Analysis of fucosylation in liver-secreted N-glycoproteins from human hepatocellular carcinoma plasma using liquid chromatography with tandem mass spectrometry

Recent Insights into the Biomarkers, Molecular Targets and Mechanisms of Non-Alcoholic Steatohepatitis-Driven Hepatocarcinogenesis

Non-alcoholic fatty liver disease (NAFLD) or metabolic dysfunction-associated steatotic liver disease (MASLD) and steatohepatitis (NASH) are chronic hepatic conditions leading to hepatocellular carcinoma (HCC) development. According to the recent "multiple-parallel-hits hypothesis", NASH could be caused by abnormal metabolism, accumulation of lipids, mitochondrial dysfunction, and oxidative and endoplasmic reticulum stresses and is found in obese and non-obese patients. Recent translational research studies have discovered new proteins and signaling pathways that are involved not only in the development of NAFLD but also in its progression to NASH, cirrhosis, and HCC. Nevertheless, the mechanisms of HCC developing from precancerous lesions have not yet been fully elucidated. Now, it is of particular importance to start research focusing on the discovery of novel molecular pathways that mediate alterations in glucose and lipid metabolism, which leads to the development of liver steatosis. The role of mTOR signaling in NASH progression to HCC has recently attracted attention. The goals of this review are (1) to highlight recent research on novel genetic and protein contributions to NAFLD/NASH; (2) to investigate how recent scientific findings might outline the process that causes NASH-associated HCC; and (3) to explore the reliable biomarkers/targets of NAFLD/NASH-associated hepatocarcinogenesis.

Alpha-1-antichymotrypsin as a novel biomarker for diagnosis, prognosis, and therapy prediction in human diseases

The glycoprotein alpha-1-antichymotrypsin (AACT), a serine protease inhibitor, is mainly synthesized in the liver and then secreted into the blood and is involved in the acute phase response, inflammation, and proteolysis. The dysregulation of AACT and its glycosylation levels are associated with tumor progression and recurrence, and could be used as a biomarker for tumor monitoring. In this review, we summarized the expression level, glycosylation modification, and biological characteristics of AACT during inflammation, neurodegenerative or other elderly diseases, and tumorigenesis, as well as, focused on the biological roles of AACT in cancer. The aberrant expression of AACT in cancer might be due to genetic alterations and/or immune by bioinformatics analysis. Moreover, AACT may serve as a diagnostic or prognostic biomarker or therapeutic target in tumors. Furthermore, we found that the expression of AACT was associated with the overall survival of patients with human cancers. Decreased AACT expression was associated with poor survival in patients with liver cancer, increased AACT expression was associated with shorter survival in patients with pancreatic cancer, and decreased AACT expression was associated with shorter survival in patients with early lung cancer. The review confirmed the key roles of AACT in tumorigenesis, suggesting that the glycoprotein AACT may serve as a biomarker for tumor diagnosis and prognosis, and could be a potential therapeutic target for human diseases.

Serum Glycoprotein Markers in Nonalcoholic Steatohepatitis and Hepatocellular Carcinoma

Fatty liver disease progresses through stages of fat accumulation and inflammation to nonalcoholic steatohepatitis (NASH), fibrosis and cirrhosis, and eventually hepatocellular carcinoma (HCC). Currently available diagnostic tools for HCC lack sensitivity and specificity. In this study, we investigated the use of circulating serum glycoproteins to identify a panel of potential prognostic markers that may be indicative of progression from the healthy state to NASH and further to HCC. Serum samples were processed and analyzed using a novel high-throughput glycoproteomics platform. Our initial dataset contained healthy, NASH, and HCC serum samples. We analyzed 413 glycopeptides, representing 57 abundant serum proteins, and compared among the three phenotypes. We studied the normalized abundance of common glycoforms and found 40 glycopeptides with statistically significant differences in abundances in NASH and HCC compared to controls. Summary level relative abundances of core-fucosylated, sialylated, and branched glycans containing glycopeptides were higher in NASH and HCC as compared to controls. We replicated some of our findings in an independent set of samples of individuals with benign liver conditions and HCC. Our results may be of value in the management of liver diseases. Data generated in this work can be downloaded from MassIVE (https://massive.ucsd.edu) with identifier MSV000088809.

