Chaerkady Raghothama, Thuluvath Paul J, Kim Min-Sik, Nalli Anuradha, Vivekanandan Perumal, Simmers Jessica, Torbenson Michael, Pandey Akhilesh
Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India; McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Clin Proteomics. 2008 Jul 18;4(3-4):137-155. doi: 10.1007/s12014-008-9013-0.
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 (18)O/(16)O 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 (18)O 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.
使用串联质谱的定量蛋白质组学是鉴定潜在癌症生物标志物的一种有吸引力的方法。在进行质谱分析之前，将复杂的组织样本分离成亚蛋白质组，增加了鉴定可能以低丰度存在的癌症特异性蛋白质的可能性。在这方面，糖基化蛋白质是一类有趣的蛋白质，它们已被确立为几种癌症的生物标志物。
在本研究中，我们对肝细胞癌（HCC）患者的肿瘤及相邻非癌肝组织进行了蛋白质组分析。使用凝集素亲和色谱从肝脏样本中富集糖蛋白，并随后对肽段进行（18）O/（16）O标记，使我们能够获得凝集素结合蛋白的相对丰度水平。作为一种补充方法，我们还检测了未进行糖蛋白富集的HCC中蛋白质的相对表达。发现凝集素亲和富集有利于定量几种有趣的蛋白质，这些蛋白质在全蛋白质组筛选方法中未被检测到。我们从基于凝集素的方法中鉴定并定量了200多种蛋白质。其中有趣的有胎球蛋白、富含半胱氨酸蛋白1、丝氨酸蛋白酶抑制剂、富含亮氨酸的α-2-糖蛋白1、黑色素瘤细胞粘附分子和硫酸乙酰肝素蛋白聚糖-2。通过凝集素亲和结合PNGase F消化并结合（18）O标记，我们鉴定了34个具有一致序列N-X-T/S的糖基化位点。对几种蛋白质进行了蛋白质印迹和免疫组织化学染色以确认质谱结果。
本研究表明，肿瘤组织与非癌组织的定量蛋白质组分析是鉴定HCC潜在生物标志物的一种有前景的方法。
