Protein glycosylation in viral hepatitis-related HCC: Characterization of heterogeneity, biological roles, and clinical implications

Single cell glycan-linkages profiling for hepatocellular carcinoma early diagnosis using lanthanide encoded bacteriophage MS2 based ICP-MS

Early diagnosis is paramount for enhancing survival rates and prognosis in the context of malignant diseases. Hepatocellular carcinoma (HCC), the second leading cause of cancer-related deaths worldwide, poses significant challenges for its early detection. In this study, we present an innovative approach which contributed to the early diagnosis of HCC. By lanthanide encoding signal amplification to map glycan-linkages at the single-cell level, the minute quantities of "soft" glycan-linkages on single cell surface were converted into "hard" elemental tags through the use of an MS2 signal amplifier. Harnessing the power of lanthanides encoded within MS2, we achieve nearly three orders of magnitude signal amplification. These encoded tags are subsequently quantified using single-cell inductively coupled plasma mass spectrometry (SC-ICP-MS). Linear discriminant analysis (LDA) identifies seven specific glycan-linkages (α-2,3-Sia, α-Gal, α-1,2-Fuc, α-1,6-Fuc, α-2,6-Sia, α-GalNAc, and Gal-β-1,3-GalNAc) as biomarkers. Our methodology is initially validated at the cellular level with 100% accuracy in discriminating between hepatic carcinoma HepG2 cells and their normal HL7702 cells. We apply this approach to quantify and classify glycan-linkages on the surfaces of 55 clinical surgical HCC specimens. Leveraging these seven glycan-linkages as biomarkers, we achieve precise differentiation between 8 normal hepatic specimens, 40 early HCC specimens, and 7 colorectal metastasis HCC specimens. This pioneering work represents the first instance of employing single-cell glycan-linkages as biomarkers promising for the early diagnosis of HCC with a remarkable 100% predictive accuracy rate, which holds immense potential for enhancing the feasibility and precision of HCC diagnosis in clinical practice.

Histomolecular characterisation of hepatitis B virus induced liver cancer

Hepatitis B virus (HBV)-associated liver cancer is the third most prevalent cancer-related cause of death worldwide. Different studies have been done on the histomolecular analysis of HBV induced-liver cancer including epigenetics which are dynamic molecular mechanisms to control gene expression without altering the host deoxyribonucleic acid, genomics characterise the integration of the viral genome with host genome, proteomics characterise how gene modifies and results overexpression of proteins, glycoproteomics discover different glyco-biomarker candidates and show glycosylation in malignant hepatocytes, metabolomics characterise how HBV impairs a variety of metabolic functions during hepatocyte immortalisation, exosomes characterise immortalised liver cells in terms of their differentiation and proliferation, and autophagy plays a role in the development of hepatocarcinogenesis linked to HBV infection.

Diagnostic potential of site-specific serotransferrin N-glycosylation in discriminating different liver diseases

BACKGROUND

Altered glycosylation modulates the structure and function of disease-related proteins. The associations between serotransferrin (STF) N-glycosylation and liver diseases (LDs) have been revealed. However, how intact N-glycopeptides vary among different types of liver diseases remains unclear.

METHODS

Intact STF N-glycopeptides from patients with chronic liver disease (CLD, n = 92), primary liver cancer (PLC, n = 123), metastatic liver cancer (MLC, n = 57), and healthy controls (HCs, n = 59) were determined using high-resolution mass spectrometry.

RESULTS

Significant changes were displayed in STF glycosylation among 4 groups. The LD screening model, including Asn432 G1S/G2S, Asn432 G2S/G2S2, and Asn630 G2NS2/G2FNS2, was constructed to differentiate LDs from HCs, with a AUC of 0.92. The liver cancer (LC) diagnostic model, a combination of Asn432 G1-N/G1S-N, Asn432 G1/G2, Asn432 G2FS/G2FS2, and Asn630 G1S-N /G1S, showed good performance in discriminating LC from CLD (AUC = 0.93). Moreover, AFP-negative LC patients (93 %) were successfully predicted by the LC diagnostic model. Furthermore, the MLC triage model, composed of Asn432 G1/G2, Asn432 G3F/G3FS, Asn630 G2/G2S, Asn630 G2S2/G2NS2, and Asn630 G3FS/G3FS2, yielded an AUC of 0.98 between PLC and MLC.

