High predictive accuracy of an unbiased proteomic profile for sustained virologic response in chronic hepatitis C patients

Correlation between IL-28 polymorphism and spontaneous clearance in HCV patients: systematic review and meta-analysis

Hepatitis C virus (HCV) is a serious global health issue. Nearly 20% of HCV patients spontaneously clear the virus. While some studies have shown an association of spontaneous clearance (SC) of the virus with interleukin (IL) 28B single-nucleotide polymorphisms (SNPs), others did not show such a relationship. Thus, the purpose of the present study was to investigate the association of IL28B polymorphisms (12979860 SNP) with SC of HCV infection. Upon initial screening of the databases, a total of 545 articles were retrieved, of which 22 studies that met predefined eligibility criteria were entered into the meta-analysis. Odds ratios (ORs) with confidence intervals (95% CI), heterogeneity, publication bias, and sensitivity analysis were assessed. According to the meta-analysis results, a significant association was observed between the rs12979860 SNP and SC of HCV infection. The results indicated that the ORs of SC from hepatitis C virus infection were 2.75 times higher in those with cytokine gene polymorphisms (95% CI, 2.23 to 3.38). Moreover, it was found that the prevalence of rs12979860 CC was 0.33 with 95 CI 0.28-0.38 in genotype 1 and was 0.40 with 95 CI 0.34-0.47 in other genotypes. Our meta-analysis results suggest that IL28B rs12979860 CC is a strong predictor for SC of hepatitis C infection in PEG IFN-a/RBV-treated patients.

Using Stepwise Pharmacogenomics and Proteomics to Predict Hepatitis C Treatment Response in Difficult to Treat Patient Populations

PURPOSE

In the interferon era of hepatitis C virus (HCV) therapies, genotype/subtype, cirrhosis, prior treatment failure, sex, and race predicted relapse. Our objective is to validate a targeted proteomics platform of 17 peptides to predict sustained virologic response (SVR).

EXPERIMENTAL DESIGN

Stored plasma from three, open-label, trials of HIV/HCV-coinfected subjects receiving interferon-containing regimens is identified. LC-MS/MS is used to quantitate the peptides directly from plasma, and IL28B genotyping is completed using stored peripheral blood mononuclear cells (PBMC). A logistic regression model is built to analyze the probability of SVR using responders and nonresponders to interferon-based regimens.

RESULTS

The cohort (N = 35) is predominantly black (51.4%), male (86%), and with median age 48 years. Most patients achieve SVR (54%). Using multivariable models, it is verified that three human corticosteroid binding globulin (CBG) peptides are predictive of SVR in patients with the unfavorable IL28B genotypes (CT/TT). The model performs better than IL28B alone, with an area under the curve of 0.870.

CONCLUSIONS AND CLINICAL RELEVANCE

In HIV/HCV-coinfected patients, three human CBG peptides that accurately predict treatment response with interferon-based therapy are identified. This study suggests that a stepwise approach combining a genetic predictor followed by targeted proteomics can improve the accuracy of clinical decision-making.

Vitamin D and K signaling pathways in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a primary liver malignancy, and is now the six most common in between malignancies. Early diagnosis of HCC with prompt treatment increases the opportunity of patients to survive. With the advances in understanding the molecular biology of HCC, new therapeutic strategies to treat HCC have emerged. There is a growing consensus that vitamins are important for the control of various cancers. Biochemical evidence clearly indicates that HCC cells are responsive to the inhibitory effect of vitamin D, vitamin D analogues and vitamin K. In this review, we summarize the mechanisms used by vitamin D and K to influence the development of HCC and the latest development of vitamin analogues for potential HCC therapy.

Association of Overt Diabetes Mellitus with the Non-CC but not the CC Genotype of Interleukin-28B in Hepatitis C Virus Infected Patients

BACKGROUND

Interleukin-28B (IL-28B) polymorphism is an important predictor for hepatitis C virus (HCV) treatment response. Whether IL-28b genotypes also influence other nontreatment related clinical parameters is unclear.

METHODS

Patients with HCV-related chronic liver diseases who attended our department during 2012-2014 were retrospectively analyzed. The single nucleotide polymorphisms (SNPs) of rs12979860 (IL-28B) were correlated with various clinical parameters. We also compared these parameters in patients with and without overt diabetes to identify possible associations.

RESULTS

A total of 115 patients were included (median age 48, range 15-76 years; 70% males). Overall, 43/115 (37%) patients had chronic hepatitis, while the remaining 72/115 (63%) had cirrhosis. The most common IL-28B genotype was CC, which was found in 53% of patients (61/115), while the remaining 47% were nonCC [CT 42% (48/115) and TT 5% (6/115)]. Clinical and laboratory parameters like Hb, white blood cell (WBC), platelets, bilirubin, transaminases, and albumin were similar in the CC and nonCC genotypes. Overt diabetes mellitus was present in 22% (25/115) of patients. Patients with nonCC genotype had significantly higher prevalence of overt diabetes mellitus than patients with CC genotype (31% [17/54] versus 13% [8/61]; p < 0.05). When parameters were compared in patients with and without overt diabetes mellitus, only IL-28B and age were significantly associated with overt diabetes mellitus (p < 0.05).

