Breast Cancer Implications of Functional Proteomics in Breast Cancer
Functional proteomics is a rapidlyevolving field that will have "vast clinical implications in thenear future" in improving diagnosis through better classification of breast cancer and in predicting prognosis and response to different therapies.
Abstract
Breast cancer is one of themajor public health problemsof the Western world. Recent advances in genomics and gene expression-profiling approaches have enriched our understanding of this heterogeneous disease. However, progress in functional proteomics in breast cancer research has been relatively slow. Allied with genomics, the functional proteomics approach will be important in improving diagnosis through better classificationofbreast cancer and inpredicting prognosis and response to different therapies, including chemotherapy, hormonal therapy, and targeted therapy. In this review,wewill present functional proteomic approaches with a focus on the recent clinical implicationsof utilizing the reverse-phase protein arrayplatform inbreast cancer research.TheOncologist 2014;19:328–335 Implications forPractice:Functional proteomics is a rapidlyevolving field thatwill havevast clinical implications in thenear future. Therefore, it is important tounderstand its conceptand role in thediagnosis, prognostication, and treatment inbreastcancer.Mass spectrometry serves as a discovery platform,whereas reverse-phase protein array (RPPA) serves as a validation platform in breast cancer research. RPPA-based classification will complement gene expression-based classification. RPPA-based breast cancer subgroups are shown to be both prognostic of survival and predictive of response to chemotherapy. Prognostic or predictive protein panels in breast cancer will lead to discovery of novel therapeutic targets in breast cancer treatment.