Identification of complement C3a as a candidate biomarker in human chronic hepatitis C and HCV-related hepatocellular carcinoma using a proteomics approach

Although the significant risk factors for hepatocellular carcinoma (HCC) are well known from epidemiological studies, diagnosis of this disease at an early stage is difficult, and HCC remains one of the leading causes of cancer death worldwide. Thus, to identify any useful HCC-related biomarkers is still a need. We performed SELDI-TOF MS to identify differentially expressed proteins in HCC serum using weak cation exchange protein chips. Protein characterization was performed by 2-DE separation and nano flow LC-MS/MS. A total of 55 sera were collected from HCC patients and compared with those from 48 patients with chronic hepatitis and 9 healthy individuals. A candidate marker of about 8900 Da was detected as differentially expressed in patients with chronic hepatitis C and hepatitis C virus (HCV)-related HCC. We identified this differentially expressed protein as complement C3a. The expression of C3a in HCC sera was further validated by PS20 chip immunoassay and Western blotting. Complement C3a was found to be elevated in patients with chronic hepatitis C and HCV-related HCC. The combination of SELDI-TOF MS and 2-DE provides a solution to identify disease-associated serum biomarkers.     

Enrichment of low molecular weight fraction of serum for MS analysis of peptides associated with hepatocellular carcinoma

A challenging aspect of biomarker discovery in serum is the interference of abundant proteins with identification of disease-related proteins and peptides. This study describes enrichment of serum by denaturing ultrafiltration, which enables an efficient profiling and identification of peptides up to 5 kDa. We consistently detect several hundred peptide-peaks in MALDI-TOF and SELDI-TOF spectra of enriched serum. The sample preparation is fast and reproducible with an average CV for all 276 peaks in the MALDI-TOF spectrum of 11%. Compared to unenriched serum, the number of peaks in enriched spectra is 4 times higher at an S/N ratio of 5 and 20 times higher at an S/N ratio of 10. To demonstrate utility of the methods, we compared 20 enriched sera of patients with hepatocellular carcinoma (HCC) and 20 age-matched controls using MALDI-TOF. The comparison of 332 peaks at p < 0.001 identified 45 differentially abundant peaks that classified HCC with 90% accuracy in this small pilot study. Direct TOF/TOF sequencing of the most abundant peptide matches with high probability des-Ala-fibrinopeptide A. This study shows that enrichment of the low molecular weight fraction of serum facilitates an efficient discovery of peptides that could serve as biomarkers for detection of HCC as well as other diseases.     

Rapid determination of serological cytokine biomarkers for hepatitis B virus-related hepatocellular carcinoma using antibody microarrays

Hepatocellular carcinoma (HCC) is one of the most frequent tumors worldwide with an increasing incidence. The exploration of biomarkers for HCC is one of the main aims for improving the efficacy of diagnosis and treatment. The microarray technology provides a high-throughput platform for parallel exploration of biomarkers for clinics. In this study, we used antibody microarrays to screen the novel cytokine biomarkers of hepatitis B virus (HBV)-related HCC. Cytokine-secreting patterns in sera were determined from 109 cases including 43 HBV-related HCC patients, 33 chronic hepatitis B patients, and 33 normal controls by RayBio Biotin label-based human antibody array. The correlation analysis was performed with conventional clinical diagnostic biomarkers, including serum alanine aminotransferase, alpha-fetoprotein (AFP) and hepatitis B surface antigen. Our results showed that in HBV-related HCC group, which had the highest percentage of AFP positive (>20 ng/ml) ratio, six cytokines were found differentially expressed in HCC patients (P < 0.05), compared with either normal controls or chronic hepatitis B group. Two macrophage-related cytokines, macrophage-derived chemokine (MDC) and macrophage-stimulating protein α (MSPα), displayed significant difference in the HCC group. Furthermore, an HCC diagnostic model for prediction was constructed, by which the combination of MDC and MSPα together with AFP had improved the diagnostic sensitivity from 60% (AFP alone) to 73.2% with similar specificity. Our results suggested that MDC and MSPα screened by antibody microarrays might serve as novel cytokines biomarkers for potential auxiliary diagnosis of HBV-related HCC.     