CONCLUSIONS

STF N-glycosylation is a potential biomarker for the accurate classification of different LDs.

B3galt5 deficiency attenuates hepatocellular carcinoma by suppressing mTOR/p70s6k-mediated glycolysis

Hepatocellular carcinoma (HCC) is one of the most common malignancies with high morbidity and mortality. Beta-1,3-galactosyltransferase 5 (b3galt5) plays crucial roles in protein glycosylation, but its function in HCC remains unclear. Here, we investigated the role and underlying mechanism of b3galt5 in HCC. We found that b3galt5 is highly expressed and associated with a poor prognosis in HCC patients. In vitro studies showed that b3galt5 promoted the proliferation and survival of HCC cells. We also demonstrated that b3galt5 deficiency suppressed hepatocarcinogenesis in DEN/TCPOBOP-induced HCC. Further investigation confirmed that b3galt5 promoted aerobic glycolysis in HCC. Mechanistically, b3galt5 promoted glycolysis by activating the mTOR/p70s6k pathway through O-linked glycosylation modification on mTOR. Moreover, p70s6k inhibition reduced the expression of key glycolytic enzymes and the glycolysis rate in b3galt5-overexpressing cells. Our study uncovers a novel mechanism by which b3galt5 mediates glycolysis in HCC and highlights the b3galt5-mTOR/p70s6k axis as a potential target for HCC therapy.

Serum Mac-2 Binding Protein Glycosylation Isomer to Predict the Severity of Hepatic Fibrosis in Patients with Hepatitis C Virus Infection

Large-scale studies to assess the utility of the Mac-2 binding protein glycosylation isomer (M2BPGi) in predicting hepatic fibrosis in patients with hepatitis C virus (HCV) infection are limited. Serum M2BPGi level determination was performed in 1460 patients with HCV who received liver stiffness measurement (LSM) using transient elastography (TE). The correlation of LSM and grade of hepatic fibrosis as staged by TE with M2BPGi was assessed. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic power of M2BPGi for fibrosis stages of ≥F2, ≥F3, and F4. The selected M2BPGi cutoff values were chosen based on the maximal Youden index, a positive likelihood ratio (LR) ≥ 10, and a negative LR ≤ 0.1. Serum M2BPGi level was highly correlated with LSM (Pearson correlation coefficient: 0.567, p < 0.001) and hepatic fibrosis stage (Spearman’s rank correlation coefficient: 0.772, p < 0.001). The areas under ROC curves (AUROCs) of M2BPGi for ≥F2, ≥F3, and F4 were 0.865 (95% confidence interval [CI]: 0.846−0.884), 0.937 (95 % CI: 0.922−0.952), and 0.962 (95% CI: 0.951−0.972). The maximal Youden indices for ≥F2, ≥F3, and F4 were 1.72, 2.65, and 3.93. By selecting M2BPGi cutoff values with a positive LR ≥ 10 and a negative LR ≤ 0.1, clinicians were able to correctly discriminate F2, F3, and F4 in 69.1%, 77.8%, and 90.1% of patients. In conclusion, serum M2BPGi is a good diagnostic tool to predict the severity of hepatic fibrosis in patients with HCV infection.

