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ABSTRACTIntroductionRegenerative medicine involves the replacement of damaged cells, tissues, or organs to restore normal function. Mesenchymal stem cells (MSCs) and exosomes secreted by MSCs have unique advantages that make them a suitable candidate in the field of regenerative medicine.Areas coveredThis article provides a comprehensive overview of regenerative medicine, focusing on the use of MSCs and their exosomes as potential therapies for replacing damaged cells, tissues, or organs. This article discusses the distinct advantages of both MSCs and their secreted exosomes, including their immunomodulatory effects, lack of immunogenicity, and recruitment to damaged areas. While both MSCs and exosomes have these advantages, MSCs also have the unique ability to self-renew and differentiate. This article also assesses the current challenges associated with the application of MSCs and their secreted exosomes in therapy. We have reviewed proposed solutions for improving MSC or exosome therapy, including ex-vivo preconditioning strategies, genetic modification, and encapsulation. Literature search was conducted using Google Scholar and PubMed databases.Expert opinionProviding insight into the future development of MSC and exosome-based therapies and to encourage the scientific community to focus on the identified gaps, develop appropriate guidelines, and enhance the clinical application of these therapies.

Glycosylation is one of the most common post-translational modifications (PTM) occurring in a large variety of proteins with important biological functions in human and other higher organisms. Liquid chromatography tandem mass spectrometry (LC-MS/MS) has been routinely used to characterize site-specific protein glycosylation at high throughput in complex glycoproteomic samples. Recently, electron transfer/high-energy collision dissociation (EThcD) was introduced for glycopeptide identification, which offers rich structural information on glycopepides with the fragment ions from the cleavages of both the glycan and the peptide backbone. Herein, we present the software GlycoHybridSeq for automated interpretation of EThcD-MS/MS spectra from glycoproteomic data using a customized scoring function, which enables the functionalities of identifying glycopeptides, characterizing glycosylation sites, and distinguishing some isomeric glycans. We evaluate GlycoHybridSeq on glycoproteomic data collected for cancer biomarker discovery. The results showed that it achieved comparable or better performance than that of Byonic and MSFragger. GlycoHybridSeq is released as an open source software and is ready to be used in large-scale glycoproteomic data analyses.

•For the first time we assessed the specificity of Haptoglobin bifucosylated tetra-antennary glycan for early HCC detection according to the presence or not of cirrhosis.•We constructed a potential new liver-cancer multi-analyte blood test LCR-glycan, including Haptoglobin bifucosylated tetra-antennary glycan.•In patients without cirrhosis, the intention-to-diagnose analyses showed that haptoglobin bifucosylated tetra-antennary glycan had a sensitivity of 71% and a specificity of 96%.•In patients without cirrhosis LCR-glycan showed a sensitivity of 86%, with an AUROC of 0.943.•Haptoglobin bifucosylated tetra-antennary glycan is associated with the presence of HCC in patients with chronic liver disease including those without cirrhosis.

Nonalcoholic steatohepatitis (NASH) is rising in prevalence in the United States and is a growing cause of hepatocellular carcinomas (HCCs). Site-specific glycan heterogeneity on glycoproteins has been shown as a potential diagnostic biomarker for HCC. Herein, we have performed a comprehensive screening of site-specific N-glycopeptides in serum haptoglobin (Hp), a reporter molecule for aberrant glycosylation in HCC, to characterize glycopeptide markers for NASH-related HCCs. In total, 70 NASH patients (22 early HCC, 15 advanced HCC, and 33 cirrhosis cases) were analyzed, with Hp purified from 20 μL of serum in each patient, and 140 sets of mass spectrometry (MS) data were collected using liquid chromatography coupled with electron-transfer high-energy collisional dissociation tandem MS (LC-EThcD-MS/MS) for quantitative analysis on a novel software platform, Byos. Differential quantitation analysis revealed that five N-glycopeptides at sites N184 and N241 were significantly elevated during the progression from NASH cirrhosis to HCC (p< 0.05). Receiver operating characteristic (ROC) curve analysis demonstrated that the N-glycopeptides at sites N184 and N241 bearing a monofucosylated triantennary glycan A3G3F1S3 had the best diagnostic performance in detection of early NASH HCC, area under the curve (AUC) = 0.733 and 0.775, respectively, whereas α-fetoprotein (AFP) had an AUC of 0.692. When combined with AFP, the two panels improved the sensitivity for early NASH HCC from 59% (AFP alone) to 73% while maintaining a specificity of 70%, based on the optimal cutoff. Two-dimensional (2-D) scatter plots of the AFP value and N-glycopeptides showed that these N-glycopeptide markers detected 58% of AFP-negative HCC patients as distinct from cirrhosis. These site-specific N-glycopeptides could serve as potential markers for early detection of HCC in patients with NASH-related cirrhosis.

