The complement system is crucial for maintaining immunological homeostasis in the liver, playing a significant role in both innate and adaptive immune responses. Dysregulation of this system is closely linked to the pathogenesis of various liver diseases. Modulating the complement system can affect the progression of these conditions. To provide insights into treating liver injury by targeting the regulation of the complement system, we conducted a comprehensive search of major biomedical databases, including MEDLINE, PubMed, EMBASE, and Web of Science, to identify articles on complement and liver injury and reviewed the functions and mechanisms of the complement system in liver injury.

• Complement system
• Liver injury
• Immune homeostasis
• Pathogenesis
• Review

As a main producer of complement, the environment in the liver is greatly affected by the complement system. Although the complement system is considered to have the ability of nonself discrimination, remarkable studies have revealed the tight association between improper complement activation in tumour initiation and progression. As complement activation predominantly occurs within the liver, the protumourigenic role of the complement system may contribute to the development of hepatocellular carcinoma (HCC). Improvement in the understanding of the molecular targets involved in complement-mediated tumour development, metastasis, and tumour-promoting inflammation in HCC would certainly aid in the development of better treatments. This minireview is focused on recent findings of the protumourigenic role of the complement system in HCC.

• Humans
• Carcinoma, Hepatocellular/pathology
• Liver Neoplasms/pathology
• Inflammation

Viral hepatitis is a major global public health problem that affects hundreds of millions of people and is associated with significant morbidity and mortality. Five biologically unrelated hepatotropic viruses account for the majority of the global burden of viral hepatitis, including hepatitis A virus (HAV), hepatitis B virus (HBV), hepatitis C virus (HCV), hepatitis D virus (HDV), and hepatitis E virus (HEV). Omics is defined as the comprehensive study of the functions, relationships and roles of various types of molecules in biological cells. The multi-omics analysis has been proposed and considered key to advancing clinical precision medicine, mainly including genomics, transcriptomics and proteomics, metabolomics. Overall, the applications of multi-omics can show the origin of hepatitis viruses, explore the diagnostic and prognostics biomarkers and screen out the therapeutic targets for viral hepatitis and related diseases. To better understand the pathogenesis of viral hepatitis and related diseases, comprehensive multi-omics analysis has been widely carried out. This review mainly summarizes the applications of multi-omics in different types of viral hepatitis and related diseases, aiming to provide new insight into these diseases.

• HCC and COVID-19
• complement activation
• complement proteins
• complement-based therapeutics
• hepatocellular carcinoma
• immunotherapy
• inflammatory factors
• prognostic markers

• P30 DK078392 NIDDK NIH HHS

• Complement
• Immunology
• Liver cancer
• Oncology

• Animals
• Carcinoma, Hepatocellular/genetics
• Carcinoma, Hepatocellular/metabolism
• Carcinoma, Hepatocellular/pathology
• Complement Factor H/deficiency
• Complement Factor H/genetics
• Complement Factor H/metabolism
• Gene Expression Regulation, Neoplastic
• Hereditary Complement Deficiency Diseases/genetics
• Hereditary Complement Deficiency Diseases/metabolism
• Hereditary Complement Deficiency Diseases/pathology
• Humans
• Kidney Diseases/genetics
• Kidney Diseases/metabolism
• Kidney Diseases/pathology
• Liver/metabolism
• Liver/pathology
• Liver Neoplasms/genetics
• Liver Neoplasms/metabolism
• Liver Neoplasms/pathology
• Mice
• Mice, Knockout
• Neoplasm Proteins/deficiency
• Neoplasm Proteins/metabolism

• P30 CA046934 NCI NIH HHS
• R01 CA236222 NCI NIH HHS
• S10 OD023485 NIH HHS
• UL1 TR001082 NCATS NIH HHS
• Wellcome Trust
• 212252/Z/18/Z Wellcome Trust
• R01 DK113586 NIDDK NIH HHS
• R01 DK076690 NIDDK NIH HHS
• National Institutes of Health
• Wellcome

The complement system bridges innate and adaptive immunity against microbial infections, with viral infection being a major trigger. Activation of the classical, alternative, and lectin pathways have been reported in chronic hepatitis C virus (HCV) infection and/or cryoglobulinemia. HCV infection leads to dysregulation of complement-mediated immune responses. Clinical and experimental evidence support involvement of complement in intra- and extrahepatic manifestations of HCV infection, such as liver fibrosis and type II cryoglobulinemia. In this review, we summarize studies that have investigated the interplay between HCV and the complement system to establish chronic infection and autoimmunity, as well as the association between HCV pathogenesis and abnormal complement profiles. Several unanswered questions are highlighted which suggest additional informative lines of investigation.