CONCLUSION

In HCV patients, overt diabetes mellitus was more commonly associated with the nonCC genotype of IL-28B than the CC genotype. Carriers of the T-allele of SNP rs12979860 were more likely to have insulin resistance than CC homozygotes, and this finding may explain the higher prevalence of diabetes in non-CC genotypes. Thus, an IL-28B test may be useful in patients of HCV in order to determine their likelihood of developing diabetes mellitus.

Comprehensive Proteomic and Metabolomic Signatures of Nontypeable Haemophilus influenzae-Induced Acute Otitis Media Reveal Bacterial Aerobic Respiration in an Immunosuppressed Environment

A thorough understanding of the molecular details of the interactions between bacteria and host are critical to ultimately prevent disease. Recent technological advances allow simultaneous analysis of host and bacterial protein and metabolic profiles from a single small tissue sample to provide insight into pathogenesis. We used the chinchilla model of human otitis media to determine, for the first time, the most expansive delineation of global changes in protein and metabolite profiles during an experimentally induced disease. After 48 h of infection with nontypeable Haemophilus influenzae, middle ear tissue lysates were analyzed by high-resolution quantitative two-dimensional liquid chromatography-tandem mass spectrometry. Dynamic changes in 105 chinchilla proteins and 66 metabolites define the early proteomic and metabolomic signature of otitis media. Our studies indicate that establishment of disease coincides with actin morphogenesis, suppression of inflammatory mediators, and bacterial aerobic respiration. We validated the observed increase in the actin-remodeling complex, Arp2/3, and experimentally showed a role for Arp2/3 in nontypeable Haemophilus influenzae invasion. Direct inhibition of actin branch morphology altered bacterial invasion into host epithelial cells, and is supportive of our efforts to use the information gathered to modify outcomes of disease. The twenty-eight nontypeable Haemophilus influenzae proteins identified participate in carbohydrate and amino acid metabolism, redox homeostasis, and include cell wall-associated metabolic proteins. Quantitative characterization of the molecular signatures of infection will redefine our understanding of host response driven developmental changes during pathogenesis. These data represent the first comprehensive study of host protein and metabolite profiles in vivo in response to infection and show the feasibility of extensive characterization of host protein profiles during disease. Identification of novel protein targets and metabolic biomarkers will advance development of therapeutic and diagnostic options for treatment of disease.

S-Nitrosylation of Sarcomeric Proteins Depresses Myofilament Ca2+)Sensitivity in Intact Cardiomyocytes

AIMS

The heart responds to physiological and pathophysiological stress factors by increasing its production of nitric oxide (NO), which reacts with intracellular glutathione to form S-nitrosoglutathione (GSNO), a protein S-nitrosylating agent. Although S-nitrosylation protects some cardiac proteins against oxidative stress, direct effects on myofilament performance are unknown. We hypothesize that S-nitrosylation of sarcomeric proteins will modulate the performance of cardiac myofilaments.

RESULTS

Incubation of intact mouse cardiomyocytes with S-nitrosocysteine (CysNO, a cell-permeable low-molecular-weight nitrosothiol) significantly decreased myofilament Ca(2+) sensitivity. In demembranated (skinned) fibers, S-nitrosylation with 1 μM GSNO also decreased Ca(2+) sensitivity of contraction and 10 μM reduced maximal isometric force, while inhibition of relaxation and myofibrillar ATPase required higher concentrations (≥ 100 μM). Reducing S-nitrosylation with ascorbate partially reversed the effects on Ca(2+) sensitivity and ATPase activity. In live cardiomyocytes treated with CysNO, resin-assisted capture of S-nitrosylated protein thiols was combined with label-free liquid chromatography-tandem mass spectrometry to quantify S-nitrosylation and determine the susceptible cysteine sites on myosin, actin, myosin-binding protein C, troponin C and I, tropomyosin, and titin. The ability of sarcomere proteins to form S-NO from 10-500 μM CysNO in intact cardiomyocytes was further determined by immunoblot, with actin, myosin, myosin-binding protein C, and troponin C being the more susceptible sarcomeric proteins.

INNOVATION AND CONCLUSIONS

Thus, specific physiological effects are associated with S-nitrosylation of a limited number of cysteine residues in sarcomeric proteins, which also offer potential targets for interventions in pathophysiological situations.

Cerebrospinal fluid proteomics in children during induction for acute lymphoblastic leukemia: A pilot study

BACKGROUND

Thrombosis in patients with acute lymphocytic leukemia (ALL) can develop after treatment with L-asparaginase (asp) and is often localized to the central nervous system (CNS). We hypothesize that changes in the cerebrospinal fluid (CSF) proteome will occur after asp therapy and will anticipate CNS clots.

