title: An integrated genomics approach identifies drivers of proliferation in luminal-subtype human breast cancer.
abstract: Elucidating the molecular drivers of human breast cancers requires a strategy that is capable of integrating multiple forms of data and an ability to interpret the functional consequences of a given genetic aberration. Here we present an integrated genomic strategy based on the use of gene expression signatures of oncogenic pathway activity (n = 52) as a framework to analyze DNA copy number alterations in combination with data from a genome-wide RNA-mediated interference screen. We identify specific DNA amplifications and essential genes within these amplicons representing key genetic drivers, including known and new regulators of oncogenesis. The genes identified include eight that are essential for cell proliferation (FGD5, METTL6, CPT1A, DTX3, MRPS23, EIF2S2, EIF6 and SLC2A10) and are uniquely amplified in patients with highly proliferative luminal breast tumors, a clinical subset of patients for which few therapeutic options are effective. This general strategy has the potential to identify therapeutic targets within amplicons through an integrated use of genomic data sets.
authors.affiliation: 1] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
authors.forename: Michael L
authors.initials: ML
authors.lastname: Gatza
authors.affiliation: 1] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
authors.forename: Grace O
authors.initials: GO
authors.lastname: Silva
authors.affiliation: 1] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
authors.forename: Joel S
authors.initials: JS
authors.lastname: Parker
authors.affiliation: Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
authors.forename: Cheng
authors.initials: C
authors.lastname: Fan
authors.affiliation: 1] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [4] Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
authors.forename: Charles M
authors.initials: CM
authors.lastname: Perou
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics* / Q000473:pathology; D045744:Cell Line, Tumor; D049109:Cell Proliferation; D016000:Cluster Analysis; D056915:DNA Copy Number Variations; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D020043:Genes, Essential / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000235:genetics; D023281:Genomics / Q000379:methods*; D006801:Humans; D015999:Multivariate Analysis; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data; D011379:Prognosis; D016016:Proportional Hazards Models; D034622:RNA Interference; D015398:Signal Transduction / Q000235:genetics; D016019:Survival Analysis