Prediction of chronic hepatitis B, liver cirrhosis and hepatocellular carcinoma by SELDI-based serum decision tree classification

Clinical significance of novel biomarkers to predict the natural course of hepatitis B infection

Background and aim

Chronic hepatitis B (CHB) can be divided into immune tolerance (IT), immune clearance (IC), hepatitis B e antigen (HBeAg)-negative inactive/quiescent carrier (ENQ), and HBeAg-negative hepatitis (ENH) phases. The conventional biomarkers used to distinguish these phases have limitations. We examined the clinical significance of hepatitis B virus (HBV) RNA and hepatitis B core-related antigen (HBcrAg) as novel biomarkers.

Methods

One hundred eighty-nine patients without treatment currently were categorized by CHB phase (IT = 46, IC = 45, ENQ = 49, ENH = 49). The associations of HBV RNA and HBcrAg with HBV DNA and alanine transaminase (ALT) were analyzed. The decision tree model was used to distinguish the four phases in the natural course of CHB.

Results

The concentrations of HBV RNA and HBcrAg were highest in the IT and IC phases (P < 0.01). Serum HBV RNA was similar to HBcrAg in treatment-naïve patients. HBV RNA and HBcrAg correlated with HBV DNA in the HBeAg⁺ and HBeAg^- status (HBV RNA: e⁺ r = 0.51, e^- r = 0.62; HBcrAg: e⁺ r = 0.51, e^- r = 0.71), but their association with HBV DNA differed among phases. The accuracy, sensitivity, and specificity of HBcrAg with ALT in distinguishing the CHB phases were 95.65%, 95.83%, and 95.55%, respectively.

Conclusion

Serum HBV RNA and HBcrAg may be useful to monitor CHB progression.

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.

Potential Serum Markers for Monitoring the Progression of Hepatitis B Virus-Associated Chronic Hepatic Lesions to Liver Cirrhosis

BACKGROUND/AIMS

To screen for serum protein/peptide biomarkers of hepatitis B virus (HBV)-associated chronic hepatic lesions in an attempt to profile the progression of HBV-associated chronic hepatic lesions using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) techniques.

METHODS

Using SELDI-TOF MS, serum protein/peptide profiles on the CM10 ProteinChip arrays were obtained from a training group including 26 HBV-associated hepatocellular carcinoma patients with liver cirrhosis (LC), 30 HBV-associated LC patients, 85 patients at different stages of liver fibrosis, and 30 asymptomatic HBV carriers. The most valuable SELDI peak for predicting the progression to LC in HBV-infected patients was identified.

RESULTS

A SELDI peak of M/Z 5805 with value for predicting LC in HBV-infected patients was found and was identified as a peptide of the C-terminal fraction of the fibrinogen a-chain precursor, isoform 1.

CONCLUSIONS

The peptide of the C-terminal fraction of the fibrinogen α-chain precursor, isoform 1 with M/Z 5805, may be a serological biomarker for progression to LC in HBV-infected patients.

Biomarkers of liver fibrosis

Liver fibrosis is the final common pathway for almost all causes of chronic liver injury. Liver fibrosis is now known to be a dynamic process having significant potential for resolution. Therefore, fibrosis prediction is an essential part of the assessment and management of patients with chronic liver disease. As such, there is strong demand for reliable liver biomarkers that provide insight into disease etiology, diagnosis, therapy, and prognosis in lieu of more invasive approaches such as liver biopsy. Current diagnostic strategies range from use of serum biomarkers to more advanced imaging techniques including transient elastography and magnetic resonance imaging. In addition to these modalities, there are other approaches including the use of novel, but yet to be validated, biomarkers. In this chapter, we discuss the biomarkers of liver fibrosis including the use of invasive and noninvasive biomarkers and disease-specific biomarkers in various chronic liver diseases.

