Integrative analysis of N-linked human glycoproteomic data sets reveals PTPRF ectodomain as a novel plasma biomarker candidate for prostate cancer.

ABSTRACT

In an attempt to identify prostate cancer biomarkers with greater diagnostic and prognostic capabilities, we have developed an integrative proteomic discovery workflow focused on N-linked glycoproteins that refines the target selection process. In this work, hydrazide-based chemistry was used to identify N-linked glycopeptides from 22Rv1 prostate cancer cells cultured in vitro, which were compared with glycopeptides identified from explanted 22Rv1 murine tumor xenografts. One hundred and four human glycoproteins were identified in the former analysis and 75 in the latter, with 40 proteins overlapping between data sets. Of the 40 overlapping proteins, 80% have multiple literature references to the neoplastic process and ∼40% to prostatic neoplasms. These include a number of well-known prostate cancer-associated biomarkers, such as prostate-specific membrane antigen (PSMA). By integrating gene expression data and available literature, we identified members of the overlap data set that deserve consideration as potential prostate cancer biomarkers. Specifically, the identification of the extracellular domain of protein tyrosine phosphatase receptor type F (PTPRF) was of particular interest due to the direct involvement of PTPRF in the control of ß-catenin signaling, as well as dramatically elevated gene expression levels in the prostate compared to other tissues. In this investigation, we demonstrate that the PTPRF E-subunit is more abundant in human prostate tumor tissue compared to normal control and also detectable in murine plasma by immunoblot and ELISA. Specifically, PTPRF distinguishes between animals xenografted with the 22Rv1 cells and control animals as early as 14 days after implantation. This result suggests that the ectodomain of PTPRF has the potential to function as a novel plasma or tissue-based biomarker for prostate cancer. The workflow described adds to the literature of potential biomarker candidates for prostate cancer and demonstrates a pathway to developing new diagnostic assays.