Abstract. The aim of this study was to better understand the altered functional modules in breast cancer at pathway and network levels. An integrated bioinformatics analysis of differentially expressed proteins in human breast cancer was performed. Breast cancer protein profiles were constructed by data mining proteins in literature and public databases, including 1031 proteins with 153 secretory and 69 cell surface proteins. An experimental investigation was performed by two-dimensional electrophoresis, and 4 proteins were further validated by western blotting. Enriched bioinformatics functions were clustered. This study may be used as a reference in further studies to help identify the underlying biological interactions associated with breast cancer and discover potential cancer targets.
IntroductionBreast cancer is the most common neoplasia in women and its pathogenesis is related to an acquired or inherited genetic disorder influenced by environmental, behavioral or reproductive factors (1). Cancer biomarker discovery is important for both cancer biology and clinical applications. These markers may come from DNA, RNA, miRNA or proteins (2), with proteins being the most significant (3).The development and improvement of biotechnologies has allowed researchers to perform high-throughput analyses of genomes, transcriptomes and proteomes in health and disease, and identify hundreds of potential biomarkers (4), offering the potential to discover diagnostic, prognostic or therapeutic targets. However, less than two dozen cancer biomarkers are currently approved by the Food and Drug Administration (FDA) (5), including only 9 protein biomarkers identified in the blood (6). Due to the lack of sensitivity and specificity of these known biomarkers (7), researchers continue to search for more significant targets. Proteomics is a promising approach for the discovery of cancer targets and biomarkers (8). The mapping of proteome profiles and differential proteomics has been widely performed in breast cancer to identify potential biomarkers (9). The identified proteins were reported to have potential clinical significance, and certain proteins may be used as potential diagnostic, prognostic or predictive biomarkers (10,11,12,13,14). However, due to the heterogeneity in the different studies, including experimental design, sample collection and classification and analytical method (15), these results lack good reproducibility and require further validation before they can be used in clinical detection and to explain the underlying mechanisms of breast cancer. In addition, few protein candidates were warranted to be specific to breast cancer, and were often differentially expressed in other cancer types (16). Hence, research encountered the challenge of how to decipher and use these individual results and bring them into clinical applications. In addition, an understanding of the underlying biological mechanisms of carcinogenesis and the altered molecular events in breast cancer at integrated pathway levels is necessary. Prot...