The elucidation of the human genome sequence has made it possible to identify genetic alterations in cancers in unprecedented detail. To begin a systematic analysis of such alterations, we determined the sequence of well-annotated human protein-coding genes in two common tumor types. Analysis of 13,023 genes in 11 breast and 11 colorectal cancers revealed that individual tumors accumulate an average of approximately 90 mutant genes but that only a subset of these contribute to the neoplastic process. Using stringent criteria to delineate this subset, we identified 189 genes (average of 11 per tumor) that were mutated at significant frequency. The vast majority of these genes were not known to be genetically altered in tumors and are predicted to affect a wide range of cellular functions, including transcription, adhesion, and invasion. These data define the genetic landscape of two human cancer types, provide new targets for diagnostic and therapeutic intervention, and open fertile avenues for basic research in tumor biology.

Human cancer is caused by the accumulation of mutations in oncogenes and tumor suppressor genes. To catalog the genetic changes that occur during tumorigenesis, we isolated DNA from 11 breast and 11 colorectal tumors and determined the sequences of the genes in the Reference Sequence database in these samples. Based on analysis of exons representing 20,857 transcripts from 18,191 genes, we conclude that the genomic landscapes of breast and colorectal cancers are composed of a handful of commonly mutated gene "mountains" and a much larger number of gene "hills" that are mutated at low frequency. We describe statistical and bioinformatic tools that may help identify mutations with a role in tumorigenesis. These results have implications for understanding the nature and heterogeneity of human cancers and for using personal genomics for tumor diagnosis and therapy.

Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database (www.proteinatlas.org/pathology) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.

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We have performed a genome-wide analysis of copy number changes in breast and colorectal tumors using approaches that can reliably detect homozygous deletions and amplifications. We found that the number of genes altered by major copy number changes, deletion of all copies or amplification to at least 12 copies per cell, averaged 17 per tumor. We have integrated these data with previous mutation analyses of the Reference Sequence genes in these same tumor types and have identified genes and cellular pathways affected by both copy number changes and point alterations. Pathways enriched for genetic alterations included those controlling cell adhesion, intracellular signaling, DNA topological change, and cell cycle control. These analyses provide an integrated view of copy number and sequencing alterations on a genome-wide scale and identify genes and pathways that could prove useful for cancer diagnosis and therapy.amplification ͉ copy number changes ͉ Digital Karyotyping ͉ high-density SNP arrays ͉ homozygous deletion

This study systematically analyzes platelet-derived growth factor (PDGF) receptor expression in six types of common tumors as well as examines associations between PDGF ␤-receptor status and clinicopathological characteristics in breast cancer. PDGF receptor expression was determined by immunohistochemistry on tumor tissue microarrays. Breast tumor data were combined with prognostic factors and related to outcome endpoints. PDGF ␣-and ␤-receptors were independently expressed, at variable frequencies, in the tumor stroma of all tested tumor types. There was a significant association between PDGF ␤-receptor expression on fibroblasts and perivascular cells in individual colon and prostate tumors. In breast cancer, high stromal PDGF ␤-receptor expression was significantly associated with high histopathological grade, estrogen receptor negativity, and high HER2 expression. High stromal PDGF ␤-receptor expression was correlated with significantly shorter recurrence-free and breast cancer-specific survival. The prognostic significance of stromal PDGF ␤-receptor expression was particularly prominent in tumors from premenopausal women. Stromal PDGF ␣-and ␤-receptor expression is a common, but variable and independent, property of solid tumors. In breast cancer, stromal PDGF ␤-receptor expression significantly correlates with less favorable clinicopatho-

Improved methods are needed for in situ characterization of post-translational modifications in cell lines and tissues. For example, it is desirable to monitor the phosphorylation status of individual receptor tyrosine kinases in samples from human tumors treated with inhibitors to evaluate therapeutic responses. Unfortunately the leading methods for observing the dynamics of tissue post-translational modifications in situ, immunohistochemistry and immunofluorescence, exhibit limited sensitivity and selectivity. Proximity ligation assay is a novel method that offers improved selectivity through the requirement of dual recognition and increased sensitivity by including DNA amplification as a component of detection of the target molecule. Here we therefore established a generalized in situ proximity ligation assay to investigate phosphorylation of platelet-derived growth factor receptor ␤ (PDGFR␤) in cells stimulated with platelet-derived growth factor BB. Antibodies specific for immunoglobulins from different species, modified by attachment of DNA strands, were used as secondary proximity probes together with a pair of primary antibodies from the corresponding species. Dual recognition of receptors and phosphorylated sites by the primary antibodies in combination with the secondary proximity probes was used to generate circular DNA strands; this was followed by signal amplification by replicating the DNA circles via rolling circle amplification. We detected tyrosine phosphorylated PDGFR␤ in human embryonic kidney cells stably overexpressing human influenza hemagglutinin-tagged human PDGFR␤ in porcine aortic endothelial cells transfected with the ␤-receptor, but not in cells transfected with the ␣-receptor, and also in immortalized human foreskin fibroblasts, BJ hTert, endogenously expressing the PDGFR␤. We furthermore visualized tyrosine phosphorylated PDGFR␤ in tissue sections from fresh frozen human scar tissue undergoing wound healing. The method should be of great value to study signal transduction, screen for effects of pharmacological agents, and enhance the diagnostic potential in histopathology. Molecular & Cellular Proteomics 6:1500 -1509, 2007.