Proteomic analysis of breast cancer tissues to identify biomarker candidates by gel-assisted digestion and label-free quantification methods using LC-MS/MS

Abstract

This study presents a proteomic method that differentiates between matched normal and breast tumor tissues from ductal carcinoma in situ (DCIS) and invasive carcinoma from Korean women, to identify biomarker candidates and to understand pathogenesis of breast cancer in protein level. Proteins from tissues obtained by biopsy were extracted by RIPA buffer, digested by the gel-assisted method, and analyzed by nano-UPLC-MS/MS. From proteomic analysis based on label-free quantitation strategy, a non-redundant list of 298 proteins was identified from the normal and tumor tissues, and 244 proteins were quantified using IDEAL-Q software. Hierarchical clustering analysis showed two patterns classified as two groups, invasive carcinoma and DCIS, suggesting a difference between two carcinoma at the protein expression level as expected. Differentially expressed proteins in tumor tissues compared to the corresponding normal tissues were related to three biological pathways: antigen-processing and presentation, glycolysis/gluconeogenesis, and complement and coagulation cascades. Among them, the up-regulation of calreticulin (CRT) and protein disulfide isomerase A3 (PDIA3) was confirmed by Western blot analysis. In conclusion, this study showed the possibility of identifying biomarker candidates for breast cancer using tissues and might help to understand the pathophysiology of this cancer at the protein level.