Viral exposure signature for early detection of hepatocellular carcinoma

Abstract

A viral exposure signature (VES) that can identify early, presymptomatic hepatocellular carcinoma (HCC) in patients at risk is described. The VES was developed using serological analysis and synthetic virome technology to identify unique viral peptide epitopes corresponding to 61 viruses. Methods of using the VES to identify subjects with early (presymptomatic) HCC are described.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of U.S. Provisional Application No. 62 / 914,138, filed on October 11, 2019, which is incorporated herein by reference in its entirety. Technical Field

[0003] The present disclosure relates to viral exposure signatures and their use for identifying subjects with early-stage (presymptomatic) hepatocellular carcinoma.

[0004] Government Support Statement

[0005] This invention was made with government support under Grant No. Z01-BC010313 awarded by the National Institutes of Health. The government has certain rights in this invention. Background Art

[0006] Hepatocellular carcinoma (HCC) is considered a virus-related malignancy, with hepatitis B and C viruses (HCV and HBV) being the main causes (Farazi et al., Nat Rev Cancer 2006; 6: 674-687). Viral hepatitis leads to inflammation and chronic liver disease (CLD), which may lead to fibrosis, cirrhosis, and ultimately HCC. Although chronic HBV or HCV carriers are at increased risk of HCC, the risk varies from individual to individual, and not all patients with liver disease develop liver cancer (Arzumanyan et al., Nat Rev Cancer 2013; 13: 123-135). An effective strategy for preventing HCC is to eliminate the causative factors. However, while direct-acting antiviral (DDA) therapy is highly effective in eliminating HCV infection, it reduces but does not completely eliminate HCC risk (Janjua et al., J Hepatol 2017;66:504-513; Carrat et al., Lancet 2019;393:1453-1464). Similarly, HBV vaccination, introduced in the early 1980s, has successfully reduced HBV carriers significantly but only modestly reduced the burden of HCC in HBV-endemic areas (Chang et al., Gastroenterology 2016;151:472-480). Puzzlingly, despite decades of success in controlling HBV infection as well as HCV infection in HBV-endemic areas, global HCC incidence and mortality have continued to rise since the 1990s (Liu et al., J Hepatol 2019;70:674-683). Changing trends in etiology (alcohol and non-alcohol / non-viral-related liver disease) may contribute to the observed increases. Therefore, in addition to cancer prevention, early detection is a key area of ​​research to prevent deaths caused by HCC. Currently, medical guidelines recommend twice-yearly monitoring using ultrasound (with or without alpha-fetoprotein (AFP)) for individuals with chronic liver disease (e.g., cirrhosis) (Sherman et al., Hepatology 2012; 56: 793-796). However, these practices have produced mixed results on whether early detection of HCC is effective and whether it can provide survival benefits (Tzartzeva et al., Gastroenterology 2018; 154: 1706-1718; Moon et al., Gastroenterology 2018; 155: 1128-1139; Sherman et al., Hepatology 1995; 22: 432-438). It is worth noting that most HCC patients are still diagnosed at an advanced stage, which excludes them from receiving potentially curative therapies, resulting in poor survival. Therefore, there is an unmet need to implement an effective biomarker-guided early cancer detection monitoring program. Summary of the invention

[0007] This article describes a viral exposure signature (VES) that can be used to identify subjects with early HCC, particularly presymptomatic HCC. The VES is based on the presence or absence of antibodies to a specific viral strain in the subject. For example, the detection of the VES in a subject can be used to guide treatment and disease monitoring decisions.

[0008] Provided herein is a method for identifying a subject with early HCC. In some embodiments, the method includes detecting the presence or absence of antibodies to multiple viruses in a sample obtained from the subject; determining the presence of a virus exposure feature (VES) in a sample obtained from the subject; and when the VES is present, identifying the subject with a risk of HCC. In some embodiments, the multiple viruses include at least 10, at least 20, at least 30, at least 40, at least 50, or at least 60 of the viruses listed in Table 5A. In some embodiments, the multiple viruses include or consist of 61 viruses listed in Table 5A or 31 viruses listed in Table 6.

[0009] In some embodiments, the presence of VES is determined by recognizing antibodies against one or more of the following: hepatitis C virus (HCV) genotype 3b, Tr-Kj isolate; HCV genotype 1b, Taiwan isolate; HCV genotype 1a, 1 isolate; human cytomegalovirus, AD169 strain; HCV genotype 6g, JK046 isolate; HCV genotype 1b, BK isolate; HCV genotype 1c, HC-G9 isolate; HCV genotype 1b, HC-J4 strain; HCV genotype 4a, ED4 isolate. 3 isolates; hepatitis D virus; HCV genotype 5a, isolate EUH1480; human cytomegalovirus; Crimean-Congo hemorrhagic fever virus, Nigeria / IbAr10200 / 1970 strain; HCV genotype 1b, isolate HC-J1; influenza A virus, A / USSR / 90 / 1977H1N1 strain; influenza A virus, A / Bangkok / 1 / 1979H3N2 strain; HCV genotype 1c, isolate India; and Chapare virus, isolate Human / Bolivia / 810419 / 2003.

[0010] In some embodiments, the presence of VES is determined by the absence of detection of one or more of the following: Epstein-Barr virus virus, strain B95-8; human rhinovirus 23; HCMV, Towne strain; human herpesvirus 2 (HHV-2), strain HG52; human herpesvirus 3; varicella-zoster virus, strain Dumas; rhesus monkey herpesvirus 16; human adenovirus C serotype 2; human astrovirus-1; human respiratory syncytial virus; human herpesvirus 6B, strain Z29; human herpesvirus 7, strain JI; human rhinovirus 14; Lordsdale virus, strain GII / human / UK / Lordsdale / 1993; human herpesvirus 1, strain KOS; human metapneumovirus, strain CAN97-83; coxsackievirus A16, strain G-10; Epstein-Barr virus, strain AG876; vaccinia virus; human herpesvirus 1, strain 17; human adenovirus E serotype 4; human adenovirus F serotype 40; Tanapox virus; human adenovirus C serotype Type 5; rhinovirus B; human herpesvirus 8; human herpesvirus 6A, Uganda-1102; human rhinovirus A serotype 89, 41467-Gallo strain; norovirus MD145, GII / human / USA / MD145-12 / 1987 strain; molluscum contagiosum virus subtype 1; vaccinia virus, Copenhagen strain; poliovirus type 1, Sabin strain; aphthous ulcer virus; HHV-2, 33 3 strains; hepatitis B virus; Epstein-Barr virus, GD1; human parainfluenza 3 virus, Wash / 47885 / 57 strain; HHV-2; human enterovirus 71, BrCr strain; human herpesvirus 6A, GS strain; simian herpesvirus 1; influenza B virus, B / Yamagata / 16 / 1988 strain; and influenza A virus, A / Philippines / 2 / 1982H3N2 strain.

[0011] In other embodiments, a method for identifying a subject with early HCC comprises (i) detecting the presence or absence of antibodies specific for a plurality of viruses in a sample obtained from the subject, wherein the plurality of viruses comprises hepatitis C virus (HCV) genotype 3b, Tr-Kj isolate; HCV genotype 1b, Taiwan isolate; HCV genotype 1a, 1 isolate; human cytomegalovirus (HCMV) AD169 strain; HCV genotype 6g, JK046 isolate; Epstein-Barr virus (EBV), B95-8 strain; human rhinovirus 23; HCMV Towne strain; HCV genotype 1b, BK isolate; and human herpes virus 2 (HHV-2), HG52 strain; and (ii) identifying the subject as being at risk for developing HCC when: (a) antibodies specific for HCV genotype 3b, Tr-Kj isolate; HCV genotype 1b, Taiwan isolate; HCV genotype 1a, 1 isolate; HCMV AD169 strain; HCV genotype 6g, JK046 isolate; and / or HCV genotype 1b, BK isolate have specific antibodies; and / or (b) antibodies specific to EBV, B95-8 strain; human rhinovirus 23; HCMV Towne strain; and / or HHV-2, HG52 strain were not detected in the sample.

[0012] In some embodiments, the sample is a blood or serum sample.

[0013] In some embodiments, the antibodies are detected by phage immunoprecipitation, immunoblotting, or enzyme-linked immunosorbent assay.

[0014] In some embodiments, the method further includes administering an appropriate therapy for treating HCC or providing an appropriate procedure (e.g., surgery). In some embodiments, the method further includes performing a liver transplant on a subject with early HCC. In other examples, the method further includes performing a liver resection on a subject with early HCC, with or without radiofrequency ablation (RFA). In some embodiments, if the subject is also positive for HBV or HCV, an antiviral drug is administered to the subject.

[0015] In some embodiments, the method further comprises active diagnostic monitoring of the subject with early HCC. For example, ultrasound, contrast-enhanced computed tomography (CT) and / or magnetic resonance imaging (MRI) can be used to regularly monitor the subject, for example, every 3 months or every 6 months.

[0016] Also provided is a phage display library expressing a unique peptide epitope from each virus listed in Table 5A or Table 6. In some embodiments, the phage display library expresses peptides of SEQ ID NO: 1-61 or a subset thereof. In some embodiments, the phage display library expresses peptides of SEQ ID NO: 1-102 or a subset thereof. In other examples, the phage display library expresses peptides of SEQ ID NO: 62-102 or a subset thereof.

[0017] Further provided is an array comprising unique peptide epitopes from each virus listed in Table 5A or Table 6. In some embodiments, the unique peptide epitopes comprise peptides of SEQ ID NOs: 1-61 (shown in Table 5B), peptides of SEQ ID NOs: 62-102 (shown in Table 3B), or SEQ ID NOs: 1-102.

[0018] The foregoing and other objects and features of the present disclosure will become more apparent from the following detailed description, which proceeds with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figures 1A-1E : Abundance of viruses in serum and frequency of infection spectrum. Figure 1A )Schematic diagram of the NCI-UMD cohort screening, including 899 serum samples tested by VirScan and 849 matched buffy coat or cheek swab samples tested by genome-wide association study (GWAS), and combined analysis in the cohorts: population controls (PC, n=412), high-risk chronic liver disease cases (HR, n=337), and hepatocellular carcinoma cases (HCC, n=150); VES was validated in the prospective NIDDK cohort with NIDDK-HR (n=129) and NIDDK-HCC (n=44). ( Figure 1B ) shows a histogram of VirScan sequencing reads with an average coverage accuracy of 0.93. ( Figure 1C ) Rarefaction plot showing the abundance of viral species detected in PC, HR, and HCC groups. Figure 1D ) Rain cloud plot showing the viral species of each individual among the population. From left to right, each comprehensive box plot shows: minimum, first quantile, mean, third quantile and maximum value. ( Figure 1E ) Left: Bar graph showing the percentage of prevalent virus infection in all samples. Right: Dot plot showing the corresponding number of unique epitopes in each sample. Each dot represents the number of unique epitopes in an individual. The blue bar on the dot plot represents the mean.

[0020] Figure 2A-2C : Comparison of VirScan with medical charts on antigenicity of HCV1b and HIV co-infecting viruses. Figure 2A ) Contingency matrix comparing HCV, HBV, and HIV testing using VirScan with viral detection laboratory tests reported in the patient's medical chart. To calculate binary classification test statistics, clinical results were considered true values ​​and VirScan results were considered predicted values. ( Figure 2B )Left: Heat map showing HCV proteome enrichment between PC, HR, and HCC groups. Each row represents a significant peptide tile. Each column is a sample. The colored bar on the left side of the inset shows the proteome location of the tiled peptide (green). The first colored bar at the top of the inset represents the sample group in the PC, HR, and HCC groups. The second bar at the top is HCV species positive based on VirScan data (HCV species +). The intensity of each cell corresponds to the scale-log10 (p value) measure of the enrichment significance of the peptide in the sample (larger values ​​indicate stronger antibody responses). Right: A bar graph showing the B cell epitope prediction score for each peptide. ( Figure 2C ) represents a bar graph of co-infecting virus status in HIV-positive (HIV+) versus HIV-negative (HIV-) cases. Asterisks indicate a false discovery rate of less than 0.05.

[0021] Figures 3A-3E :Composition of VES associated with HCC. Figure 3A )Identification of VES using the Xgboost machine learning approach. Flowchart showing the training set and 10X cross validation set for comparing viral profiles in HCC relative to PC. Scoring results for predicted VES scores for each sample between PC, HR, and HCC are shown. Figure 3B ) Gradient boosting plot showing the area under the curve (AUC) values ​​for the training set and the 10X cross validation set. The vertical line indicates that gradient boosting was stopped at epoch 108 to avoid overfitting. ( Figure 3C ) shows a bar graph comparing 61-VES identified by using Xgboost in the NCI-UMD cohort for HCC versus PC. ( Figure 3D ) Violin plot showing the predicted VES score between PC, HR and HCC groups. (****P<0.0001, two-tailed p value in Mann Whitney test). ( Figure 3E ) Phylogenetic analysis of 61 virus strains produced eight clear branches.

[0022] Figures 4A-4H : To determine the predictive accuracy of VES and its association with clinical outcomes. Figure 4A ) Receiver operating characteristic curve (ROC) estimates for the NCI-UMD cohort at HCC diagnosis. The figure shows the AUC estimates for the 61-VES at HCC diagnosis (PC, n=412; HR, n=337; HCC, n=150). ( Figure 4B) As listed below, the VES levels of the NCI-UMD cohort are low and high. The dashed line indicates that less than 0.5 is a low VES level. Low and high VES levels are defined by greater than 0.5 VES levels (with the median greater than 0.5 characteristic levels as delimiters). ( Figure 4C ) Kaplan Meier (KM) plot survival curves for the NCI-UMD cohort using either 61-VES. ( Figure 4D , 4E ) Receiver operating characteristic curve (ROC) estimates in the NIDDK validation cohort for prediction of HCC at diagnosis and baseline. The figure shows the area under the curve for 61-VES and clinical variables AFP at HCC diagnosis (NIDDK-HR2, n=106; NIDDK-HCC, n=44) and baseline (NIDDK-HR1, n=129; NIDDK-HCC, n=44). ( Figure 4F ) Time-dependent AUC showing VES performance at landmark time points from 1 to 10 years relative to baseline. Figure 4G ) Boxplot showing the relationship between 61-VES and clinical diagnosis in the NIDDK validation cohort at different follow-up (F / U) time points. ( Figure 4H ) AUC values ​​corresponding to predictions based on clinical indicators based on patient charts compared with predictions based on VES and predictions based on a combination of clinical and VES for the NIDDK cohort at baseline.