The change in glycosylation of serum proteins is often associated with the development of various diseases and thus can be used for diagnosis. In this study, a liquid chromatography-tandem mass spectrometry-based method is used for accurate structural analysis and quantification of site-specific glycoforms of serum α-1-antitrypsin (A1AT) in early-stage HCC and cirrhosis patients. Serum protein A1AT was purified from patient sera by immunoprecipitation with anti-A1AT antibody conjugated agarose beads, and the isolated A1AT protein was digested and analyzed by LC-MS/MS. Two tandem mass spectrometry strategies are integrated in this study: a nontargeted stepped HCD strategy for structural analysis of A1AT glycopeptides and a targeted parallel reaction monitoring (PRM) strategy for quantification of site-specific glycoforms of A1AT in HCC and cirrhosis patient sera. Accordingly, pGlyco2.0 software was used for glycopeptide identification, and Skyline software was used for glycoform quantification using the Y1 ion (peptide+GlcNAc) in MS/MS spectra. Ten site-specific glycopeptides of A1AT were identified with stepped HCD-MS/MS in patient samples, 7 of which were further quantified using HCD-PRM-MS among patient samples. We found that our strategy was able to distinguish isomers of glycopeptides where several isomers showed distinctly different patterns between cirrhosis and HCC patients. We also found that the ratio of different charge states (2+/3+) of one glycopeptide of A1AT can significantly discriminate early-stage HCC from cirrhosis with the area under the receiver operating characteristic curve AUC of 0.9. Further analysis showed that the difference may be related to the sialic acid/galactose linkage of the glycan motif.

Identifying single amino acid variants (SAAVs) in cancer is critical for precision oncology. Several advanced algorithms are now available to identify SAAVs, but attempts to combine different algorithms and optimize them on large data sets to achieve a more comprehensive coverage of SAAVs have not been implemented. Herein, we report an expanded detection of SAAVs in the PANC-1 cell line using three different strategies, which results in the identification of 540 SAAVs in the mass spectrometry data. Among the set of 540 SAAVs, 79 are evaluated as deleterious SAAVs based on analysis using the novel AssVar software in which one of the driver mutations found in each protein of KRAS, TP53, and SLC37A4 is further validated using independent selected reaction monitoring (SRM) analysis. Our study represents the most comprehensive discovery of SAAVs to date and the first large-scale detection of deleterious SAAVs in the PANC-1 cell line. This work may serve as the basis for future research in pancreatic cancer and personal immunotherapy and treatment.

