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      Integrated Genomic Analyses of Ovarian Carcinoma

      research-article
      Author(s): The Cancer Genome Atlas Research Network
      Publication date (Electronic):
      Journal: Nature

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          The Cancer Genome Atlas (TCGA) project has analyzed mRNA expression, miRNA expression, promoter methylation, and DNA copy number in 489 high-grade serous ovarian adenocarcinomas (HGS-OvCa) and the DNA sequences of exons from coding genes in 316 of these tumors. These results show that HGS-OvCa is characterized by TP53 mutations in almost all tumors (96%); low prevalence but statistically recurrent somatic mutations in 9 additional genes including NF1, BRCA1, BRCA2, RB1, and CDK12; 113 significant focal DNA copy number aberrations; and promoter methylation events involving 168 genes. Analyses delineated four ovarian cancer transcriptional subtypes, three miRNA subtypes, four promoter methylation subtypes, a transcriptional signature associated with survival duration and shed new light on the impact on survival of tumors with BRCA1/2 and CCNE1 aberrations. Pathway analyses suggested that homologous recombination is defective in about half of tumors, and that Notch and FOXM1 signaling are involved in serous ovarian cancer pathophysiology.

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          The emerging roles of forkhead box (Fox) proteins in cancer.

          Stephen S Myatt, Eric Lam (2007)
          Forkhead box (Fox) proteins are a superfamily of evolutionarily conserved transcriptional regulators, which control a wide spectrum of biological processes. As a consequence, a loss or gain of Fox function can alter cell fate and promote tumorigenesis as well as cancer progression. Here we discuss the evidence that the deregulation of Fox family transcription factors has a crucial role in the development and progression of cancer, and evaluate the emerging role of Fox proteins as direct and indirect targets for therapeutic intervention, as well as biomarkers for predicting and monitoring treatment responses.
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            Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma.

            Rameen Beroukhim, Gad Getz, Leia Nghiemphu … (2007)
            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 describe a systematic method, called Genomic Identification of Significant Targets in Cancer (GISTIC), designed for analyzing chromosomal aberrations in cancer. We use it to study chromosomal aberrations in 141 gliomas and compare the results with two prior studies. Traditional methods highlight hundreds of altered regions with little concordance between studies. The new approach reveals a highly concordant picture involving approximately 35 significant events, including 16-18 broad events near chromosome-arm size and 16-21 focal events. Approximately half of these events correspond to known cancer-related genes, only some of which have been previously tied to glioma. We also show that superimposed broad and focal events may have different biological consequences. Specifically, gliomas with broad amplification of chromosome 7 have properties different from those with overlapping focalEGFR amplification: the broad events act in part through effects on MET and its ligand HGF and correlate with MET dependence in vitro. Our results support the feasibility and utility of systematic characterization of the cancer genome.
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              Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM

              Charles Vaske, Stephen Benz, J Sanborn … (2010)
              Motivation: High-throughput data is providing a comprehensive view of the molecular changes in cancer tissues. New technologies allow for the simultaneous genome-wide assay of the state of genome copy number variation, gene expression, DNA methylation and epigenetics of tumor samples and cancer cell lines. Analyses of current data sets find that genetic alterations between patients can differ but often involve common pathways. It is therefore critical to identify relevant pathways involved in cancer progression and detect how they are altered in different patients. Results: We present a novel method for inferring patient-specific genetic activities incorporating curated pathway interactions among genes. A gene is modeled by a factor graph as a set of interconnected variables encoding the expression and known activity of a gene and its products, allowing the incorporation of many types of omic data as evidence. The method predicts the degree to which a pathway's activities (e.g. internal gene states, interactions or high-level ‘outputs’) are altered in the patient using probabilistic inference. Compared with a competing pathway activity inference approach called SPIA, our method identifies altered activities in cancer-related pathways with fewer false-positives in both a glioblastoma multiform (GBM) and a breast cancer dataset. PARADIGM identified consistent pathway-level activities for subsets of the GBM patients that are overlooked when genes are considered in isolation. Further, grouping GBM patients based on their significant pathway perturbations divides them into clinically-relevant subgroups having significantly different survival outcomes. These findings suggest that therapeutics might be chosen that target genes at critical points in the commonly perturbed pathway(s) of a group of patients. Availability:Source code available at http://sbenz.github.com/Paradigm Contact: jstuart@soe.ucsc.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Journal
                Journal ID (nlm-journal-id): 0410462
                Journal ID (pubmed-jr-id): 6011
                Journal ID (nlm-ta): Nature
                Journal ID (iso-abbrev): Nature
                Title: Nature
                ISSN (Print): 0028-0836
                ISSN (Electronic): 1476-4687
                Publication date Nihms-submitted: 16 August 2011
                Publication date (Electronic): 29 June 2011
                Publication date PMC-release: 30 December 2011
                Volume: 474
                Issue: 7353
                Pages: 609-615
                Article
                Manuscript ID: nihpa313090
                DOI: 10.1038/nature10166
                PMC ID: 3163504
                PubMed ID: 21720365
                SO-VID: b6e335e2-d6a4-4a5a-9266-76aa2311bdba
                License:

                Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

                History
                Funding
                Funded by: National Cancer Institute : NCI
                Award ID: R21 CA135877-02 || CA
                Funded by: National Cancer Institute : NCI
                Award ID: R21 CA135877-01 || CA
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                Subject: Article

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