METHODS

Five newly diagnosed patients, ages 1-11 years, with ALL (n = 4) or lymphoblastic lymphoma (LL) (n = 1) underwent serial lumbar punctures during induction. CSF was depleted of abundant plasma proteins and analyzed by gel-free, label-free quantitative proteomics.

RESULTS

More than 600 proteins were quantified across all CSF samples. In four subjects, the expression of proteins involved in coagulation such as protein C Inhibitor (SERPINA5) and heparin cofactor II (SERPIND1) changed over the course of asp therapy. Antithrombin III (ATIII) and plasminogen (PLMN) levels were shown to have decreased expression over time in one child who developed a CNS thrombosis, compared to other subjects.

CONCLUSIONS

CSF proteomics is feasible and reproducible in ALL and LL. CSF ATIII and PLMN should be further investigated as predictive markers of CNS thrombosis.

Proteomic approaches to analyzing hepatitis C virus biology

Hepatitis C virus (HCV) is a major cause of liver disease worldwide. Acute infection often progresses to chronicity resulting frequently in fibrosis, cirrhosis, and in rare cases, in the development of hepatocellular carcinoma. Although HCV has proven to be an arduous object of research and has raised important technical challenges, several experimental models have been developed all over the last two decades in order to improve our understanding of the virus life cycle, pathogenesis and virus-host interactions. The recent development of direct acting-agents, leading to considerable progress in treatment of patients, represents the direct outcomes of these achievements. Proteomic approaches have been of critical help to shed light on several aspect of the HCV biology such as virion composition, viral replication, and virus assembly and to unveil diagnostic or prognostic markers of HCV-induced liver disease. Here, we review how proteomic approaches have led to improve our understanding of HCV life cycle and liver disease, thus highlighting the relevance of these approaches for studying the complex interactions between other challenging human viral pathogens and their host.

Biomarkers in HCV Infection

Liver-related biomarkers have been developed and validated mainly in patients with chronic hepatitis C for the prediction of liver fibrosis or cirrhosis, which is a final pathway of chronic liver injury. They are noninvasive, traceable, and easy-to-use. Biomarkers provide implications related to screening, diagnosis, treatment, and prognosis of chronic hepatitis. For the improvement of performance and coverage, biomarker panels, imaging biomarkers, and even genetic biomarkers have been developed. With the advancement of genomics and proteomics, earlier and more precise prediction is expected in the near future. In this review, multiple biomarker panels for the estimation of the degree of fibrosis in chronic hepatitis C, biomarkers for the screening and diagnosis of hepatitis C, biomarkers for the treatment of hepatitis C, biomarkers for the prediction of complications related to the chronic hepatitis C, and future perspectives will be summarized.

A signature for immune response correlates with HCV treatment outcome in Caucasian subjects

Broad proteomic profiling was performed on serum samples of phase 2 studies (PROVE1, PROVE2, and PROVE3) of the direct-acting antiviral drug telaprevir in combination with peg-interferon and ribavirin in subjects with HCV. Using only profiling data from subjects treated with peg-interferon and ribavirin, a signature composed of pretreatment levels of 13 components was identified that correlated well (R(2)=0.68) with subjects' underlying immune response as measured by week 4 viral decline and was highly predictive of sustained virologic response in non-African American subjects (AUC=0.99). The signature was validated by predicting in an independent cohort of non-African American subjects treated with telaprevir, peg-interferon and ribavirin (AUC=0.854). Samples from extreme responders were over-represented in these analyses. Proteins identified as differentially-expressed between responders and non-responders to HCV treatment were quantified using multiple reaction monitoring in samples from all Caucasian subjects in the peg-interferon and ribavirin arms of PROVE1 and PROVE2, revealing 15 proteins that were significantly differentially expressed between treatment responders and non-responders. Seven of the proteins are part of focal adhesions or other macromolecular assemblies that form structural links between integrins and the actin cytoskeleton and are involved in antiviral response.

BIOLOGICAL SIGNIFICANCE

HCV is a significant health problem. We describe a novel approach for identifying markers that predicts HCV treatment response different treatment regimens and use this approach to identify a novel HCV treatment response signature. The signature has potential to guide optimization of HCV treatment regimens.

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.

Individualized therapy for hepatitis C infection: focus on the interleukin-28B polymorphism in directing therapy

Hepatitis C virus—a major global cause of chronic hepatitis, cirrhosis, and hepatocellular carcinoma—affects millions of people worldwide. Pegylated interferon (Peg-IFN) and ribavirin (RBV) had been the standard treatment for a decade until availability of the protease inhibitors in 2011. However, current antiviral therapy is still IFN-based and is associated with significant side effects and variable treatment response. Thus, various host and viral factors have been evaluated before and during treatment for the prediction of sustained virologic response to antiviral therapy. In 2009, genome-wide association studies found the single-nucleotide polymorphisms, located near the host interleukin-28B (IL28B) gene that encodes IFN-λ3, to be the best pretreatment predictor of virologic response to Peg-IFN and RBV therapy in chronic hepatitis C genotype 1 patients. Additionally, inosine triphosphatase (ITPA) gene variants were found to be associated with RBV-induced hemolytic anemia, which could affect treatment dose for selected patients. IL28B, ITPA, and other treatment predictors allowed for a potential individualized approach to treat hepatitis C. In the era of increased overall virologic response rates and good tolerability of the rapidly developing non-IFN oral direct-acting antiviral therapy regimens, the need for individualized treatment is likely to diminish. Various predictors of response, including IL28B will likely be of reduced importance in the near future.

