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TCGARN. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 455: 1061-1068

Citation of this study should reference The Cancer Genome Atlas Research Network, not individual participants. A list of participants are listed by contributing centers below.
Nature (Impact Factor: 42.35). 10/2008; 455(7216). DOI: 10.1038/nature07385
Source: PubMed

ABSTRACT Human cancer cells typically harbour 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 multi-dimensional 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-the most common type of adult brain cancer-and nucleotide sequence aberrations in 91 of the 206 glioblastomas. This analysis provides new insights into the roles of ERBB2, NF1 and TP53, uncovers frequent mutations of the phosphatidylinositol-3-OH kinase regulatory subunit gene PIK3R1, and provides a network view of the pathways altered in the development of glioblastoma. 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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    • "An increasing array of publically available genetics and omics data is helping to greatly expand the use of molecular subtyping in complex diseases. This is most readily apparent in cancer where the Cancer Genome Atlas (TCGA) (McLendon et al., 2008; TCGA Network, 2011, 2012) maintains a repository of omics data including sequencing, gene and protein expression, SNPs, miRNA, and methylation for thousands of tumors across dozens of types of cancer. GEO and Array Express maintain huge repositories of gene expression data (Barrett et al., 2010; Kolesnikov et al., 2015) and other repositories are now storing raw proteomics data (Farrah et al., 2014; Vizcaíno et al., 2013). "
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    ABSTRACT: Complex diseases are caused by a combination of genetic and environmental factors, creating a difficult challenge for diagnosis and defining subtypes. This review article describes how distinct disease subtypes can be identified through integration and analysis of clinical and multi-omics data. A broad shift toward molecular subtyping of disease using genetic and omics data has yielded successful results in cancer and other complex diseases. To determine molecular subtypes, patients are first classified by applying clustering methods to different types of omics data, then these results are integrated with clinical data to characterize distinct disease subtypes. An example of this molecular-data-first approach is in research on Autism Spectrum Disorder (ASD), a spectrum of social communication disorders marked by tremendous etiological and phenotypic heterogeneity. In the case of ASD, omics data such as exome sequences and gene and protein expression data are combined with clinical data such as psychometric testing and imaging to enable subtype identification. Novel ASD subtypes have been proposed, such as CHD8, using this molecular subtyping approach. Broader use of molecular subtyping in complex disease research is impeded by data heterogeneity, diversity of standards, and ineffective analysis tools. The future of molecular subtyping for ASD and other complex diseases calls for an integrated resource to identify disease mechanisms, classify new patients, and inform effective treatment options. This in turn will empower and accelerate precision medicine and personalized healthcare.
    Omics: a journal of integrative biology 04/2015; 19(4):197-208. DOI:10.1089/omi.2015.0020 · 2.73 Impact Factor
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    • "RB1 mutation or deletion and CDK4 amplification account for inactivation of RB1, and cyclin-dependent kinase inhibitor 2A (CDKN2A) gene mutation or homozygous deletion also results in loss of normal RB1 function [15] [21]. Overall, the frequency of genetic alterations in this pathway amounts to 78% of GBMs, with CDKN2B deletion (47%), CDKN2C deletion (2%), cyclin D2 (CCND2) amplification (2%), CDK6 amplification (1%), RB1 mutation or deletion (11%), CDK4 amplification (18%), and CDKN2A(p16 INK4a ) mutation or homozygous deletion (52%), as reported by TCGA [15]. Among them, CDKN2A mutation or homozygous deletion leads to loss of p16 INK4a , which is an inhibitor of CDK4, and the CDKN2A gene encodes p16 INK4a and p14 ARF that exert respective functions in the RB and p53 pathways, therefore revealing the critical importance of the single genetic inactivation of CDKN2A for these two core pathways in the growth of glioma [25]. "
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    ABSTRACT: Malignant gliomas are the most common malignant primary brain tumors and one of the most challenging forms of cancers to treat. Despite advances in conventional treatment, the outcome for patients remains almost universally fatal. This poor prognosis is due to therapeutic resistance and tumor recurrence after surgical removal. However, over the past decade, molecular targeted therapy has held the promise of transforming the care of malignant glioma patients. Significant progress in understanding the molecular pathology of gliomagenesis and maintenance of the malignant phenotypes will open opportunities to rationally develop new molecular targeted therapy options. Recently, therapeutic strategies have focused on targeting pro-growth signaling mediated by receptor tyrosine kinase/RAS/phosphatidylinositol 3-kinase pathway, proangiogenic pathways, and several other vital intracellular signaling networks, such as proteasome and histone deacetylase. However, several factors such as cross-talk between the altered pathways, intratumoral molecular heterogeneity, and therapeutic resistance of glioma stem cells (GSCs) have limited the activity of single agents. Efforts are ongoing to study in depth the complex molecular biology of glioma, develop novel regimens targeting GSCs, and identify biomarkers to stratify patients with the individualized molecular targeted therapy. Here, we review the molecular alterations relevant to the pathology of malignant glioma, review current advances in clinical targeted trials, and discuss the challenges, controversies, and future directions of molecular targeted therapy. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
    Neoplasia (New York, N.Y.) 03/2015; 114(3). DOI:10.1016/j.neo.2015.02.002 · 5.40 Impact Factor
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    • "For example, in RCC, the use of IG biopsy, has allowed determination of imaging phenotypes with clinical relevance, since it has been shown that the clear cell variant is often subject to intra-tumoral genomic heterogeneity [30]. Use of IG biopsy coupled with deformable image registration should permit improved longitudinal sampling [12]. "
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    ABSTRACT: The National Cancer Institute (NCI) Cancer Imaging Program organized two related workshops on June 26–27, 2013, entitled “Correlating Imaging Phenotypes with Genomics Signatures Research” and “Scalable Computational Resources as Required for Imaging-Genomics Decision Support Systems.” The first workshop focused on clinical and scientific requirements, exploring our knowledge of phenotypic characteristics of cancer biological properties to determine whether the field is sufficiently advanced to correlate with imaging phenotypes that underpin genomics and clinical outcomes, and exploring new scientific methods to extract phenotypic features from medical images and relate them to genomics analyses. The second workshop focused on computational methods that explore informatics and computational requirements to extract phenotypic features from medical images and relate them to genomics analyses and improve the accessibility and speed of dissemination of existing NIH resources. These workshops linked clinical and scientific requirements of currently known phenotypic and genotypic cancer biology characteristics with imaging phenotypes that underpin genomics and clinical outcomes. The group generated a set of recommendations to NCI leadership and the research community that encourage and support development of the emerging radiogenomics research field to address short-and longer-term goals in cancer research.
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