Lessons from the Cancer Genome

Department of Medical Oncology and Center for Cancer Genome Discovery, Dana-Farber Cancer Institute, Boston, MA 02215, USA
Cell (Impact Factor: 32.24). 03/2013; 153(1):17-37. DOI: 10.1016/j.cell.2013.03.002
Source: PubMed


Systematic studies of the cancer genome have exploded in recent years. These studies have revealed scores of new cancer genes, including many in processes not previously known to be causal targets in cancer. The genes affect cell signaling, chromatin, and epigenomic regulation; RNA splicing; protein homeostasis; metabolism; and lineage maturation. Still, cancer genomics is in its infancy. Much work remains to complete the mutational catalog in primary tumors and across the natural history of cancer, to connect recurrent genomic alterations to altered pathways and acquired cellular vulnerabilities, and to use this information to guide the development and application of therapies.

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    • "Several studies using human and mouse tumour cells have suggested that not all tumour cells have the potential to migrate, invade, circulate and colonise to form metastatic foci (Garraway and Lander, 2013; Vogelstein et al., 2013; Kreso and Dick, 2014). A seemingly uniform tumour tissue contains numerous genetically and epigenetically heterogeneous cells. "
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    ABSTRACT: Metastases are associated with a poor prognosis for canine mammary gland tumours (CMGTs). Metastatic and non-metastatic clones were isolated previously from a single malignant CMGT cell line. The difference in metastatic potential between the two cell lines was hypothesised to be associated with distinct cellular signalling. The aim of this study was to screen for compounds that specifically target metastatic cells in order to improve CMGT therapeutic outcomes. The two clonal cell lines were characterised by transcriptome analysis and their sensitivity to a library of 291 different compounds was compared. The metastatic clone exhibited elevated expression of molecules associated with degradation of the extracellular matrix, epithelial-mesenchymal transition and cancer stem cell phenotype. This was confirmed using a matrigel invasion assay and by assessment of aldehyde dehydrogenase activity. The mitochondrial respiratory chain complex inhibitors (MRCIs; rotenone, antimycin and oligomycin) significantly inhibited the growth of the metastatic clone. Although MRCIs similarly depleted mitochondrial ATP in both clones, the subsequent cellular response was different, with toxicity to the metastatic clone being independent of AMP-activated protein kinase activity. The results of this study suggest a potential utility of MRCIs as anti-tumour agents against metastatic CMGTs. Further studies are needed to investigate the clinical utility of MRCIs and to determine the association between MRCI sensitivity and malignancy. Copyright © 2015 Elsevier Ltd. All rights reserved.
    The Veterinary Journal 04/2015; 205(2). DOI:10.1016/j.tvjl.2015.04.025 · 1.76 Impact Factor
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    • "Using this approach, a considerable number of driver genes have been discovered in a variety of cancer types. However, many seemingly unrelated genes have also been identified in recent cancer genome sequencing studies (Garraway and Lander, 2013; Watson et al., 2013). The heterogeneity of mutational processes within individuals and cancer types could explain this anomaly (Lawrence et al., 2013). "
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    ABSTRACT: Motivation: The recent advance in high-throughput sequencing technologies is generating a huge amount of data that are becoming an important resource for deciphering the genotype underlying a given phenotype. Genome sequencing has been extensively applied to the study of the cancer genomes. Although a few methods have been already proposed for the detection of cancer-related genes, their automatic identification is still a challenging task. Using the genomic data made available by The Cancer Genome Atlas Consortium (TCGA), we propose a new prioritization approach based on the analysis of the distribution of putative deleterious variants in a large cohort of cancer samples.Results: In this paper, we present ContastRank, a new method for the prioritization of putative impaired genes in cancer. The method is based on the comparison of the putative defective rate of each gene in tumor versus normal and 1000 genome samples. We show that the method is able to provide a ranked list of putative impaired genes for colon, lung and prostate adenocarcinomas. The list significantly overlaps with the list of known cancer driver genes previously published. More importantly, by using our scoring approach, we can successfully discriminate between TCGA normal and tumor samples. A binary classifier based on ContrastRank score reaches an overall accuracy >90% and the area under the curve (AUC) of receiver operating characteristics (ROC) >0.95 for all the three types of adenocarcinoma analyzed in this paper. In addition, using ContrastRank score, we are able to discriminate the three tumor types with a minimum overall accuracy of 77% and AUC of 0.83.Conclusions: We describe ContrastRank, a method for prioritizing putative impaired genes in cancer. The method is based on the comparison of exome sequencing data from different cohorts and can detect putative cancer driver genes.ContrastRank can also be used to estimate a global score for an individual genome about the risk of adenocarcinoma based on the genetic variants information from a whole-exome VCF (Variant Calling Format) file. We believe that the application of ContrastRank can be an important step in genomic medicine to enable genome-based diagnosis.Availability and implementation: The lists of ContrastRank scores of all genes in each tumor type are available as supplementary materials. A webserver for evaluating the risk of the three studied adenocarcinomas starting from whole-exome VCF file is under development.Contact: emidio@uab.eduSupplementary information: Supplementary data are available at Bioinformatics online.
    Bioinformatics 09/2014; 30(17):i572-i578. DOI:10.1093/bioinformatics/btu466 · 4.98 Impact Factor
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    • "ALK, BRAF), whereas others undergo amplification in copy number (e.g. MYCN, ERBB2) (Garraway and Lander, 2013; Small et al., 1987). Because of the exceedingly high read coverage of amplicon sequencing data, there is no methodological issue in the identification of point mutations and small insertions or deletions (indels). "
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    ABSTRACT: Motivation: Because of its low cost, amplicon sequencing, also known as ultra-deep targeted sequencing, is now becoming widely used in oncology for detection of actionable mutations, i.e. mutations influencing cell sensitivity to targeted therapies. Amplicon sequencing is based on the polymerase chain reaction amplification of the regions of interest, a process that considerably distorts the information on copy numbers initially present in the tumor DNA. Therefore, additional experiments such as single nucleotide polymorphism (SNP) or comparative genomic hybridization (CGH) arrays often complement amplicon sequencing in clinics to identify copy number status of genes whose amplification or deletion has direct consequences on the efficacy of a particular cancer treatment. So far, there has been no proven method to extract the information on gene copy number aberrations based solely on amplicon sequencing. Results: Here we present ONCOCNV, a method that includes a multifactor normalization and annotation technique enabling the detection of large copy number changes from amplicon sequencing data. We validated our approach on high and low amplicon density datasets and demonstrated that ONCOCNV can achieve a precision comparable with that of array CGH techniques in detecting copy number aberrations. Thus, ONCOCNV applied on amplicon sequencing data would make the use of additional array CGH or SNP array experiments unnecessary. Availability and implementation: Contact: Supplementary information: Supplementary data are available at Bioinformatics online.
    Bioinformatics 07/2014; 30(24). DOI:10.1093/bioinformatics/btu436 · 4.98 Impact Factor
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