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      Mutational heterogeneity in cancer and the search for new cancer genes

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          Abstract

          Major international projects are now underway aimed at creating a comprehensive catalog of all genes responsible for the initiation and progression of cancer. These studies involve sequencing of matched tumor–normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here, we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false positive findings that overshadow true driver events. Here, we show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumor-normal pairs and discover extraordinary variation in (i) mutation frequency and spectrum within cancer types, which shed light on mutational processes and disease etiology, and (ii) mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and allow true cancer genes to rise to attention.

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          Most cited references 31

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          Comprehensive Molecular Characterization of Human Colon and Rectal Cancer

          Summary To characterize somatic alterations in colorectal carcinoma (CRC), we conducted genome-scale analysis of 276 samples, analyzing exome sequence, DNA copy number, promoter methylation, mRNA and microRNA expression. A subset (97) underwent low-depth-of-coverage whole-genome sequencing. 16% of CRC have hypermutation, three quarters of which have the expected high microsatellite instability (MSI), usually with hypermethylation and MLH1 silencing, but one quarter has somatic mismatch repair gene mutations. Excluding hypermutated cancers, colon and rectum cancers have remarkably similar patterns of genomic alteration. Twenty-four genes are significantly mutated. In addition to the expected APC, TP53, SMAD4, PIK3CA and KRAS mutations, we found frequent mutations in ARID1A, SOX9, and FAM123B/WTX. Recurrent copy number alterations include potentially drug-targetable amplifications of ERBB2 and newly discovered amplification of IGF2. Recurrent chromosomal translocations include fusion of NAV2 and WNT pathway member TCF7L1. Integrative analyses suggest new markers for aggressive CRC and important role for MYC-directed transcriptional activation and repression.
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            Comprehensive genomic characterization defines human glioblastoma genes and core pathways

              (2008)
            Human cancer cells typically harbor multiple chromosomal aberrations, nucleotide substitutions and epigenetic modifications that drive malignant transformation. The Cancer Genome Atlas (TCGA) pilot project aims to assess the value of large-scale multidimensional analysis of these molecular characteristics in human cancer and to provide the data rapidly to the research community. Here, we report the interim integrative analysis of DNA copy number, gene expression and DNA methylation aberrations in 206 glioblastomas (GBM), the most common type of adult brain cancer, and nucleotide sequence aberrations in 91 of the 206 GBMs. This analysis provides new insights into the roles of ERBB2, NF1 and TP53, uncovers frequent mutations of the PI3 kinase regulatory subunit gene PIK3R1, and provides a network view of the pathways altered in the development of GBM. Furthermore, integration of mutation, DNA methylation and clinical treatment data reveals a link between MGMT promoter methylation and a hypermutator phenotype consequent to mismatch repair deficiency in treated glioblastomas, an observation with potential clinical implications. Together, these findings establish the feasibility and power of TCGA, demonstrating that it can rapidly expand knowledge of the molecular basis of cancer.
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              Integrated Genomic Analyses of Ovarian Carcinoma

              Summary 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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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                6 January 2014
                16 June 2013
                11 July 2013
                10 February 2014
                : 499
                : 7457
                : 214-218
                Affiliations
                [1 ]The Broad Institute of MIT and Harvard, Cambridge, MA, 02141, USA.
                [2 ]Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
                [3 ]Harvard Medical School, Boston, MA, 02115, USA.
                [4 ]Instituto Nacional de Medicina Genómica, Mexico City, 14610, Mexico.
                [5 ]Yale Cancer Center, Department of Hematology, New Haven, CT
                [6 ]Massachusetts General Hospital, Boston, MA, 02114, USA.
                [7 ]Brigham and Women’s Hospital, Boston, MA, 02115, USA.
                [8 ]Howard Hughes Medical Institute, Chevy Chase, MD, 20815, USA.
                [9 ]Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
                [10 ]Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, 76100, Israel
                [11 ]Boston Children’s Hospital, Boston, MA, 02115, USA.
                [12 ]Children’s Hospital, Philadelphia, PA, 19104, USA
                [13 ]Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, NIH, DHHS, Durham, NC 27709, USA
                [14 ]Department of Pediatric Oncology, Hospital Sant Joan de Déu, Barcelona, Spain
                [15 ]Genome Sciences, University of Washington, Seattle, WA 98195
                NIHMS471461
                10.1038/nature12213
                3919509
                23770567

                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

                Funding
                Funded by: National Human Genome Research Institute : NHGRI
                Award ID: U54 HG003067 || HG
                Funded by: National Cancer Institute : NCI
                Award ID: U24 CA143845 || CA
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