Orosomucoid in liver diseases

In this editorial, the roles of orosomucoid (ORM) in the diagnoses and follow-up assessments of both nonneoplastic diseases and liver tumors are discussed with respect to the publication by Zhu et al presented in the previous issue of World Journal of Gastroenterology (2020; 26(8): 840-817). ORM, or alpha-1 acid glycoprotein (AGP), is an acute-phase protein that constitutes 1% to 3% of plasma proteins in humans and is mainly synthesized in the liver. ORM exists in serum as two variants: ORM1 and ORM2. Although the variants share 89.6% sequence identity and have similar biological properties, ORM1 constitutes the main component of serum ORM. An interesting feature of ORM is that its biological effects differ according to variations in glycosylation patterns. This variable feature makes ORM an attractive target for diagnosing and monitoring many diseases, including those of the liver. Recent findings suggest that a sharp decrease in ORM level is an important marker for HBV-associated acute liver failure (ALF), and ORM1 plays an important role in liver regeneration. In viral hepatitis, increases in both ORM and its fucosylated forms and the correlation of these increases with fibrosis progression suggest that this glycoprotein can be used with other markers as a noninvasive method in the follow-up assessment of diseases. In addition, similar findings regarding the level of the asialylated form of ORM, called asialo-AGP (AsAGP), have been reported in a follow-up assessment of fibrosis in chronic liver disease. An increase in ORM in serum has also been shown to improve hepatocellular carcinoma (HCC) diagnosis performance when combined with other markers. In addition, determination of the ORM level has been useful in the diagnosis of HCC with AFP concentrations less than 500 ng/mL. For monitoring patients with AFP-negative HCC, a unique trifucosylated tetra-antennary glycan of ORM may also be used as a new potential marker. The fact that there are very few studies investigating the expression of this glycoprotein and its variants in liver tissues constitutes a potential limitation, especially in terms of revealing all the effects of ORM on carcinogenesis and tumor behavior. Current findings indicate that ORM2 expression is decreased in tumors, and this is related to the aggressive course of the disease. Parallel to this finding, in HCC cell lines, ORM2 decreases HCC cell migration and invasion, supporting reports of its tumor suppressor role. In conclusion, the levels of ORM and its different glycosylated variants are promising additional biomarkers for identifying ALF, for monitoring fibrosis in viral hepatitis, and for diagnosing early HCC. Although there is evidence that the loss of ORM2 expression in HCC is associated with poor prognosis, further studies are needed to support these findings. Additionally, investigations of ORM expression in borderline dysplastic nodules and hepatocellular adenomas, which pose diagnostic problems in the differential diagnosis of HCC, especially in biopsy samples, may shed light on whether ORM can be used in histopathological differential diagnosis.

Apo-H (beta-2-glycoprotein) intact N-glycan analysis by MALDI-TOF-MS using sialic acid derivatization

Apo-H is a plasma glycoprotein. Nearly 19% of the molecular weight of this protein is composed of glycans. Up- and down-regulation and structural changes in protein glycans provide diagnostic value for disease detection. Here, an efficient, sensitive, and optimized method is developed for Apo-H N-glycans analysis by MALDI-TOF-MS in positive mode. This bioanalytical method includes sample preparation, sample purification, and detection. An Apo-H enrichment method is developed using standard proteins by anti-Apo-H beads followed by enrichment from plasma samples. SDS-PAGE confirms the Apo-H protein enrichment, which is further verified by LC-MS/MS analysis. The lower ionization efficiency of sialylated glycan hampers their analysis by MALDI-MS. For this, stabilization of sialic acids is done by selective derivatization of carboxyl groups to differentiate between α(2,3)- and α(2,6)-linked sialic acids. Glycans are further purified by HILIC-SPE and analyzed by MALDI-MS. Several branched bi- and tri-antennary glycans with fucosylation and sialylation are identified. The reproducibility of the developed method is tested by analyzing multiple replicates of human plasma, where the same glycans are consistently identified. This method could be applied for the Apo-H glycan profiling of large clinical cohorts for diagnostic purposes.

