Clinical utility of serum fucosylated hemopexin in Japanese patients with hepatocellular carcinoma

Benchmark N-glycoproteomics study of common differential tissue and serum N-glycoproteins of patients with hepatocellular carcinoma

For hepatocellular carcinoma (HCC), N-glycosylation has been proved to be widely involved in various aspects of the disease, including development, metastasis, subtyping, diagnosis and prognosis. The common practice is to discover biomarkers in situ of cancer occurrence (i.e., cancer vs. adjacent tissues) yet to clinically monitor in sera because of non-invasiveness. This study benchmarks N-glycoproteomics characterization of common differential tissue and serum N-glycoproteins of patients with HCC. Differential N-glycosylation in matched tissue and serum samples from the same patients were quantitatively characterized at the intact N-glycopeptide molecular level, and 29 common N-glycoproteins were found. Subcellular localization analysis was carried out to confirm the tissue originality. Secreted N-glycoprotein APOH was up-regulated, and transmembrane and intracellular N-glycoproteins including OSMR, GAT2, CSF-1 and MAGI3 were down-regulated.

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.

Labile Heme and Heme Oxygenase-1 Maintain Tumor-Permissive Niche for Endometriosis-Associated Ovarian Cancer

Endometriosis, a painful gynecological condition accompanied by inflammation in women of reproductive age, is associated with an increased risk of ovarian cancer. We evaluated the role of peritoneal heme accumulated during menstrual cycling, as well as peritoneal and lesional macrophage phenotype, in promoting an oncogenic microenvironment. We quantified the heme-degrading enzyme, heme oxygenase-1 (HO-1, encoded by Hmox1) in normal peritoneum, endometriotic lesions and endometriosis-associated ovarian cancer (EAOC) of clear cell type (OCCC). HO-1 was expressed primarily in macrophages and increased in endometrioma and OCCC tissues relative to endometriosis and controls. Further, we compared cytokine expression profiles in peritoneal macrophages (PM) and peripheral blood mononuclear cells (PBMC) in women with endometriosis versus controls as a measure of a tumor-promoting environment in the peritoneum. We found elevated levels of HO-1 along with IL-10 and the pro-inflammatory cytokines (IL-1β, IL-16, IFNγ) in PM but not in PBMC from endometriosis patients. Using LysM-Cre:Hmox1flfl conditional knockout mice, we show that a deficiency of HO-1 in macrophages led to the suppression of growth of ID8 ovarian tumors implanted into the peritoneum. The restriction of ID8 ovarian tumor growth was associated with an increased number of Mac3+ macrophage and B cells in LysM-Cre:Hmox1flfl mice compared to controls. Functional experiments in ovarian cancer cell lines show that HO-1 is induced by heme. Low levels of exogenous heme promoted ovarian cancer colony growth in soft agar. Higher doses of heme led to slower cancer cell colony growth in soft agar and the induction of HO-1. These data suggest that perturbation of heme metabolism within the endometriotic niche and in cancer cells themselves may be an important factor that influences tumor initiation and growth.

Identification of noninvasive diagnostic biomarkers for hepatocellular carcinoma by urinary proteomics

Hepatocellular carcinoma (HCC) ranks fourth in cancer mortality worldwide, and third in China. Hepatitis B virus (HBV) infection is a main risk factor for HCC in China, and the early diagnosis of HCC in high-risk population is very important. However, the commonly used diagnostic biomarker alpha-fetoprotein has limitations in clinical practice. In order to identify reliable and noninvasive HCC urinary biomarkers, a high-throughput proteomics streamline was applied in the analysis of urine samples from 74 HCC and 82 high-risk patients with chronic HBV infected liver diseases. Candidate diagnostic markers were screened by feature selection algorithm, and were combined with random forest or simple voting algorithms in the training dataset. Then the multiple feature models were validated in an independent test dataset. The selected features were further verified by Multiple Reaction Monitoring (MRM) in another independent dataset. By integrating 7 features screened in the discovery phase, random forest model achieved AUC of 0.92 and 0.87 in training and test datasets, respectively, while voting model performed better with AUC of 0.94 and 0.90, respectively. In the MRM dataset, the 7 features were targeted quantified, and voting model integrating the 7 features achieved AUC of 0.95. Our work highlights the potential of noninvasive urinary protein biomarkers in HCC diagnosis with high-risk population, which will be beneficial to HCC auxiliary diagnosis and HCC surveillance. SIGNIFICANCE: A high throughput urinary proteome analysis platform was committed into the discovery of noninvasive HCC biomarkers in high-risk patients with chronic HBV infected liver diseases. The combination of 7 urinary features achieved good performance in distinguishing HCC from high-risk population. The expression of the 7 features was validated by targeted MRM, and the integration of the features also worked well in the MRM dataset. This is the first time that urinary proteomic strategy was applied in discovering HCC biomarkers from high-risk population. This result will be helpful for HCC auxiliary diagnosis and surveillance in a noninvasive way.