Two classifiers based on serum peptide pattern for prediction of HBV-induced liver cirrhosis using MALDI-TOF MS

Chronic infection with hepatitis B virus (HBV) is associated with the majority of cases of liver cirrhosis (LC) in China. Although liver biopsy is the reference method for evaluation of cirrhosis, it is an invasive procedure with inherent risk. The aim of this study is to discover novel noninvasive specific serum biomarkers for the diagnosis of HBV-induced LC. We performed bead fractionation/MALDI-TOF MS analysis on sera from patients with LC. Thirteen feature peaks which had optimal discriminatory performance were obtained by using support-vector-machine-(SVM-) based strategy. Based on the previous results, five supervised machine learning methods were employed to construct classifiers that discriminated proteomic spectra of patients with HBV-induced LC from those of controls. Here, we describe two novel methods for prediction of HBV-induced LC, termed LC-NB and LC-MLP, respectively. We obtained a sensitivity of 90.9%, a specificity of 94.9%, and overall accuracy of 93.8% on an independent test set. Comparisons with the existing methods showed that LC-NB and LC-MLP held better accuracy. Our study suggests that potential serum biomarkers can be determined for discriminating LC and non-LC cohorts by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. These two classifiers could be used for clinical practice in HBV-induced LC assessment.

Serum biomarkers identification by mass spectrometry in high-mortality tumors

Cancer affects millions of people worldwide. Tumor mortality is substantially due to diagnosis at stages that are too late for therapies to be effective. Advances in screening methods have improved the early diagnosis, prognosis, and survival for some cancers. Several validated biomarkers are currently used to diagnose and monitor the progression of cancer, but none of them shows adequate specificity, sensitivity, and predictive value for population screening. So, there is an urgent need to isolate novel sensitive, specific biomarkers to detect the disease early and improve prognosis, especially in high-mortality tumors. Proteomic techniques are powerful tools to help in diagnosis and monitoring of treatment and progression of the disease. During the last decade, mass spectrometry has assumed a key role in most of the proteomic analyses that are focused on identifying cancer biomarkers in human serum, making it possible to identify and characterize at the molecular level many proteins or peptides differentially expressed. In this paper we summarize the results of mass spectrometry serum profiling and biomarker identification in high mortality tumors, such as ovarian, liver, lung, and pancreatic cancer.

Mass spectrometry of peptides and proteins from human blood

It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.

Establishing a serologic decision tree model of extrapulmonary tuberculosis by MALDI-TOF MS analysis

Matrix-assisted laser desorption-ionization time of flight mass spectrometry (MALDI-TOF MS) combined with weak cationic exchange (WCX) magnetic beads was used to establish a decision tree model that distinguished extrapulmonary tuberculosis (EPTB) from non-EPTB individuals. Eight-one patients with EPTB and 112 non-EPTB individuals (72 disease controls and 40 healthy controls) were involved in this study. The model was set up by 5 of 19 differentially expressed peaks (P < 0.05), m/z 4100, 4310, 6093, 8605, and 14,019. This model can discriminate patients with EPTB from non-EPTB with a sensitivity of 97.7% and a specificity of 84.1%. The test set verified that this model had good sensitivity and specificity: 94.4% and 83.6%, respectively. In conclusion, MALDI-TOF MS combined with WCX magnetic beads is a powerful technology for constructing a decision tree model and the model we built could serve as a potential diagnostic tool for EPTB.

Clinical proteomics for liver disease: a promising approach for discovery of novel biomarkers