Identification of serum glycobiomarkers for Hepatocellular Carcinoma using lectin microarrays

Objective

Hepatocellular carcinoma (HCC) is the sixth most commonly occurring cancer and ranks third in mortality among all malignant tumors; as a result, HCC represents a major human health issue. Although aberrant glycosylation is clearly implicated in HCC, changes in serum immunoglobulin (Ig)G and IgM glycosylation have not been comprehensively characterized. In this study, we used lectin microarrays to evaluate differences in serum IgG and IgM glycosylation among patients with HCC, hepatitis B cirrhosis (HBC), or chronic hepatitis B (CHB), and healthy normal controls (NC) and aimed to establish a model to improve the diagnostic accuracy of HCC.

Methods

In total, 207 serum samples collected in 2019–2020 were used for lectin microarray analyses, including 97 cases of HCC, 50 cases of HBC, 30 cases of CHB, and 30 cases of NC. Samples were randomly divided into training and validation groups at a 2:1 ratio. Training group data were used to investigate the diagnostic value of the relative signal intensity for the lectin probe combined with alpha-fetoprotein (AFP). The efficacy of models for HCC diagnosis were analyzed by receiver operating characteristic (ROC) curves.

Results

In terms of IgG, a model combining three lectins and AFP had good diagnostic accuracy for HCC. The area under the ROC curve was 0.96 (P < 0.05), the sensitivity was 82.54%, and the specificity was 100%. In terms of IgM, a model including one lectin combined with AFP had an area under the curve of 0.90 (P < 0.05), sensitivity of 75.41%, and specificity of 100%.

Conclusion

Estimation of serum IgG and IgM glycosylation could act as complementary techniques to improve diagnosis and shed light on the occurrence and development of the HCC

Nascent Proteome and Glycoproteome Reveal the Inhibition Role of ALG1 in Hepatocellular Carcinoma Cell Migration

Asparagine-linked glycosylation protein 1 homolog (ALG1) participates in the initial stage of protein N-glycosylation and N-glycosylation has been implicated in the process of hepatocellular carcinoma (HCC) progression. However, whether ALG1 plays a role in human HCC remains unknown. In this study, the expression profile of ALG1 in tumorous and corresponding adjacent non-tumor tissues was analyzed. The relationship of ALG1 expression with clinical features and prognosis of HCC patients was also evaluated using immuno-histochemical method. Here we found ALG1 decreased in HCC tissues compared with adjacent normal liver tissues, which predicted an unfavorable prognosis. Combined with RNA interference, nascent proteome and glycoproteome were determined systematically in Huh7 cell line. Bioinformatics analysis indicated that the differentially expressed proteins participating in the response of ALG1 knockdown were most significantly associated with cell-cell adhesion. Functional studies confirmed that knockdown of ALG1 reduced cell adhesion capacity, and promoted cell migration. Furthermore, down-regulation of H8N2 (on N-glycosite N651) and H5N4S2F1 (on N-glycosite N692) from N-cadherin was identified as a feature of ALG1 knockdown. Our findings revealed that ALG1 controlled the expression of glycosylated N-cadherin and played a role in HCC migration, with implications for prognosis.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-022-00050-5.

Integrated Multi-Omics Data Analysis Reveals Associations Between Glycosylation and Stemness in Hepatocellular Carcinoma

Background

Glycosylation plays an essential role in driving the progression and treatment resistance of hepatocellular carcinoma (HCC). However, its function in regulating the acquisition and maintenance of the cancer stemness-like phenotype in HCC remains largely unknown. There is also very little known about how CAD and other potential glycosylation regulators may influence stemness. This study explores the relationship between glycosylation and stemness in HCC.

Methods

Gene set variance analysis (GSVA) was used to assess the TCGA pan-cancer enrichment in glycosylation-related pathways. Univariate, LASSO, and multivariate COX regression were then used to identify prognostic genes in the TCGA-LIHC and construct a prognostic signature. HCC patients were classified into high- and low-risk subgroups based on the signature. The relationship between gene expression profiles and stemness was confirmed using bulk and single-cell RNA-sequencing data. The role of CAD and other genes in regulating the stemness of HCC was also validated by RT-qPCR, CCK-8, and colony formation assay. Copy number variation (CNV), immune infiltration, and clinical features were further analyzed in different subgroups and subsequent gene expression profiles. Sensitive drugs were also screened.