Stromal expression of hemopexin is associated with lymph-node metastasis in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma is one of the most aggressive types of cancer. Certain proteins in the tumor microenvironment have attracted considerable attention owing to their association with tumor invasion and metastasis. Here, we used proteomics to identify proteins associated with lymph-node metastasis, which is one of the prognostic factors. We selected lymph node metastasis-positive and -negative patients (n = 5 each) who underwent pancreatectomy between 2005 and 2015 and subjected to comprehensive proteomic profiling of tumor stroma. A total of 490 proteins were detected by mass spectrometry. Software analysis revealed that nine of these proteins were differentially expressed between the two patient groups. We focused on hemopexin and ferritin light chain based on immunohistochemistry results. We assessed the clinicopathological data of 163 patients and found that hemopexin expression was associated with UICC N2 (p = 0.0399), lymph node ratio (p = 0.0252), venous invasion (p = 0.0096), and lymphatic invasion (p = 0.0232). Notably, in vitro assays showed that hemopexin promotes invasion of the pancreatic cancer cells. Our findings suggest that hemopexin is a lymph node metastasis-associated protein that could potentially serve as a useful therapeutic target or biomarker of pancreatic ductal adenocarcinoma.

Biomarkers for the Early Detection of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, and the cancer with the fastest increase in mortality in the United States, with more than 39,000 cases and 29,000 deaths in 2018. As with many cancers, survival is significantly improved by early detection. The median survival of patients with early HCC is >60 months but <15 months when detected at an advanced stage. Surveillance of at-risk patients improves outcome, but fewer than 20% of those at risk for HCC receive surveillance, and current surveillance strategies have limited sensitivity and specificity. Ideally, blood-based biomarkers with adequate sensitivity or specificity would be available for early detection of HCC; however, the most commonly used biomarker for HCC, alpha-fetoprotein, has inadequate performance characteristics. There are several candidate serum proteomic, glycomic, and genetic markers that have gone through early stages of biomarker validation and have shown promise for the early detection of HCC, but these markers require validation in well-curated cohorts. Ongoing prospective cohort studies will permit retrospective longitudinal (phase III biomarker study) validation of biomarkers. In this review, we highlight promising candidate biomarkers and biomarker panels that have completed phase II evaluation but require further validation prior to clinical use.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Glycoproteomic markers of hepatocellular carcinoma-mass spectrometry based approaches

Hepatocellular carcinoma (HCC) is the third most-common cause of cancer-related death worldwide. Most cases of HCC develop in patients that already have liver cirrhosis and have been recommended for surveillance for an early onset of HCC. Cirrhosis is the final common pathway for several etiologies of liver disease, including hepatitis B and C, alcohol, and increasingly non-alcoholic fatty liver disease. Only 20-30% of patients with HCC are eligible for curative therapy due primarily to inadequate early-detection strategies. Reliable, accurate biomarkers for HCC early detection provide the highest likelihood of curative therapy and survival; however, current early-detection methods that use abdominal ultrasound and serum alpha fetoprotein are inadequate due to poor adherence and limited sensitivity and specificity. There is an urgent need for convenient and highly accurate validated biomarkers for HCC early detection. The theme of this review is the development of new methods to discover glycoprotein-based markers for detection of HCC with mass spectrometry approaches. We outline the non-mass spectrometry based methods that have been used to discover HCC markers including immunoassays, capillary electrophoresis, 2-D gel electrophoresis, and lectin-FLISA assays. We describe the development and results of mass spectrometry-based assays for glycan screening based on either MALDI-MS or ESI analysis. These analyses might be based on the glycan content of serum or on glycan screening for target molecules from serum. We describe some of the specific markers that have been developed as a result, including for proteins such as Haptoglobin, Hemopexin, Kininogen, and others. We discuss the potential role for other technologies, including PGC chromatography and ion mobility, to separate isoforms of glycan markers. Analyses of glycopeptides based on new technologies and innovative softwares are described and also their potential role in discovery of markers of HCC. These technologies include new fragmentation methods such as EThcD and stepped HCD, which can identify large numbers of glycopeptide structures from serum. The key role of lectin extraction in various assays for intact glycopeptides or their truncated versions is also described, where various core-fucosylated and hyperfucosylated glycopeptides have been identified as potential markers of HCC. Finally, we describe the role of LC-MRMs or lectin-FLISA MRMs as a means to validate these glycoprotein markers from patient samples. These technological advancements in mass spectrometry have the potential to lead to novel biomarkers to improve the early detection of HCC.

