Beroukhim R, Getz G, Nghiemphu L, Barretina J, Hsueh T, Linhart D et al.. Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma. Proc Natl Acad Sci USA 104: 20007-20012

Broad Institute, Massachusetts Institute of Technology and Harvard University, 7 Cambridge Center, Cambridge, MA 02142, USA.
Proceedings of the National Academy of Sciences (Impact Factor: 9.81). 01/2008; 104(50):20007-12. DOI: 10.1073/pnas.0710052104
Source: PubMed

ABSTRACT 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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Available from: John R Prensner, Mar 16, 2014
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    • "ISAR ISAR is based on the G score metric, a significance measure of the aberration for each marker, which was originally defined in GISTIC (Beroukhim et al., 2007). Specifically, the G score for a marker m is the summation of the copy number across samples that surpass an aberration threshold q. "
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    ABSTRACT: Identifying driver genes in cancer remains a crucial bottleneck in therapeutic development and basic understanding of the disease. We developed Helios, an algorithm that integrates genomic data from primary tumors with data from functional RNAi screens to pinpoint driver genes within large recurrently amplified regions of DNA. Applying Helios to breast cancer data identified a set of candidate drivers highly enriched with known drivers (p < 10(-14)). Nine of ten top-scoring Helios genes are known drivers of breast cancer, and in vitro validation of 12 candidates predicted by Helios found ten conferred enhanced anchorage-independent growth, demonstrating Helios's exquisite sensitivity and specificity. We extensively characterized RSF-1, a driver identified by Helios whose amplification correlates with poor prognosis, and found increased tumorigenesis and metastasis in mouse models. We have demonstrated a powerful approach for identifying driver genes and how it can yield important insights into cancer. Copyright © 2014 Elsevier Inc. All rights reserved.
    Cell 11/2014; 159(6). DOI:10.1016/j.cell.2014.10.048 · 33.12 Impact Factor
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    • "Furthermore, GISTIC2.0 is geared towards the identification of genes. Consequently, this method prioritizes amplifications and homozygous deletions over recurrent single CNAs [27] [35]. Genomic regions without a known target or infrequent focal CNAs may not be identified. "
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    ABSTRACT: The extent of focal chromosomal copy number aberrations (CNAs) in cancer has been uncovered through technical innovations and this discovery has been critical for the identification of new cancer driver genes in genomics projects such as TCGA and ICGC. Unlike constitutive copy number variations (CNVs), focal CNAs are the result of many selection events during the evolution of cancer genomes. Therefore it is possible that a single gene in a focal CNA gives the tumor a selective growth advantage. This concept has been instrumental in the discovery of new cancer driver genes. However, focal CNAs lack a consensus definition, therefore we propose one based on pragmatic considerations. We also describe different strategies to identify focal CNAs and procedures to distinguish them from large CNAs and CNVs.
    Biochimica et Biophysica Acta (BBA) - Molecular Cell Research 08/2014; 1843(11). DOI:10.1016/j.bbamcr.2014.08.001 · 5.30 Impact Factor
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    • "In seven out of the 15 affected We identified 107 focal minimal common regions (MCRs) of aberration (84 of loss and 23 of gain) encompassing 1–3 protein-coding genes, which most likely represent the target of the lesion (Fig. 4 b). The relevance of the identified lesions was confirmed through GISTIC, an algorithm based on the amplitude and frequency of occurrence of CN changes (Beroukhim et al., 2007; Fig. 4 d). To address the specificity of these newly identified recurrent regions of CN aberration for RS, we compared their frequency with that reported in a cohort of 353 newly diagnosed and previously untreated CLL cases (Edelmann et al., 2012), focusing on genes altered in ≥10% of RS cases as well as on known recurrent cytogenetic abnormalities (Edelmann et al., 2012; Fig. 4, b and c). "
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    ABSTRACT: Richter syndrome (RS) derives from the rare transformation of chronic lymphocytic leukemia (CLL) into an aggressive lymphoma, most commonly of the diffuse large B cell lymphoma (DLBCL) type. The molecular pathogenesis of RS is only partially understood. By combining whole-exome sequencing and copy-number analysis of 9 CLL-RS pairs and of an extended panel of 43 RS cases, we show that this aggressive disease typically arises from the predominant CLL clone by acquiring an average of ∼20 genetic lesions/case. RS lesions are heterogeneous in terms of load and spectrum among patients, and include those involved in CLL progression and chemorefractoriness (TP53 disruption and NOTCH1 activation) as well as some not previously implicated in CLL or RS pathogenesis. In particular, disruption of the CDKN2A/B cell cycle regulator is associated with ∼30% of RS cases. Finally, we report that the genomic landscape of RS is significantly different from that of de novo DLBCL, suggesting that they represent distinct disease entities. These results provide insights into RS pathogenesis, and identify dysregulated pathways of potential diagnostic and therapeutic relevance.
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