Detection of prostate cancer using serum proteomics pattern in a histologically confirmed population

Purpose: We retrospectively identified a panel of serum proteins that can discriminate between men with prostate cancer (clinically organ confined) and men with benign prostate disease. Materials and Methods: A contemporary set of 345 men who had an archival serum sample available were included in this study. The cancer group consisted of 246 men who underwent radical prostatectomy at the Johns Hopkins Hospital between March 1999 and April 2001. The noncancer group included 99 men with no histological evidence of prostate cancer on biopsy between April 1997 and April 2001 at the same institution. Serum proteomics mass spectra of these patients were generated using ProteinChip arrays and a ProteinChip Biomarker System II surface enhanced laser desorption/ionization time of flight mass spectrometer (Ciphergen Biosystems, Inc., Fremont, California). The cases and controls were randomly split into training and testing groups by a stratified sampling procedure. A combination of bioinformatics tools including ProPeak (3Z Informatics, Charleston, South Carolina) was used to reveal the optimal panel of biomarkers for maximum separation of the prostate cancer and the benign prostate disease cohorts. Results: A panel of 3 proteins (PC-1, PC-2 and PC-3) was selected using the training data. Performance of each of the protein markers and a linear regression derived composite index (PC-com3) were evaluated on the testing data. The area under the curve for prostate specific antigen (PSA), PC-1, PC-2, PC-3 and PC-com3 was 0.542, 0.585, 0.600, 0.636 and 0.643, respectively. Improvement of PC-com3 compared to PSA is observed at specificity range 30% to 80%. At a selected specificity of 45% the sensitivity of PC-com3 is 76%, significantly better than the PSA sensitivity of 57% (p <0.0001). Conclusions: Serum proteomics patterns may potentially aid in the early detection of prostate cancer.