Article

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

ABSTRACT

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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    • "Attempts to map the genetic basis of any of these disease traits will likely produce spurious associations if the genetic structure of the population is not properly accounted for (Price et al. 2006; Goldstein et al. 2013; Boomsma et al. 2014). Despite the extensive use of targeted exome sequencing to discover disease genes in Mendelian disorders (Ng et al. 2010; Bamshad et al. 2011) or cancer (Garraway, Lander 2013; Vogelstein et al. 2013), lack of information about local genetic variation can severely hinder the discrimination of real disease variants from local polymorphisms and rare variants. "
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    ABSTRACT: Recent results from large-scale genomic projects suggest that allele frequencies, which are highly relevant for medical purposes, differ considerably across different populations. The need for a detailed catalogue of local variability motivated the whole exome sequencing of 267 unrelated individuals, representative of the healthy Spanish population. Like in other studies, a considerable number of rare variants were found (almost one third of the described variants). There were also relevant differences in allelic frequencies in polymorphic variants, including about 10,000 polymorphisms private to the Spanish population. The allelic frequencies of variants conferring susceptibility to complex diseases (including cancer, schizophrenia, Alzheimer disease, type 2 diabetes and other pathologies) were overall similar to those of other populations. However, the trend is the opposite for variants linked to Mendelian and rare diseases (including several retinal degenerative dystrophies and cardiomyopathies) that show marked frequency differences between populations. Interestingly, a correspondence between differences in allelic frequencies and disease prevalence was found, highlighting the relevance of frequency differences in disease risk. These differences are also observed in variants that disrupt known drug binding sites, suggesting an important role for local variability in population-specific drug resistances or adverse effects. We have made the Spanish population variant server web page that contains population frequency information for the complete list of 170,888 variant positions we found publicly available (http://spv.babelomics.org/), We show that it if fundamental to determine population-specific variant frequencies in order to distinguish real disease associations from population-specific polymorphisms.
    Full-text · Article · Jan 2016 · Molecular Biology and Evolution
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    • "Recent large-scale genomic analyses have led to the identification of ''actionable'' driver genes of specific cancers that are therapeutically accessible, including oncogene and non-oncogene dependencies (Al-Lazikani et al., 2012; Garraway and Lander, 2013; Luo et al., 2009; Rubio-Perez et al., 2015). However , the accurate and efficient identification of drugs and drug combinations that inhibit such drivers within specific tumor contexts represents a major challenge, particularly for transcriptional regulators that, in general, are pharmacologically inaccessible . "
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    ABSTRACT: Although genetically engineered mouse (GEM) models are often used to evaluate cancer therapies, extrapolation of such preclinical data to human cancer can be challenging. Here, we introduce an approach that uses drug perturbation data from GEM models to predict drug efficacy in human cancer. Network-based analysis of expression profiles from in vivo treatment of GEM models identified drugs and drug combinations that inhibit the activity of FOXM1 and CENPF, which are master regulators of prostate cancer malignancy. Validation of mouse and human prostate cancer models confirmed the specificity and synergy of a predicted drug combination to abrogate FOXM1/CENPF activity and inhibit tumorigenicity. Network-based analysis of treatment signatures from GEM models identified treatment-responsive genes in human prostate cancer that are potential biomarkers of patient response. More generally, this approach allows systematic identification of drugs that inhibit tumor dependencies, thereby improving the utility of GEM models for prioritizing drugs for clinical evaluation.
    Full-text · Article · Sep 2015 · Cell Reports
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    • "Genomic instability is a fundamental feature of human cancer, and DNA repair defects resulting in impaired genome maintenance promote pathogenesis of many human cancers (Hanahan and Weinberg, 2011; Garraway and Lander, 2013). In prostate cancer, structural genomic rearrangements, including translocations (e.g., TMPRSS2-ERG) and copy number aberrations (e.g., 8q gain, 10q23/PTEN loss) are a key mechanism driving tumorigenesis (Visakorpi et al., 1995; Cher et al., 1996; Tomlins et al., 2005; Zhao et al., 2005; Liu et al., 2006; Demichelis et al., 2009; Beroukhim et al., 2010). "
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    ABSTRACT: Genomic instability is a fundamental feature of human cancer often resulting from impaired genome maintenance. In prostate cancer, structural genomic rearrangements are a common mechanism driving tumorigenesis. However, somatic alterations predisposing to chromosomal rearrangements in prostate cancer remain largely undefined. Here, we show that SPOP, the most commonly mutated gene in primary prostate cancer modulates DNA double strand break (DSB) repair, and that SPOP mutation is associated with genomic instability. In vivo, SPOP mutation results in a transcriptional response consistent with BRCA1 inactivation resulting in impaired homology-directed repair (HDR) of DSB. Furthermore, we found that SPOP mutation sensitizes to DNA damaging therapeutic agents such as PARP inhibitors. These results implicate SPOP as a novel participant in DSB repair, suggest that SPOP mutation drives prostate tumorigenesis in part through genomic instability, and indicate that mutant SPOP may increase response to DNA-damaging therapeutics.
    Full-text · Article · Sep 2015 · eLife Sciences
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