Toward the proteomic identification of biomarkers for the prediction of HBV related hepatocellular carcinoma

Acute-phase serum amyloid A for early detection of hepatocellular carcinoma in cirrhotic patients with low AFP level

Regular hepatocellular carcinoma (HCC) surveillance by ultrasonography in combination with the α-fetoprotein (AFP) examination is unsatisfactory in diagnostic sensitivity for early-stage HCC especially in cirrhotic patients. We conducted a prospective study in a tertiary medical center in Taiwan and consecutively collected serum samples from patients with chronic hepatitis, liver cirrhosis (LC), or HCC for new biomarker discovery. Overall, 166 patients were enrolled, including 40 hepatitis, 30 LC, and 96 HCC. Four acute-phase serum amyloid A (A-SAA) derived biomarkers including total A-SAA, A-SAA monomer and oligomer, and protein misfolding cyclic amplification (PMCA) signal were measured and compared between patients with and without HCC. A-SAA biomarkers significantly increased in the HCC group when compared to the hepatitis and LC groups, and generally increased in more advanced tumor stages. Among A-SAA biomarkers, the area under the receiver operator characteristic curves (AUROCs) for PMCA signal in discrimination of all-stage and early-stage HCC were 0.86 and 0.9 in cirrhotic patients, which is comparable to AFP. For cirrhotic patients with low AFP (< 7 ng/mL), PMCA signal maintained good capacity in prediction of early-stage HCC (AUROC: 0.94). Serum A-SAA and its prion-like property showed a potential to complement AFP in detection of early-stage HCC.

The prognostic value of integration of pretreatment serum amyloid A (SAA)-EBV DNA (S-D) grade in patients with nasopharyngeal carcinoma

Background

Serum amyloid A (SAA) has been associated with the development and prognosis of cancer. The purpose of this study was to evaluate the predictive value of integration of pretreatment SAA–EBV DNA (S-D) grade and comparison with the TNM staging system in patients with nasopharyngeal carcinoma (NPC). The S-D grade was calculated based on the cut-off values of serum SAA and EBV DNA copy numbers which were determined by receiver operating characteristic (ROC) curves. We evaluated the prognostic value of pretreatment SAA, EBV DNA and S-D grade on overall survival (OS) of NPC patients. We also evaluated the predictive power of S-D grade with TNM staging system using 4 indices: concordance statistics (C-index), time-dependent ROC (ROCt) curve, net reclassification index (NRI) and integrated discrimination improvement (IDI).

Results

A total of 304 NPC patients were enrolled in this study. Multivariate analysis showed that TNM stage (P = 0.007), SAA (P = 0.013), and EBV DNA (P = 0.033) were independent prognostic factors in NPC. The S-D grade was divided into S-D grade 1, S-D grade 2, and S-D grade 3, which had more predictive accuracy for OS than TNM staging according to all 4 indices.

Conclusions

We found that the S-D grade could be used as a new tool to predict the OS in NPC patients.

The Diagnostic Value of MicroRNAs as a Biomarker for Hepatocellular Carcinoma: A Meta-Analysis

BACKGROUND

Recently, the role of microRNAs (miRNAs) in diagnosing cancer has been attracted increasing attention. However, few miRNAs have been applied in clinical practice. The purpose of this study was to evaluate the diagnostic efficacy of miRNAs for hepatocellular carcinoma (HCC) at early stages clinically.

METHODS

A literature search was carried out using PubMed, Web of Science, and EMBASE databases. We explored the diagnostic value of miRNAs in distinguishing HCC from healthy individuals. The quality assessment was performed in Review Manager 5.3 software. The overall sensitivity and specificity and 95% confidence intervals (CIs) were obtained with random-effects models through Stata 14.0 software. And heterogeneity was assessed using Q test and I 2 statistics. Meta-regression and subgroup analyses were conducted based on the sample, nation, quality of studies, and miRNA profiling. The publication bias was evaluated through Deeks' funnel plot.