[0023] Figures 5A-5E : VirScan reproducibility and viral composition at the DNA, RNA virus level and viral family level. Figure 5A ) shows the distribution of reproducibility threshold - log10 (p value). Histogram of reproducibility threshold frequency - log10 (p value). The distribution mode is about 2.358. ( Figure 5B ) Example of experimental replication in VirScan, the lower panel shows the background signal of the blank PBS sample and the hits of the serum sample (upper panel) with a significant -log10 (P value) exceeding 2.358. Figure 5C ) Pie chart showing DNA and RNA viral composition before and after immunoprecipitation in VirScan (as library input and Phage-IP, respectively). Figure 5D ) Stacked bar graph showing the phylogenetic composition of common viral taxa (0.1% abundance) at the viral family level between PC, HR, and HCC. ( Figure 5E ) The figure includes details on participants excluded from initial enrollment, sample allocation with specified criteria, QC, and final data analysis.

[0024] Figure 6A-6B : Expanded information on the composition of viral signatures in the study population. Fig. 6A) Heatmap showing hierarchical clustering (hCluster) of samples between PC, HR, and HCC with different viral signatures. The 17 viruses listed showed a fold change greater than 2 in the PC and HCC ANOVA test with FDR<0.05. The bottom bar shows the scaled density signal. ( Figure 6B ) Histogram showing the most different viral species (sp) and strains in HCC compared with PC.

[0025] Figures 7A-7C :Quality control of GWAS studies. Fig. 7A )QQ plot representing all 729,000 variants in the GWAS. Figure 7B )Principal component analysis (PCA) of all samples after quality control (QC) in different ethnic groups. Figure 7C ) SNPrs12979860 is significantly associated with epitopes in the core region and NS5B region of HCV. Left: Heat map showing the significance of SNP associated with 375 epitope abundances of HCV genotypes 2 and 3. The core region and NS5B region are highly correlated with genotypes. Right: Box plot representing the difference in epitope abundance between core region and NS5B region genotypes.

[0026] Figures 8A-8E : CONSORT flow diagram of the NIDDK cohort and evaluation of the association between clinical outcomes and VES in the NIDDK cohort. Fig. 8A ) The figure includes details on participants excluded from initial enrollment, sample allocation with indicated criteria, follow-up, QC, and final data analysis. ( Figure 8B ) Kaplan-Meier survival curves of the NIDDK cohort grouped by VES level. Figure 8C ) ROC curve analysis of the time-dependent performance of VES at landmark time points 1-10 years relative to baseline. Fig.8D ) Predictive performance of AUC based on univariate and multivariate clinical indicators compared with VES (vertical bands) in the NIDDK cohort at diagnosis. ( Fig. 8E ) Predictive performance by AUC based on univariate and multivariate clinical indicators compared with VES (vertical strips) in the NCI-UMD cohort.

[0027] Figures 9A-9G : Genome-wide scan identifies specific genetic variants associated with VES. Fig. 9A ) Manhattan plot showing genetic variants detected from GWAS associated with viral signature phenotypes in the NCI-UMD cohort. P values ​​less than 10 -7 The annotated name of the locus. ( Fig. 9B) Locus zoom diagram showing the LD structure of rs16960234, one of the lead SNPs around CDH13 and RP11-543N12.1 region. ( Fig. 9C ) shows a heatmap of high linkage disequilibrium (LD) SNPs for rs16960234 from the 1000Genomes database (R2>0.6). The density of the heatmap represents the r2 value of the association. The labeled SNPs are the SNPs with available eQTLs. ( Fig.9D ) eQTL of CDH13 in tibial tissue arteries between SNP rs1690234 genotypes from the GTEx database. ( Fig.9E ) Relative to PC, genotype odds ratio (OR) of rs1690234 between HR and HCC. ( Fig.9F , 9G ) Fold changes (FD) in VES scores among genotypes AA, AG, and GG of rs1690234 based on 61-VES and 31-VES among HCC relative to PC.

[0028] Fig.10 : Prevalence of viral infection and unique viral epitope counts between population control (PC), risk group (AR), and HCC groups. The prevalence of viral infection for all PC, AR, and HCC samples is shown on a bar graph. The unique epitope counts for each sample are shown on a dot plot, with the vertical line representing the mean of the unique epitope counts.

[0029] Figures 11A-11G :Further verify the robustness of 61-VES. ( Fig.11A )XGBoost performance was evaluated by 10× cross validation on the AUC of HCC relative to AR. Fig. 11B ) ROC curves for PC versus HCC prediction, and ROC curves for AR versus HCC prediction, using features from HCC versus AR prediction. ( Fig. 11C ) The features selected for HCC prediction relative to AR highly overlap with the VES features. Fig.11D )XGBoost performance is evaluated by AUC of HCC relative to PC with 60 / 40 training-test split. Fig.11E )ROC curve shows the performance of the training and test datasets. Fig.11F )1000 permutations with 60 / 40 train / test split. Fig.11G ) Selected features and feature importance after 1000 permutation tests.

[0030] Sequence Listing

[0031] The amino acid sequences listed in the accompanying sequence listing are shown using the standard three-letter amino acid code, as defined in 37 C.FR 1.822. The sequence listing is submitted as an ASCII text file, created on October 8, 2020, 58.3 KB, which is incorporated herein by reference. In the accompanying sequence listing:

[0032] SEQ ID NOs: 1-102 are amino acid sequences of unique peptide epitopes from human viruses. DETAILED DESCRIPTION

[0033] I. Terminology and Methodology

[0034] Unless otherwise indicated, technical terms are used according to conventional usage. Definitions of commonly used terms in molecular biology can be found in Benjamin Lewin, Genes VII, Oxford University Press, 2000 (ISBN 019879276X); Kendrew et al. (eds.), The Encyclopedia of Molecular Biology, Blackwell Publishing, 1994 (ISBN 0632021829); Robert A. Meyers (ed.), Molecular Biology and Biotechnology: a Comprehensive Desk Reference, Wiley, John & Sons, Inc., 1995 (ISBN 0471186341); and George P. Rédei, Encyclopedic Dictionary of Genetics, Genomics, and Proteomics, 2nd edition, 2003 (ISBN: 0-471-26821-6).

[0035] The singular forms "a", "an", and "the" refer to one or more, unless the context clearly dictates otherwise. For example, the term "comprising a probe" includes a single or multiple probes and is considered equivalent to the phrase "comprising at least one probe". Unless the context clearly indicates otherwise, the term "or" refers to a single element or a combination of two or more elements of the optional element. As used herein, "comprising" means "including". Therefore, "comprising A or B" means "including A, B, or A and B", without excluding additional elements.

[0036] Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present disclosure, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. The same is true for the accession number (sequence shown on February 8, 2016). In the event of a conflict, the present specification (including explanations of terms) will prevail. In addition, the materials, methods, and examples are illustrative only and not limiting.

[0037] The methods and techniques of the present disclosure are generally performed according to conventional methods well known in the art and as described in various general and more specific references that are cited and discussed throughout the present specification unless otherwise indicated. See, e.g., Sambrook et al., Molecular Cloning: A Laboratory Manual, 2nd ed., Cold Spring Harbor Laboratory Press, 1989; Sambrook et al., Molecular Cloning: A Laboratory Manual, 3rd ed., Cold Spring Harbor Press, 2001; Ausubel et al., Current Protocols in Molecular Biology, Greene Publishing Associates, 1992 (and 2000 supplement); Ausubel et al., Short Protocols in Molecular Biology: A Compendium of Methods from Current Protocols in Molecular Biology, 4th ed., Wiley & Sons, 1999; Harlow and Lane, Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory Press, 1990; and Harlow and Lane, Using Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory Press, 1999.

[0038] To facilitate a review of various embodiments of the present disclosure, the following explanations of specific terms are provided:

[0039] Administration: Introducing an agent (e.g., an antiviral therapeutic agent) into a subject via a selected route. Administration can be local or systemic. For example, if the selected route is intravascular, the agent is administered by introducing the composition into a blood vessel of the subject. Exemplary routes of administration include, but are not limited to, oral, injection (e.g., subcutaneous, intramuscular, intradermal, intraperitoneal, and intravenous), sublingual, rectal, transdermal (e.g., topical), intranasal, vaginal, and inhalation routes.

[0040] Antibody: A polypeptide ligand that contains at least one variable region that recognizes and binds (e.g., specifically recognizes and specifically binds) an epitope of an antigen (e.g., a viral antigen). Mammalian immunoglobulin molecules are composed of heavy (H) chains and light (L) chains, each with a variable region, called a variable heavy (V H ) area and variable lightness (V L ) area. H Area and V L The heavy chain domains are responsible for binding to the antigen recognized by the antibody. There are five major classes (or isotypes) of mammalian immunoglobulins that determine the functional activity of the antibody molecule: IgM, IgD, IgG, IgA, and IgE. Antibody isotypes not found in mammals include IgX, IgY, IgW, and IgNAR. IgY is a primary antibody produced by birds and reptiles and is somewhat similar in function to mammalian IgG and IgE. IgW and IgNAR antibodies are produced by cartilaginous fish, while IgX antibodies are found in amphibians.

[0041] Array: An arrangement of molecules, such as biomacromolecules (e.g., peptides or nucleic acid molecules) or biological samples (e.g., tissue sections), located at addressable locations on or within a substrate. In some embodiments herein, the array comprises at least 10, at least 20, at least 30, at least 40, at least 50, at least 60 (e.g., 61) addressable locations. In a specific example, the array comprises peptide epitopes from each virus listed in Table 5A or Table 6.

[0042] Control: A "control" refers to a sample or standard used for comparison with an experimental sample (e.g., a serum sample obtained from a subject suspected of having HCC or at risk for HCC). In some embodiments, the control is a sample obtained from a healthy patient (e.g., a patient without HCC or cirrhosis). In some embodiments, the control is a historical control or a standard reference value or range of values ​​(e.g., a previously tested control sample, such as a set of samples representing a baseline or normal value).

[0043] Diagnosis: The process of identifying disease through signs, symptoms, and results of various tests. The conclusion reached through this process is also called the "diagnosis." Common forms of testing performed include blood tests, medical imaging, and biopsies.

[0044] Early stage: In the context of the present disclosure, detecting "early stage" HCC refers to identifying HCC in a subject before the onset of symptoms and / or before standard clinical diagnosis. In this context, "early stage" is not a synonym for stage 0 or stage I cancer. In some embodiments, early stage HCC is characterized by the presence of a single lesion with a diameter less than 3 cm (e.g., 0.1 to 2.9 cm in diameter, e.g., 0.5 to 2.5 cm, 0.5 to 1 cm, or 1 to 2.9 cm in diameter) without detectable local or distant metastatic lesions (e.g., detectable by CT or MRI).

[0045] Epitope: Antigenic determinant. These are specific chemical groups or peptide sequences on a molecule that are antigenic, i.e., that elicit a specific immune response. Antibodies specifically bind to specific antigenic epitopes on polypeptides (e.g., viral polypeptides).

[0046] Hepatocellular carcinoma (HCC): A primary malignant tumor of the liver that occurs in some cases in patients with inflammatory livers caused by viral hepatitis, hepatotoxins, or cirrhosis (often caused by alcoholism). Exemplary treatments for HCC include, but are not limited to, one or more of surgery, transarterial chemoembolization (TACE), ablative therapy (including thermal ablation and cryoablation), radioembolization, and percutaneous alcohol injection.

[0047] Isolated: An "isolated" biological component (e.g., a nucleic acid molecule, protein, or cell) has been substantially separated or purified from other biological components (e.g., other chromosomal and extrachromosomal DNA and RNA, proteins, and cells). Nucleic acid molecules and proteins that have been "isolated" include nucleic acid molecules and proteins purified by standard purification methods. The term also includes nucleic acid molecules and proteins prepared by recombinant expression in a host cell and chemically synthesized nucleic acid molecules and proteins.

[0048] Sample (or biological sample): a biological sample obtained from a subject containing genomic DNA, RNA (including mRNA), protein (e.g., antibody), or a combination thereof. Examples include, but are not limited to, peripheral blood, plasma, urine, saliva, tissue biopsy, fine needle aspirate, puncture biopsy surgical specimens, and autopsy material. In specific embodiments herein, the sample is a blood or serum sample.

[0049] Sequence Identity: The identity or similarity between two or more nucleic acid sequences or two or more amino acid sequences, expressed as the identity or similarity between the sequences. Sequence identity can be measured as a percentage of identity; the higher the percentage, the higher the sequence identity. Sequence similarity can be measured as a percentage of similarity (taking into account conservative amino acid substitutions); the higher the percentage, the higher the sequence similarity.

[0050] Methods of sequence alignment for comparison are well known in the art. Various programs and alignment algorithms are described in: Smith and Waterman, Adv. Appl. Math. 2:482, 1981; Needleman and Wunsch, J. Mol. Biol. 48:443, 1970; Pearson and Lipman, Proc. Natl. Acad. Sci. USA 85:2444, 1988; Higgins and Sharp, Gene, 73:237-44, 1988; Higgins and Sharp, CABIOS 5:151-3, 1989; Corpet et al., Nuc. Acids Res. 16:10881-90, 1988; Huang et al., Computer Appls. in the Biosciences 8, 155-65, 1992; and Pearson et al., Meth. Mol. Bio. 24:307-31, 1994. Altschul et al., J. Mol. Biol. 215:403-10, 1990, consider sequence alignment methods and homology calculations in detail.

[0051] NCBI Basic Local Alignment Search Tool (BLAST) (Altschul et al., J. Mol. Biol. 215:403-10, 1990) is available from multiple sources, including the National Center for Biological Information (NCBI) and the Internet, and is used in conjunction with the sequence analysis programs blastp, blastn, blastx, tblastn, and tblastx. More information can be found on the NCBI website.

[0052] Subject: A living multicellular vertebrate organism, a class that includes humans and non-human mammals. In some examples herein, the subject is suspected of having or being at risk of having HCC.

[0053] Tumor: All neoplastic cell growth and proliferation, whether malignant or benign, and all precancerous and cancerous cells and tissues. In some embodiments, the tumor is an HCC tumor.

[0054] II. Virus Exposure Characteristics and Methods of Use

[0055] Viruses are known to affect human health by changing host immunity, which makes the interaction between the virus group and the host crucial in the pathogenesis of human chronic diseases (including cancer) (Foxman et al., Nat Rev Microbiol 2011; 9: 254-64; Cadwell, Immunity 2015; 42: 805-813). A variety of pathogenic and non-pathogenic viruses may interact with each other and interact with the host to form host immunity, which may change its response to new infections. Therefore, viruses that persist or are cleared in the host may leave unique molecular footprints, thereby changing the susceptibility of the disease to cancer and may become an excellent window for early onset (Cadwell, Immunity 2015; 42: 805-813). It is assumed that the unique post-virus exposure characteristics generated by virus-host interactions may reflect a series of events that may change the risk of HCC. These features can be used as early detection biomarkers and provide knowledge about potential modifiable factors for early-onset HCC. In the study disclosed herein, VirScan, a synthetic virome technology based on high-throughput sequencing methods, was used to analyze serum samples from 899 individuals enrolled in a liver cancer case-control study (NCT00913757; clinicaltrials.gov) to detect the history of exposure to all known human viruses (Xu et al., Science 2015; 348: aaa0698). This article discloses a unique viral exposure signature (VES) that can distinguish HCC cases from CLD from age- and sex-matched healthy volunteers. The VES was validated in the prospective National Institute of Diabetes, Digestive and Kidney Diseases (NIDDK) HCC risk cohort.