Results

In the pan-cancer analysis, HCC was shown to have specific glycosylation alterations. Five genes, CAD, SLC51B, LGALS3, B3GAT3, and MT3, identified from 572 glycosylation-related genes, were used to construct a gene signature and predict HCC patient survival in the TCGA cohort. The results demonstrated a significant positive correlation between patients in the high-risk group and both elevated gene expression and HCC dedifferentiation status. A significant reduction in the stemness-related markers, CD24, CD44, CD20, FOXM1, and EpCAM, was found after the knockdown of CAD and other genes in HepG2 and Huh7 cells. Frequent mutations increased CNVs, immune-suppressive responses, and poor prognosis were also associated with the high-risk profile. The ICGC-LIRI-JP cohort confirmed a similar relationship between glycosylation-related subtypes and stemness. Finally, 84 sensitive drugs were screened for abnormal glycosylation of HCC, and carfilzomib was most highly correlated with CAD.

Conclusions

Glycosylation-related molecular subtypes are associated with HCC stemness and disease prognosis. These results provide new directions for further research on the relationship between glycosylation and stemness phenotypes.

Identification of a Novel Glycosyltransferase Prognostic Signature in Hepatocellular Carcinoma Based on LASSO Algorithm

Although many prognostic models have been developed to help determine personalized prognoses and treatments, the predictive efficiency of these prognostic models in hepatocellular carcinoma (HCC), which is a highly heterogeneous malignancy, is less than ideal. Recently, aberrant glycosylation has been demonstrated to universally participate in tumour initiation and progression, suggesting that dysregulation of glycosyltransferases can serve as novel cancer biomarkers. In this study, a total of 568 RNA-sequencing datasets of HCC from the TCGA database and ICGC database were analysed and integrated via bioinformatic methods. LASSO regression analysis was applied to construct a prognostic signature. Kaplan-Meier survival, ROC curve, nomogram, and univariate and multivariate Cox regression analyses were performed to assess the predictive efficiency of the prognostic signature. GSEA and the "CIBERSORT" R package were utilized to further discover the potential biological mechanism of the prognostic signature. Meanwhile, the differential expression of the prognostic signature was verified by western blot, qRT-PCR and immunohistochemical staining derived from the HPA. Ultimately, we constructed a prognostic signature in HCC based on a combination of six glycosyltransferases, whose prognostic value was evaluated and validated successfully in the testing cohort and the validation cohort. The prognostic signature was identified as an independent unfavourable prognostic factor for OS, and a nomogram including the risk score was established and showed the good performance in predicting OS. Further analysis of the underlying mechanism revealed that the prognostic signature may be potentially associated with metabolic disorders and tumour-infiltrating immune cells.

Potential Biomarkers for Liver Cancer Diagnosis Based on Multi-Omics Strategy

Liver cancer is the fourth leading cause of cancer-related death worldwide. Hepatocellular carcinoma (HCC) accounts for about 85%-90% of all primary liver malignancies. However, only 20-30% of HCC patients are eligible for curative therapy mainly due to the lack of early-detection strategies, highlighting the significance of reliable and accurate biomarkers. The integration of multi-omics became an important tool for biomarker screening and unique alterations in tumor-associated genes, transcripts, proteins, post-translational modifications and metabolites have been observed. We here summarized the novel biomarkers for HCC diagnosis based on multi-omics technology as well as the clinical significance of these potential biomarkers in the early detection of HCC.