RESULTS

A total of 34 studies, involving in 2747 HCC patients and 2053 healthy individuals, met the inclusion criteria in the 33 included literature studies. In the summary receiver operating characteristic (sROC) curve, AUC was 0.92 (95% CI, 0.90-0.94), with 0.84 (95% CI, 0.79-0.88) sensitivity and 0.87 (95% CI, 0.83-0.90) specificity. There was no publication bias (P=0.48).

CONCLUSION

miRNAs in vivo can be acted as a potential diagnostic biomarker for HCC, which can facilitate the early diagnosis of HCC in clinical practice.

Cytokines and serum amyloid A in the pathogenesis of hepatitis C virus infection

Expression of the acute phase protein serum amyloid A (SAA) is dependent on the release of the pro-inflammatory cytokines IL-1, IL-6 and TNF-α during infection and inflammation. Hepatitis C virus (HCV) upregulates SAA-inducing cytokines. In line with this, a segment of chronically infected individuals display increased circulating levels of SAA. SAA has even been proposed to be a potential biomarker to evaluate treatment efficiency and the course of disease. SAA possesses antiviral activity against HCV via direct interaction with the viral particle, but might also divert infectivity through its function as an apolipoprotein. On the other hand, SAA shares inflammatory and angiogenic activity with chemotactic cytokines by activating the G protein-coupled receptor, formyl peptide receptor 2. These latter properties might promote chronic inflammation and hepatic injury. Indeed, up to 80 % of infected individuals develop chronic disease because they cannot completely clear the infection, due to diversion of the immune response. In this review, we summarize the interconnection between SAA and cytokines in the context of HCV infection and highlight the dual role SAA could play in this disease. Nevertheless, more research is needed to establish whether the balance between those opposing activities can be tilted in favor of the host defense.

Acute phase reactant serum amyloid A in inflammation and other diseases

Acute-phase reactant serum amyloid A (A-SAA) plays an important role in acute and chronic inflammation and is used in clinical laboratories as an indicator of inflammation. Although both A-SAA and C-reactive protein (CRP) are acute-phase proteins, the detection of A-SAA is more conclusive than the detection of CRP in patients with viral infections, severe acute pancreatitis, and rejection reactions to kidney transplants. A-SAA has greater clinical diagnostic value in patients who are immunosuppressed, patients with cystic fibrosis who are treated with corticoids, and preterm infants with late-onset sepsis. Nevertheless, for the assessment of the inflammation status and identification of viral infection in other pathologies, such as bacterial infections, the combinatorial use of A-SAA and other acute-phase proteins (APPs), such as CRP and procalcitonin (PCT), can provide more information and sensitivity than the use of any of these proteins alone, and the information generated is important in guiding antibiotic therapy. In addition, A-SAA-associated diseases and the diagnostic value of A-SAA are discussed. However, the relationship between different A-SAA isotypes and their human diseases are mostly derived from research laboratories with limited clinical samples. Thus, further clinical evaluations are necessary to confirm the clinical significance of each A-SAA isotype. Furthermore, the currently available A-SAA assays are based on polyclonal antibodies, which lack isotype specificity and are associated with many inflammatory diseases. Therefore, these assays are usually used in combination with other biomarkers in the clinic.

Circulating predictive and diagnostic biomarkers for hepatitis B virus-associated hepatocellular carcinoma

Chronic hepatitis B virus (HBV) infected patients have an almost 100-fold increased risk to develop hepatocellular carcinoma (HCC). HCC is the fifth most common and third most deadly cancer worldwide. Up to 50% of newly diagnosed HCC cases are attributed to HBV infection. Early detection improves survival and can be achieved through regular screening. Six-monthly abdominal ultrasound, either alone or in combination with alpha-fetoprotein serum levels, has been widely endorsed for this purpose. Both techniques however yield limited diagnostic accuracy, which is not improved when they are combined. Alternative circulating or histological markers to predict or diagnose HCC are therefore urgently needed. Recent advances in systems biology technologies have enabled the identification of several new putative circulating biomarkers. Although results from studies assessing combinations of these biomarkers are promising, evidence for their clinical utility remains low. In addition, most of the studies conducted so far show limitations in design. Attention must be paid for instance to different ethnicities and different etiologies when studying biomarkers for hepatocellular carcinoma. This review provides an overview on the current understandings and recent progress in the field of diagnostic and predictive circulating biomarkers for hepatocellular carcinoma in chronically infected HBV patients and discusses the future prospects.