• C1q
• complement
• gC1qR
• hepatitis C virus
• liver
• mixed cryoglobulinemia

• Anaphylatoxin
• C3a
• C5a
• Cancer
• Complement system
• Immunotherapy

• Biomedicine
• Cancer biomarker discovery
• Hepatocellular carcinoma
• LC-MS/MS
• Liver cirrhosis
• MRM

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.

• biomarker
• clinical chemistry
• genotyping
• hepatitis C virus
• serology
• viral load

• A1BG
• CIN III
• HPV
• cervical cancer
• complement C3

• Biomarkers/blood
• Humans
• Mass Spectrometry
• Peptides/blood
• Proteomics

• Chronic hepatitis C;
• Complement;
• Fibronectin
• Fibrosis;
• Inflammation;
• Stellate cell;

• Adult
• Africa, Western
• Apolipoprotein A-I/blood
• Apolipoprotein A-I/metabolism
• Biomarkers, Tumor/blood
• Biomarkers, Tumor/metabolism
• Carcinoma, Hepatocellular/blood
• Carcinoma, Hepatocellular/complications
• Carcinoma, Hepatocellular/diagnosis
• Carcinoma, Hepatocellular/metabolism
• Case-Control Studies
• Complement C3/metabolism
• Enzyme-Linked Immunosorbent Assay
• Female
• Hemopexin/metabolism
• Hepatitis B, Chronic/complications
• Humans
• Liver Cirrhosis/blood
• Liver Cirrhosis/complications
• Liver Cirrhosis/metabolism
• Liver Neoplasms/blood
• Liver Neoplasms/complications
• Liver Neoplasms/diagnosis
• Liver Neoplasms/metabolism
• Male
• Mass Spectrometry
• Middle Aged
• Proteome
• Proteomics/methods
• ROC Curve
• Reproducibility of Results
• Young Adult
• alpha 1-Antitrypsin/blood
• alpha 1-Antitrypsin/metabolism

• 084655 Wellcome Trust
• Medical Research Council
• N02CP40521 NCI NIH HHS

• biomarker
• osteoarthritis
• proteomics
• surface-enhanced laser desorption/ionization (SELDI)

• Biomarkers/blood
• Blood Proteins/analysis
• Colonic Neoplasms/blood
• Colonic Neoplasms/diagnosis
• Cryopreservation
• Electrophoresis, Gel, Two-Dimensional
• Hot Temperature
• Humans
• Nitrogen
• Principal Component Analysis
• Protein Stability
• Proteomics/standards
• Reproducibility of Results
• Spectrometry, Mass, Electrospray Ionization
• Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization

Early serum detection is of critical importance to improve the therapy for hepatocellular carcinoma (HCC), one of the most deadly cancers. Hepatitis infection is a leading cause of HCC.

In the present study, we collected total serum samples with informed consent from 80 HCC patients with HBV (+)/cirrhosis (+), 80 patients with benign diseases (50 liver cirrhosis patients and 30 HBV-infected patients) and 60 healthy controls. Analysis was by using surface-enhanced laser desorption/ionisation-time-of-flight mass spectroscopy (SELDI-TOF-MS) to find new serum markers of HCC. SELDI peaks were isolated by SDS–PAGE, identified by LC-MS/MS and validated by immunohistochemistry (IHC) in liver tissues. Migration and invasion assay were performed to test the ability of cell migration and invasion in vitro.

SELDI-TOF-MS revealed a band at 7777 M/Z in the serum samples from HCC patients but not from healthy controls or patients with benign diseases. The protein (7777.27 M/Z) in the proteomic signature was identified as C-C motif chemokine 15 (CCL15) by peptide mass fingerprinting. A significant increase in serum CCL15 was detected in HCC patients. Functional analysis showed that HCC cell expressed CCL15, which in turn promoted HCC cell migration and invasion.

CCL15 may be a specific proteomic biomarker of HCC, which has an important role in tumorigenesis and tumour invasion.

