Input of serum haptoglobin fucosylation profile in the diagnosis of hepatocellular carcinoma in patients with non-cirrhotic liver disease

Systematic review: Glycomics as diagnostic markers for hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the most prevalent primary liver cancer with one of the highest cancer-related mortality rates worldwide. Early diagnosis is crucial for improving the therapeutic options and reducing the disease-related mortality.

AIM

To investigate serum N-glycomics as diagnostic markers for HCC.

METHODS

We performed a comprehensive search in PubMed, EMBASE, Web of Science and Scopus through August 17, 2023. Eligible studies assessed the potential use of serum N-glycomics as diagnostic biomarkers for HCC. Study selection, data extraction and quality assessment were performed by two independent reviewers.

RESULTS

Of the 48 articles included, 11 evaluated the utility of N-glycomics for the diagnosis of HCC in whole serum while the remaining articles focused on specific protein glycoforms or protein levels. Of these specific proteins, haptoglobin, alpha-fetoprotein (AFP), kininogen (Kin), α-1-antitrypsin and Golgi protein 73 (GP73) were the most frequently studied. Increased levels of fucosylation and branching presented as the most prevalent post-translational modifications of glycoproteins in patients with HCC compared to controls. Notably, glycomics-based biomarkers may provide a clinical benefit for the diagnosis of early HCC, as several algorithms achieved AUCs between 0.92-0.97. However, these were based on single studies with limited sample sizes and should therefore be validated.

CONCLUSIONS

Alterations in serum N-glycomics, characterised by increased levels of fucosylation and branching, have potential as diagnostic biomarkers for HCC. Optimisation of study design, patient selection and analysing techniques are needed before clinical implementation will be possible.

Discovery of a haptoglobin glycopeptides biomarker panel for early diagnosis of hepatocellular carcinoma

Background

There is a need for new serum biomarkers for early detection of hepatocellular carcinoma (HCC). Haptoglobin (Hp) N-glycosylation is altered in HCC, but the diagnostic value of site-specific Hp glycobiomarkers is rarely reported. We aimed to determine the site-specific glycosylation profile of Hp for early-stage HCC diagnosis.

Method

Hp glycosylation was analyzed in the plasma of patients with liver diseases (n=57; controls), early-stage HCC (n=50) and late-stage HCC (n=32). Hp phenotype was determined by immunoblotting. Hp was immunoisolated and digested into peptides. N-glycopeptides were identified and quantified using liquid chromatography-mass spectrometry. Cohort samples were compared using Wilcoxon rank-sum (Mann-Whitney U) tests. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves and area under curve (AUC).

Results

Significantly higher fucosylation, branching and sialylation of Hp glycans, and expression of high-mannose glycans, was observed as disease progressed from cirrhosis to early- and late-stage HCC. Several glycopeptides demonstrated high values for early diagnosis of HCC, with an AUC of 93% (n=1), >80% (n=3), >75% (n=13) and >70% (n=11), compared with alpha-fetoprotein (AFP; AUC of 79%). The diagnostic performance of the identified biomarkers was only slightly affected by Hp phenotype.

Conclusion

We identified a panel of Hp glycopeptides that are significantly differentially regulated in early- and late-stage HCC. Some glycobiomarkers exceeded the diagnostic value of AFP (the most commonly used biomarker for HCC diagnosis). Our findings provide evidence that glycobiomarkers can be effective in the diagnosis of early HCC - individually, as a panel of glycopeptides or combined with conventional serological biomarkers.

Selective profiling of liver-related specific proteins based on sofosbuvir-modified magnetic separation material

It has great significance in profiling specific proteins throughout for better understanding of complex pathological processes and in-depth pharmacological studies. In this work, an efficient protein profiling strategy was developed based on the specific protein-drug interaction. Sofosbuvir (SOF), as a first-line drug for the treatment of hepatitis C, was modified onto the surface of nanoparticles through stable chemical bonds to fabricate a novel magnetic separation material denoted as Fe₃O₄@SiO₂@PAA@SOF. With sequence coverage as the screening parameter, nine proteins were profiled from fetal bovine serum (FBS) of which eight were liver related. Similarly, the strategy was applied to hepatocellular carcinoma (HCC) patient serum. Eight proteins were profiled and all of them were liver related, demonstrating the superb specificity and selectivity of this strategy for profiling liver-related proteins by virtue of protein-SOF interaction. When serum proteins from HCC patients were compared to those from healthy people, one unique differential protein (D3DQX7) was profiled, which was liver related and was a potential target for ameliorating liver diseases. For further research, this material design concept and protein profiling strategy can be extended to employ other drugs for corresponding studies. Sofosbuvir, as a therapeutic drug for liver diseases, was modified onto the surface of magnetic nanoparticles to fabricate the specific selective separation material (Fe₃O₄@SiO₂@PAA@SOF). Based on protein-SOF interaction, the material was applied to adsorb specific proteins from different serum samples. After MS analysis, specific proteins, most of which were liver related, were successfully profiled from FBS and HCC patient serum, fully demonstrating the superb specificity and selectivity of this protein profiling strategy.