[0056] Provided herein is a method for identifying a subject to have a risk of developing HCC. In some embodiments, the method includes detecting the presence or absence of antibodies to multiple viruses in a sample obtained from the subject; determining the presence of a viral exposure signature (VES) in a sample obtained from the subject; and identifying the subject to have a risk of developing HCC when a VES is present.

[0057] In some embodiments, the presence of VES is determined by recognizing antibodies against one or more of the following: hepatitis C virus (HCV) genotype 3b, Tr-Kj isolate; HCV genotype 1b, Taiwan isolate; HCV genotype 1a, 1 isolate; human cytomegalovirus, AD169 strain; HCV genotype 6g, JK046 isolate; HCV genotype 1b, BK isolate; HCV genotype 1c, HC-G9 isolate; HCV genotype 1b, HC-J4 strain; HCV genotype 4a, ED4 isolate. 3 isolates; hepatitis D virus; HCV genotype 5a, isolate EUH1480; human cytomegalovirus; Crimean-Congo hemorrhagic fever virus, Nigeria / IbAr10200 / 1970 strain; HCV genotype 1b, isolate HC-J1; influenza A virus, A / USSR / 90 / 1977H1N1 strain; influenza A virus, A / Bangkok / 1 / 1979H3N2 strain; HCV genotype 1c, isolate India; and Chapare virus, isolate Human / Bolivia / 810419 / 2003.

[0058] In some embodiments, the presence of VES is determined by the absence of detection of antibodies to one or more of the following: Epstein-Barr virus, strain B95-8; human rhinovirus 23; HCMV, strain Towne; human herpesvirus 2 (HHV-2), strain HG52; human herpesvirus 3; varicella-zoster virus, strain Dumas; cynomolgus herpesvirus 16; human adenovirus C serotype 2; human astrovirus-1; human respiratory syncytial virus; human herpesvirus 6B, strain Z29; human herpesvirus 7, strain JI; human rhinovirus 14; Lordsdale virus, strain GII / human / UK / Lordsdale / 1993; human herpesvirus 1, strain KOS; human metapneumovirus, strain CAN97-83; coxsackievirus A16, strain G-10; Epstein-Barr virus, strain AG876; vaccinia virus; human herpesvirus 1, strain 17; human adenovirus E serotype 4; human adenovirus F serotype 40; Tadalafil poxvirus; human adenovirus C serotype 5; rhinovirus B; human herpesvirus 8; human herpesvirus 6A, Uganda-1102 strain; human rhinovirus A serotype 89, 41467-Gallo strain; norovirus MD145, GII / human / USA / MD145-12 / 1987 strain; molluscum contagiosum virus subtype 1; vaccinia virus, Copenhagen strain; poliovirus type 1, S abin strain; aphthous ulcer virus; HHV-2, strain 333; hepatitis B virus; Epstein-Barr virus, strain GD1; human parainfluenza 3 virus, strain Wash / 47885 / 57; HHV-2; human enterovirus 71, strain BrCr; human herpesvirus 6A, strain GS; simian herpesvirus 1; influenza B virus, strain B / Yamagata / 16 / 1988; and influenza A virus, strain A / Philippines / 2 / 1982H3N2.

[0059] In some embodiments, the plurality of viruses includes at least 10, at least 20, at least 30, at least 40, at least 50, or at least 60 of the viruses listed in Table 5A. In some instances, the plurality of viruses includes or consists of 61 viruses listed in Table 5A. In some instances, the plurality of viruses includes or consists of 31 viruses listed in Table 6.

[0060] In certain embodiments, step (ii) comprises determining the presence of VES in a sample obtained from a subject when: (a) antibodies specific for three or more, four or more, five or more, six or more, or seven or more of the following are detected in the sample: hepatitis C virus (HCV) genotype 3b, Tr-Kj isolate; HCV genotype 1b, Taiwan isolate; HCV genotype 1a, 1 isolate; human cytomegalovirus, AD169 strain; HCV genotype 6g, JK046 isolate; HCV genotype 1b, BK isolate; HCV genotype 1c, HC-J9 isolate; HCV genotype 1d, HC-J4 isolate; genotype 4a, isolate ED43; hepatitis D virus; HCV genotype 5a, isolate EUH1480; human cytomegalovirus; Crimean-Congo hemorrhagic fever virus, Nigeria / IbAr10200 / 1970 strain; HCV genotype 1b, isolate HC-J1; influenza A virus, A / USSR / 90 / 1977H1N1 strain; influenza A virus, A / Bangkok / 1 / 1979H3N2 strain; HCV genotype 1c, isolate India; and Chapare virus, isolate Human / Bolivia / 810419 / 2003; and / or (b) no detection in the sample of three or more, four or more, five or more, six or more of the following Multiple, or seven or more antibodies specific for: Epstein-Barr virus, strain B95-8; human rhinovirus 23; HCMV, Towne strain; human herpesvirus 2 (HHV-2), strain HG52; human herpesvirus 3; varicella-zoster virus, strain Dumas; macaque herpesvirus 16; human adenovirus C serotype 2; human astrovirus-1; human respiratory syncytial virus; human herpesvirus 6B, strain Z29; human herpesvirus 7, strain JI; human rhinovirus 14; Lordsdale virus, strain GII / human / UK / Lordsdale / 1993; human herpesvirus 1, strain KOS; human metapneumovirus, strain CAN97-83; coxsackievirus A16, G-1 0 strain; Epstein-Barr virus, strain AG876; vaccinia virus; human herpesvirus 1, strain 17; human adenovirus E serotype 4; human adenovirus F serotype 40; Tanapox virus; human adenovirus C serotype 5; rhinovirus B; human herpesvirus 8; human herpesvirus 6A, strain Uganda-1102; human rhinovirus A serotype 89, strain 41467-Gallo; norovirus MD145, strain GII / human / USA / MD145-12 / 1987; molluscum contagiosum virus subtype 1; vaccinia virus, strain Copenhagen; poliovirus type 1, strain Sabin; aphthous ulcer virus; HHV-2, strain 333; hepatitis B virus; Epstein-Barr virus, strain GD1;Human parainfluenza 3 virus, strain Wash / 47885 / 57; HHV-2; human enterovirus 71, strain BrCr; human herpesvirus 6A, strain GS; macaque herpesvirus 1; influenza B virus, strain B / Yamagata / 16 / 1988; and influenza A virus, strain A / Philippines / 2 / 1982H3N2.

[0061] In some embodiments, the sample is a blood or serum sample. In some instances, the method further comprises obtaining a biological sample from a subject. In some instances, the subject is a human subject.

[0062] Any immunoassay can be used to detect the presence of the antibody. In some embodiments, the antibody is detected by phage immunoprecipitation, immunoblotting, or enzyme-linked immunosorbent assay.

[0063] Also provided is a phage display library expressing unique peptide epitopes from each virus listed in Table 5A or Table 6. The phage display library can be used to determine the presence of VES. In some embodiments, the phage display library expresses peptides of SEQ ID NO: 1-61 (see Table 5B). In other examples, the phage display library expresses peptides of SEQ ID NO: 62-102 (see Table 3B). In some examples, the phage display library expresses peptides of SEQ ID NO: 1-102. In some examples, the phage display library expresses peptides with at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99% or 100% identity to any one of SEQ ID NO: 1-61, SEQ ID NO: 62-102 and SEQ ID NO: 1-102.

[0064] Further provided is an array comprising unique peptide epitopes from each virus listed in Table 5A or Table 6. The array can be used to determine the presence of VES. In some examples, the unique peptide epitopes include peptides of SEQ ID NO: 1-61 (shown in Table 5B), peptides of SEQ ID NO: 62-102 (shown in Table 3B), or peptides of SEQ ID NO: 1-102. In some examples, the peptide has an amino acid sequence that is at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% identical to any one of SEQ ID NO: 1-61, SEQ ID NO: 62-102, and SEQ ID NO: 1-102.

[0065] In other embodiments provided herein, a method for identifying a subject at risk for developing HCC comprises (i) detecting the presence or absence of antibodies specific for a plurality of viruses in a sample obtained from the subject, wherein the plurality of viruses comprises hepatitis C virus (HCV) genotype 3b, Tr-Kj isolate; HCV genotype 1b, Taiwan isolate; HCV genotype 1a, 1 isolate; human cytomegalovirus (HCMV) AD169 strain; HCV genotype 6g, JK046 isolate; Epstein-Barr virus (EBV), B95-8 strain; human rhinovirus 23; HCMV Towne strain; HCV genotype 1b, BK isolate; and human herpes virus 2 (HHV-2), HG52 strain; and (ii) the subject is determined to be at risk for developing HCC in the following circumstances: (a) antibodies specific to HCV genotype 3b, Tr-Kj isolate; HCV genotype 1b, Taiwan isolate; HCV genotype 1a, 1 isolate; HCMVAD169 strain; HCV genotype 6g, JK046 isolate; and / or HCV genotype 1b, BK isolate are detected in the sample; and / or (b) antibodies specific to EBV, B95-8 strain; human rhinovirus 23; HCMV Towne strain; and / or HHV-2, HG52 strain are not detected in the sample.

[0066] In some instances, step (ii) includes identifying the subject as being at risk for developing HCC when: (a) antibodies specific to at least two, at least three, at least four, at least five, or all six of HCV genotype 3b, Tr-Kj isolate; HCV genotype 1b, Taiwan isolate; HCV genotype 1a, 1 isolate; HCMVAD169 strain; HCV genotype 6g, JK046 isolate; and HCV genotype 1b, BK isolate are detected in the sample; and / or (b) antibodies specific to at least one, at least two, at least three, or all four of EBV B95-8 strain; human rhinovirus 23; HCMV Towne strain; and / or HHV-2HG52 strain are not detected in the sample.

[0067] In some instances, the sample is a blood or serum sample. In specific instances, the method further comprises obtaining a biological sample from the subject.

[0068] In some embodiments, the antibodies are detected by phage immunoprecipitation, immunoblotting, or enzyme-linked immunosorbent assay.

[0069] In some embodiments of the disclosed methods, the method further comprises treating the subject with an appropriate therapy to help prevent or treat HCC. In some examples, the appropriate therapy comprises vaccination against hepatitis B virus (HBV) (e.g., administration of Engerix- Recombivax or Heplisav- ), antiviral therapy for HBV (e.g., administration of PEG-IFN, entecavir, tenofovir, lamivudine, adefovir and / or telbivudine) and / or antiviral therapy for HCV (e.g., administration of one or more of glecaprevir, sofosbuvir, daclatasvir, grazoprevir and ombitasvir). Antiviral drugs include, for example, nucleoside / nucleotide analogs (e.g., entecavir and tenofovir disoproxil fumarate), interferon and lamivudine. In some instances, the method further includes performing a liver transplant on a subject with early HCC. In other instances, the method further includes performing a liver resection on a subject with early HCC, with or without radiofrequency ablation (RFA).

[0070] In some embodiments, the method further includes active diagnostic monitoring of subjects with early HCC. For example, ultrasound, contrast agent enhanced computed tomography (CT) and / or magnetic resonance imaging (MRI) can be used to monitor subjects regularly, such as every 2 months, every 3 months, every 4 months, every 5 months or every 6 months.

[0071] In some instances, additional treatments include lifestyle or dietary changes, including programs to reduce intravenous drug use, needle exchange programs, prevention of sexually transmitted diseases, reduction or elimination of drinking, reduction of inflammation associated with obesity (e.g., by improving diet and increasing exercise), improvement of insulin resistance, increase of vegetable intake, intake of branched-chain amino acids, and / or vitamin D. For some patients, such as patients with hereditary hemochromatosis, iron overload can increase the risk of HCC. Therefore, in some instances, appropriate therapy includes treatment of iron overload. Aflatoxin B1 is a known carcinogen produced by Aspergillus fungi, which is commonly found in contaminants of grains, nuts, and vegetables in multiple regions (e.g., Asia and Africa). Therefore, reducing aflatoxin exposure can also be used to prevent or treat HCC. Additional preventive therapies and treatments are described in Schütte et al., Gastrointest Tumors 3(1):37-43,2016 and Schütte et al., Gastrointest Tumors 2(4):188-194,2016.

[0072] III. Phage immunoprecipitation sequencing

[0073] In some embodiments of the present disclosure, the method of detecting the presence or absence of specific antibodies in a patient sample and thereby determining the presence of VES can be performed using phage immunoprecipitation sequencing (PhIP-Seq). This method is a high-throughput method that enables a comprehensive analysis of the antibody repertoire of a subject (see U.S. Publication No. 2016 / 0320406; Larman et al., Nat. Biotechnol 29:535-541, 2011; and Mohan et al., Nat Protoc 13:1958-1978, 2018; each of which is incorporated herein by reference).

[0074] PhIP-Seq is a method that can be used to quickly detect the presence or absence of multiple virus-specific antibodies in patient samples. In short, the method includes designing a peptide library representing the virus to be detected. In the context of the present disclosure, the library includes, for example, 61 or 31 unique peptide epitopes of 61-VES or 31-VES, respectively (see Tables 5A and 6). A library of oligonucleotides encoding peptides is constructed and PCR amplified with adapters to be cloned into a selected phage display vector to produce a phage display library. Patient samples, such as blood or serum samples, are contacted with the phage display library to form phage-antibody complexes and subsequent immunoprecipitation. The oligonucleotide sequence library encoding the peptides is amplified directly from the immunoprecipitate by PCR, barcoded and deeply sequenced. More details of this method can be found in U.S. Publication No. 2016 / 0320406; Larman et al. (Nat. Biotechnol 29:535-541, 2011), Mohan et al. (Nat Protoc 13:1958-1978, 2018) and the Novagen T7Select System Manual (available online)

[0075] The following examples are provided to illustrate certain specific features and / or embodiments. These examples should not be construed as limiting the disclosure to the specific features or embodiments described.

[0076] Example

[0077] Example 1: Method

[0078] This example describes the materials and experimental procedures used for the studies described in Example 2.