A flexible statistical model for alignment of label-free proteomics data--incorporating ion mobility and product ion information

Background

The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing - the matching of peptide measurements across samples.

Results

We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates.

Conclusions

Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits. Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods.

Human systems immunology: hypothesis-based modeling and unbiased data-driven approaches

Systems immunology is an emerging paradigm that aims at a more systematic and quantitative understanding of the immune system. Two major approaches have been utilized to date in this field: unbiased data-driven modeling to comprehensively identify molecular and cellular components of a system and their interactions; and hypothesis-based quantitative modeling to understand the operating principles of a system by extracting a minimal set of variables and rules underlying them. In this review, we describe applications of the two approaches to the study of viral infections and autoimmune diseases in humans, and discuss possible ways by which these two approaches can synergize when applied to human immunology.

Serum proteins in chronic hepatitis B patients treated with peginterferon alfa-2b

AIM: To study the differential protein profile in serum of hepatitis B patients.

METHODS: Serum samples were obtained from patients with chronic hepatitis B who were receiving peginterferon alfa-2b. The serum samples were subjected to albumin depletion and analyzed by two-dimensional gel electrophoresis (2-DE). Differentially expressed protein spots were identified by electrospray ionization-quadrupole time-of-flight mass spectrometry. Alpha-2-HS-glycoprotein, complement component C3c and CD5 antigen were further analyzed by an enzyme-linked immunosorbent assay and immunonephelometry.

RESULTS: Nineteen patients with HBeAg-positive chronic hepatitis B (CHB) were studied. These patients were followed for at least 1 year after treatment and were classified according to their treatment response: responders (n = 9) and non-responders (n = 10). 2-DE and MS/MS analysis were performed to compare the serum proteins before initiating peginterferon alfa-2b. From the quantitative analysis of the 2-D gel, 7 proteins were detected between the two groups at different levels before treatment. Among these potential candidates, serum levels of alpha-2-HS-glycoprotein, complement component C3c and CD5 antigen-like precursor were further analyzed. In the validation phase, 23 subjects, 9 sustained responders and 14 non-responders, were recruited. Interestingly, the levels of alpha-2-HS-glycoprotein and complement component C3c were elevated in the serum of the non-responders compared to the responders.

CONCLUSION: Serum alpha-2-HS-glycoprotein and complement component C3c may be potential serum biomarkers in predicting the treatment response of peginterferon alfa-2b in patients with CHB prior to treatment.

Serum proteome predicts virological response in chronic hepatitis C genotype 1b patients treated with pegylated interferon plus ribavirin

BACKGROUND/PURPOSE

Whether serum proteome changes can predict treatment response in chronic hepatitis C remains unclear. We investigated the association between serum proteome changes and virological responses in chronic hepatitis C virus genotype 1b (HCV-1b) patients treated with pegylated interferon (PegIFN) plus ribavirin (RBV).

METHODS

One hundred and thirty-six HCV-1b patients who had completed a course of PegIFN plus RBV for 24 weeks, had a 24-week follow-up, and had pretreatment serum available were enrolled. These patients were divided into training and validation groups. We used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS) for peptide profiling and ClinPro Tools version 2.0 bioinformatics software for data analysis.

RESULTS

Seventy-four patients (54%) had a sustained virological response (SVR), whereas 62 did not. We identified three protein peaks in pretreatment sera where the expression levels significantly differed between SVR and non-SVR (p < 0.05). Using the class prediction tool composed of the three protein peaks, we were able to correctly predict SVR in 95% of validation group patients with sensitivity = 95%, specificity = 56.3%, positive predictive value = 73.1%, and negative predictive value = 90%. We also identified a set of 20 protein peaks where the expression levels significantly differed in pretreatment sera between patients with nonresponse (NR) and virological response (SVR plus relapse; p < 0.05). Using the class prediction tool composed of these 20 protein peaks, we were able to correctly predict virological NR in 82% of validation group patients with sensitivity = 100%, specificity = 82%, positive predictive value = 92.6%, and negative predictive value = 100%.

CONCLUSION

Pretreatment serum proteome allows prediction of SVR and NR to PegIFN plus RBV treatment in HCV-1b patients.

Serum peptides, represented by complement 3f des-arginine, are useful for prediction of the response to pegylated interferon-α plus ribavirin in patients with chronic hepatitis C

AIM

Biomarkers predicting sustained virological response (SVR) to pegylated interferon-α plus ribavirin (PEG IFN-α/RBV) were investigated.