Identification of Fucosylated SERPINA1 as a Novel Plasma Marker for Pancreatic Cancer Using Lectin Affinity Capture Coupled with iTRAQ-Based Quantitative Glycoproteomics

Pancreatic cancer (PC) is an aggressive cancer with a high mortality rate, necessitating the development of effective diagnostic, prognostic and predictive biomarkers for disease management. Aberrantly fucosylated proteins in PC are considered a valuable resource of clinically useful biomarkers. The main objective of the present study was to identify novel plasma glycobiomarkers of PC using the iTRAQ quantitative proteomics approach coupled with Aleuria aurantia lectin (AAL)-based glycopeptide enrichment and isotope-coded glycosylation site-specific tagging, with a view to analyzing the glycoproteome profiles of plasma samples from patients with non-metastatic and metastatic PC and gallstones (GS). As a result, 22 glycopeptides with significantly elevated levels in plasma samples of PC were identified. Fucosylated SERPINA1 (fuco-SERPINA1) was selected for further validation in 121 plasma samples (50 GS and 71 PC) using an AAL-based reverse lectin ELISA technique developed in-house. Our analyses revealed significantly higher plasma levels of fuco-SERPINA1 in PC than GS subjects (310.7 ng/mL v.s. 153.6 ng/mL, p = 0.0114). Elevated fuco-SERPINA1 levels were associated with higher TNM stage (p = 0.024) and poorer prognosis for overall survival (log-rank test, p = 0.0083). The increased plasma fuco-SERPINA1 levels support the utility of this protein as a novel prognosticator for PC.

Computational classification of core and outer fucosylation of N-glycoproteins in human plasma using collision-induced dissociation in mass spectrometry

RATIONALE

Glycoprotein fucosylation, one of the major posttranslational modifications, is known to be highly involved in proteins related to various cancers. Fucosylation occurs in the core and/or outer sites of N-glycopeptides. Elucidation of the fucosylation type of N-glycoproteins is therefore important. However, it has remained a challenge to classify the fucosylation types of N-glycopeptides using collision-induced dissociation (CID) tandem mass (MS/MS) spectra.

METHODS

The relative intensities of the Y₁ F, Y₂ F, Y₃ F, and Y₄ F product ions in the CID-MS/MS spectra of the IgG N-glycopeptides were measured for core fucosylation. The Core Fucose Index (CFI) was then calculated by multiplication of the relative intensities with a weight factor from logistic regression to differentiate between the core and none fucosylation. From the relative intensities of the B₂ F and B₃ SF ions of the MS/MS spectra of the AGP N-glycopeptides for outer fucosylation, the Outer Fucose Index (OFI) was calculated to differentiate between the outer and none fucosylation.

RESULTS

In order to classify core and/or outer fucosylation of N-glycoproteins, we defined the fucosylation score (F-score) by a sigmoidal equation using a combination of the CFI and the OFI. For application, we classified the fucosylation types of N-glycoproteins in human plasma with 99.7% accuracy from the F-score. Human plasma samples showed 54.4%, 33.3%, 10.3%, and 1.6% for none, core, outer, and dual fucosylated N-glycopeptides, respectively. Core fucosylation was abundant at mono- and bi-antennary N-glycopeptides. Outer fucosylation was abundant at tri- and tetra-antennary N-glycopeptides. In total, 113 N-glycopeptides of 29 glycoproteins from 3365 glycopeptide spectral matches (GPSMs) were classified for different types of fucosylation.

CONCLUSIONS

We established an F-score to classify three different fucosylation types: core, outer, and dual types of N-glycopeptides. The fucosylation types of 20 new N-glycopeptides from 11 glycoproteins in human plasma were classified using the F-score. Therefore, the F-score can be useful for the automatic classification of different types of fucosylation in N-glycoproteins of biological fluids including plasma, serum, and urine.

Machine Learning Classifies Core and Outer Fucosylation of N-Glycoproteins Using Mass Spectrometry

Protein glycosylation is known to be involved in biological progresses such as cell recognition, growth, differentiation, and apoptosis. Fucosylation of glycoproteins plays an important role for structural stability and function of N-linked glycoproteins. Although many of biological and clinical studies of protein fucosylation by fucosyltransferases has been reported, structural classification of fucosylated N-glycoproteins such as core or outer isoforms remains a challenge. Here, we report for the first time the classification of N-glycopeptides as core- and outer-fucosylated types using tandem mass spectrometry (MS/MS) and machine learning algorithms such as the deep neural network (DNN) and support vector machine (SVM). Training and test sets of more than 800 MS/MS spectra of N-glycopeptides from the immunoglobulin gamma and alpha 1-acid-glycoprotein standards were selected for classification of the fucosylation types using supervised learning models. The best-performing model had an accuracy of more than 99% against manual characterization and area under the curve values greater than 0.99, which were calculated by probability scores from target and decoy datasets. Finally, this model was applied to classify fucosylated N-glycoproteins from human plasma. A total of 82N-glycopeptides, with 54 core-, 24 outer-, and 4 dual-fucosylation types derived from 54 glycoproteins, were commonly classified as the same type in both the DNN and SVM. Specifically, outer fucosylation was dominant in tri- and tetra-antennary N-glycopeptides, while core fucosylation was dominant in the mono-, bi-antennary and hybrid types of N-glycoproteins in human plasma. Thus, the machine learning methods can be combined with MS/MS to distinguish between different isoforms of fucosylated N-glycopeptides.