Serum amyloid A is a novel prognostic biomarker in hepatocellular carcinoma

PURPOSE

To investigate the prognostic value of serum amyloid A (SAA) in patients with hepatocellular carcinoma (HCC) undergoing surgery.

MATERIALS AND METHODS

Preoperative serum samples of 328 patients with HCC who underwent curative resection and of 47 patients with benign liver lesion were assayed. Serum levels of SAA were measured by enzyme-linked immunosorbent assay and its correlations with clinicopathological characteristics and survival were explored.

RESULTS

Levels of SAA were significantly higher in patients with HCC than those with benign liver lesion. There were strong correlations between preoperative serum SAA level and tumor size and more advanced BCLC stage. On univariate analysis, elevated SAA was associated with reduced disease-free survival and overall survival (p=0.001 and 0.03, respectively). Multivariate analyses showed that serum SAA level was an independent prognostic factor for overall survival (hazard ratio 2.80, p=0.01).

CONCLUSIONS

High SAA serum level is a novel biomarker for the prognosis of HCC patients.

Proteomic and metabonomic biomarkers for hepatocellular carcinoma: a comprehensive review

Hepatocellular carcinoma (HCC) ranks third in overall global cancer-related mortality. Symptomatic presentation often means advanced disease where potentially curative treatment options become very limited. Numerous international guidelines propose the routine monitoring of those with the highest risk factors for the condition in order to diagnose potential tumourigenesis early. To aid this, the fields of metabonomic- and proteomic-based biomarker discovery have applied advanced tools to identify early changes in protein and metabolite expression in HCC patients vs controls. With robust validation, it is anticipated that from these candidates will rise a high-performance non-invasive test able to diagnose early HCC and related conditions. This review gathers the numerous markers proposed by studies using mass spectrometry and proton nuclear magnetic resonance spectroscopy and evaluates areas of consistency as well as discordance.

Diagnostic value of circulating microRNAs for hepatocellular carcinoma

Much evidence indicates that microRNAs could play potential roles as diagnostic and prognostic biomarkers of human cancers, including hepatocellular carcinoma (HCC). The present meta-analysis aimed to systematically evaluate the diagnostic accuracy of circulating microRNAs for HCC. Eligible studies were identified through multiple search strategies and assessed for relevance and quality. Results from different studies were pooled using random-effects models. The quality of each study was scored with the revised quality assessment of diagnostic accuracy studies tool. The summary receiver operator characteristic (SROC) curve and other measures were used to assess the overall performance of microRNA-based assays. Evidence of heterogeneity was evaluated using the I (2) test. Meta-regressions were conducted to analyze potential sources of heterogeneity. Deeks' test was used to test for potential publication bias. Thirty studies from 13 publications, including 1,314 patients with HCC and 1,407 controls, comprised healthy individuals and patients with hepatitis B/C or cirrhosis, were included in this meta-analysis. For diagnostic meta-analysis, the overall pooled results were as follows: sensitivity was 0.80 (95 % CI 0.74-0.84), specificity was 0.81 (95 % CI 0.74-0.87), positive likelihood ratio was 4.2 (95 % CI 3.0-6.0), negative likelihood ratio was 0.25 (95 % CI 0.19-0.38) and diagnostic odds ratio was 17 (95 % CI 10-29). The area under the SROC curve was 0.86 (95 % CI 0.84-0.90). Subgroup analyses suggested that multiple microRNAs had much better accuracy than single microRNA. Our findings suggest that circulating microRNAs show significant potential as diagnostic markers of HCC, particularly when using multiple microRNAs. However the results of this meta-analysis justify larger, more rigorous studies to confirm our conclusions.