Advances in Multi-Omics Applications in HBV-Associated Hepatocellular Carcinoma

Hepatitis B virus (HBV) specifically infects liver cells, leading to progressive liver cirrhosis and significantly increasing the risk of hepatocellular carcinoma (HCC). The maturity of sequencing technology, improvement in bioinformatics data analysis and progress of omics technologies had improved research efficiency. The occurrence and progression of HCC are affected by multisystem and multilevel pathological changes. With the application of single-omics technologies, including genomics, transcriptomics, metabolomics and proteomics in tissue and body fluid samples, and even the novel development of multi-omics analysis on a single-cell platform, HBV-associated HCC changes can be better analyzed. The review summarizes the application of single omics and combined analysis of multi-omics data in HBV-associated HCC and proposes the importance of multi-omics analysis in the type of HCC, which provide the possibility for the precise diagnosis and therapy of HBV-associated HCC.

Glycosylation in viral hepatitis

BACKGROUND

The interaction between hepatitis viruses and host cells is regulated by glycans exposed on the surfaces of human and viruses cells. As the biosynthesis and degradation of human glycoproteins take place at the highest level in the liver, the changes in glycosylation of serum proteins may potentially be useful in the diagnosis of liver pathology. On the other hand, specific alterations in viruses envelope glycans could cause large changes in the entry process of hepatitis viruses into a host cells.

SCOPE OF REVIEW

Unique alterations in glycosylation of specific proteins can be detected in HBV and HCV infected patients especially with confirmed fibrosis/cirrhosis. On the other hand, viral envelope proteins that bind to host cells are glycosylated. These glycosylated proteins play a key role in recognition, binding and penetration of the host cells. In this review we summarized the knowledge about significance of glycosylation for viral and host factors.

MAJOR CONCLUSIONS

Glycosylation changes in single serum glycoproteins are noticed in the sera of patients with viral hepatitis. However, a more specific biomarker for the diagnosis of chronic hepatitis than that of a single glycosylated molecule is systemic investigation of complete set of glycan structures (N-glycome). Glycans play important roles in the viral biology cycle especially as a connecting element with host receptors.

GENERAL SIGNIFICANCE

The interaction between virus glycoproteins and cellular receptors, which are also glycoproteins, determines the possibility of virus penetration into host cells. Therefore these glycans can be the targets for the developing of novel treatment strategies of viral hepatitis.

Analysis of HBsAg mutations in the 25 years after the implementation of the hepatitis B vaccination plan in China

Since 1992, China has promoted hepatitis B vaccination. Concurrently, during this period, increasing use of immunoglobulins and nucleoside analogues might have exerted selective pressure on the hepatitis B virus (HBV) S gene, driving mutations in the HBsAg and changed the subtype. Using the National Center for Biotechnology Information database, we obtained gene sequence information for HBV strains from China and analysed changes in HBsAg subtypes and substitution mutations in HBsAg in 5-year intervals over 25 years to identify potential challenges to the prevention and treatment of hepatitis B. Most HBV sequences from China were genotype C (1996/2833, 70.46%) or B (706/2833, 24.92%). During the implementation of hepatitis B vaccination (recombinant hepatitis B vaccine was subgenotype A2 and HBsAg subtype adw2), the proportion of subtypes ayw1 and adw3 in genotype B and ayw2 in genotype C increased over the programme period. The overall mutation rate in HBsAg tended to decrease for genotype B, whereas, for genotype C, the rate increased gradually and then decreased slightly. Moreover, the mutation rate at some HBsAg amino acid sites (such as sG145 of genotype B and sG130 and sK141 of genotype C) is gradually increasing. HBV strains with internal stop codons of HBsAg (e.g., sC69*) and additional N-glycosylation (e.g., sG130N) mutations should be studied extensively to prevent them from becoming dominant circulating strains. The development of HBV vaccines and antiviral immunoglobulins and use of antiviral drugs may require making corresponding changes.