• Animals
• Complement System Proteins/immunology
• Humans
• Peptides/immunology
• Receptors, Complement/immunology

• PG/09/018/25279 British Heart Foundation

• 2-Acetylamino fluorine
• 2DE/LC–MS/MS
• Complement C3
• Diethyl nitrosamine
• Hepatotumorogenesis
• Western blot

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%.

• Liver Cancer. Hepatitis C Virus. Urine. Proteins. Biomarkers

Discovering new biomarkers has a great role in improving early diagnosis of Hepatocellular carcinoma (HCC). The experimental determination of biomarkers needs a lot of time and money. This motivates this work to use in-silico prediction of biomarkers to reduce the number of experiments required for detecting new ones. This is achieved by extracting the most representative genes in microarrays of HCC.

In this work, we provide a method for extracting the differential expressed genes, up regulated ones, that can be considered candidate biomarkers in high throughput microarrays of HCC. We examine the power of several gene selection methods (such as Pearson’s correlation coefficient, Cosine coefficient, Euclidean distance, Mutual information and Entropy with different estimators) in selecting informative genes. A biological interpretation of the highly ranked genes is done using KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, ENTREZ and DAVID (Database for Annotation, Visualization, and Integrated Discovery) databases. The top ten genes selected using Pearson’s correlation coefficient and Cosine coefficient contained six genes that have been implicated in cancer (often multiple cancers) genesis in previous studies. A fewer number of genes were obtained by the other methods (4 genes using Mutual information, 3genes using Euclidean distance and only one gene using Entropy). A better result was obtained by the utilization of a hybrid approach based on intersecting the highly ranked genes in the output of all investigated methods. This hybrid combination yielded seven genes (2 genes for HCC and 5 genes in different types of cancer) in the top ten genes of the list of intersected genes.

To strengthen the effectiveness of the univariate selection methods, we propose a hybrid approach by intersecting several of these methods in a cascaded manner. This approach surpasses all of univariate selection methods when used individually according to biological interpretation and the examination of gene expression signal profiles.

AIM: To establish a serum protein pattern model for diagnosing hepatocellular carcinoma (HCC) by using the surface-enhanced laser desorption ionization time-of-fligh mass spectrometry (SELDI-TOF-MS), and to evaluate the value of this model in predicting the effect of interventional treatment for HCC.

METHODS: Serum samples collected from patients with HCC (n = 60) and healthy people (n = 60) were used for SELDI-TOF-MS on CM10 chips. The proteomic spectra were analyzed by using the Biomarker Wizard software. The diagnosis model was established by using the Biomarker Pattern software.

RESULTS: Three significantly different protein peaks were found in serum samples between HCC patients and healthy controls. A protein peak at 6 992 Da showed higher expression and the other two protein peaks (4 182 Da, 5 710 Da) showed lower expression in HCC patients than in healthy people. The diagnostic model containing these three candidate biomarkers could distinguish patients with HCC from healthy controls with a sensitivity of 93.3% (28/30), a specificity of 90.0% (27/30), an accuracy of 91.7% (55/60), and a Youden index value of 0.833. The protein peak at 4 182 Da was significantly decreased one month after interventional treatment in HCC patients (P < 0.05).

CONCLUSION: The diagnostic model developed by using SELDI-TOF-MS allows efficiently identifying patients with HCC and may play a valuable role in the diagnosis of HCC. The protein peak at 4 182 Da is helpful for the evaluation of interventional curative effect in HCC patients.

• Hepatocellular carcinoma
• Protein chip
• Surface-enhanced laser desorption ionization time-of-fligh mass spectrometry
• Interventional treatment

Background. To explore the application of serum proteomic patterns for the preoperative detection of regional lymph node involvement of colorectal cancer (CRC). Methods. Serum samples were applied to immobilized metal affinity capture ProteinChip to generate mass spectra by Surface-Enhanced Laser Desorption/ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS). Proteomic spectra of serum samples from 70 node-positive CRC patients and 75 age- and gender-matched node-negative CRC patients were employed as a training set, and a classification tree was generated by using Biomarker Pattern Software package. The validity of the classification tree was then challenged with a blind test set including another 65 CRC patients. Results. The software identified an average of 46 mass peaks/spectrum and 5 of the identified peaks at m/z 3,104, 3,781, 5,867, 7,970, and 9,290 were used to construct the classification tree. The classification tree separated effectively node-positive CRC patients from node-negative CRC patients, achieving a sensitivity of 94.29% and a specificity of 100.00%. The blind test challenged the model independently with a sensitivity of 91.43% a specificity of 96.67%. Conclusions. The results indicate that SELDI-TOF-MS can correctly distinguish node-positive CRC patients from node-negative ones and show great potential for preoperative screening for regional lymph node involvement of CRC.

