Andrey Sivachenko

Exome sequencing identifies recurrent SPOP, FOXA1 and MED12 mutations in prostate cancer

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 factor genes with androgen-responsive promoters. Recurrent somatic base-pair substitutions are believed to be less contributory in prostate tumorigenesis but have not been systematically analyzed in large cohorts. Here, we sequenced the exomes of 112 prostate tumor and normal tissue pairs. New 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. Prostate cancers with mutant SPOP lacked ETS family gene rearrangements and showed a distinct pattern of genomic alterations. Thus, SPOP mutations may define a new molecular subtype of prostate cancer.

Integrative and Comparative Genomic Analysis of Lung Squamous Cell Carcinomas in East Asian Patients

PURPOSEnLung squamous cell carcinoma (SCC) is the second most prevalent type of lung cancer. Currently, no targeted therapeutics are approved for treatment of this cancer, largely because of a lack of systematic understanding of the molecular pathogenesis of the disease. To identify therapeutic targets and perform comparative analyses of lung SCC, we probed somatic genome alterations of lung SCC by using samples from Korean patients.nnnPATIENTS AND METHODSnWe performed whole-exome sequencing of DNA from 104 lung SCC samples from Korean patients and matched normal DNA. In addition, copy-number analysis and transcriptome analysis were conducted for a subset of these samples. Clinical association with cancer-specific somatic alterations was investigated.nnnRESULTSnThis cancer cohort is characterized by a high mutational burden with an average of 261 somatic exonic mutations per tumor and a mutational spectrum showing a signature of exposure to cigarette smoke. Seven genes demonstrated statistical enrichment for mutation: TP53, RB1, PTEN, NFE2L2, KEAP1, MLL2, and PIK3CA). Comparative analysis between Korean and North American lung SCC samples demonstrated a similar spectrum of alterations in these two populations in contrast to the differences seen in lung adenocarcinoma. We also uncovered recurrent occurrence of therapeutically actionable FGFR3-TACC3 fusion in lung SCC.nnnCONCLUSIONnThese findings provide new steps toward the identification of genomic target candidates for precision medicine in lung SCC, a disease with significant unmet medical needs.

A Pan-Cancer Analysis of Transcriptome Changes Associated with Somatic Mutations in U2AF1 Reveals Commonly Altered Splicing Events

Although recurrent somatic mutations in the splicing factor U2AF1 (also known as U2AF35) have been identified in multiple cancer types, the effects of these mutations on the cancer transcriptome have yet to be fully elucidated. Here, we identified splicing alterations associated with U2AF1 mutations across distinct cancers using DNA and RNA sequencing data from The Cancer Genome Atlas (TCGA). Using RNA-Seq data from 182 lung adenocarcinomas and 167 acute myeloid leukemias (AML), in which U2AF1 is somatically mutated in 3–4% of cases, we identified 131 and 369 splicing alterations, respectively, that were significantly associated with U2AF1 mutation. Of these, 30 splicing alterations were statistically significant in both lung adenocarcinoma and AML, including three genes in the Cancer Gene Census, CTNNB1, CHCHD7, and PICALM. Cell line experiments expressing U2AF1 S34F in HeLa cells and in 293T cells provide further support that these altered splicing events are caused by U2AF1 mutation. Consistent with the function of U2AF1 in 3′ splice site recognition, we found that S34F/Y mutations cause preferences for CAG over UAG 3′ splice site sequences. This report demonstrates consistent effects of U2AF1 mutation on splicing in distinct cancer cell types.

PRADA: pipeline for RNA sequencing data analysis

SUMMARYnTechnological advances in high-throughput sequencing necessitate improved computational tools for processing and analyzing large-scale datasets in a systematic automated manner. For that purpose, we have developed PRADA (Pipeline for RNA-Sequencing Data Analysis), a flexible, modular and highly scalable software platform that provides many different types of information available by multifaceted analysis starting from raw paired-end RNA-seq data: gene expression levels, quality metrics, detection of unsupervised and supervised fusion transcripts, detection of intragenic fusion variants, homology scores and fusion frame classification. PRADA uses a dual-mapping strategy that increases sensitivity and refines the analytical endpoints. PRADA has been used extensively and successfully in the glioblastoma and renal clear cell projects of The Cancer Genome Atlas program.nnnAVAILABILITY AND IMPLEMENTATIONnhttp://sourceforge.net/projects/prada/nnnCONTACTnu2003gadgetz@broadinstitute.org or rverhaak@mdanderson.orgnnnSUPPLEMENTARY INFORMATIONnu2003Supplementary data are available at Bioinformatics online.

Massively parallel sequencing of human urinary exosome/microvesicle RNA reveals a predominance of non-coding RNA.

Intact RNA from exosomes/microvesicles (collectively referred to as microvesicles) has sparked much interest as potential biomarkers for the non-invasive analysis of disease. Here we use the Illumina Genome Analyzer to determine the comprehensive array of nucleic acid reads present in urinary microvesicles. Extraneous nucleic acids were digested using RNase and DNase treatment and the microvesicle inner nucleic acid cargo was analyzed with and without DNase digestion to examine both DNA and RNA sequences contained in microvesicles. Results revealed that a substantial proportion (∼87%) of reads aligned to ribosomal RNA. Of the non-ribosomal RNA sequences, ∼60% aligned to non-coding RNA and repeat sequences including LINE, SINE, satellite repeats, and RNA repeats (tRNA, snRNA, scRNA and srpRNA). The remaining ∼40% of non-ribosomal RNA reads aligned to protein coding genes and splice sites encompassing approximately 13,500 of the known 21,892 protein coding genes of the human genome. Analysis of protein coding genes specific to the renal and genitourinary tract revealed that complete segments of the renal nephron and collecting duct as well as genes indicative of the bladder and prostate could be identified. This study reveals that the entire genitourinary system may be mapped using microvesicle transcript analysis and that the majority of non-ribosomal RNA sequences contained in microvesicles is potentially functional non-coding RNA, which play an emerging role in cell regulation.