Prostate cancer is the most prevalent type of cancer for U.S. men (about 192,280 new cases this year), and it is the second highest contributor to cancer death among men in the U.S. (27,360 will die of it this year). A major issue in prostate cancer detection and therapy is that we currently have no method to reliably distinguish aggressive prostate cancer from non-aggressive prostate cancer using available biomarkers. This leads to significant unnecessary suffering among prostate cancer patients and leads to massive unnecessary health care expenditures. We hypothesize that specific glycoproteins and glycan modifications of glycoproteins can be used to distinguish aggressive from non-aggressive prostate cancer in tissue and serum. We propose in four specific aims to develop novel glycoprotein biomarkers that can detect aggressive cancer in primary tissues and pre-surgical serum.
In Aim 1, we will analyze glycans and glycoproteins from metastatic, aggressive cancer, non-aggressive cancer, and normal prostate tissues to identify glycoproteins associated with aggressive prostate cancer.
In Aim 2, we will develop highly sensitive, specific, and high throughput MS based SRM assays for the candidate glycopeptides identified from Aim 1. We will optimize the SRM assays and determine their analytical performance, and construct an SRM database and make the assay available to the research community.
In Aim 3, we will use the developed SRM assays from Aim 2 to verify the glycoproteins for aggressive prostate cancer in additional prostate cancer tissues and validate these tissue glycoproteins using tissue microarrays.
In Aim 4, we will use the SRM assays to determine which of the verified glycopeptides in tissues can be detected in patient's sera, and therefore can be used as serum tests. Then, we will apply the SRM assays to the serum samples and develop validate multivariate models for detecting aggressive prostate cancer using serum tests. In addition, we will validate these markers and multivariate models using an independent testing set of prostate cancer serum. If successful, the identified and validated biomarkers will be tested by EDRN biomarker reference (BRL) and clinical validation (CVC) laboratories in retrospective and prospective studies. Biomarkers capable of distinguishing aggressive from nonaggressive prostate cancer would present men with non-aggressive prostate cancer from overtreatment, and could allow men with aggressive cancer to receive appropriate treatment earlier in the course of their diseases. SRM = selected reaction monitoring
|Thomas, Stefani N; Zhang, Hui (2016) Targeted proteomic assays for the verification of global proteomics insights. Expert Rev Proteomics :1-3|
|Lilo, Mohammed T; Allison, Derek; Wang, Yuting et al. (2016) Expression of P40 and P63 in lung cancers using fine needle aspiration cases. Understanding clinical pitfalls and limitations. J Am Soc Cytopathol 5:123-132|
|Sun, Shisheng; Shah, Punit; Eshghi, Shadi Toghi et al. (2016) Comprehensive analysis of protein glycosylation by solid-phase extraction of N-linked glycans and glycosite-containing peptides. Nat Biotechnol 34:84-8|
|Toghi Eshghi, Shadi; Yang, Weiming; Hu, Yingwei et al. (2016) Classification of Tandem Mass Spectra for Identification of N- and O-linked Glycopeptides. Sci Rep 6:37189|
|Yang, Shuang; Rubin, Abigail; Eshghi, Shadi Toghi et al. (2016) Chemoenzymatic method for glycomics: Isolation, identification, and quantitation. Proteomics 16:241-56|
|Yang, Weiming; Jackson, Brooks; Zhang, Hui (2016) Identification of glycoproteins associated with HIV latently infected cells using quantitative glycoproteomics. Proteomics 16:1872-80|
|Li, Qing Kay; Chen, Li; Ao, Ming-Hui et al. (2015) Serum fucosylated prostate-specific antigen (PSA) improves the differentiation of aggressive from non-aggressive prostate cancers. Theranostics 5:267-76|
|Shah, Punit; Zhang, Bai; Choi, Caitlin et al. (2015) Tissue proteomics using chemical immobilization and mass spectrometry. Anal Biochem 469:27-33|
|Li, Yan; Shah, Punit; De Marzo, Angelo M et al. (2015) Identification of glycoproteins containing specific glycans using a lectin-chemical method. Anal Chem 87:4683-7|
|Thomas, Stefani N; Harlan, Robert; Chen, Jing et al. (2015) Multiplexed Targeted Mass Spectrometry-Based Assays for the Quantification of N-Linked Glycosite-Containing Peptides in Serum. Anal Chem 87:10830-8|
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