METHODS

Peptides in pretreatment sera from 107 patients with hepatitis C virus (HCV) genotype 1 were comprehensively analyzed by mass spectrometry. Ion intensity of the peptides was used to generate discriminant models between the responders who achieved SVR (R) and the non-responders (NR) to PEG IFN-α/RBV.

RESULTS

In total, 107 peptides were detected in a training set (n = 23). A discriminant model using a peptide, complement 3f des-arginine (C3f-dR), showed sensitivity of 35% and specificity of 94% for SVR prediction in a testing set (n = 68). In all the R and NR (n = 96), an area under the receiver-operator curve (AUROC) of 0.64 in the C3f-dR model was increased to 0.78 by addition of platelet (PLT) counts (C3f-dR/PLT model). Another model using the 107 peptides (AUROC, 0.77) also showed higher AUROC (0.79) by addition of hemoglobin (Hb), body mass index (BMI) and age (107P/Hb/BMI/Age model). The sensitivity and specificity of the C3f-dR/PLT model were 59% and 88%, and those of the 107P/Hb/BMI/Age model were 70% and 92%, respectively. The C3f-dR/PLT model showed high AUROC (0.82), similar to that of interleukin-28B rs8099917 genotype analysis (0.86) in the 45 tested patients. Prediction by the combination of the C3f-dR/PLT model, the 107P/Hb/BMI/Age model and the rs8099917 genotype analysis was accurate in 44 out of the 45 patients (AUROC, 0.95).

CONCLUSION

Serum peptides, especially C3f-dR, would be useful predictors for SVR to PEG IFN-α/RBV. The complements may be involved in the HCV elimination.

Proteomic analysis of human bronchoalveolar lavage fluid after subsgemental exposure

The analysis of airway fluid, as sampled by bronchoalveolar lavage (BAL), provides a minimally invasive route to interrogate lung biology in health and disease. Here, we used immunodepletion, coupled with gel- and label-free LC-MS/MS, for quantitation of the BAL fluid (BALF) proteome in samples recovered from human subjects following bronchoscopic instillation of saline, lipopolysaccharide (LPS) or house dust mite antigen into three distinct lung subsegments. Among more than 200 unique proteins quantified across nine samples, neutrophil granule-derived and acute phase proteins were most highly enriched in the LPS-exposed lobes. Of these, peptidoglycan response protein 1 was validated and confirmed as a novel marker of neutrophilic inflammation. Compared to a prior transcriptomic analysis of airway cells in this same cohort, the BALF proteome revealed a novel set of response factors. Independent of exposure, the enrichment of tracheal-expressed proteins in right lower lung lobes suggests a potential for constitutive intralobar variability in the BALF proteome; sampling of multiple lung subsegments also appears to aid in the identification of protein signatures that differentiate individuals at baseline. Collectively, this proof-of-concept study validates a robust workflow for BALF proteomics and demonstrates the complementary nature of proteomic and genomic techniques for investigating airway (patho)physiology.

Meta-analysis: implications of interleukin-28B polymorphisms in spontaneous and treatment-related clearance for patients with hepatitis C

BACKGROUND

Since 2009, several studies have identified single-nucleotide polymorphisms (SNPs) near the gene encoding for interleukin (IL)-28 (IL28B) that are strongly associated with spontaneous and treatment-induced hepatitis C virus (HCV) clearance. Because this large amount of data includes some inconsistencies, we consider assessment of the global estimate for each SNP to be essential.

METHODS

Relevant studies assessing IL28B polymorphisms associated with sustained virologic response (SVR) and spontaneous clearance (SC) were identified from a literature search of PubMed up to 9 July, 2012. Studies were eligible studies if they included patients infected with HCV or HCV/HIV, or assessed any SNP located within or near the IL28B gene, SVR data available under standard treatment, and/or SC data in patients with acute HCV infection. Pooled odds ratios were estimated by fixed or random effects models when appropriate. Variables such as HCV genotype, ethnicity, and type of co-infection were studied.

RESULTS

Of 282 screened studies, 67 were selected for SVR and 10 for SC. In total, 20,163 patients were studied for SVR and 3,554 for SC. For SVR, we found that all SNPs showed strong associations in patients with HCV genotypes 1 and 4, whereas the pooled ORs were almost three times lower for genotypes 2 and 3 (rs12979860 and rs8099917). Regarding ethnicity, the SNP most associated with SVR was rs12979860 in white patients, whereas in East Asians it seemed to be rs8099917. The most studied SNP (rs12979860) showed similar results for patients co-infected with HCV/HIV, as for those infected with HCV only. Finally, rs12979860 and rs8099917 both appeared to be associated with SC.

CONCLUSIONS

IL28B polymorphisms influence both the outcome of interferon treatment and the natural clearance of HCV. However we did not identify a universal predictor SNP, as the best genetic markers differed depending on patient ethnicity, genotype, and type of infection. Nevertheless, our results may be useful for more precise treatment decision-making.

