Cancers develop over a period of several years and they are characterized by molecular changes prior to invasion and metastasis. Development of a technology that enables screening of cancer from body fluids could permit cancer detection at early and treatable stages. It is expected that the composition of the serum proteome contains valuable information about the state of the human body in health and disease, and that this information can be extracted via quantitative proteomic measurements. Suitable proteomic techniques need to be sensitive, reproducible and robust, to detect potential biomarkers below the level of highly expressed proteins, to generate data sets that are comparable between experiments and laboratories, and have high throughput to support studies with sufficient statistical power. In this proposal, we will develop a method for high throughput quantitative analysis of serum proteins. It consists of the selective isolation of the peptides that are N-linked glycosylated in the intact protein using solid-phase extraction of glycopeptides (SPEG) on a robotic workstation, the analysis of these now de-glycosylated peptides by liquid chromatography mass spectrometry (LC-MS), and the comparative analysis of the resulting patterns. By focusing selectively on a few formerly N-linked glycopeptides per serum protein, the complexity of the analyte sample is significantly reduced, and the sensitivity, reproducibility, and throughput of serum proteome analysis are increased compared with the analysis of total tryptic peptides from unfractionated samples. We will explore the feasibility to identify cancer-specific serum proteins in the background of normal variation using a carcinogen-induced skin cancer mouse model.
The specific aims are: 1) To develop chemistries and protocols for an automatic robotic system to isolate N-linked glycopeptides from serum in a high throughput and highly reproducible fashion; 2) To develop efficient and reproducible procedures for LC-MS analyses, and sequence identification of discriminatory peptides by tandem mass spectrometry; 3) To explore the feasibility of this method for the identification of distinctive serum peptides specific to cancer-bearing mice in the background of normal variations. If successful, the proposed research could subsequently be used for profiling human serum samples from cancer patients and normal individuals to identify the cancer-associated proteins in serum. The identified biomarkers will open a new paradigm for performing screening and detection of human cancer at early stage and for clinical therapeutic management.
|Aiyetan, Paul; Zhang, Bai; Chen, Lily et al. (2014) M2Lite: An Open-source, Light-weight, Pluggable and Fast Proteome Discoverer MSF to mzIdentML Tool. J Bioinform 1:40-49|
|Liu, Yansheng; Chen, Jing; Sethi, Atul et al. (2014) Glycoproteomic analysis of prostate cancer tissues by SWATH mass spectrometry discovers N-acylethanolamine acid amidase and protein tyrosine kinase 7 as signatures for tumor aggressiveness. Mol Cell Proteomics 13:1753-68|
|Baycin-Hizal, Deniz; Gottschalk, Allan; Jacobson, Elena et al. (2014) Physiologic and pathophysiologic consequences of altered sialylation and glycosylation on ion channel function. Biochem Biophys Res Commun 453:243-53|
|Ao, Ming-Hui; Zhang, Hui; Sakowski, Lynne et al. (2014) The utility of a novel triple marker (combination of TTF1, napsin A, and p40) in the subclassification of non-small cell lung cancer. Hum Pathol 45:926-34|
|Sun, Shisheng; Zhou, Jian-Ying; Yang, Weiming et al. (2014) Inhibition of protein carbamylation in urea solution using ammonium-containing buffers. Anal Biochem 446:76-81|
|Aiyetan, Paul; Zhang, Bai; Zhang, Zhen et al. (2014) XGlycScan: An Open-source Software For N-linked Glycosite Assignment, Quantification and Quality Assessment of Data from Mass Spectrometry-based Glycoproteomic Analysis. MOJ Proteom Bioinform 1:|
|Chen, Jing; Toghi Eshghi, Shadi; Bova, George Steven et al. (2013) Epithelium percentage estimation facilitates epithelial quantitative protein measurement in tissue specimens. Clin Proteomics 10:18|
|Li, Qing Kay; Shah, Punit; Li, Yan et al. (2013) Glycoproteomic analysis of bronchoalveolar lavage (BAL) fluid identifies tumor-associated glycoproteins from lung adenocarcinoma. J Proteome Res 12:3689-96|
|Sun, Shisheng; Zhang, Bai; Aiyetan, Paul et al. (2013) Analysis of N-glycoproteins using genomic N-glycosite prediction. J Proteome Res 12:5609-15|
|Tian, Yuan; Kelly-Spratt, Karen S; Kemp, Christopher J et al. (2010) Mapping tissue-specific expression of extracellular proteins using systematic glycoproteomic analysis of different mouse tissues. J Proteome Res 9:5837-47|
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