Integrated peptide and glycan biomarker discovery using MALDI-TOF mass spectrometry

Development of a monoclonal antibody to ITPRIPL1 for immunohistochemical diagnosis of non-small cell lung cancers: accuracy and correlation with CD8+ T cell infiltration

Introduction: Cancer biomarkers are substances or processes highly associated with the presence and progression of cancer, which are applicable for cancer screening, progression surveillance, and prognosis prediction in clinical practice. In our previous studies, we discovered that cancer cells upregulate inositol 1,4,5-triphosphate receptor-interacting protein-like 1 (ITPRIPL1), a natural CD3 ligand, to evade immune surveillance and promote tumor growth. We also developed a monoclonal ITPRIPL1 antibody with high sensitivity and specificity. Here, we explored the application of anti-ITPRIPL1 antibody for auxiliary diagnosis of non-small cell lung cancer (NSCLC). Methods: NSCLC patient tissue samples (n = 75) were collected and stained by anti-ITPRIPL1 or anti-CD8 antibodies. After excluding the flaked samples (n = 15), we evaluated the expression by intensity (0-3) and extent (0-100%) of staining to generate an h-score for each sample. The expression status was classified into negative (h-score < 20), low-positive (20-99), and high-positive (≥ 100). We compared the h-scores between the solid cancer tissue and stroma and analyzed the correlation between the h-scores of the ITPRIPL1 and CD8 expression in situ in adjacent tissue slices. Results: The data suggested ITPRIPL1 is widely overexpressed in NSCLC and positively correlates with tumor stages. We also found that ITPRIPL1 expression is negatively correlated with CD8 staining, which demonstrates that ITPRIPL1 overexpression is indicative of poorer immune infiltration and clinical prognosis. Therefore, we set 50 as the cutoff point of ITPRIPL1 expression H scores to differentiate normal and lung cancer tissues, which is of an excellent sensitivity and specificity score (100% within our sample collection). Discussion: These results highlight the potential of ITPRIPL1 as a proteomic immunohistochemical NSCLC biomarker with possible advantages over the existing NSCLC biomarkers, and the ITPRIPL1 antibody can be applied for accurate diagnosis and prognosis prediction.

Detection of Aberrant Glycosylation of Serum Haptoglobin for Gastric Cancer Diagnosis Using a Middle-Up-Down Glycoproteome Platform

Gastric cancer is a frequently occurring cancer and is the leading cause of cancer-related deaths. Recent studies have shown that aberrant glycosylation of serum haptoglobin is closely related to gastric cancer and has enormous potential for use in diagnosis. However, there is no platform with high reliability and high reproducibility to comprehensively analyze haptoglobin glycosylation covering microheterogeneity to macroheterogeneity for clinical applications. In this study, we developed a middle-up-down glycoproteome platform for fast and accurate monitoring of haptoglobin glycosylation. This platform utilizes an online purification of LC for sample desalting, and an in silico haptoglobin glycopeptide library constructed by combining peptides and N-glycans to readily identify glycopeptides. In addition, site-specific glycosylation with glycan heterogeneity can be obtained through only a single MS analysis. Haptoglobin glycosylation in clinical samples consisting of healthy controls (n = 47) and gastric cancer patients (n = 43) was extensively investigated using three groups of tryptic glycopeptides: GP1 (including Asn184), GP2 (including Asn207 and Asn211), and GP3 (including Asn241). A total of 23 individual glycopeptides were determined as potential biomarkers (p < 0.00001). In addition, to improve diagnostic efficacy, we derived representative group biomarkers with high AUC values (0.929 to 0.977) through logistic regression analysis for each GP group. It has been found that glycosylation of haptoglobin is highly associated with gastric cancer, especially the glycosite Asn241. Our assay not only allows to quickly and easily obtain information on glycosylation heterogeneity of a target glycoprotein but also makes it an efficient tool for biomarker discovery and clinical diagnosis.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: an update for 2007-2008

This review is the fifth update of the original review, published in 1999, on the application of MALDI mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2008. The first section of the review covers fundamental studies, fragmentation of carbohydrate ions, use of derivatives and new software developments for analysis of carbohydrate spectra. Among newer areas of method development are glycan arrays, MALDI imaging and the use of ion mobility spectrometry. The second section of the review discusses applications of MALDI MS to the analysis of different types of carbohydrate. Specific compound classes that are covered include carbohydrate polymers from plants, N- and O-linked glycans from glycoproteins, biopharmaceuticals, glycated proteins, glycolipids, glycosides and various other natural products. There is a short section on the use of MALDI mass spectrometry for the study of enzymes involved in glycan processing and a section on the use of MALDI MS to monitor products of the chemical synthesis of carbohydrates with emphasis on carbohydrate-protein complexes and glycodendrimers. Corresponding analyses by electrospray ionization now appear to outnumber those performed by MALDI and the amount of literature makes a comprehensive review on this technique impractical. However, most of the work relating to sample preparation and glycan synthesis is equally relevant to electrospray and, consequently, those proposing analyses by electrospray should also find material in this review of interest.

Identification of N-glycan serum markers associated with hepatocellular carcinoma from mass spectrometry data

Glycocylation represents the most complex and widespread post-translational modifications in human proteins. The variation of glycosylation is closely related to oncogenic transformation. Therefore, profiling of glycans detached from proteins is a promising strategy to identify biomarkers for cancer detection. This study identified candidate glycan biomarkers associated with hepatocellular carcinoma by mass spectrometry. Specifically, mass spectrometry data were analyzed with a peak selection procedure which incorporates multiple random sampling strategies with recursive feature selection based on support vector machines. Ten peak sets were obtained from different combinations of samples. Seven peaks were shared by each of the 10 peaksets, in which 7-12 peaks were selected, indicating 58-100% of peaks were shared by the 10 peaksets. Support vector machines and hierarchical clustering method were used to evaluate the performance of the peaksets. The predictive performance of the seven peaks was further evaluated by using 19 newly generated MALDI-TOF spectra. Glycan structures for four glycans of the seven peaks were determined. Literature search indicated that the structures of the four glycans could be found in some cancer-related glycoproteins. The method of this study is significant in deriving consistent, accurate, and biological significant glycan marker candidates for hepatocellular carcinoma diagnosis.