Identification of deacetylase substrates with the biotin switch approach

The identification of lysine-acetylated proteins and deacetylase substrates has primarily relied on protein immune-affinity techniques with antibodies that recognize acetylated lysine residues (Kac antibodies). While these antibody-based techniques are continuously improving, they can be limited by the narrow and many times unknown epitope specificity of Kac antibodies. An alternative approach is the biotin switch capture of deacetylated proteins. Similar in part to other biotin switch methodologies, this technique relies on the blocking of native lysine residues and removal of the modification of interest in vitro, after which the newly deacetylated proteins can be captured and identified by mass spectrometry (MS). In this chapter, we cover the essential steps of the procedure, highlight key points in the assay to reduce false positive protein identification, and discuss the quantitative MS methods useful for identifying the captured deacetylase substrates. We also discuss potential strategies and future improvements to overcome current limitations of the assay.

Solid-phase capture for the detection and relative quantification of S-nitrosoproteins by mass spectrometry

The proteomic analysis of S-nitrosylated protein (SNO-proteins) has long depended on the biotin switch technique (BST), which requires blocking of free thiols, ascorbate-based denitrosylation of SNO-Cys, biotinylation of nascent thiol and avidin-based affinity isolation. A more recent development is resin assisted-capture of SNO-proteins (SNO-RAC), which substitutes thiopropyl Sepharose (TPS) for biotin-avidin, thus reducing the number of steps required for enrichment of S-nitrosylated proteins. In addition, SNO-RAC facilitates on-resin proteolytic digestion following SNO-protein capture, greatly simplifying the purification of peptides containing sites of S-nitrosylation ("SNO-sites"). This resin-based approach has also now been applied to detection of alternative Cys-based modifications, including S-palmitoylation (Acyl-RAC) and S-oxidation (Ox-RAC). Here, we review the important steps to minimize false-positive identification of SNO-proteins, give detailed methods for processing of protein-bound TPS for mass spectrometry (MS) based analysis, and discuss the various quantitative MS methods that are compatible with SNO-RAC. We also discuss strategies to overcome the current limitations surrounding MS-based SNO-site localization in peptides containing more than one potential target Cys residue. This article therefore serves as a starting point and guide for the MS-focused exploration of SNO-proteomes by SNO-RAC.

Applying proteomic technology to clinical virology

Developing antiviral drugs, vaccines and diagnostic markers is still the most ambitious challenge in clinical virology. In the past few decades, data from high‐throughput technologies have allowed for the rapid development of new antiviral therapeutic strategies, thus making a profound impact on translational research. Most of the current preclinical studies in virology are aimed at evaluating the dynamic composition and localization of the protein platforms involved in various host–virus interactions. Among the different possible approaches, mass spectrometry‐based proteomics is increasingly being used to define the protein composition in subcellular compartments, quantify differential protein expression among samples, characterize protein complexes, and analyse protein post‐translational modifications. Here, we review the current knowledge of the most useful proteomic approaches in the study of viral persistence and pathogenicity, with a particular focus on recent advances in hepatitis C research.

Interleukin-28B polymorphisms on the SVR in the treatment of naïve chronic hepatitis C with pegylated interferon-α plus ribavirin: a meta-analysis

There are accurate but inconclusive data on the association between single nucleotide polymorphisms (SNPs) of interleukin (IL)-28B and sustained virological response (SVR) in chronic hepatitis C (CHC). This meta-analysis aimed to derive a more precise estimation of the effects of IL-28B SNPs locus (rs12979860 and rs8099917) on SVR in naïve CHC patients receiving pegylated interferon alpha (PEG-IFN-α) plus ribavirin. Literature search was conducted up to June, 2011, in PubMed, EMBASE and Cochrane Database of Systematic Reviews. A total of 36 studies involving 10912 cases with CHC receiving PEG-IFN-α plus ribavirin met the inclusion criteria. Analyses were stratified either by ethnicity or genotype of hepatitis C virus. In genotype 1/4 patients, rs12979860 CC was associated with high SVR in CHC patients (Caucasian: odds ratio (OR), 4.567; 95% confidence interval (CI), 3.826-5.452; Asian: OR, 4.033; 95%CI, 3.050-5.333; African American: OR, 4.297; 95%CI, 2.168-8.515; Hispanics: OR, 4.350; 95%CI, 2.817-6.717) but had no effect in genotype 2/3. In Caucasian (genotype 1/4: OR, 2.542; 95%CI, 2.108-3.065; genotype 2/3: OR, 1.363; 95%CI, 1.020-1.820) and Asian (genotype 1/4: OR, 5.214; 95%CI, 3.694-7.360; genotype 2/3: OR, 1.785; 95%CI, 1.095-2.910), rs8099917 TT was associated with high SVR in both genotype 1/4 and 2/3. Meta-regression showed that in Caucasians with CHC genotype 1/4, gender male might contribute to the effect of rs12979860 on SVR but advanced fibrosis might weaken this effect. Furthermore, in Asians with CHC genotype 1/4, high baseline viral load and advanced fibrosis might also undermine the effect of rs8099917 on SVR. This meta-analysis suggested that IL-28B rs12979860 CC and rs8099917 TT were associated with high SVR rate in CHC genotype 1/4. In CHC genotype 2/3, rs8099917 TT carriers also had higher SVR.