[0079] Participants and VirScan analysis

[0080] The patient cohort consisted of 899 participants enrolled sequentially (clinicaltrials.gov ID: NCT0091375), including 150 HCC cases, 337 CLD as at-risk individuals (HR or AR, used interchangeably), and 412 healthy volunteers as age- and sex-matched population controls (PC) ( Figure 1A ).

[0081] Study Cohort

[0082] UMD cohort. To measure virus-host interactions, 899 participants were recruited. Participants were grouped into (1) a population control group (PC, n = 412) if they were relatively healthy without any liver disease diagnosis; (2) a high-risk group (HR, n = 337) if they were diagnosed with chronic liver disease (hepatitis B virus (HBV), hepatitis C virus (HCV), hepatitis D virus (HDV), aflatoxin from fungal contamination, alcohol, non-alcoholic fatty liver disease (NAFLD), and non-alcoholic steatohepatitis (NASH); or a hepatocellular carcinoma group (HCC, n = 150) if they were diagnosed with HCC. NCT0091375 (clinicaltrials.gov) covered all clinical measurements, and the inclusion criterion was liver disease status. Serum, matched buffy coat, and cheek swab samples were collected from each individual.

[0083] NIDDK cohort. The cohort consisted of 173 patients with chronic liver disease, including 44 HCC cases and 129 controls matched for liver disease etiology, age, and sex. Patients were enrolled in a natural history protocol (clinicaltrials.gov ID; NCT0001971) and underwent serologic testing and imaging at least annually for up to 20 years. Only cases with complete clinical and laboratory data and available longitudinal serologic samples were selected for analysis. In this natural history study of chronic liver disease, 44 HCC cases were sequentially ascertained from 3,067 patients, and controls were matched 2:1 as described above. HCC was diagnosed by radiographic imaging and / or liver biopsy as described in the American Association for the Study of Liver Diseases (AASLD) practice guidelines (see Marrero et al., “Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidelines of the American Association for the Study of Liver Diseases,” Hepatology 68(2):723–750, 2018). For the purpose of this analysis, stored serum samples (-80°C) were analyzed at the beginning of the study (baseline) and at repeated time points until HCC diagnosis.

[0084] Sample collection

[0085] Blood samples were collected and stored at -80°C (n=899 from UMD, n=488 from NIDDK). Buffy coat and cheek swab samples were also collected and stored at -80°C (n=849 from UMD).

[0086] Virscan PhIP-seq

[0087] Phage immunoprecipitation and sequencing were performed using a slightly modified version of the previously published PhIP-Seq protocol. First, 96-well plates were blocked overnight with bovine serum albumin in TBST on a rotator at 4°C. 1 ml of diluted phage library was added to each blocked well. Serum samples containing 2 mg of IgG were mixed with the phage library. Two technical replicates were set up for each sample. After overnight rotation, protein A and protein G Dynabeads were added to each well. After another 4 h incubation on a 4°C rotator with a 96-well magnetic stand, the beads were washed 3 times with 400 ml of PhIP-Seq wash buffer. Next, the beads were resuspended in water and lysed at 95°C for 10 min. A blank PBS sample (instead of serum) was also set up as a negative control on each plate. Two rounds of PCR were performed to amplify and multiplex the lysed phage DNA products. After the second round of PCR, PCR products were pooled using equimolar amounts of all 192 samples for gel extraction. After gel extraction, the size and quality of the library were assessed on an Agilent Bioanalyzer instrument. DNA samples were aliquoted and stored at -80°C until sequencing. Sequencing was performed on an Illumina HiSeq 4000 platform (1X50 bp) using a 50 bp single read protocol, obtaining approximately 100 million to 200 million reads per lane (~1,000,000 reads per sample at current settings).

[0088] Raw data from the Illumina HiSeq 4000 platform were processed by BCL2FASTQ2 for demultiplexing and conversion of binary base calls and quality to fastq format. The fastq files were mapped to the raw virome peptide reference sequences using the Bowtie program. Two sequencing samples were truncated from the next step of analysis because they had fewer than 30,000 reads. Initial informatics and statistical analyses were performed using previously published techniques and slightly modified versions of in-house scripts. Briefly, log10 scatter plots of –log10(P value) and a sliding window of width 0.005 across the axis from 0 to 2 for one replicate were used. The distribution of the threshold –log10(P value) was determined to be centered around a mode of ∼2.358 ( Figure 5B). 593 hits that appeared in at least 3 of the 22 immunoprecipitations of the blank sample using PBS beads alone were excluded. In addition, any peptides that were not enriched in at least two samples were filtered out. The threshold number of hits for each virus was set based on the size of the virus. If the hit shared a subsequence of at least 7 amino acids with any hit previously observed in any virus in that sample, the hit was considered to be from a cross-reactive antibody and was ignored for that virus. Peptide hits that did not share any linear epitopes were summed into strain and species scoring data. The final score for each virus was compared to the threshold for that virus to determine whether the sample was positive for exposure to that virus species. Raw count data were calculated based on a cutoff of –log10(p-value)2.358.

[0089] DNA sample extraction

[0090] DNA was extracted from buffy coat or lymphocyte samples according to the manufacturer's instructions (DNeasy blood and tissue kit from Qiagen). Eluted DNA was stored at -20°C for further analysis.

[0091] GWAS platform

[0092] Illumina OmniExpress was applied to SNP arrays. 200 ng of genomic DNA was genotyped using Illumina Infinium HTS Global Screening Arrays on the Illumina iScan system. Raw genotyping data were processed by Illumina GenomeStudio software 2.0. Quality control was performed using PLINK version 2.0 (available online). Samples with genotyping detection rates < 95% were removed. SNPs with MAF (minor allele frequency) < 0.05, HWE (Hardy-Weinberg equilibrium) < 10-4, and detection rates < 95% were excluded.

[0093] GWAS analysis

[0094] Variant quality control was performed. After filtering, 849 individuals and 713,111 SNPs remained for further analysis, with a total typing rate of 99.79%. Deviations from Hardy-Weinberg equilibrium were marked as p-values ​​< 0.0001. PLINK was used to identify independent loci in regions of SNPs associated with viral characteristic phenotypes at P < 5 × 10-7. LocusZoom was used to plot regional signals associated with phenotypes with LD and recombination rates calculated from 1000 genomes. Haploview was used to further investigate the LD structure of the signal. Linear regression with an additive model was applied to estimate the genotypic effect of SNPs on the disease or phenotype.

[0095] ELISA assay

[0096] IgG, IgA and IgG4 levels in serum were measured using human ELISA kits (Bethyl and Thermo Fisher) according to the manufacturer's instructions. ELISA result reading was performed using a machine (Biorad).

[0097] Statistical methods

[0098] To identify differences between populations, Xgboost and LEfSe were used to calculate the significance of the association of viral exposure traits with HCC compared with PC.

[0099] XGBoost

[0100] XGBoost (available online) is a software for regression and classification machine learning methods using ensemble learning and gradient tree boosting. It is designed to improve the scalability and acceleration of optimization computations for practical use. XGBoost includes three types of parameters—general, boosting, and task. Each type has several hyperparameters that need to be adjusted, such as the maximum depth of the regression tree, the number of weak learners, the learning rate, and regularization. These parameters are adjusted using grid search to maximize the average AUC value calculated from 5-fold cross validation on the training data. After finding the best values ​​for the hyperparameters, the model was built with the following main parameter settings: max_depth = 3, eta = 0.1, subsample = 1, colsample_bytree = 0.5, min_child_weight = 1. XGBoost was then applied to the entire dataset for 200 boosting iterations. To avoid overfitting, the model training was stopped for at least 20 rounds (early_stopping_rounds = 20) when no improvement was observed in the AUC value. The best iteration model was used as the final model. XGBoost automatically performs feature selection and calculates the importance of each feature. Multiple feature subsets were tested to achieve the highest AUC, and it was decided to use all output features for further analysis. For each training and test sample, a viral feature score was also generated based on the features selected and implemented in the XGBoost classification prediction.

[0101] LqCy

[0102] The LEfSe analysis method first compares the abundance of all viral evolutionary branches (in this case, between PC and HCC) by the Kruskal-Wallis test, with a predefined alpha of 0.05. The significantly different vectors generated by the relative abundance comparison between PC and HCC were used as input for linear discriminant analysis (LDA), which produced effect sizes and p-values. The LDA threshold for the logarithmic LDA score of the discriminant features was set to 2.0. LEfSe also calculated hierarchically organized viral taxa. The relative abundance data for the Lefse test were prepared based on the strain and species score data.

[0103] Other statistical methods

[0104] All analyses were performed in R and GraphPad Prism 7 (La Jolla, CA) for statistical analysis. Data are presented as mean + / - sem or median for continuous values ​​and analyzed by two-sided Student t test or Mann-Whitney test for comparison of two groups, respectively. Fisher's exact X2 t test was used to calculate the statistical significance of categorical values ​​between groups. Two-tailed P values ​​not exceeding 0.05 were considered significant. Linear regression was used to determine the correlation between two different variables.

[0105] Virus characteristic levels, clinical outcomes, and ROC curves

[0106] All HCC patients were divided into high, low, or below viral signature score groups based on viral signature levels ( Figure 4B and 6A ). Overall survival in each group was estimated by Kaplan-Meier and compared using the log-rank test. Hazard ratios and 95% confidence intervals were calculated using univariate and multivariate Cox proportional hazards models to assess the association between different viral signature levels and several clinical factors. The ability of clinical and viral signatures to predict HCC was assessed by calculating receiver operating characteristic (ROC) curves using logistic regression in R. Area under the curve (AUC) values ​​were calculated for these variables.

[0107] Example 2: Virus Exposure Signature (VES) for Diagnosis of Hepatocellular Carcinoma (HCC)

[0108] This example describes the development of two viral exposure signatures—the first VES based on detection of 61 viral strains and the second VES based on detection of 31 viral strains—to identify subjects at risk for developing HCC.

[0109] Overview of viral exposure characteristics

[0110] VirScan uses a phage display library of 93,904 viral epitopes, representing 206 human viral species and more than 1000 strains, to screen for prior exposure (Xu et al., Science 2015;348:aaa0698). Phage particles bearing epitopes recognized by the participant's antibodies are immunoprecipitated (Phage-IP), and the encoded DNA barcodes are then sequenced ( Figure 1A A case-control design of the Maryland (NCI-UMD) cohort was used to characterize viral exposure. Figure 5E As outlined in CONSORT guidelines (Schulz et al., BMJ 340:c332, 2010) (Table 8). For the NCI-UMD cohort, the VirScan Phage-IP product generated 0.5-5 million single-end reads per serum sample, with an average mapped read rate of 0.93 ( Figure 1B Based on two replicates, a total of 30,033 viral epitopes were significantly enriched with p-values ​​(-log10) greater than the reproducibility threshold of 2.358 ( Figure 5A-5B ). Note that the composition of virus types at the viral taxonomic level showed small but significant differences between the obtained Phage-IP products and the library input ( Figure 5D-5E ), indicating that there were measurable differences between the patient-derived data and the original input. When evaluating viral richness in PC, HR, and HCC, the number of identified viral infections increased with sample size and reached saturation when the sample size exceeded 200 ( Figure 1C An average of 7 viruses were detected per sample, and more than 20 of the 206 viruses were found in 4 individuals ( Figure 1D ). Overall, the distribution of viral species was similar among PC, HR, and HCC ( Figure 1D ), indicating that the overall viral exposure characteristics between different groups were unbiased. The abundance of the most prevalent viral species in all volunteers, such as human herpesvirus 4 (EBV) and human herpesvirus 5 (HCMV), was similar to previous population studies ( Figure 1E , Table 2A) (Xu et al., Science 2015;348:aaa0698) and is consistent with previous epidemiological reports (Straus et al., Ann Intern Med 1993;118:45-58; Ho, Rev Infect Dis 1990;12 Suppl 7:S701-S710). However, the HCV infection rate in this study (26.4%) was higher, mainly contributed by AR (48.4%) and HCC (39.3%) (Table 2A; Fig.10A wide range of unique viral epitopes for each viral species that were recognized between different participants were detected, indicating that B cell antigenicity to the same viral species varied between participants ( Figure 1E , right picture; Fig.10 ). In addition, the overall composition of virus types at the viral taxonomic level showed small but significant differences between phage-IP products and library input ( Figure 5C-5D ).

[0111] To further evaluate the quality of VirScan, the results of VirScan were compared with existing medical chart entries of HCV, HBV, and HIV test results and found that VirScan had a specificity of 45%, 47%, and 70% in detecting HCV, HBV, and HIV, respectively, when compared with these medical record data ( Figure 2A ). In contrast, its sensitivity was 84% ​​for HCV, 48% for HBV, and 73% for HIV. Most of the viral status data from the medical table were unknown or missing (Table 2B), making this comparison suboptimal. Epitope enrichment of HCV1b, the major type associated with HCC, was also examined (Bruno et al., Hepatology 2007;46:1350-1356). Consistently, increased enrichment of peptides corresponding primarily to core, NS4, and NS5A of HCV1b was observed in AR and HCC compared with PC, and these regions were consistent with the predictive score for B cell antigenicity ( Figure 2B The presence of HIV and other viruses known to co-infect with HIV (Xu et al., Science 2015;348:aaa0698; Chang et al., Immunol Rev 2013;254:114-142; Echavarria, Clin Microbiol Rev 2008;21:704-715; Stover et al., J Infect Dis 2003;187:1388-1396) was also examined. Co-infection of HIV with human herpesvirus 5, human adenovirus C, human adenovirus D, human herpesvirus B, or HBV was found to be significantly increased with a false discovery rate (FDR) <0.05 ( Figure 2C ). Taken together, these results suggest that VirScan is a reliable method to capture a broad spectrum of viral exposures via serological testing.

[0112] HCC-related VES

[0113] A gradient boosting method was applied to search for the optimal viral composition that could distinguish HCC from PC ( Figure 3AUsing 10-fold cross-validation and 1,000 random permutations, it was found that VES could significantly distinguish HCC from PC, with AUC values ​​of 0.9 and 0.7 for training and cross-validation, respectively ( Figure 3B ). The signature consists of unique peptides corresponding to 61 viral strains ( Figure 3C ). Among them, 18 viruses were positively correlated with HCC, and the rest were negatively correlated with HCC. HCV, including 11 unique variants, such as 3b or 1b in Taiwan, was the main contributing virus. This was not unexpected, as 39.3% of HCC cases in this cohort were HCV+. Herpesvirus 5, HDV, influenza virus H1N1, and influenza virus H3N2 were also found to be enriched in the HCC group. In contrast, 43 viruses (such as human respiratory syncytial virus and human rhinovirus 23) were preferentially absent in the HCC group (Table 5A, Figure 3C The weighted VES scores of 61 viruses were significantly different between HCC and PC (p<0.0001) and between HCC and HR (p<0.0001) or between HR and PC (p<0.0001). Figure 3D ). There was a significant increase among PC, HR and HCC (p value trend < 0.0001), indicating that VES was positively correlated with hepatocarcinogenesis.