Associated measurement of fucosylated levels of AFP, DCP, and GPC3 for early diagnosis in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma is a serious health problem worldwide, especially in Asian countries, such as China. However, there are difficulties in diagnosing and treating hepatocellular carcinoma. The alteration of fucosylated proteins was closely associated with carcinogenesis. This study is designed to evaluate the early diagnostic value of associated detection of fucosylated alpha-fetoprotein (fuc-AFP), fucosylated des-γ-carboxy prothrombin (fuc-DCP), and fucosylated glypican 3 (fuc-GPC3) in hepatocellular carcinoma.

METHODS

All serum specimens collected from patients were diagnosed by complete clinicopathological examination and then subjected to the associated detection of fuc-AFP, fuc-DCP, and fuc-GPC3 by protein microarray. Canonical discriminant analysis was adopted to discriminate between the hepatocellular carcinoma group and the benign liver disease group.

RESULTS

A total of 51 patients with hepatocellular carcinoma and 47 patients in the benign liver disease group were included in this study. Fuc-AFP, fuc-DCP, and fuc-GPC3 were significantly higher in the hepatocellular carcinoma group than in the benign liver disease group. The sensitivity, specificity, and accuracy of canonical discriminant analysis classification were 80.4%, 97.9%, and 88.8%, respectively.

CONCLUSIONS

Fuc-AFP, fuc-DCP, and fuc-GPC3 are effective and useful tumor biomarkers. Associated measurement of these biomarkers with canonical discriminant analysis classification is a promising method for the early diagnosis of hepatocellular carcinoma.

HST-MRM-MS: A Novel High-Sample-Throughput Multiple Reaction Monitoring Mass Spectrometric Method for Multiplex Absolute Quantitation of Hepatocellular Carcinoma Serum Biomarker

Absolute quantification of clinical biomarkers by mass spectrometry (MS) has been challenged due to low sample-throughput of current multiple reaction monitoring (MRM) methods. For this problem to be overcome, in this work, a novel high-sample-throughput multiple reaction monitoring mass spectrometric (HST-MRM-MS) quantification approach is developed to achieve simultaneous quantification of 24 samples. Briefly, triplex dimethyl reagents (L, M, and H) and eight-plex iTRAQ reagents were used to label the N- and C-termini of the Lys C-digested peptides, respectively. The triplex dimethyl labeling produces three coelute peaks in MRM traces, and the iTRAQ labeling produces eight peaks in MS2, resulting in 24 (3×8) channels in a single experiment. HST-MRM-MS has shown good accuracy ( R² > 0.98 for absolute quantification), reproducibility (RSD < 15%), and linearity (2-3 orders of magnitude). Moreover, the novel method has been successfully applied in quantifying serum biomarkers in hepatocellular carcinoma (HCC)-related serum samples. In conclusion, HST-MRM-MS is an accurate, high-sample-throughput, and broadly applicable MS-based absolute quantification method.

Integrated GlycoProteome Analyzer (I-GPA) for Automated Identification and Quantitation of Site-Specific N-Glycosylation

Human glycoproteins exhibit enormous heterogeneity at each N-glycosite, but few studies have attempted to globally characterize the site-specific structural features. We have developed Integrated GlycoProteome Analyzer (I-GPA) including mapping system for complex N-glycoproteomes, which combines methods for tandem mass spectrometry with a database search and algorithmic suite. Using an N-glycopeptide database that we constructed, we created novel scoring algorithms with decoy glycopeptides, where 95 N-glycopeptides from standard α1-acid glycoprotein were identified with 0% false positives, giving the same results as manual validation. Additionally automated label-free quantitation method was first developed that utilizes the combined intensity of top three isotope peaks at three highest MS spectral points. The efficiency of I-GPA was demonstrated by automatically identifying 619 site-specific N-glycopeptides with FDR ≤ 1%, and simultaneously quantifying 598 N-glycopeptides, from human plasma samples that are known to contain highly glycosylated proteins. Thus, I-GPA platform could make a major breakthrough in high-throughput mapping of complex N-glycoproteomes, which can be applied to biomarker discovery and ongoing global human proteome project.

Mass-Selected Site-Specific Core-Fucosylation of Serum Proteins in Hepatocellular Carcinoma

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.