Hepatocellular carcinoma (HCC) is the fifth most common cancer and advanced hepatic fibrosis is a major risk factor for HCC. Hepatic fibrosis including liver cirrhosis and HCC are mainly induced by persistent hepatitis B or C virus infection, with approximately 500 million people infected with hepatitis B or C virus worldwide. Furthermore, the number of patients with non-alcoholic fatty liver disease (NAFLD) has recently increased and NAFLD can progress to cirrhosis and HCC. These chronic liver diseases are major causes of morbidity and mortality, and the identification of non-invasive biomarkers is important for early diagnosis. Recent advancements in quantitative and large-scale proteomic methods could be used to optimize the clinical application of biomarkers. Early diagnosis of HCC and assessment of the stage of hepatic fibrosis or NAFLD can also contribute to more effective therapeutic interventions and an improve prognosis. Furthermore, advancements of proteomic techniques contribute not only to the discovery of clinically useful biomarkers, but also in clarifying the molecular mechanisms of disease pathogenesis by using body fluids, such as serum, and tissue samples and cultured cells. In this review, we report recent advances in quantitative proteomics and several findings focused on liver diseases, including HCC, NAFLD, hepatic fibrosis and hepatitis B or C virus infections.

Plasma gelsolin protein: a candidate biomarker for hepatitis B-associated liver cirrhosis identified by proteomic approach

BACKGROUND

Despite the significant improvement in internal medicine and supportive therapy in recent years, liver fibrosis/cirrhosis remains a serious health issue in hepatitis B virus (HBV) infected patients. Invasive liver biopsy is presently the best means of diagnosing cirrhosis, but it carries a significant risk and has well recognised limitations such as sampling error, hence the importance in developing early diagnosis biomarkers. With this aim, we performed a pilot proteomic study to assess this as a strategy for plasma marker detection in patients suffering from HBV-associated liver cirrhosis.

METHODS

Plasma from eight chronic HBV-infection patients and from eight HBV-related cirrhotic patients were selected and proteome profiles were created by two-dimensional electrophoresis. The strategy included the use of ProteoMiner enrichment kit for the reduction of highly abundance proteins (e.g. albumin and IgG) prior to proteomic analyses with the goal to improve detection of novel candidate markers.

RESULTS

One reproducible spot was found to be completely repressed in plasma samples from cirrhotic patients and mass spectrometry analysis identified this a specific variant of the gelsolin actin-depolymerizing factor. Though further investigations are needed, especially in term of clinical validation, to our knowledge this is the first time that gelsolin is proposed as potential biomarker in HBV-related liver pathologies.

CONCLUSIONS

Our findings confirm the potential utility of gelsolin either as a prognostic marker or a replacement therapeutic agent to alleviate liver injury.

Enhanced detection of early hepatocellular carcinoma by serum SELDI-TOF proteomic signature combined with alpha-fetoprotein marker

Background

Biomarkers for accurate diagnosis of early hepatocellular carcinoma (HCC) are limited in number and clinical validation. We applied SELDI-TOF-MS ProteinChip technology to identify serum profile for distinguishing HCC and liver cirrhosis (LC) and to compare the accuracy of SELDI-TOF-MS profile and alpha-fetoprotein (AFP) level in HCC diagnosis.

Patients and Methods

Serum samples were obtained from 120 HCC and 120 LC patients for biomarker discovery and validation studies. ProteinChip technology was employed for generating SELDI-TOF proteomic features and analyzing serum proteins/peptides.

Results

A diagnostic model was established by CART algorithm, which is based on 5 proteomic peaks with m/z values at 3324, 3994, 4665, 4795, and 5152. In the training set, the CART algorithm could differentiate HCC from LC subjects with a sensitivity and specificity of 98% and 95%, respectively. The results were assessed in blind validation using separate cohorts of 60 HCC and 60 LC patients, with an accuracy of 83% for HCC and 92% for LC patients. The diagnostic odd ratio (DOR) indicated that SELDI-TOF proteomic signature could achieve better diagnostic performance than serum AFP level at a cutoff of 20 ng/mL (AFP₂₀) (92.72 vs 9.11), particularly superior for early-stage HCC (87% vs 54%). Importantly, a combined use of both tests could enhance the detection of HCC (sensitivity, 95%; specificity, 98%; DOR, 931).

Conclusion

Serum SELDI-TOF proteomic signature, alone or in combination with AFP marker, promises to be a good tool for early diagnosis and/screening of HCC in at-risk population with liver cirrhosis.