[0114] Phylogenetic analysis of the reactive epitopes of 61 virus strains was performed to determine the similarities between these HCC-associated viruses ( Figure 3E ). To search for common reactive viral epitopes that are enriched or depleted in HCC, we limited the viral epitopes that ranked highly for HCC relevance. These viruses can be divided into eight major branches, in which different HCV epitopes clustered with other viral epitopes, except for cluster #6, which contained six HCV variants (out of 12 viruses) ( Figure 3E ; Table 5B). In general, there was no obvious enrichment of increased or decreased viruses within each branch, suggesting that different viral epitopes involved in the immune response are often shared between HCC. Since most HCC patients had evidence of CLD, to avoid this confounding variable, AR was also compared with HCC using the same gradient boosting method. It was found that the AR vs. HCC VES could significantly distinguish HCC from AR or PC, with AUC values ​​similar to those of the VES used for training and cross-validation ( Figures 11A-11B Most of these VES-related virus strains overlap ( Fig. 11C ). To further test the robustness of VES, a 60 / 40 split was performed, where 60% of the cases were used for VES discovery, while the remaining 40% of the cases were used for independent prediction. A total of 1,000 split permutations were performed to establish confidence intervals (CIs). Again, similar VESs were found, with an average AUC of 0.7 ( Figures 11D-11G ).

[0115] Another statistically conservative approach, linear discriminant analysis of effect size (LEfSe, or LDA) (Segata et al., Genome Biol 2011;12:R60) was used to search for HCC-associated viruses. In addition, pairwise comparisons of all levels of viral taxa (including DNA / RNA viruses, viral families, viral species, and viral strains) between HCC and PC were performed. In addition to strain-level VES, this analysis also identified differences in viral taxa by viral family, such as Flaviviridae for positive single-stranded RNA viruses, Pneumoviridae for negative single-stranded RNA viruses, and Circoviridae for single-stranded DNA viruses. These analyses generated 341 viruses that could significantly distinguish HCC from PC. Among them, several HCV variants, herpesvirus 5 variants, Norwalk virus variants, cytomegalovirus, adenovirus variants, and Astrovirus 1 had unique differences between PC and HCC ( Figure 6B ). A total of 31 viruses overlapped between Xgboost and LEfSe (Table 6) and differed between PC and HCC. Unsupervised hierarchical clustering of the top-ranked viral abundances showed that HCC was more closely associated with HR than with PC, which was consistent with the VES prediction score ( Fig. 6A , Figure 3D ). Overall, these results suggest that a unique set of VESs are robust in defining HCC.

[0116] Validation of VES in HCC

[0117] To further validate the clinical utility of the two VESs mentioned above, the VirScan signature was analyzed in the NIDDK at-risk cohort for HCC. The cohort consisted of 173 CLD patients (NIDDK-HR) who were enrolled in the Natural History of Liver Disease Study and followed up for up to 20 years (Table 1; Fig. 8A ). Of these, 44 developed HCC. The cohort included serum samples collected at enrollment (baseline) and at different follow-up time points until the diagnosis of HCC (diagnosis). Logistic regression analysis was performed using VES from all 61 viruses (Figure 4) or overlapping 31 viruses (Figure 7), and receiver operating characteristic (ROC) curves corresponding to the Maryland cohort or NIDDK-HR cohort, respectively, were generated. In the Maryland cohort, the 61-VES ( Figure 4A ) was 0.89, 95% CI (0.86-0.92) and 31-VES was 0.85, 95% CI (0.81-0.88) ( Fig. 7A ). It was observed that the 61-VES score levels of HCC cases in the Maryland cohort varied, with some being below the detection limit and others being low or high ( Figure 4BPatients with high levels had significantly worse survival compared with those with low levels or below the detection limit (log rank p = 0.026, p value trend = 0.033) ( Figure 4C ). Similar results were observed with 31-VES. In patients from the NIDDK cohort, VirScan data were available for 40 HCC cases at baseline, 129 controls at baseline, 44 HCC cases at diagnosis, and 106 controls at diagnosis (n=106). The average number of viral species per case in the NIDDK cohort was 6.

[0118] Table 9A shows the results of univariate and multivariate Cox model survival analyses of several clinicopathological variables to elucidate the independent and additional prognostic value of VES. Among patients from the NIDDK cohort, VirScan data were available for 40 HCC cases at baseline, 129 controls at baseline, 44 HCC cases at diagnosis, and 106 controls at diagnosis. Using the 61-VES, it was found that Figure 4D )AUC value was 0.98, 95%CI (0.97-1.00), at baseline ( Figure 4E ) with an AUC value of 0.91, 95% CI (0.87-0.96). Similar results were obtained using 31-VES. VES outperformed alpha-fetoprotein (AFP), a known HCC diagnostic marker used clinically. When used in combination with AFP, 31-VES produced AUC values ​​of 0.92, 95% CI (0.87-0.97) at diagnosis and 0.81, 95% CI (0.74-0.89) at baseline. The DeLong test showed a significant improvement between VES and AFP (p-values ​​at baseline and diagnosis were 4 × 10 -12 and 8×10 -10 )( Figure 4D and 4E A similar trend was found between VES levels and overall survival in the 44 patients in the NIDDK cohort (p-trend = 0.19) ( Figure 8B). To evaluate the time-dependent performance of VES in predicting the onset of HCC, 104 cancer-free controls and 40 HCC cases (from the NIDDK validation cohort) with at least two time points available were analyzed. In the context of the survival model, an event was defined as the occurrence of an HCC diagnosis. Under this interpretation, the censoring time was defined as the time difference between baseline and follow-up in the cancer-free control group, while the event time was defined as the time difference between baseline and HCC diagnosis within the HCC group. Table 9B shows the results of a multivariate Cox regression model predicting the occurrence of an HCC diagnosis based on the VES score at baseline and adjusted for clinical prognostic variables. In addition, time-dependent ROC curve analysis (Bansal and Heagerty, Diagn Progn Res 3:14, 2019; Blanche et al., StatMed 32:5381-5397, 2013) was performed to evaluate the performance of the VES over a range of landmark time points from 1 to 10 years relative to baseline ( Figure 4F and 8C ), which appears to be very robust and stable within this range. The results found that, on average, patients who developed HCC had significantly higher VES scores at baseline and at different times of follow-up until HCC diagnosis, when compared with high-risk patients without cancer who did not develop HCC and were followed up at similar intervals ( Figure 4G ). During the monitoring period of the NIDDK cohort, a significant increase in viral exposure was observed only in patients who developed HCC over time (p<0.05). It appears that HCC cases with high viral exposure had more aggressive disease than those with low viral exposure, and VES was a strong indicator of early HCC in this prospective cohort. In addition, the predictive performance of VES-based AR for HCC was superior to other clinical indicators in the patient's chart, such as AFP, alanine aminotransferase (ALT), cirrhosis, and platelet count, as well as the combination of all key clinical variables, as shown in the baseline NIDDK cohort analysis ( Figure 4H ), which is consistent with the NIDDK at diagnosis ( Fig.8D ) and the NCI-UMD cohort ( Fig. 8E The association between VES and HCC was also found in HCV-positive and HCV-negative patients (Table 9C).

[0119] Table 1. Clinical characteristics of patients.*

[0120]

[0121] *Clinical characteristics of 173 at-risk patients in the prospective NIDDK cohort.

[0122] Phenotype-genotype association with VES

[0123] To determine whether host genetic background may be associated with VES, a genome-wide association study (GWAS) was performed in the Maryland cohort, as this approach may help identify susceptibility variants associated with viral infection and cancer (McKay J et al., Nat Genet 2017;49:1126-1132; Pharoah et al., Nat Genet 2013;45:362-370; Fumagalli et al., PLoS Genet 2010;6:e1000849). After evaluation using genetic quality control measures, 849 participants (PC, n = 402; HR, n = 323; HCC, n = 124) were included in the analysis. After removing monoallelic SNPs and SNPs that deviated from Hardy-Weinberg equilibrium, all remaining SNPs were tested for association. To further assess the quality of the GWAS data, it was determined whether there was an association between the SNP, rs12979860 in IL28B, and HCV infection. As its favorable genotype, CC has been shown to be associated with better HCV treatment response or natural clearance. rs12979860-CC was found to be significantly associated with HCV genotype 3, with an odds ratio (OR) of 2.74 (95% CI 1.14-7.97) in a dominant model manner (Table 3A). In addition, 375 SNPs associated with the abundance of epitopes in HCV genotypes 2 and 3 were evaluated. It was found that the CC allele was associated with a decreased abundance of core epitopes but an increased abundance of NS5B epitopes in the HCV genome ( Figure 7C ; Table 3B), which is consistent with a recent study (Ansari et al., Nat Genet 49:666-673, 2017). To evaluate VES-associated SNPs, the HCC and PC groups were combined and then divided into two groups based on the dichotomy of VES scores. In the relevant quantile-quantile plot ( Figure 8B ), a wider distribution with smaller differences in allele frequencies is evident as the slope of the line increases. Principal component analysis based on genotyping revealed racial differences ( Figure 7B ).

[0124] Manhattan plot analysis revealed several SNPs with greater differences between high and low VES scores with p-values ​​< 10 -5 ( Fig. 9A Three SNPs, rs34725101, rs4483229, and rs16960234, located in three different genomic regions corresponding to RHOA, EPB41L4B, and CDH13, respectively, were associated with VES with p values ​​< 10-7, which is an acceptable standard for universal variant GWAS (Table 3C and Fig. 9A). Among them, rs16960234 was further analyzed because both the major and minor alleles of this variant could be detected in this cohort. For rs16960234, high linkage disequilibrium (LD) SNPs (r2>0.6) were also found, but rs34725101 and rs4483229 ( Figures 9B-9C ; Table 7). The seven highly LD SNPs of rs16960234 showed expression profiles of CDH13 as expression quantitative trait loci (eQTLs) in the Genotype Tissue Expression (GTEx) database (McKay et al., Nat Genet 2017; 49: 1126-1132). The expression level of CDH13 in arterial tibial tissue from carriers of the risk / protective G / G genotype of rs16960234 was significantly higher than that of carriers of the protective / risk genotype A / A ( Fig.9D To obtain the genotype effect of rs16960234 in HCC or HR, a logistic regression was constructed and the genotype odds ratio of this SNP in HR or HCC was calculated and compared with the PC ( Fig.9E ). rs16960234 genotype G / G showed a significantly increased risk of HR vs. PC, OR; 1.89 (0.30-11.4), and an even higher risk of HCC vs. PC, OR: 7.22 (1.30-40.0) ( Fig.9E ; Table 4). Consistent with the genotype effect in HCC, the VES score also showed a gradual increase in heterogeneity between A / G and G / G compared with A / A ( Figure 9F-9G ). Therefore, rs16960234 and its linked gene CDH13 may be associated with VES and lead to disease risk.

[0125] Diagnostic Applications

[0126] Detecting cancer at an early stage, preferably before symptoms appear, may provide an opportunity to achieve cure and improve outcomes of cancer-related mortality. There is evidence that early detection of cancer can improve survival in some cancer types (e.g., cervical and colon cancer). The traditional approach is to develop cancer cell-specific biomarkers to aid in early cancer diagnosis. CancerSEEK is an emerging platform that has successfully achieved good sensitivity and specificity for a variety of clinically detected cancer types by analyzing circulating free DNA (ctDNA) that may be shed from tumor cells (Cohen et al., Science 2018; 359: 926-930). Recent studies have provided a warning for using ctDNA to measure cancer genomes because of its high false positive rate in healthy individuals (Liu et al., Ann Oncol 2019; 30: 464-470). The molecular and biological heterogeneity of cancer cells caused by complex etiologies poses a dilemma, namely how to best design a cancer-specific diagnostic panel that is effective for early cancer detection. Therefore, in recent decades, there has been debate over whether existing approaches are sufficient to achieve this goal for many malignant diseases, including HCC (Sherman et al., Hepatology 2012;56:793-796; Shieh et al., Nat Rev Clin Oncol 2016;13:550-56).

[0127] HCC is a unique malignancy, most of whose major causes are known (Wang and Thorrgeirsson, Oncology 2014; 1: 5). However, due to its complex genomic profile and extensive intra-tumor and inter-tumor heterogeneity, it has been challenging to define HCC cell-specific biomarkers. Are there common features between HCC patients that can be used as alternative indicators for early detection? The emerging concept is that the interaction between viral infection and host genetic background is crucial for maintaining viral body homeostasis or causing human disease (Virgin, Cell 2014; 157: 142-150). The study disclosed in this article evaluated the relationship between an individual's history of viral exposure and their risk of HCC. Using synthetic virus scanning technology (VirScan) and a simple blood test (Xu et al., Science 2015; 348: aaa0698), VES that can distinguish HCC from chronic liver disease patients or healthy volunteers with high confidence were identified. It is worth noting that this feature was able to identify individuals in an 8.8-year mid-term follow-up before the clinical diagnosis of HCC. Therefore, these results provide a sensitive tool suitable for HCC surveillance programs to improve early diagnosis.

[0128] The current study utilized simple tools to analyze serum samples to link an individual’s history of viral infection and the corresponding response to early-onset HCC. The strategy first searched for VES using a case-control design that included HCC cases as well as at-risk individuals with chronic liver disease and healthy volunteers matched for age and sex. VES that could distinguish HCC from at-risk and healthy individuals were then validated using a prospective cohort consisting of sequentially enrolled at-risk patients who were followed for the development of HCC. The VES consisted of known causes of HCC, such as HCV, HBV, and HDV, but also included other viruses, such as herpesviruses 4 and 5, Crimean-Congo hemorrhagic fever virus, cytomegalovirus, and influenza A virus, among others. Several features were noted. First, HCV appeared to be the main cause driving the VES, but extended heterogeneity of various HCV subtypes was noted in both the Maryland and NIDDK cohorts. Second, a group of viruses was enriched in HCC patients, while many others, including HBV, were absent.