Exosomes are nanosized vesicles commonly found in biological fluids as a result of a secretion process involving endosomes and multivesicular bodies. The isolation and analysis of exosomes can be useful for noninvasive clinical diagnosis of a variety of human diseases. We investigated the utility of analyzing exosomal proteins, using matrix-assisted laser desorption/ionization combined with Fourier-transform ion cyclotron resonance mass spectrometry (MALDI-FTICR-MS), as a means of determining the presence of exosomes. MALDI-FTICR-MS analyses of exosomes enriched from human serum via centrifugation in a mass range of m/z1000–20 000 yielded a distinctive protein around m/z7766. The high mass accuracy and resolution of MALDI-FTICR-MS allowed for reliable comparisons against a protein database, through which the protein was identified as platelet factor 4 (PLF4), whose singly charged protein peak has an elemental composition of C341H577N96O101S4+, with a theoretical most abundant isotopic peak at m/z7765.194 and a theoretical average peak at m/z7766. The MALDI-TOF MS analysis of exosomes from the serum of 27 patients with different states of liver diseases provided the most abundant PLF4 peak for each mass spectrum, along with several additional minor peaks. In conclusion, MALDI-MS is suitable as an alternative exosome detection method, serving as a valuable confirmation tool, greatly decreasing the time and workload associated with exosome identification.

The poor prognosis of melanoma and the high cost of lymph node biopsy for melanoma patients have led to an urgent need for the discovery of convenient and accurate prognostic indicators. Here, we have developed a natural glycoprotein microarray to discover serum autoantibodies to distinguish between patients with node negative melanoma and node positive melanoma. Dual-lectin affinity chromatography was used to extract glycoproteins from a melanoma cell line. Liquid-based reverse phase separation and microarray platforms were then applied to separate and spot these natural proteins on nitrocellulose slides. The serum autoantibodies were investigated by exposing these proteins to sera from 43 patients that have already been diagnosed to have different stages of early melanoma. The combination of 9 fractions provides a 55% sensitivity with 100% specificity for the detection of node positive against node negative and a 62% sensitivity with 100% specificity for the detection of node negative against node positive. Recombinant proteins were used to confirm the results using a sample set with 79 patients with diagnosed melanoma. The response of sera against recombinant 94 kD glucose-regulated protein (GRP94), acid ceramidase (ASAH1), cathepsin D (CTSD), and lactate dehydrogenase B (LDHB) shared a similar pattern to the fractions where they were identified. The glycoarray platform provides a convenient and highly reproducible method to profile autoantibodies that could be used as serum biomarkers for prognosis of melanoma.

Intact N-glycopeptide analysis remains challenging due to the complexity of glycopeptide structures, low abundance of glycopeptides in protein digests, and difficulties in data interpretation/quantitation. Herein, we developed a workflow that involved advanced methodologies, the EThcD-MS/MS fragmentation method and data interpretation software, for differential analysis of the microheterogeneity of site-specific intact N-glycopeptides of serum haptoglobin between early hepatocellular carcinoma (HCC) and liver cirrhosis. Haptoglobin was immunopurified from 20 μL of serum in patients with early HCC, liver cirrhosis, and healthy controls, respectively, followed by trypsin/GluC digestion, glycopeptide enrichment, and LC-EThcD-MS/MS analysis. Identification and differential quantitation of site-specific N-glycopeptides were performed using a combination of Byonic and Byologic software. In total, 93, 87, and 68 site-specific N-glycopeptides were identified in early HCC, liver cirrhosis, and healthy controls, respectively, with high confidence. The increased variety of N-glycopeptides in liver diseases compared to healthy controls was due to increased branching with hyper-fucosylation and sialylation. Differential quantitation analysis showed that 5 site-specific N-glycopeptides on sites N184 and N241 were significantly elevated in early HCC compared to cirrhosis (p< 0.05) and normal controls (p≤ 0.001). The result demonstrates that the workflow provides a strategy for detailed profiles of N-glycopeptides of patient samples as well as for relative quantitation to determine the level changes in site-specific N-glycopeptides between disease states.

