18 O Labeling for a Quantitative Proteomic Analysis of Glycoproteins in Hepatocellular Carcinoma

Clinical Proteomics

Akhilesh Pandey¹  Min-Sik Kim⁵  Anuradha Nalli³  Michael Torbenson²  Raghothama Chaerkady³  Paul J. Thuluvath⁴  Perumal Vivekanandan²  Jessica Simmers⁵ 

[1] McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, USA;Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, USA;Institute of Bioinformatics, International Technology Park, Bangalore, IndiaMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USAInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USAInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USAInstitute of Bioinformatics, International Technology Park, Bangalore, IndiaMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USA;Departments of Hepatology and Liver Transplantation, Johns Hopkins University School of Medicine, Baltimore, USADepartments of Hepatology and Liver Transplantation, Johns Hopkins University School of Medicine, Baltimore, USADepartments of Hepatology and Liver Transplantation, Johns Hopkins University School of Medicine, Baltimore, USA;McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USAMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USADepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, USA

关键词: Hepatocellular carcinoma;    Lectin affinity enrichment;    Quantitative proteomics;    Mass spectrometry;   

DOI  :  10.1007/s12014-008-9013-0

来源: Humana Press Inc

【 摘 要 】

Abstract

Introduction

Quantitative proteomics using tandem mass spectrometry is an attractive approach for identification of potential cancer biomarkers. Fractionation of complex tissue samples into subproteomes prior to mass spectrometric analyses increases the likelihood of identifying cancer-specific proteins that might be present in low abundance. In this regard, glycosylated proteins are an interesting class of proteins that are already established as biomarkers for several cancers.

Materials and Methods

In this study, we carried out proteomic profiling of tumor and adjacent non-cancer liver tissues from hepatocellular carcinoma (HCC) patients. Glycoprotein enrichment from liver samples using lectin affinity chromatography and subsequent ¹⁸O/¹⁶O labeling of peptides allowed us to obtain relative abundance levels of lectin-bound proteins. As a complementary approach, we also examined the relative expression of proteins in HCC without glycoprotein enrichment. Lectin affinity enrichment was found to be advantageous to quantitate several interesting proteins, which were not detected in the whole proteome screening approach. We identified and quantitated over 200 proteins from the lectin-based approach. Interesting among these were fetuin, cysteine-rich protein 1, serpin peptidase inhibitor, leucine-rich alpha-2-glycoprotein 1, melanoma cell adhesion molecule, and heparan sulfate proteoglycan-2. Using lectin affinity followed by PNGase F digestion coupled to ¹⁸O labeling, we identified 34 glycosylation sites with consensus sequence N-X-T/S. Western blotting and immunohistochemical staining were carried out for several proteins to confirm mass spectrometry results.

Conclusion

This study indicates that quantitative proteomic profiling of tumor tissue versus non-cancerous tissue is a promising approach for the identification of potential biomarkers for HCC.

【 授权许可】

Unknown