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Comprehensive knowledge of the genomic alterations that underlie cancer is a critical foundation for diagnostics, prognostics, and targeted therapeutics. Systematic efforts to analyze cancer genomes are underway, but the analysis is hampered by the lack of a statistical framework to distinguish meaningful events from random background aberrations. Here we(More)
A powerful way to discover key genes with causal roles in oncogenesis is to identify genomic regions that undergo frequent alteration in human cancers. Here we present high-resolution analyses of somatic copy-number alterations (SCNAs) from 3,131 cancer specimens, belonging largely to 26 histological types. We identify 158 regions of focal SCNA that are(More)
Prostate cancer is the second most common cause of male cancer deaths in the United States. However, the full range of prostate cancer genomic alterations is incompletely characterized. Here we present the complete sequence of seven primary human prostate cancers and their paired normal counterparts. Several tumours contained complex chains of balanced(More)
Prostate cancer is the second most common cancer in men worldwide and causes over 250,000 deaths each year. Overtreatment of indolent disease also results in significant morbidity. Common genetic alterations in prostate cancer include losses of NKX3.1 (8p21) and PTEN (10q23), gains of AR (the androgen receptor gene) and fusion of ETS family transcription(More)
We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts, such as misalignment or random pairing of transcript fragments, and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint(More)
BACKGROUND Current prostate cancer prognostic models are based on pre-treatment prostate specific antigen (PSA) levels, biopsy Gleason score, and clinical staging but in practice are inadequate to accurately predict disease progression. Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might(More)
The analysis of exonic DNA from prostate cancers has identified recurrently mutated genes, but the spectrum of genome-wide alterations has not been profiled extensively in this disease. We sequenced the genomes of 57 prostate tumors and matched normal tissues to characterize somatic alterations and to study how they accumulate during oncogenesis and(More)
Microarrays have been used to identify genes involved in cancer progression. We have now developed an algorithm that identifies dysregulated pathways from multiple expression array data sets without a priori definition of gene expression thresholds. Integrative microarray analysis of pathways (IMAP) was done using existing expression array data from(More)
A step toward the molecular classification of prostate cancer was the discovery of recurrent erythroblast transformation-specific rearrangements, most commonly fusing the androgen-regulated TMPRSS2 promoter to ERG. The TMPRSS2-ERG fusion is observed in around 90% of tumors that overexpress the oncogene ERG. The goal of the current study was to complete the(More)
Toward development of a precision medicine framework for metastatic, castration-resistant prostate cancer (mCRPC), we established a multi-institutional clinical sequencing infrastructure to conduct prospective whole-exome and transcriptome sequencing of bone or soft tissue tumor biopsies from a cohort of 150 mCRPC affected individuals. Aberrations of AR,(More)