We have performed deep proteomic profiling down to as few as 9 Panc-1 cells using sample fractionation, TMT multiplexing, and a carrier/reference strategy. Off line fractionation of the TMT-labeled sample pooled with TMT-labeled carrier Panc-1 whole cell proteome was achieved using alkaline reversed phase spin columns. The fractionation in conjunction with the carrier/reference (C/R) proteome allowed us to detect 47 414 unique peptides derived from 6261 proteins, which provided a sufficient coverage to search for single amino acid variants (SAAVs) related to cancer. This high sample coverage is essential in order to detect a significant number of SAAVs. In order to verify genuine SAAVs versus false SAAVs, we used the SAVControl pipeline and found a total of 79 SAAVs from the 9-cell Panc-1 sample and 174 SAAVs from the 5000-cell Panc-1 C/R proteome. The SAAVs as sorted into high confidence and low confidence SAAVs were checked manually. All the high confidence SAAVs were found to be genuine SAAVs, while half of the low confidence SAAVs were found to be false SAAVs mainly related to PTMs. We identified several cancer-related SAAVs including KRAS, which is an important oncoprotein in pancreatic cancer. In addition, we were able to detect sites involved in loss or gain of glycosylation due to the enhanced coverage available in these experiments where we can detect both sites of loss and gain of glycosylation.

Exosomes are nanosized vesicles that are abundant in biological fluids. In recent years, exosomes have attracted increasing attention as their cargo may provide promising biomarkers for the early diagnosis of and therapy for many diseases, such as cancer. In addition to ultracentrifugation (UC), many alternative methods including size-exclusion chromatography (SEC) have been developed for isolating exosomes. It has been reported that the SEC method provided improved performance relative to the UC method in isolating exosomes from plasma, where the former contained less residual blood protein contamination. We have compared the SEC method with an optimized UC method in isolating exosomes from human serum. This was based on dilution of the serum to reduce the viscosity and a prolonged cycle of UC, followed by another four cycles. We found that >95% of serum proteins were removed without a significant loss of exosome proteins relative to SEC. We also combined one cycle of UC with SEC and found that this method provided improved results relative to the SEC method, although the serum protein contamination was several times higher than that of our optimized UC method. The TEM showed that the size distribution of exosomes isolated from each of the three methods was similar.

Circulating exosomes in bodily fluids such as blood are being actively studied as a rich source of chemical biomarkers for cancer diagnosis and monitoring. Although nucleic acid analysis is a primary tool for the discovery of circulating biomarkers in exosomes, metabolomics holds the potential of expanding the chemical diversity of biomarkers that may be easy and rapid to detect. However, only trace amounts of exosomes can be isolated from a small volume of patient blood, and thus a very sensitive technique is required to analyze the metabolome of exosomes. In this report, we present a workflow that involves multiple cycles of ultracentrifugation for exosome isolation using a starting material of 2 mL of human serum, freeze–thaw-cycles in 50% methanol/water for exosome lysis and metabolite extraction, differential chemical isotope labeling (CIL) of metabolites for enhancing liquid chromatography (LC) separation and improving mass spectrometry (MS) detection, and nanoflow LC-MS (nLC-MS) with captivespray for analysis. As a proof-of-principle, we used dansylation labeling to analyze the amine- and phenol-submetabolomes in two sets of exosome samples isolated from the blood samples of five pancreatic cancer patients before and after chemotherapy treatment. The average number of peak pairs or metabolites detected was 1964 ± 60 per sample for a total of 2446 peak pairs (n= 10) in the first set and 1948 ± 117 per sample for a total of 2511 peak pairs (n= 10) in the second set. There were 101 and 94 metabolites positively identified in the first and second set, respectively, and 1580 and 1590 peak pairs with accurate masses matching those of metabolites in the MyCompoundID metabolome database. Analyzing the mixtures of 12C-labeled individual exosome samples spiked with a 13C-labeled pooled sample which served as an internal standard allowed relative quantification of metabolomic changes of exosomes of blood samples collected before and after treatment.

