Application of Functional Proteomic in the Diagnosis and Treatment of Breast Cancers

Breast cancer is the second cause of death from cancer among women. It consists of heterogeneous group of different tumor subtypes that vary in prognosis and response to therapy. Genetic aproaches have provide opportunities in defining the genetic and histological basis of breast cancer, leading to classification and targeted treatment. Despite this, the survival is modest. Cancer is a proteomic disease although genomic information illsuatrate the genetic basis of cancer but proteins do all of the work of the cell and they are the ultimate effector molecule of cellular functions. The genomic approach has some limitations. It does not show posttranslational modification that affects protein function. Currently because of rapid development in proteomic technologies with reproducibility and sensitivity, proteomics can be applied to extract important biological information to aid in understanding the cancer biology. The study of functional proteomics have advantages in related to genomics. At first, it canprovide high-throughput analysis of both basal and posttranslational modification of proteins such as phosphorylation and glycosylation of proteins that are important in carcinogenesis and tumor progression of breast cancer. It can provide study of protein-protein interactions and identify of hub proteins, effector and signaling pathways, so leads to move from single-marker/single-pathway study to global study. Functional pathway-based proteomic biomarkers can provide better classification of breast cancer and personalized treatment. For this resean, proteomic technologies like mass spectrometry, isotope labeling with amino acids, reverse-phase protein array (RPPA) and tissue microarray techniques can use. RPPA-based classification will complement gene expression-based classification. It is expected that proteomic approaches can provide opportunities to identify specific and sensitive proteins or biomarkers that could be used in clinical applications

Keywords:

Proteomics , Biomarker , Breast Cancer