In-depth investigation of altered glycosylation in human haptoglobin associated cancer by mass spectrometry

Serum haptoglobin (Hp), a highly sialylated biomolecule with four N-glycosylation sites, is a positive acute-phase response glycoprotein that acts as an immunomodulator. Hp has gained considerable attention due to its potential as a signature molecule that exhibits aberrant glycosylation in inflammatory disorders and malignancies. Its glycosylation can be analyzed qualitatively and quantitatively by various methods using mass spectrometry. In this review, we have provided a brief overview of Hp structure and biological function and described mass spectrometry-based techniques for analyzing glycosylation ranging from macroheterogeneity to microheterogeneity of Hp in diseases and cancer. The sugars on haptoglobin can be a sweet bridge to link the potential of cancer-specific biomarkers to clinically relevant applications.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

Mass spectrometry based biomarkers for early detection of HCC using a glycoproteomic approach

Hepatocellular carcinoma (HCC) is the fourth most common cause of cancer-related mortality worldwide and 80%-90% of HCC develops in patients that have underlying cirrhosis. Better methods of surveillance are needed to increase early detection of HCC and the proportion of patients that can be offered curative therapies. Recent work in novel mass spec-based methods for glycomic and glycopeptide analysis for discovery and confirmation of markers for early detection of HCC versus cirrhosis is reviewed in this chapter. Results from recent work in these fields by several groups and the progress made in developing markers of early HCC which can outperform the current serum-based markers are described and discussed. Also, recent developments in isoform analysis of glycans and glycopeptides and in various mass spec fragmentation methods will be described and discussed.

External validation of LCR1-LCR2, a multivariable HCC risk calculator, in patients with chronic HCV

Background & Aims

The Liver Cancer Risk test algorithm (LCR1-LCR2) is a multianalyte blood test combining proteins involved in liver cell repair (apolipoprotein-A1 and haptoglobin), known hepatocellular carcinoma (HCC) risk factors (sex, age, and gamma-glutamyl transferase), a marker of fibrosis (alpha2-macroglobulin) and alpha-fetoprotein (AFP), a specific marker of HCC. The aim was to externally validate the LCR1-LCR2 in patients with chronic HCV (CHC) treated or not with antivirals.

Methods

Pre-included patients were from the Hepather cohort, a multicentre prospective study in adult patients with CHC in France. LCR1-LCR2 was assessed retrospectively in patients with the test components and AFP, available at baseline. The co-primary study outcome was the negative predictive value (NPV) of LCR1-LCR2 for the occurrence of HCC at 5 years and for survival without HCC according to the predetermined LCR1-LCR2 cut-offs. The cut-offs were adjusted for risk covariables and for the response to HCV treatment, and were quantified using time-dependent proportional hazards models.

Results

In total, 4,903 patients, 1,026 (21.9%) with baseline cirrhosis, were included in the study. Patients were followed for a median of 5.7 (IQR 4.2–11.3) years. A total of 3,788/4,903 (77.3%) patients had a sustained virological response. There were 137 cases of HCC at 5 years and 214 at the end of follow-up. HCC occurred at 5 years in 24/3,755 patients with low-risk LCR1-LCR2 compared with 113/1,148 patients with high-risk LCR1-LCR2. The NPV was 99.4% (95% CI 99.1–99.6). Similar findings (hazard ratio, 10.8; 95% CI, 8.1–14.3; p <0.001) were obtained after adjustment for exposure to antivirals, age, sex, geographical origin, HCV genotype 3, alcohol consumption, and type 2 diabetes mellitus.

Conclusions

The results showed that LCR1-LCR2 can be used to successfully identify patients with HCV at very low risk of HCC at 5 years.

Lay summary

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related death worldwide and the fastest growing cause of cancer death in many countries. We constructed and internally validated a new multianalyte blood test to assess this Liver Cancer Risk (LCR1-LCR2). This study confirmed the performance of LCR1-LCR2 in patients with chronic HCV in the national French cohort Hepather, and its ability to identify patients at a very low risk of HCC at 5 years.

Clinical Trials registration

The study is registered at ClinicalTrials.gov (NCT01953458).

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HCC is the fourth leading cause of cancer-related death worldwide and the fastest growing cause of cancer deaths in the USA.

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The American Association for the Study of Liver Diseases recommends surveillance every 6 months only in patients with cirrhosis.

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The LCR1-LCR2 algorithm is a multianalyte blood test combining proteins involved in cell repair, fibrosis and liver cancer.

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The LCR1-LCR2 algorithm was able to identify patients with chronic HCV at very low risk of HCC at 5 years.

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This algorithm could help clinicians to reassure a percentage of patients with chronic HCV that their risk of developing HCC remains low.