Identification of potential serum biomarkers for Wilms tumor after excluding confounding effects of common systemic inflammatory factors

Wilms tumor is the most common pediatric tumor of the kidney. Previous studies have identified several serum biomarkers for Wilms tumor; however, they lack sufficient specificity and may not adequately distinguish Wilms tumor from confounding conditions. To date, no specific protein biomarker has been confirmed for this pediatric tumor. To identify novel serum biomarkers for Wilms tumor, we used proteomic technologies to perform protein profiling of serum samples from pre-surgery and post-surgery patients with Wilms tumor and healthy controls. Some common systemic inflammatory factors were included to control for systemic inflammation. By comparing protein peaks among the three groups of sera, we identified two peaks (11,526 and 4,756 Da) showing significant differential expression not only between pre-surgery and control sera but also between pre-surgery and post-surgery sera. These two peaks were identified as serum amyloid A1 (SAA1) and apolipoprotein C-III (APO C-III). Western blot analysis confirmed that both proteins were expressed at higher levels in pre-surgery sera than in post-surgery and control sera. Using the method of leave-1-out for cross detection, we demonstrate that detection of these two candidate biomarkers had high sensitivity and specificity in discriminating pre-surgery sera from post-surgery and normal control sera. Taken together, these findings suggest that SAA1 and APO C-III are two potential biomarkers for Wilms tumor.     

Heat-shock protein 27: a potential biomarker for hepatocellular carcinoma identified by serum proteome analysis

Hepatocellular carcinoma (HCC) is the third leading cause of cancer mortality worldwide and ranks second in China. The prognosis of HCC remains dismal mainly because of its late diagnosis, especially in patients with coexisting chronic liver diseases. To identify serum biomarkers for HCC, sera from 20 healthy volunteers, 20 hepatitis B virus (HBV) infected patients and 20 HCC patients were selected for screening study and same number of sera into the same three groups were used for validation study. A strategy including sonication, albumin and immunoglobulin G (IgG) depletion and desalting was optimized for screening differentially expressed proteins of low abundance in serum. By 2-DE image analysis and MALDI-TOF-MS/MS identification, eight proteins including heat-shock protein 27 (HSP27), alpha-fetoprotein (AFP), alpha-1 antitrypsin, clusterin, caeruloplasmin, haptoglobin alpha2 chain, tranferrin and transthyretin were found significantly changed among the healthy, HBV and HCC groups. Further validation study by Western blot showed the detection of HSP27 in 90% HCC sera and two HBV sera, but in none of normal sera. Thus, 2-DE based serum proteome analysis can be useful in the screening of serum biomarkers for HCC and HSP27 could aid in the diagnosis of HCC though further validation is needed.     

Hepatitis B Virus X Protein-Induced Aberrant Epigenetic Modifications Contributing to Human Hepatocellular Carcinoma Pathogenesis

Hepatocellular carcinoma (HCC) remains one of the most prevalent malignant diseases worldwide, and the majority of cases are related to hepatitis B virus (HBV) infection. Interactions between the HBV-encoded X (HBx) protein and host factors are known to play major roles in the onset and progression of HBV-related HCC. These dynamic molecular mechanisms are extremely complex and lead to prominent changes in the host genetic and epigenetic architecture. This review summarizes the current knowledge about HBx-induced epigenetic changes, including aberrations in DNA methylation, histone modifications, and microRNA expression, and their roles in HBV-infected liver cells and HBV-related HCC. Moreover, the HBx-mediated epigenetic control of HBV covalently closed circular DNA (cccDNA) is also discussed. Although this field of study is relatively new, the accumulated evidence has indicated that the epigenetic events induced by HBx play important roles in the development of HBV-related HCC. Ongoing research will help to identify practical applications of the HBV-related epigenetic signatures as biomarkers for early HCC detection or as potential targets to prevent and treat HBV-related HCC.     