N-glycopeptide Signatures of IgA2 in Serum from Patients with Hepatitis B Virus-related Liver Diseases

N-glycosylation alteration has been reported in liver diseases. Characterizing N-glycopeptides that correspond to N-glycan structure with specific site information enables better understanding of the molecular pathogenesis of liver damage and cancer. Here, unbiased quantification of N-glycopeptides of a cluster of serum glycoproteins with 40-55 kDa molecular weight (40-kDa band) was investigated in hepatitis B virus (HBV)-related liver diseases. We used an N-glycopeptide method based on 18O/16O C-terminal labeling to obtain 82 comparisons of serum from patients with HBV-related hepatocellular carcinoma (HCC) and liver cirrhosis (LC). Then, multiple reaction monitoring (MRM) was performed to quantify N-glycopeptide relative to the protein content, especially in the healthy donor-HBV-LC-HCC cascade. TPLTAN205ITK (H5N5S1F1) and (H5N4S2F1) corresponding to the glycopeptides of IgA2 were significantly elevated in serum from patients with HBV infection and even higher in HBV-related LC patients, as compared with healthy donor. In contrast, the two glycopeptides of IgA2 fell back down in HBV-related HCC patients. In addition, the variation in the abundance of two glycopeptides was not caused by its protein concentration. The altered N-glycopeptides might be part of a unique glycan signature indicating an IgA-mediated mechanism and providing potential diagnostic clues in HBV-related liver diseases.

Gangliosides profiling in serum of breast cancer patient: GM3 as a potential diagnostic biomarker

Gangliosides altered during the pathological conditions and particularly in cancers. Here, we aimed to profile the gangliosides in breast cancer serum and propose potential biomarkers. LC-FTMS method was first used to identify all the ganglioside species in serum, then LC-MS/MS-MRM method was employed to quantitate the levels of gangliosides in serum from healthy volunteers and patients with benign breast tumor or breast cancer. 49 ganglioside species were determined, including GM1, GM2, GM3, GD1, GD3 and GT1 species. Compared to healthy volunteers, the levels of GM1, GM2, GM3, GD1 and GD3 displayed a rising trend in breast cancer patients. In particular, as the major glycosphingolipid component, GM3 showed excellent diagnostic accuracy in cancer serum (AUC > 0.9). PCA profile of the GM3 species showed clear distinction between normal and cancer serum. What's more, ROC curve proved great diagnostic accuracy of GM3 between cancer and benign serum. In addition, GM3 was discovered as a diagnostic marker to differentiate luminal B subtype from other subtypes. Furthermore, a positive correlation between GM3 and Ki-67 status of patients was identified. In conclusion, our results introduced the alteration patterns of serum gangliosides in breast cancer and suggested serum GM3 as a potential diagnostic biomarker in breast cancer diagnosis and luminal B subtype distinction.

Analysis of serum Haptoglobin using glycoproteomics and lectin immunoassay in liver diseases in Hepatitis B virus infection

BACKGROUND

Hepatocellular carcinoma (HCC) due to Hepatitis B viral (HBV) infection is a major cause in Asia-Pacific countries. Its early detection is of paramount importance using a marker having both sensitivity and specificity. The present study promises diagnostic and prognostic markers by the identification of site-specific glycoforms on Haptoglobin (Hp) using LC-MS/MS and lectin ELISA in liver diseased conditions in HBV infection.

METHODS

Three groups of patients: chronic, liver cirrhosis and HCC with HBV infection along with controls were enrolled. Hp was purified using affinity column chromatography and, peptide sequence, N-glycosylation site, glycan composition and glycoforms were identified using mass spectrometry. Quantitative lectin ELISA was used to measure levels of fucosylation on Hp in liver diseases due to HBV.

RESULTS

Hp levels were significantly lower in HCC when compared with Non-HCC cases (p < .05). Fucosylated glycoforms were significantly increased at site Asn184, Asn207 and Asn211 in liver diseased stages versus controls. A significant association was observed between the Fuc-Hp/Hp Elisa index and, advanced liver disease stages and controls using lectin Elisa (p < .001).

CONCLUSION

Quantitation of fucosylation levels on Hp protein using Lectin ELISA may be useful glycobiomarker either alone or in combination (AFP + DCP + FucHp; AUC = 0.94) in HBV HCC diagnosis in clinical practice.