Predicting early intrahepatic recurrence of hepatocellular carcinoma after microwave ablation using SELDI-TOF proteomic signature

BACKGROUND/AIMS

Despite great progress in the treatment of hepatocellular carcinoma (HCC) over the last-decade, intrahepatic recurrence is still the most frequent serious adverse event after all the treatments including microwave ablation. This study aimed to predict early recurrence of HCC after microwave ablation using serum proteomic signature.

METHODS

After curative microwave ablation of HCC, 86 patients were followed-up for 1 year. Serum samples were collected before microwave ablation. The mass spectra of proteins were generated using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Serum samples from 50 patients were randomly selected as a training set and for biomarkers discovery and model development. The remaining serum samples were categorized for validation of the algorithm.

RESULTS

According to preablation serum protein profiling obtained from the 50 HCC samples in the training set, nine significant differentially-expressed proteins were detected in the serum samples between recurrent and non-recurrent patients. Decision classification tree combined with three candidate proteins with m/z values of 7787, 6858 and 6646 was produced using Biomarker Patterns Software with sensitivity of 85.7% and specificity of 88.9% in the training set. When the SELDI marker pattern was tested with the blinded testing set, it yielded a sensitivity of 80.0%, a specificity of 88.5% and a positive predictive value of 86.1%.

CONCLUSIONS

Differentially-expressed protein peaks in preablation serum screened by SELDI are associated with prognosis of HCC. The decision classification tree is a potential tool in predicting early intrahepatic recurrence in HCC patients after microwave ablation.

Promising Urinary Protein Biomarkers for the Early Detection of Hepatocellular Carcinoma among High-Risk Hepatitis C Virus Egyptian Patients

Hepatocellular Carcinoma is a major healthcare problem, representing the third most common cause of cancer-related mortality worldwide. There are 130 million Hepatitis C virus infected patients worldwide who are at a high-risk for developing Hepatocellular Carcinoma. Due to the fact that reliable parameters and/or tools for the early detection of Hepatocellular Carcinoma among high-risk individuals are severely lacking, Hepatocellular Carcinoma patients are always diagnosed at a late stage where surgical solutions or effective treatment are not possible. Urine was collected from 106 Hepatitis C infected patients patients, 32 of whom had already developed Hepatocellular Carcinoma and 74 patients who were diagnosed as Hepatocellular Carcinoma -free at the time of initial sample collection. In addition to these patients, urine samples were also collected from 12 healthy control individuals. Total urinary proteins were isolated from the urine samples and LC-MS/MS was used to identify potential protein HCC biomarker candidates. This was followed by validating relative expression levels of proteins present in urine among all the patients using quantitative real time-PCR. This approach revealed that significant over-expression of three proteins: DJ-1, Chromatin Assembly Factor-1 (CAF-1) and Heat Shock Protein 60 (HSP60), was a characteristic event among Hepatocellular Carcinoma - post Hepatitis C virus infected patients. As a single-based Hepatocellular Carcinoma biomarker, CAF-1 over-expression identified Hepatocellular Carcinoma among Hepatitis C virus infected patients with a specificity of 90%, sensitivity of 66% and with an overall diagnostic accuracy of 78%. Moreover, the CAF-1/HSP60 tandem identified Hepatocellular Carcinoma among Hepatitis C virus infected patients with a specificity of 92%, sensitivity of 61% and with an overall diagnostic accuracy of 77%.

Comparative proteomic profiles indicating genetic factors may involve in hepatocellular carcinoma familial aggregation

Familial aggregation of hepatocellular carcinoma (HCC), the third leading cause of cancer death worldwide, has shown to be a common phenomenon. We investigated the association between the genetic background and HCC familial aggregation. Serum samples were collected from HCC family members and normal control family members for screening the differentially expressed protein peaks with the approach of surface-enhanced laser desorption ionization time-of-flight mass spectrometry. Potential genetically associated protein peaks were selected and further identified by matrix assisted laser desorption ionization-time of flight mass spectrometry. A panel of six protein peaks (m/z 6432.94, 8478.35, 9381.91, 17284.67, 17418.34, and 18111.04) were speculated to reflect the genetic susceptibility of HCC familial aggregation. Three of them (m/z 6432.94, 8478.35, and 9381.91) were selected to identify as the candidate proteins. Nine identified proteins, including mostly apolipoprotein family (ApoA1, ApoA2, ApoC3, ApoE) and serum amyloid A protein (SAA), were found overexpressed in the multiple HCC cases family members. The comparative proteomic profiles have suggested that genetic factors ought to be taken into account for familial aggregation of HCC.

