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Open AccessJournal ArticleDOI

The landscape of somatic copy-number alteration across human cancers

Rameen Beroukhim, +86 more
- 18 Feb 2010 - 
- Vol. 463, Iss: 7283, pp 899-905
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TLDR
It is demonstrated that cancer cells containing amplifications surrounding the MCL1 and BCL2L1 anti-apoptotic genes depend on the expression of these genes for survival, and a large majority of SCNAs identified in individual cancer types are present in several cancer types.
Abstract
A powerful way to discover key genes with causal roles in oncogenesis is to identify genomic regions that undergo frequent alteration in human cancers. Here we present high-resolution analyses of somatic copy-number alterations (SCNAs) from 3,131 cancer specimens, belonging largely to 26 histological types. We identify 158 regions of focal SCNA that are altered at significant frequency across several cancer types, of which 122 cannot be explained by the presence of a known cancer target gene located within these regions. Several gene families are enriched among these regions of focal SCNA, including the BCL2 family of apoptosis regulators and the NF-kappaBeta pathway. We show that cancer cells containing amplifications surrounding the MCL1 and BCL2L1 anti-apoptotic genes depend on the expression of these genes for survival. Finally, we demonstrate that a large majority of SCNAs identified in individual cancer types are present in several cancer types.

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Journal ArticleDOI

Targeting Synthetic Lethal Interactions between Myc and the eIF4F Complex Impedes Tumorigenesis

TL;DR: It is found elevated Myc levels are associated with deregulated eIF4F activity in the prelymphomatous stage of the Eμ-Myc lymphoma model, and eif4F is a key Myc client that represents a tumor-specific vulnerability.
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Identification and functional analysis of 9p24 amplified genes in human breast cancer.

TL;DR: The studies support the notion that the 9p24 amplicon contains multiple oncogenes that may integrate genetic and epigenetic codes and have important roles in human tumorigenesis.
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Patchwork: allele-specific copy number analysis of whole-genome sequenced tumor tissue

TL;DR: Patchwork is a new bioinformatic tool for allele-specific copy number analysis using whole-genome sequencing data that can be used to determine the copy number of homologous sequences throughout the genome, even in aneuploid samples with moderate sequence coverage and tumor cell content.
References
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Journal ArticleDOI

Controlling the false discovery rate: a practical and powerful approach to multiple testing

TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
Journal ArticleDOI

Comprehensive genomic characterization defines human glioblastoma genes and core pathways

Roger E. McLendon, +233 more
- 23 Oct 2008 - 
TL;DR: The interim integrative analysis of DNA copy number, gene expression and DNA methylation aberrations in 206 glioblastomas reveals a link between MGMT promoter methylation and a hypermutator phenotype consequent to mismatch repair deficiency in treated gliobeasts, demonstrating that it can rapidly expand knowledge of the molecular basis of cancer.
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The clonal evolution of tumor cell populations

TL;DR: Each patient's cancer may require individual specific therapy, and even this may be thwarted by emergence of a genetically variant subline resistant to the treatment, which should be directed toward understanding and controlling the evolutionary process in tumors before it reaches the late stage usually seen in clinical cancer.
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In Vivo Gene Delivery and Stable Transduction of Nondividing Cells by a Lentiviral Vector

TL;DR: The ability of HIV-based viral vectors to deliver genes in vivo into nondividing cells could increase the applicability of retroviral vectors in human gene therapy.
Journal ArticleDOI

Model-based analysis of oligonucleotide arrays: Expression index computation and outlier detection

TL;DR: A statistical model is proposed for the probe-level data, and model-based estimates for gene expression indexes are developed, which help to identify and handle cross-hybridizing probes and contaminating array regions.
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