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Glycosylation has significant effects on protein function and cell metastasis, which are important in cancer progression. It is of great interest to identify site-specific glycosylation in search of potential cancer biomarkers. However, the abundance of glycopeptides is low compared to that of nonglycopeptides after trypsin digestion of serum samples, and the mass spectrometric signals of glycopeptides are often masked by coeluting nonglycopeptides due to low ionization efficiency. Selective enrichment of glycopeptides from complex serum samples is essential for mass spectrometry (MS)-based analysis. Herein, a strategy has been optimized using LCA enrichment to improve the identification of core-fucosylation (CF) sites in serum of pancreatic cancer patients. The optimized strategy was then applied to analyze CF glycopeptide sites in 13 sets of serum samples from pancreatic cancer, chronic pancreatitis, healthy controls, and a standard reference. In total, 630 core-fucosylation sites were identified from 322 CF proteins in pancreatic cancer patient serum using an Orbitrap Elite mass spectrometer. Further data analysis revealed that 8 CF peptides exhibited a significant difference between pancreatic cancer and other controls, which may be potential diagnostic biomarkers for pancreatic cancer.

We have developed herein a quantitative mass spectrometry-based approach to analyze the etiology-related alterations in fucosylation degree of serum haptoglobin in patients with liver cirrhosis and hepatocellular carcinoma (HCC). The three most common etiologies, including infection with hepatitis B virus (HBV), infection with hepatitis C virus (HCV), and heavy alcohol consumption (ALC), were investigated. Only 10 μL of serum was used in this assay in which haptoglobin was immunoprecipitated using a monoclonal antibody. The N-glycans of haptoglobin were released with PNGase F, desialylated, and permethylated prior to MALDI-QIT-TOF MS analysis. In total, N-glycan profiles derived from 104 individual patient samples were quantified (14 healthy controls, 40 cirrhosis, and 50 HCCs). A unique pattern of bifucosylated tetra-antennary glycan, with both core and antennary fucosylation, was identified in HCC patients. Quantitative analysis indicated that the increased fucosylation degree was highly associated with HBV- and ALC-related HCC patients compared to that of the corresponding cirrhosis patients. Notably, the bifucosylation degree was distinctly increased in HCC patients versus that in cirrhosis of all etiologies. The elevated bifucosylation degree of haptoglobin can discriminate early stage HCC patients from cirrhosis in each etiologic category, which may be used to provide a potential marker for early detection and to predict HCC in patients with cirrhosis.

A mass spectrometric method was developed to elucidate the N-glycan structures of serum glycoproteins and utilize fucosylated glycans as potential markers for pancreatic cancer. This assay was applied to haptoglobin in human serum where N-glycans derived from the serum of 16 pancreatic cancer patients were compared with those from 15 individuals with benign conditions (5 normals, 5 chronic pancreatitis, and 5 type II diabetes). This assay used only 10 μL of serum where haptoglobin was extracted using a monoclonal antibody and quantitative permethylation was performed on desialylated N-glycans followed by MALDI-QIT-TOF MS analysis. Eight desialylated N-glycan structures of haptoglobin were identified where a bifucosylated triantennary structure was reported for the first time in pancreatic cancer samples. Both core and antennary fucosylation were elevated in pancreatic cancer samples compared to samples from benign conditions. Fucosylation degree indices were calculated and show a significant difference between pancreatic cancer patients of all stages and the benign conditions analyzed. This study demonstrates that a serum assay based on haptoglobin fucosylation patterns using mass spectrometric analysis may serve as a novel method for the diagnosis of pancreatic cancer.

The purpose of this study was to investigate the serum metabolic difference between hepatocellular carcinoma (HCC, n = 20) male patients and normal male subjects (n = 20). Serum metabolome was detected through chemical derivatization followed by gas chromatography/mass spectrometry (GC/MS). The acquired GC/MS data was analyzed by stepwise discriminant analysis (SDA) and support vector machine (SVM). The metabolites including butanoic acid, ethanimidic acid, glycerol, L-isoleucine, L-valine, aminomalonic acid, D-erythrose, hexadecanoic acid, octadecanoic acid, and 9,12-octadecadienoic acid in combination with each other gave the strongest segregation between the two groups. By applying these variables, our method provided a diagnostic model that could well discriminate between HCC patients and normal subjects. More importantly, the error count estimate for each group was 0%. The total classifying accuracy of the discriminant function tested by SVM 20-fold cross validation was 75%. This technique is different from traditional ones and appears to be a useful tool in the area of HCC diagnosis.