Summary There is substantial heterogeneity among primary prostate cancers, evident in the spectrum of molecular abnormalities and its variable clinical course. As part of The Cancer Genome Atlas (TCGA), we present a comprehensive molecular analysis of 333 primary prostate carcinomas. Our results revealed a molecular taxonomy in which 74% of these tumors fell into one of seven subtypes defined by specific gene fusions (ERG, ETV1/4, FLI1) or mutations (SPOP, FOXA1, IDH1). Epigenetic profiles showed substantial heterogeneity, including an IDH1-mutant subset with a methylator phenotype. Androgen receptor (AR) activity varied widely and in a subtype-specific manner with SPOP and FOXA1 mutant tumors having the highest levels of AR-induced transcripts. 25% of the prostate cancers had a presumed actionable lesion in the PI3K or MAPK signaling pathways, and DNA repair genes were inactivated in 19%. Our analysis reveals molecular heterogeneity among primary prostate cancers, as well as potentially actionable molecular defects.

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Copy number variation (CNV) is a prevalent form of critical genetic variation that leads to an abnormal number of copies of large genomic regions in a cell. Microarray-based comparative genome hybridization (arrayCGH) or genotyping arrays have been standard technologies to detect large regions subject to copy number changes in genomes until most recently high-resolution sequence data can be analyzed by next-generation sequencing (NGS). During the last several years, NGS-based analysis has been widely applied to identify CNVs in both healthy and diseased individuals. Correspondingly, the strong demand for NGS-based CNV analyses has fuelled development of numerous computational methods and tools for CNV detection. In this article, we review the recent advances in computational methods pertaining to CNV detection using whole genome and whole exome sequencing data. Additionally, we discuss their strengths and weaknesses and suggest directions for future development.

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Purpose Salivary duct carcinoma (SDC) is an aggressive salivary malignancy which is resistant to chemotherapy and has high mortality rates. We investigated the molecular landscape of SDC, focusing on genetic alterations and gene expression profiles. Experimental Design We performed whole-exome sequencing, RNA sequencing and immunohistochemical analyses in 16 SDC tumors, and examined selected alterations via targeted sequencing of 410 genes in a second cohort of 15 SDCs. Results SDCs harbored a higher mutational burden than many other salivary carcinomas (1.7 mutations/megabase). The most frequent genetic alterations were mutations in TP53 (55%), HRAS (23%), PIK3CA (23%), and amplification of ERBB2 (35%). Most (74%) tumors had alterations in either MAP kinase (BRAF/HRAS/NF1) genes or ERBB2. Potentially targetable alterations based on supportive clinical evidence were present in 61% of tumors. Androgen receptor (AR) was overexpressed in 75%; several potential resistance mechanisms to androgen deprivation therapy (ADT) were identified, including the AR-V7 splice variant (present in 50%, often at low ratios compared to full length AR) and FOXA1 mutations (10%). Consensus clustering and pathway analyses in transcriptome data revealed striking similarities between SDC and molecular apocrine breast cancer. Conclusions This study illuminates the landscape of genetic alterations and gene expression programs in SDC, identifying numerous molecular targets and potential determinants of response to AR antagonism. This has relevance for emerging clinical studies of ADT and other targeted therapies in SDC. The similarities between SDC and apocrine breast cancer indicate that clinical data in breast cancer may generate useful hypotheses for SDC.