D-livering the message: the importance of vitamin D status in chronic liver disease

Vitamin D is synthesized predominantly in the liver and functions as an important secosteroid hormone with pleiotropic effects. While its key regulatory role in calcium and bone homeostasis is well established, recently there is increasing recognition that vitamin D also regulates cell proliferation and differentiation, and has immunomodulatory, anti-inflammatory and anti-fibrotic properties. These non-skeletal effects are relevant in the pathogenesis and treatment of many causes of chronic liver disease. Vitamin D deficiency is frequently present in chronic liver disease and may predict non-response to antiviral therapy in chronic hepatitis C. Small studies suggest that vitamin D supplementation improves sustained viral response rates, while 1α-hydroxylase polymorphisms and vitamin D-binding protein are also implicated in therapeutic outcomes. Vitamin D deficiency also closely relates to the severity of non-alcoholic fatty liver disease (NAFLD) and is implicated in the pathogenesis of insulin resistance, a key factor in the development of NAFLD. In preclinical studies, phototherapy and vitamin D supplementation ameliorate NAFLD histopathology, while vitamin D is a powerful anti-fibrotic against thioacetamide liver injury. In liver transplant recipients severe vitamin D deficiency predicts, and vitamin D supplementation prevents, acute cellular rejection. The role of vitamin D in the activation and regulation of both innate and adaptive immune systems may explain its importance in the above liver diseases. Further prospective studies are therefore warranted to investigate the therapeutic impact of vitamin D supplementation in chronic liver disease.

Association of the IL28B genotype with insulin resistance in patients with chronic hepatitis C

BACKGROUND & AIMS

Insulin resistance, fibrosis and steatosis are established predictors of response to peg-interferon/ribavirin therapy in chronic hepatitis C (CHC). Several host genetic polymorphisms (IL28B, PNPLA3) modify treatment-outcome, the degree of steatosis or fibrosis. The aim of our study was to evaluate the role of these polymorphisms on insulin resistance (IR) in treatment-naïve patients with chronic hepatitis C.

METHODS

Two hundred and two non-diabetic CHC patients (GT1: 181, GT4: 21; m = 126, f = 76) undergoing liver biopsy in two tertiary academic centers were studied. The SNPs rs12979860 (IL28B) and rs738409 (PNPLA3) were investigated by RT-PCR. HOMA-IR, BMI, stage of fibrosis, extent of steatosis, and genetic data were analyzed.

RESULTS

Insulin resistance (HOMA-IR ≥ 3.0) was associated with rs12979860 genotype, presence of advanced fibrosis, and higher BMI. HOMA-IR in CC and in TC/TT was 2.08 ± 1.61 (mean ± SD) and 2.94 ± 2.89 (p=0.041), respectively. HOMA-IR was higher in advanced than in mild fibrosis (F3-4: 3.92 ± 3.15; F0-2: 2.38 ± 2.38; p=0.004). The percentage of steatotic hepatocytes was higher in patients with advanced fibrosis (21.3 ± 21.5 vs. 9.1 ± 14.2; p<0.001), HOMA-IR ≥ 3.0 (17.7 ± 17.8 vs. 8.8 ± 15.4%; p<0.001), and BMI > 25.0 kg/m(2) (14.7 ± 17.0 vs. 9.1 ± 16.1; p<0.001). The rs738409 GG genotype was associated with advanced fibrosis and steatosis, but not with HOMA-IR. Multivariable logistic regression identified advanced fibrosis (OR: 2.820, 95% CI: 1.344-5.917; p = 0.006) and the IL28B genotype non-CC (OR: 3.000, 1.348-6.676; p = 0.007) as independent risk factors for insulin resistance.

CONCLUSIONS

Insulin resistance is more common in carriers of the T allele of SNP rs12979860 than in CC homozygotes and may partly explain the poor outcome of peginterferon/ribavirin therapy in these patients.

Opportunities in proteomics to understand hepatitis C and HIV coinfection

Antiretroviral therapy has significantly reduced morbidity and mortality associated with HIV infection. However, coinfection with HCV results in a more complicated disease course for both infections. HIV infection dramatically impacts the natural history of chronic liver disease due to HCV. Coinfected patients not on antiretroviral therapy for HIV develop liver fibrosis and cirrhosis at a faster rate, clear acute infection less commonly and respond to IFN-α-based therapy for chronic infection less often than HCV-monoinfected patients. The interaction between these two viruses, the immune system and the fibrotic machinery of the liver remains incompletely understood. In this review, we discuss recent advances in proteomics as applied to HCV and HIV and highlight issues in coinfection that are amenable to further discovery through proteomic approaches. We focus on clinical predictors of liver fibrosis and treatment outcome as these have the greatest potential clinical applicability.