Screening of autoantibodies as potential biomarkers for hepatocellular carcinoma by using T7 phase display system

Background: Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide. Autoantibodies to tumor-associated proteins in the serum profile, as new biomarkers, may improve the early detection of HCC. Methods: In this study, we interrogated a HCC cDNA T7 phage library for tumor-associated proteins using biopan enrichment techniques with HCC patient and normal sera. The enrichment of tumor-associated proteins after biopanning was tested using plaque assay and immunochemical detection. The putative tumor-associated phage clones were collected for PCR and sequencing analysis. Identities of those selected sequences were revealed through the sequence BLAST program. The identified phage-expressed proteins were then used to develop phage protein ELISA to measure matching autoantibodies using 70 HCC patients, 50 chronic hepatitis patients, and 70 normal serum samples. The logistic regression model and leave-one-out validation were used to evaluate predictive accuracies with a single marker as well as with combined markers. Results: Twenty-six phage-displayed proteins have sequence identity with known or putative tumor-associated proteins. Immunochemical reactivity of patient sera with phage-expressed proteins showed that the autoantibodies to phage-expressed protein CENPF, DDX3, HSPA4, HSPA5, VIM, LMNB1, and TP53 had statistical significance in HCC patients. Measurements of the seven autoantibodies combined in a logistic regression model showed that combined measurements of these autoantibodies was more predictive of disease than any single antibody alone, underscoring the importance of identifying multiple potential markers. Conclusion: Autoantibody in the serum profiling is a promising approach for early detection and diagnosis of HCC. The panel of autoantibodies appears preferable to achieve superior accuracy rather than an autoantibody alone, and may have significant relevance to tumor biology, novel drug development, and immunotherapies.     

Epigenetic repression of miR-132 expression by the hepatitis B virus x protein in hepatitis B virus-related hepatocellular carcinoma

Hepatitis B virus x (HBx) protein is involved in the initiation and progression of HBV-related hepatocellular carcinoma (HCC) by regulating host protein-coding genes. However, the role of HBx in the epigenetic repression of miRNAs, which play important roles in gene regulation during hepatocarcinogenesis, remains largely unknown. In this study, the expression of miR-132 in HCC cells, HBV-related HCC tissues, and serum were determined using real-time PCR. The level of DNA methylation on the promoter of miR-132 was examined using methylation-specific PCR (MSP). MiR-132 was functionally characterized in HCC cells with transiently altered miR-132 expression. HBx-induced DNA hypermethylation of the promoter of miR-132 was found to be more prevalent in HBx-expressing HepG2 cells than in control cells. Consistently, MiR-132 expression was also more frequently down-regulated in HBV-related HCC tissues than in adjacent noncancerous hepatic tissues and had a significant inverse correlation with HBx expression in HBV-related HCCs. Serum miR-132 levels were found to be significantly correlated with levels in tumor tissue. Finally, proliferation and colony formation of HCC cells were found to be suppressed by miR-132-mediated inhibition of the Akt-signaling pathway in miR132 transfected cells. Our study has demonstrated the epigenetic repression of miR-132 expression through DNA methylation induced by HBx. This work provides novel mechanistic insights into HBV-mediated hepatocarcinogenesis and suggests that miR-132 may be a promising biochemical marker and may have therapeutic applications in HBV-related HCC.     

新型冠状病毒肺炎患者血清SAA、ESR、CRP检测结果分析

目的:分析新型冠状病毒肺炎(COVID-19)患者血清淀粉样蛋白A(SAA)、血沉ESR(ESR)、C-反应蛋白CRP(CRP)的临床价值。方法:以我院2020年1月至2020年2月确诊的COVID-19患者51例为实验组:其中重症患者21例,轻症患者30例,选取非感染患者30例为对照组。分析新型冠状病毒肺炎(COVID-19)患者血清SAA、ESR、CRP水平以及临床价值。结果:实验组SAA、ESR、CRP水平高于对照组(P0.05);重症组SAA、ESR、CRP水平高于轻症组(P0.05),由ROC曲线得知SAA、ESR、CRP预测COVID-19的AUC小于三者联合预测的AUC。结论:COVID-19的SAA、ESR、CRP水平会升高,三者联合预测为疾病评估、预测疾病发展的提供依据,值得临床进一步推广应用。     