Promising Candidate Urinary MicroRNA Biomarkers for the Early Detection of Hepatocellular Carcinoma among High-Risk Hepatitis C Virus Egyptian Patients

MicroRNAs (miRNA) are small endogenously expressed non-coding RNAs that negatively regulate expression of protein-coding genes at the translational level. Accumulating evidence, such as aberrant expression of miRNAs, suggests that they play a role in the development of cancer. They have been identified in various tumor types, demonstrating that different sets of miRNAs are usually deregulated in different cancers. To identify the miRNA signatures specific for Hepatitis C virus (HCV)-associated Hepatocellular carcinoma (HCC), miRNA expression profiling of 32 HCC post-HCV infected, 74 HCV-positive and 12 control individuals was carried out using whole genome expression profiling. Differential expression of two individual miRNAs between control and high risk HCV patients was detected and found to possibly target genes related to HCC development and progression. The sensitivity and specificity of miR-618 for detecting HCC among HCV-positive individuals was found to be 64% and 68%, respectively. Whereas, the sensitivity and specificity of miR-650 were 72% and 58%, respectively. Additionally, the sensitivity and specificity for miR-618/650 in tandem were 58% and 75%, respectively. These predictive values are greatly improved compared to the traditional α-feto protein (AFP) level-based detection method. The proposed HCC miRNA signatures may therefore be of great value for the early diagnosis of HCC, before the onset of disease in HCV-positive patients. The significance of this approach is amplified by the use of urine as a sample source as it offers a non-invasive approach for developing screening methods that can reduce mortality rates.

Alpha-1 antitrypsin is a potential biomarker for hepatitis B

BACKGROUND

Function exertion of specific proteins are key factors in disease progression, thus the systematical identification of those specific proteins is a prerequisite to understand various diseases. Though many proteins have been verified to impact on hepatitis, no systematical protein screening has been documented to hepatitis B virus (HBV) induced hepatitis, hindering the comprehensive understanding to this severe disease.

AIM

To identify the major proteins in the progression of HBV infection from mild stage to severe stage.

METHODS

We performed an integrated strategy by combining two-dimensional electrophoresis (2-DE), peptide mass fingerprinting (PMF) analysis, and tissue microarray techniques to screen the functional proteins and detect the localization of those proteins.

RESULTS

Interestingly, MS/MS identification revealed the expression level of alpha-1 antitrypsin (AAT) was significantly elevated in serum samples from patients with severe chronic hepatitis. Immunoblotting with a specific AAT antibody confirmed that AAT is highly expressed in serum samples from patients with hepatic carcinoma and severe chronic hepatitis. Furthermore, we observed that AAT is with highest expression in normal tissue and cells, but lowest in hepatic carcinoma and severe chronic hepatitis tissues and cells, suggesting the specific secretion of AAT from tissues and cells to serum.

CONCLUSION

These results suggest the possibility of AAT as a potential biomarker for hepatitis B in diagnosis.

Proteomics of hepatocellular carcinoma in Chinese patients

Hepatocellular carcinoma (HCC) is a malignant tumor of liver that causes approximately half a million deaths each year, of which over half of the cases are diagnosed in China. Because of its asymptomatic nature, HCC is usually diagnosed at late and advanced stages, for which there are no effective therapies. Thus, biomarkers for early detection and molecular targets for treating HCC are urgently needed. With the advent of high-throughput omics technologies, we have begun to mine the genomics and proteomics information of HCC, and most importantly, these data can be integrated with clinical annotations of the patients. Such new horizons of integrated profiling informatics have allowed us to search for and better identify clinically useful biomarkers and therapeutic targets for cancers including HCC. Capitalizing the large clinical samples cohort (over 100 pairs of tumor and matched adjacent nontumor tissues of HCC), we herein discuss the use of proteomics approach to identify biomarkers that are potentially useful for (1) discrimination of tumorous from nonmalignant tissues, (2) detection of small-sized and early stage of HCC, and (3) prediction of early disease relapse after hepatectomy.