Glycosylation and liver cancer

Liver cancer is the fifth most common cancer, but the second leading cause of cancer death, in the world, with more than 700,000 fatalities annually. The major etiology of liver cancer is infection with an hepatotropic virus such as hepatitis B virus or hepatitis C virus infection. While chronic viral infection remains the main cause of liver disease and risk of hepatocellular carcinoma (HCC), rates of nonviral-associated HCC are occurring at an alarmingly increasing rate. Like many cancers, survival rates are closely associated with time of detection. If HCC is caught early, survival rates can be as high as 50%. Regrettably, most cases of HCC are caught late where survival rates can be as low as 2-7%. Thus, there has been great interest in discovering serum biomarkers that could be used to identify those with HCC. To this end, many groups have examined the N-linked glycans to identify changes that occur with HCC. As the liver secretes the vast majority of proteins into the serum, this has often been a starting point for study. In serum, alterations in core fucosylation, outer-arm fucosylation, increased sialylation, and glycan branching have been observed in patients with HCC. Similar findings have been found directly in HCC tissue suggesting that these glycan changes may play a role in tumor formation and development.

Comparative salivary proteome of hepatitis B- and C-infected patients

Hepatitis B and C virus (HBV and HCV) infections are an important cause of cirrhosis and hepatocellular carcinoma. The natural history has a prominent latent phase, and infected patients may remain undiagnosed; this situation may lead to the continuing spread of these infections in the community. Compelling reasons exist for using saliva as a diagnostic fluid because it meets the demands of being an inexpensive, noninvasive and easy-to-use diagnostic method. Indeed, comparative analysis of the salivary proteome using mass spectrometry is a promising new strategy for identifying biomarkers. Our goal is to apply an Orbitrap-based quantitative approach to explore the salivary proteome profile in HBV- and HCV-infected patients. In the present study, whole saliva was obtained from 20 healthy, (control) 20 HBV-infected and 20 HCV-infected subjects. Two distinct pools containing saliva from 10 subjects of each group were obtained. The samples were ultracentrifuged and fractionated, and all fractions were hydrolyzed (trypsin) and injected into an LTQ-VELOS ORBITRAP. The identification and analyses of peptides were performed using Proteome Discoverer1.3 and ScaffoldQ + v.3.3.1. From a total of 362 distinct proteins identified, 344 proteins were identified in the HBV, 326 in the HCV and 303 in the control groups. Some blood proteins, such as flavin reductase (which converts biliverdin to bilirubin), were detected only in the HCV group. The data showed a reduced presence of complement C3, ceruloplasmin, alpha(1)-acid glycoprotein and alpha(2)-acid glycoprotein in the hepatitis-infected patients. Peptides of serotransferrin and haptoglobin were less detected in the HCV group. This study provides an integrated perspective of the salivary proteome, which should be further explored in future studies targeting specific disease markers for HBV and HCV infection.

Protein profiling in hepatocellular carcinoma by label-free quantitative proteomics in two west African populations

BACKGROUND

Hepatocellular Carcinoma is the third most common cause of cancer related death worldwide, often diagnosed by measuring serum AFP; a poor performance stand-alone biomarker. With the aim of improving on this, our study focuses on plasma proteins identified by Mass Spectrometry in order to investigate and validate differences seen in the respective proteomes of controls and subjects with LC and HCC.

METHODS

Mass Spectrometry analysis using liquid chromatography electro spray ionization quadrupole time-of-flight was conducted on 339 subjects using a pooled expression profiling approach. ELISA assays were performed on four significantly differentially expressed proteins to validate their expression profiles in subjects from the Gambia and a pilot group from Nigeria. Results from this were collated for statistical multiplexing using logistic regression analysis.

RESULTS

Twenty-six proteins were identified as differentially expressed between the three subject groups. Direct measurements of four; hemopexin, alpha-1-antitrypsin, apolipoprotein A1 and complement component 3 confirmed their change in abundance in LC and HCC versus control patients. These trends were independently replicated in the pilot validation subjects from Nigeria. The statistical multiplexing of these proteins demonstrated performance comparable to or greater than ALT in identifying liver cirrhosis or carcinogenesis. This exercise also proposed preliminary cut offs with achievable sensitivity, specificity and AUC statistics greater than reported AFP averages.

CONCLUSIONS

The validated changes of expression in these proteins have the potential for development into high-performance tests usable in the diagnosis and or monitoring of HCC and LC patients. The identification of sustained expression trends strengthens the suggestion of these four proteins as worthy candidates for further investigation in the context of liver disease. The statistical combinations also provide a novel inroad of analyses able to propose definitive cut-offs and combinations for evaluation of performance.