Summary We analyzed primary breast cancers by genomic DNA copy number arrays, DNA methylation, exome sequencing, mRNA arrays, microRNA sequencing and reverse phase protein arrays. Our ability to integrate information across platforms provided key insights into previously-defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity. Somatic mutations in only three genes (TP53, PIK3CA and GATA3) occurred at > 10% incidence across all breast cancers; however, there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3, PIK3CA and MAP3K1 with the Luminal A subtype. We identified two novel protein expression-defined subgroups, possibly contributed by stromal/microenvironmental elements, and integrated analyses identified specific signaling pathways dominant in each molecular subtype including a HER2/p-HER2/HER1/p-HER1 signature within the HER2-Enriched expression subtype. Comparison of Basal-like breast tumors with high-grade Serous Ovarian tumors showed many molecular commonalities, suggesting a related etiology and similar therapeutic opportunities. The biologic finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within, and not across, these major biologic subtypes of breast cancer.

To identify genetic events underlying the genesis and progression of multiple myeloma (MM), we conducted a high-resolution analysis of recurrent copy number alterations (CNAs) and expression profiles in a collection of MM cell lines and outcome-annotated clinical specimens. Attesting to the molecular heterogeneity of MM, unsupervised classification using nonnegative matrix factorization (NMF) designed for array comparative genomic hybridization (aCGH) analysis uncovered distinct genomic subtypes. Additionally, we defined 87 discrete minimal common regions (MCRs) within recurrent and highly focal CNAs. Further integration with expression data generated a refined list of MM gene candidates residing within these MCRs, thereby providing a genomic framework for dissection of disease pathogenesis, improved clinical management, and initiation of targeted drug discovery for specific MM patients.

Summary: RNA-Seq is an exciting methodology that leverages the power of high-throughput sequencing to measure RNA transcript counts at an unprecedented accuracy. However, the data generated from this process are extremely large and biologist-friendly tools with which to analyze it are sorely lacking. MultiExperiment Viewer (MeV) is a Java-based desktop application that allows advanced analysis of gene expression data through an intuitive graphical user interface. Here, we report a significant enhancement to MeV that allows analysis of RNA-Seq data with these familiar, powerful tools. We also report the addition to MeV of several RNA-Seq-specific functions, addressing the differences in analysis requirements between this data type and traditional gene expression data. These tools include automatic conversion functions from raw count data to processed RPKM or FPKM values and differential expression detection and functional annotation enrichment detection based on published methods.Availability: MeV version 4.7 is written in Java and is freely available for download under the terms of the open-source Artistic License version 2.0. The website (http://mev.tm4.org/) hosts a full user manual as well as a short quick-start guide suitable for new users.Contact: johnq@jimmy.harvard.edu

SummaryMultiple myeloma (MM) evolves from a highly prevalent premalignant condition termed MGUS. The factors underlying the malignant transformation of MGUS are unknown. We report a MGUS/MM phenotype in transgenic mice with Eμ-directed expression of the XBP-1 spliced isoform (XBP-1s), a factor governing unfolded protein/ER stress response and plasma-cell development. Eμ-XBP-1s elicited elevated serum Ig and skin alterations. With age, Eμ-xbp-1s transgenics develop features diagnostic of human MM, including bone lytic lesions and subendothelial Ig deposition. Furthermore, transcriptional profiles of Eμ-xbp-1s lymphoid and MM cells show aberrant expression of known human MM dysregulated genes. The similarities of this model with the human disease, coupled with documented frequent XBP-1s overexpression in human MM, serve to implicate XBP-1s dysregulation in MM pathogenesis.