Screening of differentially expressed low-abundance proteins among serum samples from patients with different HBV-related hepatic diseases by SELDI-TOF-MS

AIM: To screen differentially expressed low-abundance proteins among serum samples from patients with different HBV-related hepatic diseases and to evaluate their possible value in the diagnosis of these diseases.

METHODS: The surface-enhanced laser desorption or ionization time-of-flight mass spectroscopy (SELDI-TOF-MS) was used to screen differentially expressed proteins among serum samples, in which high-abundance proteins had been removed with acetonitrile, collected from patients with asymptomatic chronic hepatitis B (ASC), chronic hepatitis B (CHB), liver cirrhosis (LC), hepatocellular carcinoma (HCC), and normal controls. Diagnostic models for each disease were then established with differentially expressed proteins. Protein databases were searched to predict the possible structure and function of differentially expressed proteins.

RESULTS: Compared with the normal control group, 63 differentially expressed protein peaks were detected in the ASC group, of which 29 were up-regulated and 34 down-regulated (P < 0.05); 57 in the CHB group, of which 29 up-regulated and 34 down-regulated; 68 in the LC group, of which 33 up-regulated and 35 down-regulated; and 74 in the HCC group, of which 28 up-regulated and 46 down-regulated. A peak with a m/z of 15 889.8 corresponded to a protein whose expression was up-regulated gradually in an order of healthy controls, ASC, CHB and LC patients, and its expression level in the HCC group was lower than those in the CHB group and LC group. The expression of a protein with a m/z of 11 742.2 was higher in the LC group and HCC group than in other groups, and its expression was gradually increased in an order of healthy controls, CHB, and LC patients, or in another order of healthy controls, CHB, and HCC patients. The sensitivity and specificity using the protein peak at 11 742.2 for diagnosis of LC were 90% and 86.67% and for HCC were 93.33% and 83.33%, respectively.

CONCLUSION: Ten protein peaks with m/z values of 8 709.7, 13 759.8, 14 004.0, 15 361.89, 16 072.3, 2 746.8, 3 449.1, 3 941.06, 4 098.3, and 9 445.5 correspond to proteins that might be involved in HBV infection. The protein peak with a m/z of 15 889.8 might be used as a biomarker for early diagnosis of HBV-related liver cirrhosis, while that with a m/z of 11 742.2 might be an important biomarker for the development of HBV-related liver cirrhosis or HCC.

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.

Serum amyloid A is elevated in the serum of lung cancer patients with poor prognosis

Background:

Lung cancer is known as the top cancer killer in most developed countries. However, there is currently no promising diagnostic or prognostic biomarker for lung cancer. This study aims to discover non-invasive differential markers in the serum of lung cancer patients, to determine the protein identity of the candidate biomarker(s), and to investigate any clinical implication of the biomarker(s) concerned.

Methods:

Blood specimens were collected from 154 pre-operative patients with lung cancer and 35 healthy blood donors with no evidence of lung cancer. Fractionated serum samples were processed by surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (MS). Candidate biomarker was identified using sodium dodecyl sulphate polyacrylamide gel electrophoresis and tryptic digestion followed by tandem MS fragmentation analysis, which was subsequently validated with immunoassay.

Results:

A differential protein with m/z 11.6 kDa was detected and identified as an isoform of human serum amyloid A (SAA). It was significantly increased by 1822% in lung cancer patients when compared with the healthy controls, which gave an area under the receiver operator characteristic curve of 0.88. In addition, the protein was also significantly elevated by 77% in lung cancer patients with survival <5 years when compared with patients with survival ⩾5 years.