Proteomic approaches in the search for biomarkers of liver fibrosis

Chronic liver diseases (CLDs) can cause progressive hepatic fibrosis culminating in cirrhosis. Fibrosis staging requires liver biopsy, which is invasive, expensive and frequently poorly tolerated by patients. Serum-based panels of fibrosis biomarkers have been developed as alternatives to biopsy. Recent advances in high-throughput proteomic methods have the potential to optimise combinations of biomarkers for the diagnosis of liver fibrosis. Here, we review the key recent developments in the field of proteomics and their application to this important clinical question. We critically discuss the challenges and priorities for future research that are of critical importance to clinical hepatology.

Serum protein biomarkers screening in HCC patients with liver cirrhosis by ICAT-LC-MS/MS

BACKGROUND

The prognosis of HCC remains poor mainly because of the lack of diagnosis biomarkers especially in patients with cirrhosis background.

METHODS

To identify serum biomarkers for HCC, we use cleavable stable isotope labeling (cICAT) combined with LC-electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) to compare the serum proteome between liver cirrhosis and HCC patients. Sera from nine liver cirrhosis patients and nine HCC patients were selected for screening study. Then the alpha-1-acid glycoprotein (AGP) was chosen for validation by western blot. AGP was measured in the separate validation study including 52 HCC patients and 40 liver cirrhosis patients by rate nephelometry. Its value for HCC diagnosis from liver cirrhosis was also appreciated through receiver operating curve (ROC).

RESULTS

We quantified and identified 31 different proteins which include AGP, complement C4, haptoglobin, alpha-1-antitrypsin precursor, alpha-2-macroglobulin precursor, prothrombin precursor and ubiquitin carboxyl-terminal hydrolase 44 (USP44), etc. The serum concentration of AGP in HCC patients (n = 52) was significantly higher than in liver cirrhosis (n = 40) (P < 0.005) in validation study. AGP was useful for discrimination of the HCC cases from LC patients when the AFP levels were below 500 ng/ml. The area under curve (AUC) of the AGP and the combination of AGP and AFP were 0.834 (P < 0.0005, 95% CI: 0.734-0.934) and 0.880 (P < 0.0005, 95% CI, 0.789-0.970) separately, which are higher than AFP alone (0.538, P = 0.604, 95% CI: 0.386-0.689).

CONCLUSION

cICAT combined with LC-MS/MS-based serum proteome analysis can be useful in the screening of serum biomarkers for HCC. Alpha-1-acid glycoprotein combining AFP could aid the diagnosis of HCC.

Serum pattern profiling for analyzing different types of stress by protein chip technology: a preliminary study

ProteinChip is a widely accepted tool for exploring serum pattern profile to evaluate the risk of somatic diseases from different stressors. In this study, by using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-ToF), the serum proteome from mice under restraint and thermal stresses were profiled in detail and compared with the control group. Around 150 characteristic peaks were detected in all three groups, with m/z ranging from 1500 to 50,000, with most peaks being within the 2000 m/z to 20,000 m/z range. Compared with the control group, three significant protein peaks with m/z values of 2780, 3303 and 3450 appeared specifically in the restrained stress group and four other peaks with m/z values of 7500, 7811, 29,950 and 38,565 in the thermal stress group. Unexpectedly, no universal positive stress peaks were detected. These preliminary results clearly suggested that there might not be a common mechanism shared by various psychophysiological disorders under different stressors. By fast serum proteomics profiling, SELDI-ToF may be a convenient tool for evaluating the risk of stress-induced illness.