The miR-545/374a Cluster Encoded in the Ftx lncRNA is Overexpressed in HBV-Related Hepatocellular Carcinoma and Promotes Tumorigenesis and Tumor Progression

Hepatitis B virus (HBV) infection is a major risk factor for hepatocellular carcinoma (HCC). Previous studies have shown several long noncoding RNAs (lncRNAs) play various roles in HCC progression, but no research has focused on the expression pattern of microRNA clusters encoded in lncRNAs. The Ftx gene encodes a lncRNA which harbors 2 clusters of microRNAs in its introns, the miR-374b/421 cluster and the miR-545/374a cluster. To date, no research has focused on the role of the miR-545/374a and miR-374b/421 clusters in HBV-related HCC. In this study, 66 pairs of HBV-related HCC tissue and matched non-cancerous liver tissue specimens were analyzed for the expression of the Ftx microRNA clusters. Our results showed that the miR-545/374a cluster was upregulated in HBV-HCC tissue and significantly correlated with prognosis-related clinical features, including histological grade, metastasis and tumor capsule. Transfection studies with microRNA mimics and inhibitors revealed that miR-545/374a expression promoted in vitro cell proliferation, cell migration and invasion. The wild-type HBV-genome-containing plasmid or full-length HBx protein encoding plasmid was transfected into the Bel-7402 cell line and observed for their influence on miR-545/374a expression. We found that transfection of the HBV genome or HBx alone resulted in an increase in miR-545/374a expression. Next, by monitoring the expression of sera miR-545/374a before and after surgical tumor excision, we found serum miR-545/374a was tumor-derived and exhibited a sharp decrease 25 days after tumor excision. We also examined the gender-based difference in miR-545/374a expression among HCC patients and utilized microRNA target prediction software to find the targets of miR-545/374a. One of these targets, namely estrogen-related receptor gamma (ESRRG) was inversely correlated with miR-545 expression. In conclusion, the overexpression of miR-545/374a cluster located in the Ftx lncRNA is partially responsible for a poor prognosis, and monitoring sera levels of miR-545/374a may be a useful diagnostic marker for HCC.     

Development and validation of robust metabolism-related gene signature in the prognostic prediction of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumours worldwide. Given metabolic reprogramming in tumours was a crucial hallmark, several studies have demonstrated its value in the diagnostics and surveillance of malignant tumours. The present study aimed to identify a cluster of metabolism-related genes to construct a prediction model for the prognosis of HCC. Multiple cohorts of HCC cases (466 cases) from public datasets were included in the present analysis. (GEO cohort) After identifying a list of metabolism-related genes associated with prognosis, a risk score based on metabolism-related genes was formulated via the LASSO-Cox and LASSO-pcvl algorithms. According to the risk score, patients were stratified into low- and high-risk groups, and further analysis and validation were accordingly conducted. The results revealed that high-risk patients had a significantly worse 5-year overall survival (OS) than low-risk patients in the GEO cohort. (30.0% vs. 57.8%; hazard ratio [HR], 0.411; 95% confidence interval [95% CI], 0.302–0.651; p < 0.001) This observation was confirmed in the external TCGA-LIHC cohort. (34.5% vs. 54.4%; HR 0.452; 95% CI, 0.299–0.681; p < 0.001) To promote the predictive ability of the model, risk score, age, gender and tumour stage were integrated into a nomogram. According to the results of receiver operating characteristic curves and decision curves analysis, the nomogram score possessed a superior predictive ability than conventional factors, which indicate that the risk score combined with clinicopathological features was able to achieve a robust prediction for OS and improve the individualized clinical decision making of HCC patients. In conclusion, the metabolic genes related to OS were identified and developed a metabolism-based predictive model for HCC. Through a series of bioinformatics and statistical analyses, the predictive ability of the model was approved.     