Conclusion:

There are several functions of the SAA protein, described in the context of inflammation, that are compatible with the mechanism of tumour invasion and metastasis. Our study not only detected increased SAA level in the serum of lung cancer patients but also identified that elevated SAA level may be a non-invasive biomarker useful for the prediction of lung cancer prognosis.

Characterization of the liver tissue interstitial fluid (TIF) proteome indicates potential for application in liver disease biomarker discovery

Tissue interstitial fluid (TIF) forms the interface between circulating body fluids and intracellular fluid. Pathological alterations of liver cells could be reflected in TIF, making it a promising source of liver disease biomarkers. Mouse liver TIF was extracted, separated by SDS-PAGE, analyzed by linear ion trap mass spectrometer, and 1450 proteins were identified. These proteins may be secreted, shed from membrane vesicles, or represent cellular breakdown products. They show different profiling patterns, quantities, and possibly modification/cleavage of intracellular proteins. The high solubility and even distribution of liver TIF supports its suitability for proteome analysis. Comparison of mouse liver TIF data with liver tissue and plasma proteome data identified major proteins that might be released from liver to plasma and serve as blood biomarkers of liver origin. This result was partially supported by comparison of human liver TIF data with human liver and plasma proteome data. Paired TIFs from tumor and nontumor liver tissues of a hepatocellular carcinoma patient were analyzed and the profile of subtracted differential proteins supports the potential for biomarker discovery in TIF. This study is the first analysis of the liver TIF proteome and provides a foundation for further application of TIF in liver disease biomarker discovery.

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 analysis of HBV-associated HCC: insights on mechanisms of disease onset and biomarker discovery

The development of hepatocellular carcinoma (HCC) can be considered as an end-stage outcome of chronic hepatitis B virus (HBV) infection. Early prognostic markers are needed to allow effective treatments and prevent HCC from developing. Proteomics analysis has been used to identify markers from clinical samples from HCC patients. This approach can be further improved by identifying early biomarkers before the onset of HCC. One way would be to use the cell-based HBV replication system, which is reflective of the early stage of virus infection and thus secreted proteins identified at this stage may have relevance in HCC prognosis. In this review, we focus the discussion on the current status of proteomics analysis of cellular proteins and HCC biomarker identification, with a special highlight on the potential of the cell-based HBV replication system for the identification of prognostic HCC biomarkers.

Current advances in tumor proteomics and candidate biomarkers for hepatic cancer

Tumor proteomics apply proteomics techniques to tumor biological research, mainly by screening candidate biomarkers for early tumor diagnosis, prognosis and treatment. Hepatocellular carcinoma (HCC) is a type of malignant tumor with one of the highest death rates in the world. With the advent of the post-genomic age, tumor biological research developing the technology of proteomics has become a major focus of researchers. The discovery of novel candidate biomarkers is one of crucial problems for the early diagnosis of HCC. In general, there are three distinct types of candidate biomarkers for HCC based on different areas: biochemical biomarkers, antigenic biomarkers and epigenetic biomarkers. This review mainly discusses current advances in the problems and prospects of candidate biomarker for the early diagnosis of HCC, discovered by technologies of tumor proteomics.

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.

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.

Serum amyloid A: an acute-phase protein involved in tumour pathogenesis

The synthesis of acute-phase protein serum amyloid A (SAA) is largely regulated by inflammation- associated cytokines and a high concentration of circulating SAA may represent an ideal marker for acute and chronic inflammatory diseases. However, SAA is also synthesized in extrahepatic tissues, e.g. human carcinoma metastases and cancer cell lines. An increasing body of in vitro data supports the concept of involvement of SAA in carcinogenesis and neoplastic diseases. Accumulating evidence suggests that SAA might be included in a group of biomarkers to detect a pattern of physiological events that reflect the growth of malignancy and host response. This review is meant to provide a broad overview of the many ways that SAA could contribute to tumour development, and accelerate tumour progression and metastasis, and to gain a better understanding of this acute-phase reactant as a possible link between chronic inflammation and neoplasia.

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.