Proteomics and liver fibrosis: identifying markers of fibrogenesis

Chronic hepatic disease damages the liver and the resulting wound-healing process might lead to liver fibrosis and subsequent cirrhosis development. Fibrosis is the excessive deposition of extracellular matrix (ECM) in the tissue as consequence of chronic liver damage. The fibrotic response triggers almost all of the complications of end-stage liver disease, including portal hypertension, ascites, encephalopathy, synthetic dysfunction and impaired metabolic capacity. Thus, efforts to understand and attenuate fibrosis have direct clinical implications. Reliable, accurate, disease-specific, noninvasive biomarkers of fibrosis and fibrogenesis in order to prevent or minimize the impact of the chronic liver disease progression are a critical need. This review aims to provide an overview of the possibilities that proteome technology can offer to the knowledge, diagnosis and prognosis of liver fibrosis.

Supervised learning with decision tree-based methods in computational and systems biology

At the intersection between artificial intelligence and statistics, supervised learning allows algorithms to automatically build predictive models from just observations of a system. During the last twenty years, supervised learning has been a tool of choice to analyze the always increasing and complexifying data generated in the context of molecular biology, with successful applications in genome annotation, function prediction, or biomarker discovery. Among supervised learning methods, decision tree-based methods stand out as non parametric methods that have the unique feature of combining interpretability, efficiency, and, when used in ensembles of trees, excellent accuracy. The goal of this paper is to provide an accessible and comprehensive introduction to this class of methods. The first part of the review is devoted to an intuitive but complete description of decision tree-based methods and a discussion of their strengths and limitations with respect to other supervised learning methods. The second part of the review provides a survey of their applications in the context of computational and systems biology.

Systematic -omics analysis of HBV-associated liver diseases

Hepatitis B virus (HBV) infection causes acute and chronic liver diseases and increases the risk of developing hepatocellular carcinoma (HCC). However, the pathogenesis of HBV infection and carcinogenesis of HBV-associated HCC are still elusive. In this review, systematic -omics studies made in the scales of genomics, transcriptomics and proteomics were discussed. The susceptibility to HBV infection and the course of disease progress are greatly different among individuals. Using population- or/and family-based approaches, relevant genes have been mapped or identified to be associated with host immune responses to HBV antigens and susceptibility to HCC. Comprehensive transcriptomic analyses have shown that the HBV-induced hepatocarcinogenesis may involve the whole course from signal transduction, transcription, translation to protein degradation, which differs in some measure from HCV-induced hepatocarcinogenesis, and that exogenous transcription factor HBX and endogenous NF-kappaB are likely two key points of the course. By the means of proteomics, dozens of important dysregulated proteins (including isoforms or fragments) were identified from carcinogenesis mechanism analysis and biomarker validation. Of them, the alteration of heat shock proteins and impairment of methylation cycle were found to be associated with clinical HBV-associated HCC. As a whole, the systematic -omics analysis of HBV-associated liver diseases has offered multi-scale pathological information in the process from HBV infection to HCC onset.

Surface enhanced laser desorption/ionization profiling: New diagnostic method of HBV-related hepatocellular carcinoma

BACKGROUND AND AIM

To screen for serum biomarkers of HBV-related hepatocellular carcinoma (HCC) and HBV-related liver cirrhosis (LC) in an attempt to seek a new method for differential diagnosis of HCC and LC using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) techniques.

METHODS

Using SELDI-TOF-MS, serum proteins/peptide profiles on the immobilized metal ion affinity capture (IMAC) protein chips were obtained from 29 HCC patients and 30 LC patients. Discriminant analysis was carried out to establish new diagnostic methods using protein/peptide peaks with or without alpha-fetoprotein (AFP).

RESULTS

Forty-five protein/peptide peaks changed much more in the HCC group than they did in the LC group. Discriminant analysis using the Wilcoxon rank-sum test showed high sensitivity and specificity in distinguishing HCC from LC. The most significantly differentiating peak, 3892, offered 69.0% sensitivity, 83.3% specificity and 80% positive predictive value in distinguishing HCC and LC. Interestingly, six HCC patients with negative serum AFP were confirmed by peak 3892. The combination of multi-protein peaks (m/z = 9297, 29 941) with AFP offered an 82.8% sensitivity, 93.3% specificity and 92.3% positive predictive value, which was much better than AFP alone (P = 0.013).