Identification of a plasma proteomic signature to distinguish pediatric osteosarcoma from benign osteochondroma

Osteosarcoma (OS) is the most common malignant bone tumor in children. To identify a plasma proteomic signature that can detect OS, we used SELDI MS to perform proteomic profiling on plasma specimens from 29 OS and 20 age-matched osteochondroma (OC) patients. Nineteen statistically significant ion peaks that were differentially expressed in OS when compared with OC patients were identified (p < 0.001 and false discovery rate < 10%). Using the proteomic profiles, we constructed a multivariate 3-nearest neighbors classifier to distinguish OS from OC patients with a sensitivity of 97% and a specificity of 80% based on external leave-one-out crossvalidation. Permutation test showed that the classification result was statistically significant (p < 0.00005). One of the proteins (m/z 11 704) in the proteomic signature was identified as serum amyloid protein A (SAA) by PMF. The higher plasma level of SAA in OS patients was further validated by Western blotting when compared to that of osteochrondroma patients and normal subjects as reference. The classifier based on this plasma proteomic signature may be useful to differentiate malignant bone cancer from benign bone tumors and for early detection of OS in high-risk individuals.     

miR-101 is down-regulated by the hepatitis B virus x protein and induces aberrant DNA methylation by targeting DNA methyltransferase 3A

The hepatitis B virus x (HBx) protein has been implicated in HBV-related hepatocellular carcinoma (HCC) pathogenesis. However, whether HBx regulates miRNA expression that plays important roles in gene regulation during hepatocarcinogenesis remains unknown. The expression of microRNA-101 (miR-101) in HBV-related HCC tissues and HCC cells was evaluated by real-time PCR. The direct target of miR-101, DNA methyltransferase 3A (DNMT3A), was identified in silico and validated using a 3′-UTR reporter assay. miR-101 was functionally characterized in cells with transiently altered miR-101 expression. HBx expression was found to have a significant inverse correlation with miR-101 expression in HBx-expressing HepG2 compared to control HepG2 cells. miR-101 expression was frequently down-regulated in HBV-related HCC tissues compared to adjacent noncancerous hepatic tissues and had a significant inverse correlation with DNMT3A expression in HBV-related HCCs. Further characterization of miR-101 revealed that it negatively regulated DNA methylation partly through targeting DNMT3A. HBx-mediated miR-101 down-regulation and DNMT3A up-regulation supported the enhanced DNA methylation of several tumor-suppressor genes in HBx-expressing cells. Our studies demonstrating the deregulation of miR-101 expression by HBx may provide novel mechanistic insights into HBV-mediated hepatocarcinogenesis and identify a potential miRNA-based targeted approach for treating HBV-related HCC.     

Evaluation of changes in serum protein profiles during neoadjuvant chemotherapy in HER2‐positive breast cancer using an LC‐MALDI‐TOF/MS procedure

Comparison of protein profiles of sera acquired before and after preoperative chemotherapy for breast cancer may reveal tumor markers that could be used to monitor tumor response. In this study, we analyzed pre‐ and post‐chemotherapy protein profiles of sera from 39 HER2‐postive breast cancer patients (n=78 samples) who received 6 months of preoperative chemotherapy using LC‐MALDI‐TOF/MS technology. We detected qualitative and quantitative differences in pair‐wise comparison of pre‐ and post chemotherapy samples that were different in patients who achieved pathological complete response (pCR, n=21) compared with those with residual disease (n=18). We identified 2329 and 3152 peaks as differentially expressed in the pre‐chemotherapy samples of the responders and non‐responders. Comparison of matching pre‐ and post‐chemotherapy samples identified 34 (32 decreased, two increased) and 304 peaks (157 decreased, 147 increased) that significantly changed (p<0.01, false discovery rate ≤20%) after treatment in responders and non‐responders, respectively. The top 11 most significantly altered peptide peaks with the greatest change in intensity were positively identified. These corresponded to eight proteins including α‐2‐macroglobulin, complement 3, hemopexin, and serum amyloid P in the responder group and chains C and A of apolipoprotein A‐I, hemopexin precursor, complement C, and amyloid P component in the non‐responding groups. All proteins decreased after therapy, except chain C apolipoprotein A and hemopexin precursor that increased. These results suggest that changes in serum protein levels occur in response to chemotherapy and these changes partly appear different in patients who are highly sensitive to chemotherapy compared with those with lesser response.     

