis-eQTL involved the IRX4 (Iroquois homeobox protein 4) transcript and rs12653946, tagged by rs10866528 in our study (P ¼ 4.91 Â 10 À5 ). Replication studies, linkage disequilibrium, and imputation analyses highlight population specificity at this locus. We independently validated IRX4 as a potential prostate cancer risk gene through cis-eQTL analysis of prostate cancer risk variants. Cis-eQTL analysis in relevant tissues, even with a small sample size, can be a powerful method to expedite functional follow-up of GWAS.

Structural variants which cause changes in copy numbers constitute an important component of genomic variability. They account for 0.7% of genomic differences in two individual genomes, of which copy number variants (CNVs) are the largest component. A recent population-based CNV study revealed the need of better characterization of CNVs, especially the small ones (<500 bp).We propose a three step computational framework (Identification of germline Changes in Copy Number or IgC2N) to discover and genotype germline CNVs. First, we detect candidate CNV loci by combining information across multiple samples without imposing restrictions to the number of coverage markers or to the variant size. Secondly, we fine tune the detection of rare variants and infer the putative copy number classes for each locus. Last, for each variant we combine the relative distance between consecutive copy number classes with genetic information in a novel attempt to estimate the reference model bias. This computational approach is applied to genome-wide data from 1250 HapMap individuals. Novel variants were discovered and characterized in terms of size, minor allele frequency, type of polymorphism (gains, losses or both), and mechanism of formation. Using data generated for a subset of individuals by a 42 million marker platform, we validated the majority of the variants with the highest validation rate (66.7%) was for variants of size larger than 1 kb. Finally, we queried transcriptomic data from 129 individuals determined by RNA-sequencing as further validation and to assess the functional role of the new variants. We investigated the possible enrichment for variant's regulatory effect and found that smaller variants (<1 Kb) are more likely to regulate gene transcript than larger variants (p-value = 2.04e-08). Our results support the validity of the computational framework to detect novel variants relevant to disease susceptibility studies and provide evidence of the importance of genetic variants in regulatory network studies.

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Molecular prognostic assays, such as Oncotype DX, are increasingly incorporated into the management of patients with invasive breast carcinoma. BreastPRS is a new molecular assay developed and validated from a meta-analysis of publically available genomic datasets. We applied the assay to matched fresh-frozen (FF) and formalin-fixed paraffin-embedded (FFPE) tumor samples to translate the assay to FFPE. A linear relationship of the BreastPRS prognostic score was observed between tissue preservation formats. BreastPRS recurrence scores were compared with Oncotype DX recurrence scores from 246 patients with invasive breast carcinoma and known Oncotype DX results. Using this series, a 120-gene Oncotype DX approximation algorithm was trained to predict Oncotype DX risk groups and then applied to series of untreated, node-negative, estrogen receptor (ER)-positive patients from previously published studies with known clinical outcomes. Correlation of recurrence score and risk group between Oncotype DX and BreastPRS was statistically significant (P < 0.0001). 59 of 260 (23 %) patients from four previously published studies were classified as intermediate-risk when the 120-gene Oncotype DX approximation algorithm was applied. BreastPRS reclassified the 59 patients into binary risk groups (high- vs. low-risk). 23 (39 %) patients were classified as low-risk and 36 (61 %) as high-risk (P = 0.029, HR: 3.64, 95 % CI: 1.40-9.50). At 10 years from diagnosis, the low-risk group had a 90 % recurrence-free survival (RFS) rate compared to 60 % for the high-risk group. BreastPRS recurrence score is comparable with Oncotype DX and can reclassify Oncotype DX intermediate-risk patients into two groups with significant differences in RFS. Further studies are needed to validate these findings.

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1554 Background: While genome-wide association studies (GWAS) have identified numerous loci at which common single nucleotide polymorphisms (SNPs) are clearly associated with the risk of developing prostate cancer, the mechanism by which these variants influence disease is not clear. Based on the observation that regions of the genome with marks of transcriptional regulatory elements harbor SNPs that are more likely to be under negative selective pressure, we hypothesized that many prostate cancer associated SNPs, or their correlated proxies in linkage disequilibrium, function by altering regulation of nearby genes through alteration of transcription factor binding sites. Two predictions of this hypothesis are that there will be an enrichment of prostate cancer risk SNPs or their proxies in regulatory elements in prostate tissue and that some of these SNPs will correlate with the expression levels of nearby genes. Methods: To test the first prediction, we compared the number of prostate cancer risk SNPs (or their proxies) that overlap with DNase hypersensitive sites in the LNCaP prostate cancer cell line with randomly selected SNPs matched for allele frequency, distance from nearby genes, and local gene density. To test the second prediction, we asked if any of the known prostate cancer risk SNPs are associated with mRNA expression levels of nearby genes. Results: We found a four-fold enrichment of real prostate cancer risk SNPs overlapping with DNase hypersensitive sites versus the random set (p=0.03) at an r2 threshold of 0.95. In both tumor and benign prostate tissue, we found that a recently identified prostate cancer risk SNP is associated with expression levels of IRX4, a transcription factor previously implicated only in cardiac development. Conclusions: These data support the hypothesis that many GWAS-identified risk SNPs alter transcriptional regulation of nearby genes.