[0129] The current VirScan method is based on phage immunoprecipitation sequencing (PhIP-Seq) technology, which provides a powerful method for analyzing the binding specificity of antibody libraries for all known human viruses with high throughput and low cost (Mohan et al., Nat Protoc 2018;13:1958-1978). VirScan results were compared with HCV and HBV status in the UMD cohort medical charts and found that VirScan showed high specificity for both HCV and HBV, and good sensitivity for HCV, but lower sensitivity for HBV. HCV encodes a large polyprotein consisting of ∼3,000 amino acids, which is cleaved during and after translation into ten different proteins associated with intracellular membranes (Bartenschlager et al., Nat Rev Microbiol 2013;11:482-496). Consistently, HCV antigen reactivity largely overlapped with the antigenicity scores predicted by B cell epitope prediction methods, which is consistent with peptides intended to be presented on the cell membrane surface. Consistent with earlier reports of the potential for coinfection with HIV and other viruses associated with AIDS and non-AIDS diseases (Xu et al., Science 2015;348:aaa0698; Slyker et al., J Infect Dis 2013;207:1798-1806; Lichtner et al., J Infect Dis 2015;211:178-186), evidence of HIV coinfection with viruses such as HBV, herpesvirus 8 and adenovirus D, influenza B virus, adenovirus C, and herpesvirus 5 was found in patients enrolled in the Maryland cohort. A history of HCV infection was common among at-risk individuals (48%), HCC patients (39%), and healthy volunteers (4%) living in Maryland. This contrasts with the estimated prevalence of HCV infection in the United States, which is approximately 4.6 million people (~1.5%) (Edlin et al., Hepatology 2015;62:1353-1363). It should be noted that 7.5%-44% of incarcerated individuals and 4%-38% of hospitalized patients tested positive for HCV (Edlin et al., Hepatology 2015;62:1353-1363), suggesting that current surveys underestimate the prevalence of HCV infection. Conversely, while 2.6% of healthy individuals in Maryland showed evidence of HBV infection, more than 800,000 chronic HBV carriers were detected in the non-institutionalized US population during 2011-2012 (Roberts et al., Hepatology 2016;63:388-397). Current survey methods may underestimate the prevalence of HBV and HCV. This is important because both HBV and HCV are major pathogenic factors for HCC.Overall, VirScan is a reliable method for analyzing viral exposure and is scalable in terms of sample throughput and relatively low cost per analysis, suitable for monitoring and early detection of HCC.

[0130] Table 2A. Virus frequencies in 899 patients and volunteers from the NCI-UMD cohort

[0131]

[0132]

[0133] 1 PC: Population control

[0134] 2 HR: High risk group

[0135] 3 HCC: Hepatocellular carcinoma

[0136] Table 2B. Comparison of VirScan with medical charts for HBV, HCV, and HIV

[0137]

[0138]

[0139] Table 3A. Association of SNPs in the IL28B gene (rs12979860) with HCV genotype 2 and genotype 3