Leukocyte Telomere Length-Related rs621559 and rs398652 Genetic Variants Influence Risk of HBV-Related Hepatocellular Carcinoma

Recent genome-wide association studies (GWAS) have identified eleven leukocyte telomere length (LTL)-related single nucleotide polymorphisms (SNPs). Since LTL has been associated with risk of many malignancies, LTL-related SNPs may contribute to cancer susceptibility. To test this hypothesis in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), we genotyped these eleven LTL-related SNPs in a case-control set including 1186 HBV-related HCC cases, 508 chronic HBV carriers and 1308 healthy controls at the discovery stage. The associations of HCC risk with these SNPs were further confirmed in an independent case-control set. We found that 1p34.2 rs621559 and 14q21 rs398652 were significantly associated with HBV-related HCC risk (both P<0.005 after Bonferroni corrections). There was no significant difference of either rs621559 or rs398652 genotypes between chronic HBV carriers and healthy controls, demonstrating that the association was not due to predisposition to HBV infection. In the pooled analyses (1806 HBV-related HCC cases and 1954 controls), we observed a decreased HCC risk, 0.72-times, associated with the 1p34.2 rs621559 AA genotype compared to the GG genotype (P = 1.6×10⁻⁶). Additionally, there was an increased HCC risk, 1.27-fold, associated with the rs398652 GG genotype (P = 3.3×10⁻⁶). A statistical joint effect between the rs621559 GG and rs398652 GG genotypes may exist in elevating risk of HBV-related HCC. We show, for the first time, that rs398652 and rs621559 might be marker genetic variants for risk of HBV-related HCC in the Chinese population.     

Identification of novel serum peptides biomarkers for female breast cancer patients in Western China

This study aimed to identify novel serum peptides biomarkers for female breast cancer (BC) patients. We analyzed the serum proteomic profiling of 247 serum samples from 96 BC patients, 48 additional paired pre‐ and postoperative BC patients, 39 fibroadenoma patients as benign disease controls, and 64 healthy controls, using magnetic‐bead‐based separation followed by MALDI‐TOF MS. ClinProTools software identified 78 m/z peaks that differed among all analyzed groups, ten peaks were significantly different (P < 0.0001), with Peaks 1–6 upregulated and Peaks 7–10 downregulated in BC. Moreover, three peaks of ten (Peak 1, m/z: 2660.11; Peak 2, m/z: 1061.09; Peak 10, m/z: 1041.25) showed a tendency to return to healthy control values after surgery. And these three peptide biomarkers were identified as FGA605‐629, ITIH4 347–356, and APOA2 43–52. Methods used in this study could generate serum peptidome profiles of BC, and provide a new approach to identify potential biomarkers for diagnosis as well as prognosis of this malignancy.     

Assessing the utility of SELDI-TOF and model averaging for serum proteomic biomarker discovery

The SELDI-TOF technique was used to profile serum proteins from Type 1 diabetes (T1D) patients and healthy autoantibody-negative (AbN) controls. Univariate and multivariate analyses were performed to identify putative biomarkers for T1D and to assess the reproducibility of the SELDI technique. We found 146 protein/peptide peaks (581 total peaks discovered) in human serum showing statistical differences in expression levels between T1D patients and controls, with 84% of these peaks showing technical replication. Because individual proteins did not offer great power for disease prediction, we used our model averaging approach that combines the information from multiple multivariate models to accurately classify T1D and control subjects (88.9% specificity and 90.0% sensitivity). Analyses of a test subset of the data showed less accuracy (82.8% specificity and 76.2% sensitivity), although the results are still positive. Unfortunately, no multivariate model could be replicated using the same samples. This first attempt of high throughput analyses of the human serum proteome in T1D patients suggests that model averaging is a viable method for developing biomarkers; however, the reproducibility of SELDI-TOF is currently not sufficient to be used for classification of complex diseases like T1D.     

