Differential proteomic analysis of pathway biomarkers in human breast cancer by integrated bioinformatics

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.