Metaprotein expression modeling for label-free quantitative proteomics

BACKGROUND

Label-free quantitative proteomics holds a great deal of promise for the future study of both medicine and biology. However, the data generated is extremely intricate in its correlation structure, and its proper analysis is complex. There are issues with missing identifications. There are high levels of correlation between many, but not all, of the peptides derived from the same protein. Additionally, there may be systematic shifts in the sensitivity of the machine between experiments or even through time within the duration of a single experiment.

RESULTS

We describe a hierarchical model for analyzing unbiased, label-free proteomics data which utilizes the covariance of peptide expression across samples as well as MS/MS-based identifications to group peptides-a strategy we call metaprotein expression modeling. Our metaprotein model acknowledges the possibility of misidentifications, post-translational modifications and systematic differences between samples due to changes in instrument sensitivity or differences in total protein concentration. In addition, our approach allows us to validate findings from unbiased, label-free proteomics experiments with further unbiased, label-free proteomics experiments. Finally, we demonstrate the clinical/translational utility of the model for building predictors capable of differentiating biological phenotypes as well as for validating those findings in the context of three novel cohorts of patients with Hepatitis C.

CONCLUSIONS

Mass-spectrometry proteomics is quickly becoming a powerful tool for studying biological and translational questions. Making use of all of the information contained in a particular set of data will be critical to the success of those endeavors. Our proposed model represents an advance in the ability of statistical models of proteomic data to identify and utilize correlation between features. This allows validation of predictors without translation to targeted assays in addition to informing the choice of targets when it is appropriate to generate those assays.

Liver protein profiling in chronic hepatitis C: identification of potential predictive markers for interferon therapy outcome

The current anti-hepatitis C virus (HCV) therapy, based on pegylated-interferon alpha and ribavirin, has limited success rate and is accompanied by several side effects. The aim of this study was to identify protein profiles in pretreatment liver biopsies of HCV patients correlating with the outcome of antiviral therapy. Cytosolic or membrane/organelle-enriched protein extracts from liver biopsies of eight HCV patients were analyzed by two-dimensional fluorescence difference gel electrophoresis and mass spectrometry. Overall, this analysis identified 21 proteins whose expression levels correlate with therapy response. These factors are involved in interferon-mediated antiviral activity, stress response, and energy metabolism. Moreover, we found that post-translational modifications of dihydroxyacetone kinase were also associated with therapy outcome. Differential expression of the five best performing markers (STAT1, Mx1, DD4, DAK, and PD-ECGF) was confirmed by immunoblotting assays in an independent group of HCV patients. Finally, we showed that a prediction model based on the expression levels of these markers classifies responder and nonresponder patients with an accuracy of 85.7%. These results provide evidence that the analysis of pretreatment liver protein profiles is valuable for discriminating between responder and nonresponder HCV patients, and may contribute to reduce the number of nonresponder patients exposed to therapy-associated risks.

Characterization of serum proteins associated with IL28B genotype among patients with chronic hepatitis C

INTRODUCTION

Polymorphisms near the IL28B gene (e.g. rs12979860) encoding interferon λ3 have recently been associated with both spontaneous clearance and treatment response to pegIFN/RBV in chronic hepatitis C (CHC) patients. The molecular consequences of this genetic variation are unknown. To gain further insight into IL28B function we assessed the association of rs12979860 with expression of protein quantitative traits (pQTL analysis) generated using open-platform proteomics in serum from patients.

METHODS

41 patients with genotype 1 chronic hepatitis C infection from the Duke Liver Clinic were genotyped for rs12979860. Proteomic profiles were generated by LC-MS/MS analysis following immunodepletion of serum with MARS14 columns and trypsin-digestion. Next, a latent factor model was used to classify peptides into metaproteins based on co-expression and using only those peptides with protein identifications. Metaproteins were then analyzed for association with IL28B genotype using one-way analysis of variance.

RESULTS

There were a total of 4,186 peptides in the data set with positive identifications. These were matched with 253 proteins of which 110 had two or more associated, identified peptides. The IL28B treatment response genotype (rs12979860_CC) was significantly associated with lower serum levels of corticosteroid binding globulin (CBG; p = 9.2×10(-6)), a major transport protein for glucocorticoids and progestins. Moreover, the CBG metaprotein was associated with treatment response (p = 0.0148), but this association was attenuated when both IL28B genotype and CBG were included in the model, suggesting that the CBG association may be independent of treatment response.

CONCLUSIONS

In this cohort of chronic hepatitis C patients, IL28B polymorphism was associated with serum levels of corticosteroid binding globulin, a major transporter of cortisol, however, CBG does not appear to mediate the association of IL28B with treatment response. Further investigation of this pathway is warranted to determine if it plays a role in other comorbidities of HCV-infection.