Circulating microvesicles are able to mediate long-distance cell–cell communications. It is essential to understand how microvesicles from pancreatic cancer act on other cells in the body. In this work, serum-derived microvesicles were isolated from 10 patients with locally advanced pancreatic cancer and healthy controls. Using Cell Transwell and WST-1 reagents, we found that microvesicles from pancreatic cancer accelerated migration and proliferation of PANC-1 cells. Meanwhile, the proliferation of these cancer-microvesicle-treated cells (CMTCs) was affected less by 10 μM of gemcitabine relative to healthy microvesicle-treated cells (HMTCs). Next, we optimized the filter-aided sample preparation method to increase the recovery of protein samples and then applied it to the quantification of the proteome of CMTCs and HMTCs. The peptides were labeled and analyzed by liquid chromatography–tandem mass spectrometry. In total, 4102 proteins were identified, where 35 proteins were up-regulated with 27 down-regulated in CMTCs. We verified the quantitative results of three key proteins CD44, PPP2R1A, and TP53 by Western blot. The Ingenuity Pathway Analysis revealed pathways that cancer microvesicles might participate in to promote cell migration and proliferation. These findings may provide novel clues of treatment for tumorigenesis and metastasis.

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.

Cancers are initiated and developed from a small population of stem-like cells termed cancer stem cells (CSCs). There is heterogeneity among this CSC population that leads to multiple subpopulations with their own distinct biological features and protein expression. The protein expression and function may be impacted by amino acid variants that can occur largely due to single nucleotide changes. We have thus performed proteomic analysis of breast CSC subpopulations by mass spectrometry to study the presence of single amino acid variants (SAAVs) and their relation to breast cancer. We have used CSC markers to isolate pure breast CSC subpopulation fractions (ALDH+ and CD44+/CD24– cell populations) and the mature luminal cells (CD49f–EpCAM+) from the MCF-7 breast cancer cell line. By searching the Swiss-CanSAAVs database, 374 unique SAAVs were identified in total, where 27 are cancer-related SAAVs. 135 unique SAAVs were found in the CSC population compared with the mature luminal cells. The distribution of SAAVs detected in MCF-7 cells was compared with those predicted from the Swiss-CanSAAVs database, where we found distinct differences in the numbers of SAAVs detected relative to that expected from the Swiss-CanSAAVs database for several of the amino acids.

Metaproteomics is one approach to analyze the functional capacity of the gut microbiome but is limited by the ability to evenly extract proteins from diverse organisms within the gut. Herein, we have developed a pipeline to optimize sample preparation of stool obtained from germ-free (GF) mice that were gavaged a defined community of 11 bacterial strains isolated from the human gut. With 64% more proteins identified, bead-beating was confirmed to be an indispensable step for the extraction of bacterial proteins, especially for Gram-positive bacteria. Bacterial enrichment from mouse fecal samples was further optimized by evaluating three different methods: (1) a high-speed differential centrifugation (HCE) or (2) a low-speed differential centrifugation (LCE) and (3) a filter-aided method (FA). The HCE method was associated with dramatic loss of bacteria and 71% less recovery of bacterial proteins than the LCE method. Compared with LCE, the FA method also showed dramatic loss of the amount of bacteria recovered and decreased protein identifications from Gram-positive bacteria in the stool samples. Ultimately, LCE may provide an alternative and complementary method for enriching bacteria from small amounts of mouse fecal samples, which could aid in investigating bacterial function in health and disease.

Supplemental digital content is available in the text.Pancreatic cancer is the fourth leading cause of cancer related deaths in the United States with a 5-year survival rate of less than 10%. The Division of Cancer Prevention of the National Cancer Institute sponsored the Pancreatic Cancer Chemoprevention Translational Workshopon September 10 to 11, 2015. The goal of the workshop was to obtain information regarding the current state of the science and future scientific areas that should be prioritized for pancreatic cancer prevention research, including early detection and intervention for high-risk precancerous lesions. The workshop addressed the molecular/genetic landscape of pancreatic cancer and precursor lesions, high-risk populations and criteria to identify a high-risk population for potential chemoprevention trials, identification of chemopreventative/immunopreventative agents, and use of potential biomarkers and imaging for assessing short-term efficacy of a preventative agent. The field of chemoprevention for pancreatic cancer is emerging, and this workshop was organized to begin to address these important issues and promote multi-institutional efforts in this area. The meeting participants recommended the development of an National Cancer Institute working group to coordinate efforts, provide a framework, and identify opportunities for chemoprevention of pancreatic cancer.