CONCLUSIONS

Special proteins/peptides of serum may differentiate HBV-related HCC and HBV-related LC, indicating that SELDI-TOF-MS may be useful to distinguish HCC from LC with the proper discriminant analytical method. SELDI peak 3892 may be a complementary diagnostic marker to positive AFP for HCC and a potential marker for the diagnosis of AFP-negative HCC as well.

The current state of proteomics in GI oncology

Proteomics refers to the study of the entire set of proteins in a given cell or tissue. With the extensive development of protein separation, mass spectrometry, and bioinformatics technologies, clinical proteomics has shown its potential as a powerful approach for biomarker discovery, particularly in the area of oncology. More than 130 exploratory studies have defined candidate markers in serum, gastrointestinal (GI) fluids, or cancer tissue. In this article, we introduce the commonly adopted proteomic technologies and describe results of a comprehensive review of studies that have applied these technologies to GI oncology, with a particular emphasis on developments in the last 3 years. We discuss reasons why the more than 130 studies to date have had little discernible clinical impact, and we outline steps that may allow proteomics to realize its promise for early detection of disease, monitoring of disease recurrence, and identification of targets for individualized therapy.

Evidence-based diagnosis and locoregional therapy for hepatocellular carcinoma

Early identification of hepatocellular carcinoma (HCC) is crucial to improving the results of therapy and for patients to be eligible for liver transplantation. Recent advances in noninvasive imaging technology include various techniques of harmonic ultrasound, new ultrasound contrast agents, multislice helical computed tomography and rapid high-quality magnetic resonance. The imaging diagnosis relies on the hallmark of arterial hypervascularity with portal venous washout. Since the use of better radiological techniques has improved the accuracy of noninvasive diagnosis, the role of liver biopsy in the diagnosis of HCC has declined. With recent advances in genomics and proteomics, a great number of potential markers have been identified and developed as new candidate markers for HCC. Locoregional therapies currently constitute the best options for early nonsurgical treatment of HCC. Percutaneous ethanol injection shows similar results to resection surgery for single tumors less than 3 cm in diameter. Radiofrequency ablation is superior to percutaneous ethanol injection in terms of local recurrence. Transarterial chemoembolization is currently the most common approach for the management of HCC without curative options since it improves patient survival, but the optimal embolizing agent, length of interval between sessions and whether the chemotherapeutic agent has any effect have not yet been determined. Combining transarterial chemoembolization with antiangiogenic agents, as well as with other techniques, such as radiofrequency ablation, may improve the results. Injection of radioisotopes such as yttrium-90, via the hepatic artery, may be particularly useful in patients with portal vein thrombosis. Comparisons with other transarterial techniques are needed.

Recent advances in tumor markers of human hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most devastating malignancies in the world and is the third most common cause of cancer-related death in Korea. Because most HCC are accompanied by chronic liver disease that results from hepatitis B or C viruses, prognosis is still poor even after surgical resection of the tumor. Moreover, diagnosis of advanced HCC still leads to an extremely bleak prognosis. Earlier detection of HCC, therefore, could improve patient survival. Accordingly, the development of tumor markers that can detect HCC at even earlier stages is essential. The functions of tumor markers include prediction of prognosis or therapeutic response as well as diagnosis or screening of cancer. Possible candidate tumor markers may be quantitative alterations in DNA-, RNA- or protein-based molecules in tumorous conditions assessed by various technologies, e.g. serological assays, microarrays, mass spectrometry and proteomics. However, validation and clinical implementation is needed after the discovery of novel genes. An ideal tumor marker for HCC would be sensitive and specific enabling to differentiate it at an early stage from premalignant lesions like dysplastic nodules. In addition, the marker should be easily measurable, reproducible and minimally invasive. Although it is important to identify new biomarkers for HCC, the validation and cost-effectiveness of those markers as diagnostic or prognostic tools need confirmation in large-scale studies in clinical practice.