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[0141] a OR: odds ratio

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[0164] In view of the many possible embodiments to which the principles of the disclosed subject matter can be applied, it should be recognized that the illustrated embodiments are merely examples of the present disclosure and should not be considered to limit the scope of the present disclosure. Instead, the scope of the present disclosure is defined by the following claims. Therefore, we claim all that falls within the scope and spirit of these claims. Sequence Listing <110> The United States Government (represented by the Secretary of Health and Human Services) <120> Viral exposure signature for early detection of hepatocellular carcinoma <130> 4239-103258-02 <150> US 62 / 914,138 <151> 2019-10-11 <160> 102 <170> PatentIn Version 3.5 <210> 1 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 1 Glu Leu Ser Asp Thr Thr Asn Ala Thr Gln Pro Glu Leu Val Pro Glu 1 5 10 15 Asp Pro Glu Asp Ser Ala Leu Leu Glu Asp Pro Ala Gly Thr Val Ser 20 25 30 Ser Gln Ile Pro Pro Asn Trp His Ile Pro Ser Ile Gln Asp Val Ala 35 40 45 Pro His His Ala Pro Ala Ala Pro 50 55 <210> 2 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 2 Glu Val Val Glu Thr Ala Asn Val Thr Arg Pro Glu Leu Ala Pro Glu 1 5 10 15 Glu Arg Gly Thr Ser Arg Thr Pro Gly Asp Glu Pro Ala Pro Ala Val 20 25 30 Ala Ala Gln Leu Pro Pro Asn Trp His Val Pro Glu Ala Ser Asp Val 35 40 45 Thr Ile Gln Gly Pro Ala Pro Ala 50 55 <210> 3 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 3 Glu Lys Pro Asn Ala Thr Asp Thr Pro Ile Glu Glu Ile Gly Asp Ser 1 5 10 15 Gln Asn Thr Glu Pro Ser Val Asn Ser Gly Phe Asp Pro Asp Lys Phe 20 25 30 Arg Glu Ala Gln Glu Met Ile Lys Tyr Met Thr Leu Val Ser Ala Ala 35 40 45 Glu Arg Gln Glu Ser Lys Ala Arg 50 55 <210> 4 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 4 Thr Pro Ser Ala Glu Ser Thr Pro Gln Ser Thr Thr Val Lys Thr Lys 1 5 10 15 Asn Thr Thr Thr Thr Gln Ile Gln Pro Ser Lys Pro Thr Thr Lys Gln 20 25 30 Arg Gln Asn Lys Pro Gln Asn Lys Pro Asn Asn Asp Phe His Phe Glu 35 40 45 Val Phe Asn Phe Val Pro Cys Ser 50 55 <210> 5 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 5 Ile Asp Tyr Asp Asp Asn Lys Asp Asp Asp Lys Asp Asp Asp Lys Asp 1 5 10 15 Asp Asn Lys Asp Asp Asp Lys Asp Asp Asn Lys Asp Asp Asp Lys Asp 20 25 30 Asp Lys Asp Asp Asn Lys Asp Asp Asp Ser Asp Ser Asp Ser Asp Ser 35 40 45 Asp Ser Asp Ser Asp Ser Asp Asp 50 55 <210> 6 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 6 Leu Tyr Ser His Ile Lys Glu Glu Asp Arg Arg Arg Ser Ser Ala Ala 1 5 10 15 Gln Ala Met Glu Ala Ile Phe Gln Gly Ile Asp Leu Gln Ser Pro Pro 20 25 30 Pro Pro Ala Ile Ala Asp Leu Leu Arg Ser Val Lys Thr Pro Glu Ile 35 40 45 Ile Lys Tyr Cys Gln Asp Asn Asn 50 55 <210> 7 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 7 Met Ser Asn Met Asp Ile Asp Gly Ile Asn Thr Gly Thr Ile Asp Lys 1 5 10 15 Thr Pro Glu Glu Ile Thr Ser Gly Thr Ser Gly Thr Thr Arg Pro Ile 20 25 30 Ile Arg Pro Ala Thr Leu Ala Pro Pro Ser Asn Lys Arg Thr Arg Asn 35 40 45 Pro Ser Pro Glu Arg Ala Thr Thr 50 55 <210> 8 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 8 Leu Tyr Gln Gln Tyr Asp Glu Met Glu Glu Cys Ser Gln Ser Ala Pro 1 5 10 15 Tyr Ile Glu Gln Ala Gln Ala Ile Ala Gln Gln Phe Lys Asp Lys Val 20 25 30 Leu Gly Leu Leu Gln Arg Ala Ser Gln Gln Glu Ala Glu Ile Arg Pro 35 40 45 Ile Val Gln Ser Gln Trp Gln Lys 50 55 <210> 9 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 9 Tyr Pro Gly His Val Ser Gly His Arg Met Ala Trp Asp Met Met Met 1 5 10 15 Asn Trp Ser Pro Thr Thr Ala Leu Val Val Ser Gln Leu Leu Arg Ile 20 25 30 Pro Gln Ala Val Val Asp Met Val Ala Gly Ala His Trp Gly Val Leu 35 40 45 Ala Gly Leu Ala Tyr Tyr Ser Met 50 55 <210> 10 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 10 Arg Arg Lys Arg Thr Val Gln Leu Thr Glu Ser Val Val Ser Thr Ala 1 5 10 15 Leu Ala Glu Leu Ala Ala Lys Thr Phe Gly Gln Ser Glu Pro Ser Ser 20 25 30 Asp Arg Asp Thr Asp Leu Thr Thr Pro Thr Glu Thr Thr Asp Ser Gly 35 40 45 Pro Ile Val Val Asp Asp Ala Ser 50 55 <210> 11 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 11 Leu Thr Val Thr Tyr Ser Ser His Thr Thr Ser Ala Ala His Ser Arg 1 5 10 15 Ser Gly Ser Val Ser Gln Arg Val Thr Ser Ser Ser Gln Thr Val Ser His 20 25 30 Gly Val Asn Glu Thr Ile Tyr Asn Thr Thr Leu Lys Tyr Gly Asp Val 35 40 45 Val Gly Val Asn Thr Thr Lys Tyr 50 55 <210> 12 <211> 49 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 12 Cys Ile Thr Pro Asn Gly Ser Ile Pro Asn Asp Lys Pro Phe Gln Asn 1 5 10 15 Val Asn Lys Ile Thr Tyr Gly Ala Cys Pro Lys Tyr Val Lys Gln Asn 20 25 30 Thr Leu Lys Leu Ala Thr Gly Met Arg Asn Val Pro Glu Lys Gln Thr 35 40 45 Arg <210> 13 <211> 36 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 13 Thr Ser Gly Ala Thr Ala Ala Ala Ser Ala Ala Ala Ala Val Asp Thr 1 5 10 15 Gly Ser Gly Gly Gly Gly Gln Pro His Asp Thr Ala Pro Arg Gly Ala 20 25 30 Arg Lys Lys Gln 35 <210> 14 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 14 Met Thr Ser Arg Pro Ala Asp Gln Asp Ser Val Arg Ser Ser Ala Ser 1 5 10 15 Val Pro Leu Tyr Pro Ala Ala Ser Pro Val Pro Ala Glu Ala Tyr Tyr 20 25 30 Ser Glu Ser Glu Asp Glu Ala Ala Asn Asp Phe Leu Val Arg Met Gly 35 40 45 Arg Gln Gln Ser Val Leu Arg Arg 50 55 <210> 15 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 15 Met Glu Pro Pro Arg Pro Pro Asp Ala Asp Ser Leu Leu Ser Asp Ala 1 5 10 15 Thr Ser Val Ile Pro Leu Thr Pro Pro Ala Gln Gly Ala Glu Ala Tyr 20 25 30 Tyr Thr Glu Ser Asp Asp Glu Thr Ala Ala Asp Phe Leu Met Arg Met 35 40 45 Gly Arg Gln Gln Thr Ala Leu Arg 50 55 <210> 16 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 16 Asn Phe Ile Lys Ile Ser Leu Gly Glu Thr Met Gly Ile Thr Pro Lys 1 5 10 15 Glu Pro Thr Asn Pro Thr Gln Leu Leu Asn Val Lys Asn Gln Thr Glu 20 25 30 Tyr Ala Asn Glu Thr His Ser Thr Glu Val Gln Thr Val Lys Thr Phe 35 40 45 Lys Glu Asp Arg Phe Gln Arg Thr 50 55 <210> 17 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 17 Glu Asp Glu Tyr Leu Ser Glu Glu Met Met Glu Leu Thr Ala Arg Ala 1 5 10 15 Leu Glu Arg Gly Asn Gly Glu Trp Ser Thr Asp Ala Ala Leu Glu Val 20 25 30 Ala His Glu Ala Glu Ala Leu Val Ser Gln Leu Gly Asn Ala Gly Glu 35 40 45 Val Phe Asn Phe Gly Asp Phe Gly 50 55 <210> 18 <211> 30 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 18 Arg Arg His Thr Gln Lys Ala Pro Lys Arg Ile Arg Leu Pro His Ile 1 5 10 15 Arg Glu Asp Asp Gln Pro Ser Ser His Gln Pro Leu Phe Tyr 20 25 30 <210> 19 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 19 Gln Pro Pro Leu Glu Ala Pro Tyr Val Pro Pro Arg Tyr Leu Ala Pro 1 5 10 15 Thr Glu Gly Arg Asn Ser Ile Arg Tyr Ser Glu Leu Thr Pro Leu Tyr 20 25 30 Asp Thr Thr Arg Leu Tyr Leu Val Asp Asn Lys Ser Ala Asp Ile Ala 35 40 45 Ser Leu Asn Tyr Gln Asn Asp His 50 55 <210> 20 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 20 Ser Gly Ser Arg Glu Ser Gly Ser Arg Glu Ser Gly Ser Arg Glu Ser 1 5 10 15 Gly Ser Arg Glu Val Arg Glu Ser Gly Val Arg Glu Thr Glu Val Gln 20 25 30 Val Val Arg Val Arg Gln Glu Ser Gly Gly Arg Val Thr Ala Pro Ser 35 40 45 Glu Ser Arg Lys Lys Phe Leu Asp 50 55 <210> twenty one <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> twenty one Gln Asn Leu Pro Gly Asn Asp Asn Ser Thr Ala Thr Leu Cys Leu Gly 1 5 10 15 His His Ala Val Pro Asn Gly Thr Leu Val Lys Thr Ile Thr Asn Asp 20 25 30 Gln Ile Glu Val Thr Asn Ala Thr Glu Leu Val Gln Ser Ser Ser Thr 35 40 45 Gly Arg Ile Cys Asp Ser Pro His 50 55 <210> twenty two <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> twenty two Thr Glu Leu Tyr Thr Ser Ala Ala Ser Arg Lys Pro Asp Pro Ala Val 1 5 10 15 Ala Pro Thr Ser Ala Ala Ser Arg Lys Pro Asp Pro Ala Val Ala Pro 20 25 30 Thr Ser Ala Ala Thr Arg Lys Pro Asp Pro Ala Val Ala Pro Thr Ser 35 40 45 Ala Ala Thr Arg Lys Pro Asp Pro 50 55 <210> twenty three <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> twenty three Leu Ser Ser Met Ala Val Thr Phe Lys Arg Ala Leu Gly Gly Arg Ala 1 5 10 15 Lys Gln Pro Pro Pro Arg Glu Thr Pro Gln Arg Pro Pro Arg Pro Pro 20 25 30 Thr Pro Glu Leu Val Lys Lys Ile Pro Pro Pro Pro Pro Asn Gly Glu 35 40 45 Asp Glu Leu Val Val Ser Tyr Ser 50 55 <210> twenty four <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> twenty four Met Lys Met Ala Ser Asn Asp Ala Ser Ala Ala Ala Val Ala Asn Ser 1 5 10 15 Asn Asn Asp Thr Ala Lys Ser Ser Ser Asp Gly Val Leu Ser Ser Met 20 25 30 Ala Ile Thr Phe Lys Arg Ala Leu Gly Ala Arg Pro Lys Gln Pro Pro 35 40 45 Pro Arg Glu Ile Leu Gln Arg Pro 50 55 <210> 25 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 25 Met Asp Gly Thr Leu Phe Pro Gly Asp Asp Asp Leu Ala Ile Pro Ala 1 5 10 15 Thr Glu Phe Phe Ser Thr Lys Ala Asp Lys Lys Pro Glu Ala Lys Arg 20 25 30 Glu Ala Ile Val Lys Ala Asp Glu Asp Asp Asn Glu Glu Thr Leu Lys 35 40 45 Gln Arg Leu Thr Asn Leu Glu Lys 50 55 <210> 26 <211> 49 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 26 Asp Ala Asp Asp His Ala Ala Ser Phe Gly Gly Leu Ala Ala Ala Ala 1 5 10 15 Ala Gly Ala Ala Gly Val Ala Arg Lys Arg Ala Phe His Gly Asp Asp 20 25 30 Pro Phe Gly Glu Gly Pro Pro Glu Lys Lys Asp Leu Thr Leu Asp Met 35 40 45 Leu <210> 27 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 27 Lys Gly Ile Ile Ala Gln Asn Pro Ile Glu Asn Tyr Val Asp Glu Val 1 5 10 15 Leu Asn Glu Val Leu Val Val Pro Asn Ile Asn Ser Ser His Pro Thr 20 25 30 Thr Ser Asn Ser Ala Pro Ala Leu Asp Ala Ala Glu Thr Gly His Thr 35 40 45 Ser Asn Val Gln Pro Glu Asp Val 50 55 <210> 28 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 28 Met Gly Ser Lys Cys Cys Lys Thr Ile His Gly Gly Ile Phe Ser Lys 1 5 10 15 Ala Glu Asp Thr Leu Val Asp Tyr Lys Gly Lys Tyr Ile Asn Leu Glu 20 25 30 Lys Glu Phe Ser Ala Leu Ser Asp Thr Glu Ser Glu Glu Glu Leu Gln 35 40 45 Leu Glu Lys Pro Leu Leu Asn Lys 50 55 <210> 29 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 29 Met Asp Phe Met Ser Lys Tyr Ser Lys Glu Leu Val Leu Thr Ala Lys 1 5 10 15 Asn Ile Lys Asp Glu Glu Pro Asn Leu Asn Lys Lys Glu Thr Ser Phe 20 25 30 Asp Leu Ser Thr Tyr Leu Lys Thr Lys Glu Thr His Tyr Gln Lys Lys 35 40 45 Ile Arg Asp Gln Leu Ala Glu Lys 50 55 <210> 30 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 30 Ile Asp Asn Thr Val Arg Glu Thr Val Gly Ala Ala Thr Ser Arg Asp 1 5 10 15 Ala Leu Pro Asn Thr Glu Ala Ser Gly Pro Ala His Ser Lys Glu Ile 20 25 30 Pro Ala Leu Thr Ala Val Glu Thr Gly Ala Thr Asn Pro Leu Val Pro 35 40 45 Ser Asp Thr Val Gln Thr Arg His 50 55 <210> 31 <211> 39 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 31 Arg Leu Asn Lys Arg Leu Asn Asp Lys Lys Lys Gln Gly Ser Gln Pro 1 5 10 15 Ser Thr Asn Pro Thr Asn Arg Thr Asn Gln Asp Glu Ile Asp Asp Leu 20 25 30 Phe Asn Ala Phe Gly Ser Asn 35 <210> 32 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 32 Thr Thr Asn Ala Thr Gln Lys Ile Glu Ser Thr Thr Phe Thr Thr Ile 1 5 10 15 Gly Ile Lys Glu Ile Asn Gly Asn Thr Tyr Ser Ser Pro Lys Asn Ser 20 25 30 Ile Tyr Leu Lys Ser Lys Ser Gln Gln Ser Thr Thr Lys Phe Thr Asp 35 40 45 Ala Glu His Thr Thr Pro Ile Leu 50 55 <210> 33 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 33 Met Ser Thr Asn Gly Lys Pro Gln Arg Lys Thr Lys Arg Asn Thr Asn 1 5 10 15 Arg Arg Pro Gln Asp Val Lys Phe Pro Gly Gly Gly Gln Ile Val Gly 20 25 30 Gly Val Tyr Leu Leu Pro Arg Arg Gly Pro Arg Leu Gly Val Arg Ala 35 40 45 Thr Arg Lys Thr Trp Glu Arg Ser 50 55 <210> 34 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 34 Met Ser Thr Asn Pro Lys Pro Gln Lys Lys Asn Lys Arg Asn Thr Asn 1 5 10 15 Arg Arg Pro Gln Asp Val Lys Phe Pro Gly Gly Gly Gln Ile Val Gly 20 25 30 Gly Val Tyr Leu Leu Pro Arg Arg Gly Pro Arg Leu Gly Val Arg Ala 35 40 45 Thr Arg Lys Thr Ser Glu Arg Ser 50 55 <210> 35 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 35 Met Ser Thr Asn Pro Lys Pro Gln Arg Gln Thr Lys Arg Asn Thr Asn 1 5 10 15 Arg Arg Pro Gln Asp Val Lys Phe Pro Gly Gly Gly Gln Ile Val Gly 20 25 30 Gly Val Tyr Leu Leu Pro Arg Arg Gly Pro Arg Leu Gly Val Arg Ala 35 40 45 Thr Arg Lys Thr Ser Glu Arg Ser 50 55 <210> 36 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 36 Asn Ile Thr Arg Val Glu Ala Glu Asn Lys Val Glu Ile Leu Asp Cys 1 5 10 15 Phe Lys Pro Leu Lys Glu Glu Glu Asp Asp Arg Glu Ile Ser Val Ser 20 25 30 Ala Asp Cys Phe Lys Lys Gly Pro Ala Phe Pro Pro Ala Leu Pro Val 35 40 45 Trp Ala Arg Pro Gly Tyr Asp Pro 50 55 <210> 37 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 37 Val Arg Leu Pro His Ile Tyr His Glu Gly Val Phe Ile Pro Gly Thr 1 5 10 15 Tyr Lys Ile Val Ile Asp Lys Lys Asn Lys Leu Asn Asp Arg Cys Thr 20 25 30 Leu Phe Thr Asp Cys Val Ile Lys Gly Arg Glu Val Arg Lys Gly Gln 35 40 45 Ser Val Leu Arg Gln Tyr Lys Thr 50 55 <210> 38 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 38 Met Ser Thr Ile Pro Lys Pro Gln Arg Lys Thr Lys Arg Asn Thr Asn 1 5 10 15 Arg Arg Pro Gln Asp Val Lys Phe Pro Gly Gly Gly Gln Ile Val Gly 20 25 30 Gly Val Tyr Leu Leu Pro Arg Arg Gly Pro Arg Leu Gly Val Arg Ala 35 40 45 Thr Arg Lys Thr Ser Glu Arg Ser 50 55 <210> 39 <211> 28 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 39 Ser Ser Ala Gly Leu Lys Asn Asp Leu Leu Glu Asn Leu Gln Ala Tyr 1 5 10 15 Gln Lys Arg Met Gly Val Gln Met Gln Arg Phe Lys 20 25 <210> 40 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 40 Ile Thr Arg Val Glu Ser Glu Asn Lys Ile Val Val Leu Asp Ser Phe 1 5 10 15 Asp Pro Leu Val Ala Glu Glu Asp Asp Arg Glu Ile Ser Ile Pro Ala 20 25 30 Glu Ile Leu Arg Lys Phe Lys Gln Phe Pro Pro Ala Met Pro Ile Trp 35 40 45 Ala Arg Pro Asp Tyr Asn Pro Pro 50 55 <210> 41 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 41 Val Lys Lys Arg Glu Asn Met Phe Ile Asp Glu Arg Pro Gly Asn Arg 1 5 10 15 Asn Pro Tyr Glu Asn Leu Leu Tyr Lys Leu Cys Leu Ser Gly Glu Gly 20 25 30 Trp Pro Tyr Ile Gly Ser Arg Ser Gln Val Lys Gly Arg Ser Trp Glu 35 40 45 Asn Thr Thr Val Asp Leu Ser Leu 50 55 <210> 42 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 42 Glu Asp Ile Glu Thr Asp Thr Asp Ile Glu Ser Thr Glu Asp Glu