• Amino Acid Sequence
• Biomarkers, Tumor/analysis
• Biomarkers, Tumor/genetics
• Blood Proteins/chemistry
• Blood Proteins/genetics
• Breast Neoplasms/blood
• Breast Neoplasms/genetics
• Breast Neoplasms/mortality
• Breast Neoplasms/pathology
• Chromatography, High Pressure Liquid
• Complement C3a/genetics
• Female
• Gene Expression Profiling
• Genetic Vectors
• Glyceraldehyde 3-Phosphate Dehydrogenase (NADP+)/chemistry
• Glyceraldehyde 3-Phosphate Dehydrogenase (NADP+)/genetics
• Humans
• Mass Spectrometry
• Molecular Sequence Data
• Neoplasm Staging
• Oligonucleotide Array Sequence Analysis
• Peptide Fragments/chemistry
• Reference Values
• Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
• Survival Rate

Proteinchip profiling is a powerful and innovative proteomic technology for the discovery of biomarkers and the development of diagnostic/prognostic assays. On the basis of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), Ciphergen’s proteinchip system offers a single, unified, and high throughput platform for a multitude of proteomic research applications. Proteins are the major functional components of the cell. The study of proteomics helps to better understand the mechanism of a disease. Remarkable findings in disease biomarkers have shed light on the early diagnosis, monitoring, and prognosis of various diseases, especially for cancer. In this paper, the development and technology of SELDI-TOF MS are introduced. The research progress and encouraging research results in malignancies, infectious diseases, neurological diseases, and diabetes mellitus using SELDI-TOF MS are reviewed. This paper concludes by evaluating the pros and cons, and the future perspectives are also expounded.

• Animals
• Computational Biology
• Humans
• Lasers
• Mass Spectrometry/methods
• Protein Array Analysis/methods
• Proteomics
• Surface Properties

Hepatocellular carcinoma (HCC) is the third most common cause of cancer mortality worldwide. Although most HCCs seem to originate from the accumulation of genetic abnormalities induced by various risk factors, underlying mechanisms of hepatocarcinogenesis remain unclear. Long-term survival of HCC patients is also poor, partly due to HCC recurrence. Although serum alpha-fetoprotein (AFP) level is a useful marker for the detection and monitoring of HCC, AFP levels may remain normal in the patients even with advanced HCC. To identify useful biomarkers for HCC, many studies have been conducted on molecular events such as genetic and epigenetic alterations, and gene expression. This review summarizes recent studies of potential molecular markers for diagnosis and monitoring metastasis or recurrence of HCC.

Hepatitis E, caused by the hepatitis E virus (HEV), is endemic to developing countries where it manifests as waterborne outbreaks and sporadic cases. Though generally self-limited with a low mortality rate, some cases progress to fulminant hepatic failure (FHF) with high mortality. With no identified predictive or diagnostic markers, the events leading to disease exacerbation are not known. Our aim is to use proteomic tools to identify biomarkers of acute and fulminant hepatitis E.

We analyzed proteins in the plasma and urine of hepatitis E patients and healthy controls by two-dimensional Differential Imaging Gel Electrophoresis (DIGE) and mass spectrometry, and identified over 30 proteins to be differentially expressed during acute hepatitis E. The levels of one plasma protein, transthyretin, and one urine protein, alpha-1-microglobulin (α1m), were then quantitated by enzyme immunoassay (EIA) in clinical samples from a larger group of patients and controls. The results showed decreased plasma transthyretin levels (p < 0.005) and increased urine α1m levels (p < 0.001) in acute hepatitis E patients, compared to healthy controls. Preliminary results also showed lower urine zinc alpha glycoprotein levels in fulminant hepatitis E compared to acute disease; this remains to be confirmed with more fulminant cases.

Our results demonstrate the utility of characterizing plasma and urine proteomes for signatures of the host response to HEV infection. We predict that plasma transthyretin and urine α1m could be reliable biomarkers of acute hepatitis E. Besides the utility of this approach to biomarker discovery, proteome-level changes in human biofluids would also guide towards a better understanding of host-virus interaction and disease.