Screening serum hepatocellular carcinoma-associated proteins by SELDI-based protein spectrum analysis

AIM: To find out potential serum hepatocellular carcinoma (HCC)-associated proteins with low molecular weight and low abundance by SELDI-based serum protein spectra analysis, that will have much application in the diagnosis or differentiated diagnosis of HCC, as well as giving a better understanding of the mechanism of hepato-carcinogenesis.

METHODS: Total serum samples were collected with informed consent from 81 HCC patients with HBV(+)/cirrhosis(+), 36 cirrhosis patients and 43 chronic hepatitis B patients. Serum protein fingerprint profiles were first generated by selected WCX2 protein chip capture integrating with SELDI-TOF-MS, then normalized and aligned by Ciphergen SELDI Software 3.1.1 with Biomarker Wizard. Comparative analysis of the intensity of corresponding protein fingerprint peaks in normalized protein spectra, some protein peaks with significant difference between HCC and cirrhosis or chronic hepatitis B were found.

RESULTS: One hundred and twenty-eight serum protein peaks between 2000 and 30 000Da were identified under the condition of signal-to-noise > 5 and minimum threshold for cluster > 20%. Eighty-seven of these proteins were showed significant differences in intensity between HCC and cirrhosis (P < 0.05). Of the above differential proteins, 45 proteins had changes greater than two-fold, including 15 upregulated proteins and 30 downregulated proteins in HCC serum. Between HCC and chronic hepatitis B, 9 of 52 differential proteins (P < 0.05) had intensities of more than two-fold, including 2 upregulated proteins and 7 downregulated proteins in HCC serum. Between cirrhosis and chronic hepatitis B, 28 of 79 significant differential proteins (P < 0.05) changes greater than two-fold in intensity, including 17 upregulated proteins and 11 downregulated proteins in cirrhosis serum. For the analysis of these leading differential proteins in subtraction difference mode among three diseases, the five common downregulated proteins in HCC serum (M/Z 2870, 3941, 2688, 3165, 5483) and two common upregulated proteins (M/Z 3588, 2017) in HCC and cirrhosis serum were screened.

CONCLUSION: Because the interference of unspecific secreted proteins from hepatitis B and cirrhosis could be eliminated partly in HCC serum under subtraction difference analysis, these seven common differential proteins have the obvious advantage of specificity for evaluating the pathological state of HCC and might become novel candidate biomarkers in the diagnosis of HCC.

Serum proteomic profiling associated with immune system impaired by stress using ProteinChip technology

We set out to use proteomic profiling as a means of defining serum peptides that are indicative of a stress response related to an impact on the immune system. Two types of mouse models with the immune response impaired under stress (restraint stress and thermal stress) comprised the stressed groups (n = 10 in each group), while mice without stress represented the control group (n = 10). ProteinChip technology (surface-enhanced laser desorption/ionization time-of-flight mass spectrometry) was used to investigate the serum proteomic profiles. Histopathological examination of spleens from the stressed and control groups was performed to select appropriate individuals. Compared with the spleens of normal mice, those of mice subjected to restraint and thermal stress had decreased white pulp and lymphoid nodules, and their distribution and structure changed irregularly. Pathological changes occurred in all individuals in both stressed groups. The m/z values of the protein peaks ranged from 1,500 to 50,000 daltons and were mainly in the 2,000- to 20,000-dalton range. One hundred and fifty protein peaks were detected in the three groups. Four downregulated universal stress protein peaks with m/z of 4,389, 5,341, 5,526, and 6,252 were finally selected. Unexpectedly, no upregulated universal stress protein peaks were detected. These results suggested that impairment of the immune system results from inhibition of growth-promoting factors associated with the immune system. Identified protein peaks may be biomarkers of the impaired immune system under stress.