title: Genome-based risk prediction for early stage breast cancer.
abstract: Tests to better characterize tumor genomic architecture are quickly becoming a standard of care in oncology. For breast cancer, the use of gene expression assays for early stage disease is already common practice. These tests have found a place in risk stratifying the heterogeneous group of stage I-II breast cancers for recurrence, for predicting chemotherapy response, and for predicting breast cancer-related mortality. In the last 5 years, more assays have become available to the practicing oncologist. Given the rapidity with which this field has evolved, it is prudent to review the tests, their indications, and the studies from which they have been validated. We present a comprehensive review of the available gene expression assays for early stage breast cancer. We review data for several individual tests and comparative studies looking at risk prediction and cost-effectiveness.
authors.affiliation: Division of Hematology/Oncology, Laura and Isaac Perlmutter Cancer Center, and Genome Technology Center, New York University Langone Medical Center, New York, New York, USA.
authors.forename: Christina
authors.initials: C
authors.lastname: Adaniel
authors.affiliation: Division of Hematology/Oncology, Laura and Isaac Perlmutter Cancer Center, and Genome Technology Center, New York University Langone Medical Center, New York, New York, USA.
authors.forename: Komal
authors.initials: K
authors.lastname: Jhaveri
authors.affiliation: Division of Hematology/Oncology, Laura and Isaac Perlmutter Cancer Center, and Genome Technology Center, New York University Langone Medical Center, New York, New York, USA.
authors.forename: Adriana
authors.initials: A
authors.lastname: Heguy
authors.affiliation: Division of Hematology/Oncology, Laura and Isaac Perlmutter Cancer Center, and Genome Technology Center, New York University Langone Medical Center, New York, New York, USA francisco.esteva@nyumc.org.
authors.forename: Francisco J
authors.initials: FJ
authors.lastname: Esteva
mesh_terms: D001943:Breast Neoplasms / Q000145:classification / Q000175:diagnosis / Q000235:genetics*; D005260:Female; D020869:Gene Expression Profiling / Q000191:economics / Q000379:methods; D015894:Genome, Human; D018398:Homeodomain Proteins / Q000032:analysis / Q000235:genetics; D006801:Humans; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000032:analysis / Q000235:genetics; D011960:Receptors, Estrogen / Q000032:analysis / Q000235:genetics; D018123:Receptors, Interleukin / Q000032:analysis / Q000235:genetics; D053722:Receptors, Interleukin-17; D012008:Recurrence; D018570:Risk Assessment
chemical_list: D018398:Homeodomain Proteins; D018719:Erb-b2 Receptor Tyrosine Kinases; D011960:Receptors, Estrogen; D018123:Receptors, Interleukin; D053722:Receptors, Interleukin-17; C484414:HOXB13 protein, human; C408922:IL17RB protein, human; C508053:ERBB2 protein, human
keywords: Breast cancer; Gene expression; Genomic profiling