Le Forum, Vol. 41 No. 1

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The Molecular Taxonomy of Primary Prostate Cancer

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, and FLI1) or mutations (SPOP, FOXA1, and 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 defectsclose

Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines

The Cancer Genome Atlas (TCGA) cancer genomicsdataset includes over 10,000 tumor-normal exomepairs across 33 different cancer types, in total >400TB of raw data files requiring analysis. Here wedescribe the Multi-Center Mutation Calling in Multi-ple Cancers project, our effort to generate a compre-hensive encyclopedia of somatic mutation calls forthe TCGA data to enable robust cross-tumor-typeanalyses. Our approach accounts for varianceand batch effects introduced by the rapid advance-ment of DNA extraction, hybridization-capture,sequencing, and analysis methods over time. Wepresent best practices for applying an ensemble ofseven mutation-calling algorithms with scoring andartifact filtering. The dataset created by this analysisincludes 3.5 million somatic variants and forms thebasis for PanCan Atlas papers. The results havebeen made available to the research communityalong with the methods used to generate them.This project is the result of collaboration from a num-ber of institutes and demonstrates how team sciencedrives extremely large genomics projects