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1.
Biochim Biophys Acta Gen Subj ; 1864(11): 129682, 2020 11.
Article in English | MEDLINE | ID: mdl-32663515

ABSTRACT

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) has the lowest survival rate of all major cancers. Surgery is the only curative intent therapy, but the majority of patients experience disease relapse. Thus, patients who do not benefit from highly morbid surgical resection needs to be identified and offered palliative chemotherapy instead. In this pilot study, we aimed to identify differentially regulated proteins in plasma and plasma derived microparticles from PDAC patients with poor and good prognosis. METHODS: Plasma and plasma derived microparticle samples were obtained before surgical resection from PDAC patients. Sequential Windowed Acquisition of all Theoretical fragment ion spectra - Mass Spectrometry (SWATH-MS) proteomic analysis was performed to identify and quantify proteins in these samples. Statistical analysis was performed to identify biomarkers for poor prognosis. RESULTS: A total of 482 and 1024 proteins were identified from plasma and microparticle samples, respectively, by SWATH-MS analysis. Statistical analysis of the data further identified nine and six differentially (log2ratio > 1, p < .05) expressed proteins in plasma and microparticles, respectively. Protein tyrosine phosphatases, PTPRM and PTPRB, were decreased in plasma of patients with poor PDAC prognosis, while proteasomal subunit PSMD11 was increased in microparticles of patients with poor prognosis. CONCLUSION AND GENERAL SIGNIFICANCE: A novel blood-based biomarker signature for PDAC prognosis was identified.


Subject(s)
Carcinoma, Pancreatic Ductal/blood , Pancreatic Neoplasms/blood , Proteasome Endopeptidase Complex/blood , Receptor-Like Protein Tyrosine Phosphatases, Class 2/blood , Receptor-Like Protein Tyrosine Phosphatases, Class 3/blood , Aged , Biomarkers, Tumor/blood , Carcinoma, Pancreatic Ductal/diagnosis , Disease Progression , Female , Humans , Male , Middle Aged , Pancreatic Neoplasms/diagnosis , Pilot Projects , Prognosis , Proteomics , Retrospective Studies
2.
J Proteome Res ; 11(5): 2653-65, 2012 May 04.
Article in English | MEDLINE | ID: mdl-22494190

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.


Subject(s)
Gene Expression Regulation, Neoplastic , Glycoproteins/analysis , Prostatic Neoplasms/diagnosis , Proteomics/methods , Receptor-Like Protein Tyrosine Phosphatases, Class 2/metabolism , Animals , Biomarkers, Tumor/blood , Biomarkers, Tumor/metabolism , Blotting, Western , Enzyme-Linked Immunosorbent Assay , Glycoproteins/genetics , Glycoproteins/metabolism , Glycosylation , Humans , Male , Mice , Mice, Inbred NOD , Mice, SCID , Prostatic Neoplasms/genetics , Prostatic Neoplasms/metabolism , Protein Structure, Tertiary , Receptor-Like Protein Tyrosine Phosphatases, Class 2/blood , Receptor-Like Protein Tyrosine Phosphatases, Class 2/genetics , Time Factors , Xenograft Model Antitumor Assays , beta Catenin/genetics , beta Catenin/metabolism
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