Interpretation of
proteome data with a focus on
biomarker discovery largely relies on comparative
proteome analyses. Here, we introduce a database-assisted interpretation strategy based on
proteome profiles of primary cells. Both 2-D-PAGE and shotgun proteomics are applied. We obtain high data concordance with these two different techniques. When applying mass analysis of tryptic spot digests from 2-D
gels of cytoplasmic fractions, we typically identify several hundred
proteins. Using the same
protein fractions, we usually identify more than thousand
proteins by shotgun proteomics. The data consistency obtained when comparing these independent data sets exceeds 99% of the
proteins identified in the 2-D
gels. Many characteristic differences in
protein expression of different cells can thus be independently confirmed. Our self-designed SQL database (CPL/MUW - database of the Clinical Proteomics Laboratories at the Medical University of Vienna accessible via www.meduniwien.ac.at/proteomics/database) facilitates (i) quality management of
protein identification data, which are based on MS, (ii) the detection of cell type-specific
proteins and (iii) of molecular signatures of specific functional cell states. Here, we demonstrate, how the interpretation of
proteome profiles obtained from human liver tissue and
hepatocellular carcinoma tissue is assisted by the Clinical Proteomics Laboratories at the Medical University of Vienna-database. Therefore, we suggest that the use of reference experiments supported by a tailored database may substantially facilitate data interpretation of
proteome profiling experiments.