Fast and facile analysis of glycosylation and phosphorylation of fibrinogen from human plasma-correlation with liver cancer and liver cirrhosis

Hepatocellular carcinoma (HCC) is one of the deadliest cancers due to its late diagnosis with the main risk factor being liver cirrhosis (LC). Glycan structures from glycoproteins are usually altered in cancer. Blood plasma from 111 healthy and sick donors was analyzed to determine the post-translational modifications (PTM) of intact Aα-, Bβ-, and γ-subunits of fibrinogen, a glycoprotein predominantly produced in liver cells. Glycosylation and phosphorylation of the protein species were quantified by liquid chromatography coupled to mass spectrometry to correlate PTMs to pathological cases. Quantities of the PTMs were used for statistical classification by principal component analysis (PCA) and multivariate analysis of variance (MANOVA). As relevant clinical finding, patients with liver disease (HCC and/or LC) were distinguished from individuals without relevant chronic liver disease with 91% sensitivity and 100% specificity. Within the group of patients with liver disease, a robust separation between LC and HCC was not possible. In more detail, the phosphorylation of Aα-subunit is decreased in HCC patients, whereas the monophosphorylated state is significantly increased in LC patients. In terms of glycosylation, the amount of O-glycans in the Aα-subunit is decreased in LC patients, while sialylation and fucosylation of N-type glycans of Bβ- and γ-subunits are increased in LC and HCC. Based on PTM of fibrinogen, starting from plasma we can assign the status of an individual as healthy or as liver disease in less than 3 h.

Quantitative analysis of core fucosylation of serum proteins in liver diseases by LC-MS-MRM

Aberrant core fucosylation of proteins has been linked to liver diseases. In this study, we carried out multiple reaction monitoring (MRM) quantification of core fucosylated N-glycopeptides of serum proteins partially deglycosylated by a combination of endoglycosidases (endoF1, endoF2, and endoF3). To minimize variability associated with the preparatory steps, the analysis was performed without enrichment of glycopeptides or fractionation of serum besides the nanoRP chromatography. Specifically, we quantified core fucosylation of 22 N-glycopeptides derived from 17 proteins together with protein abundance of these glycoproteins in a cohort of 45 participants (15 disease-free control, 15 fibrosis and 15 cirrhosis patients) using a multiplex nanoUPLC-MS-MRM workflow. We find increased core fucosylation of 5 glycopeptides at the stage of liver fibrosis (i.e., N630 of serotransferrin, N107 of alpha-1-antitrypsin, N253 of plasma protease C1 inhibitor, N397 of ceruloplasmin, and N86 of vitronectin), increase of additional 6 glycopeptides at the stage of cirrhosis (i.e., N138 and N762 of ceruloplasmin, N354 of clusterin, N187 of hemopexin, N71 of immunoglobulin J chain, and N127 of lumican), while the degree of core fucosylation of 10 glycopeptides did not change. Interestingly, although we observe an increase in the core fucosylation at N86 of vitronectin in liver fibrosis, core fucosylation decreases on the N169 glycopeptide of the same protein. Our results demonstrate that the changes in core fucosylation are protein and site specific during the progression of fibrotic liver disease and independent of the changes in the quantity of N-glycoproteins. It is expected that the fully optimized multiplex LC-MS-MRM assay of core fucosylated glycopeptides will be useful for the serologic assessment of the fibrosis of liver. BIOLOGICAL SIGNIFICANCE: We have quantified the difference in core fucosylation among three comparison groups (healthy control, fibrosis and cirrhosis patients) using a sensitive and selective LC-MS-MRM method. Despite an overall increase in core fucosylation of many of the glycoproteins that we examined, core fucosylation changed in a protein- and site-specific manner. Moreover, increased and decreased fucosylation was observed on different N-glycopeptides of the same protein. Altered core fucosylation of N-glycopeptides might be used as an alternative serologic assay for the evaluation of fibrotic liver disease.