Pancreatic cancer is a lethal disease where specific early detection biomarkers would be very valuable to improve outcomes in patients. Many previous studies have compared biosamples from pancreatic cancer patients with healthy controls to find potential biomarkers. However, a range of related disease conditions can influence the performance of these putative biomarkers, including pancreatitis and diabetes. In this study, quantitative proteomics methods were applied to discover potential serum glycoprotein biomarkers that distinguish pancreatic cancer from other pancreas related conditions (diabetes, cyst, chronic pancreatitis, obstructive jaundice) and healthy controls. Aleuria aurantia lectin (AAL) was used to extract fucosylated glycoproteins and then both TMT protein-level labeling and label-free quantitative analysis were performed to analyze glycoprotein differences from 179 serum samples across the six different conditions. A total of 243 and 354 serum proteins were identified and quantified by label-free and TMT protein-level quantitative strategies, respectively. Nineteen and 25 proteins were found to show significant differences in samples between the pancreatic cancer and other conditions using the label-free and TMT strategies, respectively, with 7 proteins considered significant in both methods. Significantly different glycoproteins were further validated by lectin-ELISA and ELISA assays. Four candidates were identified as potential markers with profiles found to be highly complementary with CA 19–9 (p < 0.001). Obstructive jaundice (OJ) was found to have a significant impact on the performance of every marker protein, including CA 19–9. The combination of α-1-antichymotrypsin (AACT), thrombospondin-1 (THBS1), and haptoglobin (HPT) outperformed CA 19–9 in distinguishing pancreatic cancer from normal controls (AUC = 0.95), diabetes (AUC = 0.89), cyst (AUC = 0.82), and chronic pancreatitis (AUC = 0.90). A marker panel of AACT, THBS1, HPT, and CA 19–9 showed a high diagnostic potential in distinguishing pancreatic cancer from other conditions with OJ (AUC = 0.92) or without OJ (AUC = 0.95).

Pancreatic cancer is the third leading cause of cancer-related death in the USA. Despite extensive research, minimal improvements in patient outcomes have been achieved. Early identification of treatment response and metastasis would be valuable to determine the appropriate therapeutic course for patients. In this work, we isolated exosomes from the serum of 10 patients with locally advanced pancreatic cancer at serial time points over a course of therapy, and quantitative analysis was performed using the iTRAQ method. We detected approximately 700–800 exosomal proteins per sample, several of which have been implicated in metastasis and treatment resistance. We compared the exosomal proteome of patients at different time points during treatment to healthy controls and identified eight proteins that show global treatment-specific changes. We then tested the effect of patient-derived exosomes on the migration of tumor cells and found that patient-derived exosomes, but not healthy controls, induce cell migration, supporting their role in metastasis. Our data show that exosomes can be reliably extracted from patient serum and analyzed for protein content. The differential loading of exosomes during a course of therapy suggests that exosomes may provide novel insights into the development of treatment resistance and metastasis.

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.

In this work, we compared the use of repeated cycles of centrifugation at conventional speeds for enrichment of exosomes from human serum compared to the use of ultracentrifugation. After removal of cells and cell debris, a speed of 110,000×g or 40,000×g was used for the ultracentrifugation or centrifugation enrichment process, respectively. The enriched exosomes were analyzed using the BCA assay, 1-D gel separation, transmission electron microscopy, Western blotting, and high resolution LC-MS/MS analysis. It was found that a five cycle repetition of ultracentrifugation or centrifugation is necessary for successful removal of non-exosomal proteins in the enrichment of exosomes from human serum. More significantly, 5×centrifugation enrichment was found to provide similar or better performance than 5×ultracentrifugation enrichment in terms of enriched exosome protein amount, Western blot band intensity for detection of CD-63 and numbers of identified exosome-related proteins and CD proteins. A total of 478 proteins were identified in the LC-MS/MS analyses of exosome proteins obtained from 5×ultracentrifugations and 5×centrifugations including many important CD membrane proteins. The presence of previously reported exosome-related proteins including key exosome protein markers demonstrates the utility of this method for analysis of proteins in human serum.

A mass spectrometry-based methodology has been developed to screen for changes in site-specific core-fucosylation (CF) of serum proteins in early stage HCC with different etiologies. The methods involve depletion of high-abundance proteins, trypsin digestion of medium-to-low-abundance proteins into peptides, iTRAQ labeling, and Lens culinaris Agglutinin (LCA) enrichment of CF peptides, followed by endoglycosidase F3 digestion before mass spectrometry analysis. 1300 CF peptides from 613 CF proteins were identified from patients sera, where 20 CF peptides were differentially expressed in alcohol (ALC)-related HCC samples compared with ALC-related cirrhosis samples and 26 CF peptides changed in hepatitis C virus (HCV)-related HCC samples compared with HCV-related cirrhosis samples. Among these, we found three CF peptides from fibronectin upregulated in ALC-related HCC samples compared with ALC-related cirrhosis samples with an AUC (area under the curve) value of 0.89 at site 1007 with a specificity of 85.7% at a sensitivity of 92.9% (generated with 10-fold cross-validation). When combined with the AFP index, the AUC value reached to 0.92 with a specificity of 92.9% at a sensitivity of 100%, significantly improved compared to that with AFP alone (LR test p < 0.001). In HCV-related samples, the CF level of cadherin-5 at site 61 showed the best AUC value of 0.75 but was not as promising as that of fibronectin site 1007 for ALC-related samples. The CF peptides of fibronectin may serve as potential biomarkers for early stage HCC screening in ALC-related cirrhosis patients.