The application of atmospheric pressure matrix-assisted laser desorption/ionization to the analysis of long-term cryopreserved serum peptidome

Although most time-of-flight (TOF) mass spectrometers come equipped with vacuum matrix-assisted laser desorption/ionization (MALDI) sources, the atmospheric pressure MALDI (API–MALDI) source is an attractive option because of its ability to be coupled to a wide range of analyzers. This article describes the use of an API–MALDI source coupled to a TOF mass spectrometer for evaluation of the effects of medium- and long-term storage on peptidomic profiles of cryopreserved serum samples from healthy women. Peptides were purified using superparamagnetic beads either from fresh sera or after serum storage at −80 °C for 18 months or at −20 °C for 8 years. Data were preprocessed using newly developed bioinformatic tools and then were subjected to statistical analysis and class prediction. The analyses showed a dramatic effect of storage on the abundance of several peptides such as fibrinopeptides A and B, complement fractions, bradykinin, and clusterin, indicated by other authors as disease biomarkers. Most of these results were confirmed by shadow clustering analysis, able to classify each sample in the correct group. In addition to demonstrating the suitability of the API–MALDI technique for peptidome profiling studies, our data are of relevance for retrospective studies that involve frozen sera stored for many years in biobanks.     

Using proteomic approach to identify tumor-associated antigens as markers in hepatocellular carcinoma

Many studies have demonstrated that intracellular proteins, which are involved in carcinogenesis, can provoke autoantibody responses. Therefore, autoantibodies can be used clinically for cancer detection and for proteomic analysis in identification of tumor-associated antigens (TAAs) that are potentially involved in malignant transformation. Liver cancer, especially hepatocellular carcinoma (HCC), is one of the most common tumors in the world. The majority of people with HCC will die within 1 year of its detection. This high case fatality rate can partially be attributed to a lack of diagnostic methods that allow early detection. In the present study, sera from 20 patients with HCC, 30 patients with chronic hepatitis (CH), and 30 patients with liver cirrhosis (LC) as well as sera from 10 normal individuals were used in a proteomic approach to identify HCC-related TAAs. Thirty-four immunoreactive protein spots were excised from the two-dimensional gel electrophoresis (2DE), digested with trypsin, and subsequently analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Of 34 immunoreactive protein spots, 28 were identified. Seventeen of them were not only reactive with serum antibodies in HCC but also with antibodies in pre-HCC conditions, and 11 were only reactive with serum antibodies in HCC but not with antibodies in pre-HCC conditions. In the subsequent analysis, two representative proteins, HSP60 and HSP70, were selected as examples for the validation purpose. The results from immunoassay were consistent with the data from proteomic analysis, supporting our hypothesis that proteins identified with autoantibodies that have been present in precancer conditions may be not appropriate to use as TAA markers in cancer detection.     

Serum protein profiling in mice: identification of Factor XIIIa as a potential biomarker for muscular dystrophy

Protein profiling in blood serum by fractionation and MS analysis has been applied in mice to assess its applicability as a fast, economical alternative to current DNA and RNA analyses for diagnosis of neuromuscular disorders. Mass spectra of peptides and proteins were generated using serum from dystrophin-deficient mdx and control mice by WCX ClinProt bead fractionation, followed by MALDI-MS. Double cross-validatory linear discriminant and logistic regression data analysis methods were compared with a new Bayesian logistic regression method. These were evaluated on their ability to discriminate between healthy and dystrophic samples, and to identify the discriminatory peaks in the mass spectra. All three approaches classified the spectra with comparable misclassification rates (between 18.4 and 20.6%), with much overlap between the differential peaks identified between the methods. The differential peak pattern from the Bayesian method was sparser and easier to interpret than from the other two methods, without compromising classifying strength. One of the two main differentiating peaks at m/z 3908 was identified as an N-terminal peptide of coagulation Factor XIIIa, previously identified in human serum. This work underlines the translational aspect of serum protein profiling in mice and supports a further study with serum from patients with neuromuscular disorders.