• Identification of Stage-Specific Breast Markers using Quantitative Proteomics

      Shaheed, Sadr-ul; Rustogi, Nitin; Scally, Andy J.; Wilson, J.; Thygesen, H.; Loizidou, M.A.; Hadjisavvas, A.; Hanby, A.; Speirs, V.; Loadman, Paul M.; et al. (2013)
      Matched healthy and diseased tissues from breast cancer patients were analyzed by quantitative proteomics. By comparing proteomic profiles of fibroadenoma (benign tumors, three patients), DCIS (noninvasive cancer, three patients), and invasive ductal carcinoma (four patients), we identified protein alterations that correlated with breast cancer progression. Three 8-plex iTRAQ experiments generated an average of 826 protein identifications, of which 402 were common. After excluding those originating from blood, 59 proteins were significantly changed in tumor compared with normal tissues, with the majority associated with invasive carcinomas. Bioinformatics analysis identified relationships between proteins in this subset including roles in redox regulation, lipid transport, protein folding, and proteasomal degradation, with a substantial number increased in expression due to Myc oncogene activation. Three target proteins, cofilin-1 and p23 (increased in invasive carcinoma) and membrane copper amine oxidase 3 (decreased in invasive carcinoma), were subjected to further validation. All three were observed in phenotype-specific breast cancer cell lines, normal (nontransformed) breast cell lines, and primary breast epithelial cells by Western blotting, but only cofilin-1 and p23 were detected by multiple reaction monitoring mass spectrometry analysis. All three proteins were detected by both analytical approaches in matched tissue biopsies emulating the response observed with proteomics analysis. Tissue microarray analysis (361 patients) indicated cofilin-1 staining positively correlating with tumor grade and p23 staining with ER positive status; both therefore merit further investigation as potential biomarkers.
    • Quantitative proteomic profiling of matched normal and tumor breast tissues.

      Sutton, Chris W.; Rustogi, Nitin; Gurkan, C.; Scally, Andy J.; Loizidou, M.A.; Hadjisavvas, A.; Kyriacou, K. (2010)
      Proteomic analysis of breast cancer tissue has proven difficult due to its inherent histological complexity. This pilot study presents preliminary evidence for the ability to differentiate adenoma and invasive carcinoma by measuring changes in proteomic profile of matched normal and disease tissues. A dual lysis buffer method was used to maximize protein extraction from each biopsy, proteins digested with trypsin, and the resulting peptides iTRAQ labeled. After combining, the peptide mixtures they were separated using preparative IEF followed by RP nanoHPLC. Following MALDI MS/MS and database searching, identified proteins were combined into a nonredundant list of 481 proteins with associated normal/tumor iTRAQ ratios for each patient. Proteins were categorized by location as blood, extracellular, and cellular, and the iTRAQ ratios were normalized to enable comparison between patients. Of those proteins significantly changed (upper or lower quartile) between matched normal and disease tissues, those from two invasive carcinoma patients had >50% in common with each other but <22% in common with an adenoma patient. In invasive carcinoma patients, several cellular and extracellular proteins that were significantly increased (Periostin, Small breast epithelial mucin) or decreased (Kinectin) have previously been associated with breast cancer, thereby supporting this approach for a larger disease-stage characterization effort.