Kiran Turaga1, Geza Acs, Christine Laronga. 1. Department of Women's Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA.
Abstract
BACKGROUND: Breast cancer is a heterogeneous group of different tumor subtypes that vary in prognosis and response to therapy. This heterogeneity has spawned an era of molecular assays striving to classify and thus predict outcome, thereby guiding the future in targeted personalized treatment strategies. METHODS: This article provides an overview of the development and application of molecular assays as applied to breast cancer. Differences in the technology used for these tests as well as scientific evidence supporting the validity of the gene expression profile are discussed. Examples of the clinical applicability of these assays are provided, but these represent only a fraction of the potential uses yet to be discovered. A comparison of the three most commonly used assays is included. RESULTS: Molecular assays have provided new genetic approaches to unravel the complexities of clinical specimens relevant to breast cancer treatment planning and assessment of outcome. In particular, on a molecular level specific to the woman's tumor, these assays allow a prediction of outcome (prognosis) in terms of low and high risk for the future development of distant metastatic disease. Additionally, one assay, Oncotype DX (Genomic Health Inc, Redwood City, CA), allows for the prediction of benefit of the addition of chemotherapy to hormone therapy alone. CONCLUSIONS: While incorporation of molecular assays into the treatment planning strategy of breast cancer continues to be a work in progress, this approach is evolving quickly due to strong scientific evidence to become standard of practice in the near future. The possibilities of these assays in terms of clinical investigation are limitless, but currently their general applicability is limited to less than half of the population of women presenting with breast cancer.
BACKGROUND:Breast cancer is a heterogeneous group of different tumor subtypes that vary in prognosis and response to therapy. This heterogeneity has spawned an era of molecular assays striving to classify and thus predict outcome, thereby guiding the future in targeted personalized treatment strategies. METHODS: This article provides an overview of the development and application of molecular assays as applied to breast cancer. Differences in the technology used for these tests as well as scientific evidence supporting the validity of the gene expression profile are discussed. Examples of the clinical applicability of these assays are provided, but these represent only a fraction of the potential uses yet to be discovered. A comparison of the three most commonly used assays is included. RESULTS: Molecular assays have provided new genetic approaches to unravel the complexities of clinical specimens relevant to breast cancer treatment planning and assessment of outcome. In particular, on a molecular level specific to the woman's tumor, these assays allow a prediction of outcome (prognosis) in terms of low and high risk for the future development of distant metastatic disease. Additionally, one assay, Oncotype DX (Genomic Health Inc, Redwood City, CA), allows for the prediction of benefit of the addition of chemotherapy to hormone therapy alone. CONCLUSIONS: While incorporation of molecular assays into the treatment planning strategy of breast cancer continues to be a work in progress, this approach is evolving quickly due to strong scientific evidence to become standard of practice in the near future. The possibilities of these assays in terms of clinical investigation are limitless, but currently their general applicability is limited to less than half of the population of women presenting with breast cancer.
Authors: Jennifer E Joh; Nicole N Esposito; John V Kiluk; Christine Laronga; M Catherine Lee; Loretta Loftus; Hatem Soliman; Judy C Boughey; Carol Reynolds; Thomas J Lawton; Peter I Acs; Lucio Gordan; Geza Acs Journal: Oncologist Date: 2011-10-20
Authors: Anne A Eaton; Catherine E Pesce; James O Murphy; Michelle M Stempel; Sujata M Patil; Edi Brogi; Clifford A Hudis; Mahmoud El-Tamer Journal: Breast Cancer Res Treat Date: 2016-12-07 Impact factor: 4.872
Authors: Piya Lahiry; Leo J Lee; Brendan J Frey; C Anthony Rupar; Victoria M Siu; Benjamin J Blencowe; Robert A Hegele Journal: PLoS One Date: 2011-09-27 Impact factor: 3.240
Authors: Zsuzsanna Varga; Peter Sinn; Florian Fritzsche; Arthur von Hochstetter; Aurelia Noske; Peter Schraml; Christoph Tausch; Andreas Trojan; Holger Moch Journal: PLoS One Date: 2013-03-07 Impact factor: 3.240