title: A systems approach to analysis of molecular complexity in breast cancer.
abstract: In this issue of Clinical Cancer Research, Andre et al. apply high-resolution arrays to elucidate copy number anomalies in breast cancer. They identify distinct copy number anomaly patterns in different breast cancer subtypes that implicate a number of genes as potential therapeutic targets and as potential markers of therapy responsiveness.
authors.affiliation: Department of Systems Biology and the Kleberg Center for Molecular Markers, M. D. Anderson Cancer Center, Houston, Texas 77030, USA. bhennessy@mdanderson.org
authors.forename: Bryan T
authors.initials: BT
authors.lastname: Hennessy
authors.forename: Ana Maria
authors.initials: AM
authors.lastname: Gonzalez-Angulo
authors.forename: Mark S
authors.initials: MS
authors.lastname: Carey
authors.forename: Gordon B
authors.initials: GB
authors.lastname: Mills
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000378:metabolism; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D019295:Computational Biology / Q000379:methods; D020869:Gene Expression Profiling; D006801:Humans; D008495:Medical Oncology / Q000379:methods; D008954:Models, Biological; D009693:Nucleic Acid Hybridization; D020411:Oligonucleotide Array Sequence Analysis; D019869:Phosphatidylinositol 3-Kinases / Q000378:metabolism; D040901:Proteomics / Q000379:methods; D049490:Systems Biology
chemical_list: D014408:Biomarkers, Tumor; D019869:Phosphatidylinositol 3-Kinases