Extracellular vesicle (EV) secretion has been observed in many types of both normal and tumor cells. EVs contain a variety of distinctive cargoes, allowing tumor-derived serum proteins in EVs to act as a minimally invasive method for clinical monitoring. We have undertaken a comprehensive study of the protein content of the EVs from several cancer cell lines using direct data-independent analysis. Several thousand proteins were detected, including many classic EV markers such as CD9, CD81, CD63, TSG101, and Syndecan-1, among others. We detected many distinctive cancer-specific proteins, including several known markers used in cancer detection and monitoring. We further studied the protein content of EVs from patient serum for both normal controls and pancreatic cancer and hepatocellular carcinoma. The EVs for these studies have been isolated by various methods for comparison, including ultracentrifugation and CD9 immunoaffinity column. Typically, 500–1000 proteins were identified, where most of them overlapped with the EV proteins identified from the cell lines studied. We were able to identify many of the cell-line EV protein markers in the serum EVs, in addition to the large numbers of proteins specific to pancreatic and HCC cancers.

Liquid chromatography coupled with tandem mass spectrometry is commonly adopted in large-scale glycoproteomic studies involving hundreds of disease and control samples. The software for glycopeptide identification in such data (e.g., the commercial software Byonic) analyzes the individual data set and does not exploit the redundant spectra of glycopeptides presented in the related data sets. Herein, we present a novel concurrent approach for glycopeptide identification in multiple related glycoproteomic data sets by using spectral clustering and spectral library searching. The evaluation on two large-scale glycoproteomic data sets showed that the concurrent approach can identify 105%–224% more spectra as glycopeptides compared to the glycopeptide identification on individual data sets using Byonic alone. The improvement of glycopeptide identification also enabled the discovery of several potential biomarkers of protein glycosylations in hepatocellular carcinoma patients.

A method for the detection of fucosylated glycans from haptoglobin in patient serum has been developed that provides enhanced sensitivity. The workflow involves isolation of the haptoglobin using an HPLC-based affinity column followed by glycan removal, extraction, and desialylation. The fucosylated glycans are then derivatized by Meladrazine, which significantly enhances the detection of the glycans in electrospray ionization. The separation of the derivatized glycans in a HILIC column shows that eight glycans from haptoglobin can be detected using less than 1 μL of a serum sample, with excellent reproducibility and quantitation, where without derivatization the glycans could not be detected. The ratio of the fucosylated peaks to their corresponding nonfucosylated forms shows that the fucosylated glycans are upregulated in the case of hepatocellular carcinoma (HCC) samples versus cirrhosis samples, where the relatively low abundance bifucosylated tetra-antennary form can be detected and may be a particularly good marker for HCC.

Alterations in glycosylation of serum glycoproteins can provide unique and highly specific fingerprints of malignancy. Our previous mass spectrometric study revealed that the bifucosylation level of serum haptoglobin was distinctly increased in hepatocellular carcinoma (HCC) patients versus liver cirrhosis of all three major etiologies. We have thus developed a method for the analysis of large numbers of serum samples based on a 96-well plate platform for the evaluation of fucosylation changes of serum haptoglobin between HCC versus cirrhosis. Haptoglobin was isolated from the serum of individual patient samples based on an HPLC column immobilized with antihaptoglobin antibody via hydrazide immobilization chemistry. Only 10 μL of serum was required for glycan extraction and processing for MALDI-QIT mass spectrometry analysis using the 96-well plate format. The bifucosylation degrees of haptoglobin in individuals were calculated using a quantitative glycomics method. The MS data confirmed that the bifucosylated tetra-anntenary glycan was upregulated in HCC samples of all etiologies. This study provides a parallel method for processing glycan content for haptoglobin and evaluating detailed changes in glycan structures for a potentially large cohort of clinical serum samples.

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 culinarisAgglutinin (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.

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.