Novel prostate cancer biomarkers derived from autoantibody signatures.

Background: Due to the low specificity of the prostate-specific antigen (PSA) assay and a high false positive rate, a large number of prostate cancer (PCA) biopsies are performed unnecessarily. Consequently, there is a need for new biomarkers that can identify PCA at any stage of progression while limiting the number of false positives. The use of autoantibody signature-developed biomarkers has proven to be an effective method to solve this problem.

Results: Using T7 phage-peptide detection, we identified a panel of eight biomarkers for PCA on a training set. The estimated receiver-operating characteristic (ROC) curve had an area under the ROC curve of 0.69 when applied to the validation set. Spearman correlations were high, within 0.7 to 0.9, indicating that the biomarkers have a degree of inter-relatedness. The identified biomarkers play a role in processes such as androgen response regulation and cellular structural integrity and are proteins that are thought to play a role in prostate tumorigenesis.

Conclusions: Autoantibodies against PCA can be developed as biomarkers for detecting PCA. The scores from the algorithm developed here can be used to indicate a relative high or low risk of PCA, particularly for patients with intermediate (4.0 to 10 ng/ml) PSA levels. Since most commercially available assays test for PSA or have a PSA component, this novel approach has the potential to improve diagnosis of PCA using a biologic measure independent of PSA.