Asp 1 5 10 15 Glu Ala Asp Arg Phe Asp Ile Ile Asp Thr Ser Asp Glu Glu Asp Glu 20 25 30 Asn Glu Thr Asp Arg Val Thr Leu Leu Ser Thr Leu Val Asn Gln Gly 35 40 45 Met Thr Met Thr Arg Ala Thr Arg 50 55 <210> 43 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 43 Met Ala Pro Lys Lys Lys Leu Gln Leu Pro Pro Pro Pro Thr Asp Glu 1 5 10 15 Glu Glu Tyr Trp Asp Ser Gln Ala Glu Glu Val Leu Asp Glu Glu Glu 20 25 30 Glu Asp Met Met Glu Asp Trp Glu Ser Leu Asp Glu Glu Ala Ser Glu 35 40 45 Val Glu Glu Val Ser Asp Glu Thr 50 55 <210> 44 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 44 Glu Pro Pro Ala Gly Ile Leu Ala Gly Pro Gln Val Lys Pro Gln Glu 1 5 10 15 Lys Pro Pro Ala Glu Pro Pro Ala Gly Leu Pro Ala Gly Pro Gln Ala 20 25 30 Lys Pro Pro Val Lys Pro Gln Ala Lys Pro Pro Ala Glu Pro Pro Val 35 40 45 Gly Ile Leu Ala Gly Pro Gln Ala 50 55 <210> 45 <211> 36 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 45 Thr Ala Ser Gly Glu Glu Val Ala Val Leu Ser His His Asp Ser Leu 1 5 10 15 Glu Ser Arg Arg Leu Arg Glu Glu Glu Asp Asp Asp Asp Asp Glu Asp 20 25 30 Phe Glu Asp Ala 35 <210> 46 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 46 Gly Ser Ser Thr Thr Ser Gly Val Thr Ser Gly Glu Ala Ala Glu Ser 1 5 10 15 Ser Pro Ala Pro Ser Cys Asp Gly Glu Leu Asp Ser Glu Ala Glu Ser 20 25 30 Tyr Ser Ser Met Pro Pro Leu Glu Gly Glu Pro Gly Asp Pro Asp Leu 35 40 45 Ser Asp Gly Ser Trp Ser Thr Val 50 55 <210> 47 <211> 39 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 47 Leu Asp Gly Gln Thr Gly Thr Gln Asp Lys Gly Gln Lys Pro Asn Leu 1 5 10 15 Leu Asp Arg Leu Arg His Arg Lys Asn Gly Tyr Arg His Leu Lys Asp 20 25 30 Ser Asp Glu Glu Glu Asn Val 35 <210> 48 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 48 Thr Gly Ser Ser Gln Ala Ala Pro Ser Ser Ser Ser Ser Val Ala Pro Val 1 5 10 15 Ala Ser Leu Ser Gly Asp Leu Glu Glu Glu Glu Glu Gly Ser Arg Glu 20 25 30 Ser Pro Ser Leu Pro Ser Ser Lys Lys Gly Ala Asp Glu Phe Glu Ala 35 40 45 Trp Leu Glu Ala Gln Asp Ala Asn 50 55 <210> 49 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 49 Gln His Phe Arg Lys Leu Leu Leu Leu Asp Glu Glu Ala Gly Pro Leu 1 5 10 15 Glu Glu Glu Leu Pro Arg Leu Ala Asp Glu Gly Leu Asn Arg Arg Val 20 25 30 Ala Glu Asp Leu Asn Leu Gly Asn Leu Asn Val Ser Ile Pro Trp Thr 35 40 45 His Lys Val Gly Asn Phe Thr Gly 50 55 <210> 50 <211> 46 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 50 Pro Ser Met Gln Gly Ile Pro Glu Ser Arg Phe Thr Arg Thr Gly Glu 1 5 10 15 Gly Leu Asp Val Arg Gly Ser Arg Gly Phe Pro Gln Asp Ile Leu Phe 20 25 30 Pro Ser Asp Pro Pro Phe Ser Pro Gln Ser Cys Arg Pro Gln 35 40 45 <210> 51 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 51 Val Ile Val Gly Arg Ile Ile Leu Ser Gly Lys Pro Ala Val Val Pro 1 5 10 15 Asp Arg Glu Val Leu Tyr Gln Glu Phe Asp Glu Met Glu Glu Cys Ala 20 25 30 Ser Gln Leu Pro Tyr Ile Glu Gln Gly Met Gln Leu Ala Glu Gln Phe 35 40 45 Lys Gln Lys Ala Leu Gly Leu Leu 50 55 <210> 52 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 52 Gly Gly Asn Asn Ser Gly Ser Gly Ala Glu Glu Asn Ser Asn Ala Ala 1 5 10 15 Ala Ala Ala Met Gln Pro Val Glu Asp Met Asn Asp His Ala Ile Arg 20 25 30 Gly Asp Thr Phe Ala Thr Arg Ala Glu Glu Lys Arg Ala Glu Ala Glu 35 40 45 Ala Ala Ala Glu Ala Ala Ala Pro 50 55 <210> 53 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 53 Thr Gly Gln Val Tyr Leu Leu Ser Phe Ile Ser Ala Cys Pro Asp Phe 1 5 10 15 Lys Leu Arg Leu Met Lys Asp Thr Gln Thr Ile Ser Gln Thr Val Ala 20 25 30 Leu Thr Glu Gly Leu Gly Asp Glu Leu Glu Glu Val Ile Val Glu Lys 35 40 45 Thr Lys Gln Thr Val Ala Ser Ile 50 55 <210> 54 <211> 30 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 54 Asn Phe Ser Ser Leu Gly Leu Thr Asp Glu Glu Lys Glu Ala Ala Glu 1 5 10 15 His Phe Leu Asn Val Ser Asp Asp Ser Gln Asn Asp Tyr Glu 20 25 30 <210> 55 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 55 Gln Val Glu Pro Thr Ala Ala Asn Thr Asn Ala Ser Glu His Arg Leu 1 5 10 15 Gly Thr Gly Leu Val Pro Ala Leu Gln Ala Ala Glu Thr Gly Ala Ser 20 25 30 Ser Asn Ala Gln Asp Glu Asn Leu Ile Glu Thr Arg Cys Val Leu Asn 35 40 45 His His Ser Thr Gln Glu Thr Thr 50 55 <210> 56 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 56 Glu Gly Val Leu Arg Cys Tyr His Gly Leu Glu Met Ile Gln Lys Glu 1 5 10 15 Gln Leu Val Glu Met Asp Val Ala Ser Glu Asn Ala Gln Arg Ala Leu 20 25 30 Lys Glu His Pro Ser Arg Ala Lys Val Val Gln Asn Arg Trp Gly Arg 35 40 45 Ser Val Val Gln Leu Lys Asn Asp 50 55 <210> 57 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 57 Thr Gly Gln Val His Leu Leu Ser Phe Ile Ser Ala Cys Pro Asp Phe 1 5 10 15 Lys Leu Arg Leu Met Lys Asp Thr Gln Thr Ile Ser Gln Thr Asp Ala 20 25 30 Leu Thr Glu Gly Leu Gly Asp Glu Leu Glu Glu Val Ile Val Glu Lys 35 40 45 Thr Lys Gln Thr Leu Ala Ser Val 50 55 <210> 58 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 58 Glu Glu Gln Glu Gln Glu Leu Glu Glu Gln Glu Gln Glu Leu Glu Glu 1 5 10 15 Gln Glu Gln Glu Leu Glu Glu Gln Glu Gln Glu Leu Glu Glu Gln Glu 20 25 30 Gln Glu Leu Glu Glu Gln Glu Gln Glu Leu Glu Glu Gln Glu Gln Glu 35 40 45 Leu Glu Glu Gln Glu Gln Glu Leu 50 55 <210> 59 <211> 56 <212> PRT <213> artificial sequence <220> <223> synthetic peptide table <400> 59 Ala Gln Ala Gln Gln Ala Gln Gln Ala Gln Ala Gln Gln Ala Gln Gln 1 5 10 15 Ala Gln Gln Ala Gln Gln Ala Gln Gln Ala Gln Gln Ala Gln Gln Ala 20 25 30 Gln Ala Gln Gln Ala Gln Gln Ala Gln Gln Ala Gln Ala Gln Gln Ala 35 40 45 Gln Ala Gln Gln Ala Gln Ala Gln 50 55 <210> 60 <211> 23 <212> PRT <213> artificial sequence <220> <223> synthetic peptide table <400> 60 Ser Gly Ser Gly Pro Arg His Arg Asp Gly Ala Arg Arg Pro Pro Lys 1 5 10 15 Arg Pro Ser Cys Ile Gly Cys 20 <210> 61 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 61 Ser Ala Ile Gly Asn Thr Ile Glu Ala Leu Phe Gln Gly Pro Pro Lys 1 5 10 15 Phe Arg Pro Ile Arg Ile Ser Leu Glu Glu Lys Pro Ala Pro Asp Ala 20 25 30 Ile Ser Asp Leu Leu Ala Ser Val Asp Ser Glu Glu Val Arg Gln Tyr 35 40 45 Cys Arg Glu Gln Gly Trp Ile Ile 50 55 <210> 62 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 62 Met Ser Thr Asn Pro Lys Pro Gln Arg Lys Thr Lys Arg Asn Thr Asn 1 5 10 15 Arg Arg Pro Gln Asp Val Lys Phe Pro Gly Gly Gly Gln Ile Val Gly 20 25 30 Gly Val Tyr Leu Leu Pro Arg Arg Gly Pro Arg Leu Gly Val Arg Ala 35 40 45 Ala Arg Lys Thr Ser Glu Arg Ser 50 55 <210> 63 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 63 Met Ser Thr Asn Pro Lys Pro Gln Arg Lys Thr Lys Arg Asn Thr Asn 1 5 10 15 Arg Arg Pro Gln Asp Val Lys Phe Pro Gly Gly Gly Gln Ile Val Gly 20 25 30 Gly Val Tyr Leu Leu Pro Arg Arg Gly Pro Arg Leu Gly Val Arg Ala 35 40 45 Thr Arg Lys Thr Ser Glu Arg Ser 50 55 <210> 64 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 64 Met Ser Thr Asn Pro Lys Pro Gln Arg Lys Thr Lys Arg Asn Thr Asn 1 5 10 15 Arg Arg Pro Gln Asp Val Lys Phe Pro Gly Gly Gly Gln Ile Val Gly 20 25 30 Gly Val Tyr Leu Leu Pro Arg Arg Gly Pro Arg Leu Gly Val Arg Ala 35 40 45 Thr Arg Lys Thr Ser Glu Arg Ser 50 55 <210> 65 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 65 Met Ser Thr Asn Pro Lys Pro Gln Arg Lys Thr Lys Arg Asn Thr Asn 1 5 10 15 Arg Arg Pro Gln Asp Val Lys Phe Pro Gly Gly Gly Gln Ile Val Gly 20 25 30 Gly Val Tyr Leu Leu Pro Arg Arg Gly Pro Arg Leu Gly Val Arg Ala 35 40 45 Thr Arg Lys Thr Ser Glu Arg Ser 50 55 <210> 66 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 66 Met Ser Thr Asn Pro Lys Pro Gln Arg Lys Thr Lys Arg Asn Thr Asn 1 5 10 15 Arg Arg Pro Glu Asp Val Lys Phe Pro Gly Gly Gly Gln Ile Val Gly 20 25 30 Gly Val Tyr Leu Leu Pro Arg Arg Gly Pro Arg Leu Gly Val Arg Thr 35 40 45 Thr Arg Lys Thr Ser Glu Arg Ser 50 55 <210> 67 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 67 Met Ser Thr Leu Pro Lys Pro Gln Arg Lys Thr Lys Arg Asn Thr Ile 1 5 10 15 Arg Arg Pro Gln Asp Val Lys Phe Pro Gly Gly Gly Gln Ile Val Gly 20 25 30 Gly Val Tyr Val Leu Pro Arg Arg Gly Pro Arg Leu Gly Val Arg Ala 35 40 45 Thr Arg Lys Thr Ser Glu Arg Ser 50 55 <210> 68 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 68 Met Ser Thr Leu Pro Lys Pro Gln Arg Ile Thr Lys Arg Asn Ile Asn 1 5 10 15 Arg Arg Pro Gln Asp Val Lys Phe Pro Gly Gly Gly Gln Ile Val Gly 20 25 30 Gly Val Tyr Val Leu Pro Arg Arg Gly Pro Lys Leu Gly Val Arg Ala 35 40 45 Val Arg Lys Thr Ser Glu Arg Ser 50 55 <210> 69 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 69 Met Ser Thr Leu Pro Lys Pro Lys Arg Gln Thr Lys Arg Asn Thr Leu 1 5 10 15 Arg Arg Pro Lys Asn Val Lys Phe Pro Ala Gly Gly Gln Ile Val Gly 20 25 30 Glu Val Tyr Val Leu Pro Arg Arg Gly Pro Gln Leu Gly Val Arg Glu 35 40 45 Val Arg Lys Thr Ser Glu Arg Ser 50 55 <210> 70 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 70 Gln Ile Val Gly Gly Val Tyr Leu Leu Pro Arg Arg Gly Pro Arg Leu 1 5 10 15 Gly Val Arg Ala Ala Arg Lys Thr Ser Glu Arg Ser Gln Pro Arg Gly 20 25 30 Arg Arg Gln Pro Ile Pro Lys Asp Arg Arg Ser Thr Gly Lys Ser Trp 35 40 45 Gly Arg Pro Gly Tyr Pro Trp Pro 50 55 <210> 71 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 71 Gln Ile Val Gly Gly Val Tyr Leu Leu Pro Arg Arg Gly Pro Arg Leu 1 5 10 15 Gly Val Arg Ala Thr Arg Lys Thr Ser Glu Arg Ser Gln Pro Arg Gly 20 25 30 Arg Arg Gln Pro Ile Pro Lys Asp Arg Arg Ser Thr Gly Lys Ser Trp 35 40 45 Gly Lys Pro Gly Tyr Pro Trp Pro 50 55 <210> 72 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 72 Gln Ile Val Gly Gly Val Tyr Leu Leu Pro Arg Arg Gly Pro Arg Leu 1 5 10 15 Gly Val Arg Ala Thr Arg Lys Thr Ser Glu Arg Ser Gln Pro Arg Gly 20 25 30 Arg Arg Gln Pro Ile Pro Lys Asp Arg Arg Ser Thr Gly Lys Ser Trp 35 40 45 Gly Lys Pro Gly Tyr Pro Trp Pro 50 55 <210> 73 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 73 Gln Ile Val Gly Glu Val Tyr Val Leu Pro Arg Arg Gly Pro Gln Leu 1 5 10 15 Gly Val Arg Glu Val Arg Lys Thr Ser Glu Arg Ser Gln Pro Arg Gly 20 25 30 Arg Arg Gln Pro Thr Pro Lys Ala Arg Pro Arg Glu Gly Arg Ser Trp 35 40 45 Ala Gln Pro Gly Tyr Pro Trp Pro 50 55 <210> 74 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 74 Gln Ile Val Gly Gly Val Tyr Leu Leu Pro Arg Arg Gly Pro Arg Leu 1 5 10 15 Gly Val Arg Thr Thr Arg Lys Thr Ser Glu Arg Ser Gln Pro Arg Gly 20 25 30 Arg Arg Gln Pro Ile Pro Lys Asp Arg Arg Ser Thr Gly Lys Ala Trp 35 40 45 Gly Lys Pro Gly Arg Pro Trp Pro 50 55 <210> 75 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 75 Gln Pro Arg Gly Arg Arg Gln Pro Thr Pro Lys Ala Arg Pro Arg Glu 1 5 10 15 Gly Arg Ser Trp Ala Gln Pro Gly Tyr Pro Trp Pro Leu Tyr Gly Asn 20 25 30 Glu Gly Cys Gly Trp Ala Gly Trp Leu Leu Pro Pro Arg Gly Ser Arg 35 40 45 Pro Ser Trp Gly Gln Asn Asp Pro 50 55 <210> 76 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 76 Gln Pro Arg Gly Arg Arg Gln Pro Ile Pro Lys Asp Arg Arg Ser Thr 1 5 10 15 Gly Lys Ser Trp Gly Lys Pro Gly Tyr Pro Trp Pro Leu Tyr Gly Asn 20 25 30 Glu Gly Leu Gly Trp Ala Gly Trp Leu Leu Ser Pro Arg Gly Ser Arg 35 40 45 Pro Ser Trp Gly Pro Asn Asp Pro 50 55 <210> 77 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 77 Gln Pro Arg Gly Arg Arg Gln Pro Ile Pro Lys Ala Arg Arg Ser Glu 1 5 10 15 Gly Arg Ser Trp Ala Gln Pro Gly Tyr Pro Trp Pro Leu Tyr Gly Asn 20 25 30 Glu Gly Cys Gly Trp Ala Gly Trp Leu Leu Ser Pro Arg Gly Ser Arg 35 40 45 Pro Ser Trp Gly Pro Asn Asp Pro 50 55 <210> 78 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 78 Leu Tyr Gly Asn Glu Gly Leu Gly Trp Ala Gly Trp Leu Leu Ser Pro 1 5 10 15 Arg Gly Ser Arg Pro Ser Trp Gly Pro Thr Asp Pro Arg His Arg Ser 20 25 30 Arg Asn Val Gly Lys Val Ile Asp Thr Leu Thr Cys Gly Phe Ala Asp 35 40 45 Leu Met Gly Tyr Ile Pro Val Val 50 55 <210> 79 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 79 Leu Tyr Gly Asn Glu Gly Leu Gly Trp Ala Gly Trp Leu Leu Ser Pro 1 5 10 15 Arg Gly Ser Arg Pro Ser Trp Gly Pro Asn Asp Pro Arg His Arg Ser 20 25 30 Arg Asn Val Gly Lys Val Ile Asp Thr Leu Thr Cys Gly Phe Ala Asp 35 40 45 Leu Met Gly Tyr Ile Pro Val Val 50 55 <210> 80 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 80 Leu Tyr Gly Asn Glu Gly Cys Gly Trp Ala Gly Trp Leu Leu Ser Pro 1 5 10 15 Arg Gly Ser Arg Pro Thr Trp Gly Pro Ser Asp Pro Arg His Arg Ser 20 25 30 Arg Asn Leu Gly Arg Val Ile Asp Thr Ile Thr Cys Gly Phe Ala Asp 35 40 45 Leu Met Gly Tyr Ile Pro Val Val 50 55 <210> 81 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 81 Leu Tyr Gly Asn Glu Gly Leu Gly Trp Ala Gly Trp Leu Leu Ser Pro 1 5 10 15 Arg Gly Ser Arg Pro Ser Trp Gly Pro Thr Asp Pro Arg His Arg Ser 20 25 30 Arg Asn Leu Gly Lys Val Ile Asp Thr Leu Thr Cys Gly Phe Ala Asp 35 40 45 Leu Met Gly Tyr Ile Pro Val Val 50 55 <210> 82 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 82 His Ile Asn Arg Thr Ala Leu Asn Cys Asn Asp Ser Leu Glu Thr Gly 1 5 10 15 Phe Leu Ala Ala Leu Phe Tyr Thr Ser Ser Ser Phe Asn Ser Ser Gly Cys 20 25 30 Pro Glu Arg Leu Ala Ala Cys Arg Ser Ile Glu Ser Phe Arg Ile Gly 35 40 45 Trp Gly Ser Leu Glu Tyr Glu Glu 50 55 <210> 83 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 83 Gln Ala Ala Cys Asn Phe Thr Arg Gly Asp Arg Cys Asn Leu Glu Asp 1 5 10 15 Arg Asp Arg Ser Gln Leu Ser Pro Leu Leu His Ser Thr Thr Glu Trp 20 25 30 Ala Ile Leu Pro Cys Ser Tyr Thr Asp Leu Pro Ala Leu Ser Thr Gly 35 40 45 Leu Leu His Leu His Gln Asn Ile 50 55 <210> 84 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 84 Cys Gly Pro Val Tyr Cys Phe Thr Pro Ser Pro Val Val Val Gly Thr 1 5 10 15 Thr Asp Arg Ala Gly Ala Pro Thr Tyr Asn Trp Gly Glu Asn Glu Thr 20 25 30 Asp Val Phe Leu Leu Asn Ser Thr Arg Pro Pro Lys Gly Ala Trp Phe 35 40 45 Gly Cys Thr Trp Met Asn Gly Thr 50 55 <210> 85 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 85 Cys Gly Pro Val Tyr Cys Phe Thr Pro Ser Pro Val Val Val Gly Thr 1 5 10 15 Thr Asp Arg Arg Gly Val Pro Thr Tyr Thr Trp Gly Glu Asn Asp Thr 20 25 30 Asp Val Phe Leu Leu Asn Ser Thr Arg Pro Pro Arg Gly Ala Trp Phe 35 40 45 Gly Cys Thr Trp Met Asn Ser Thr 50 55 <210> 86 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 86 Cys Gly Pro Val Tyr Cys Phe Thr Pro Ser Pro Val Val Val Gly Thr 1 5 10 15 Thr Asp Arg Gln Gly Val Pro Thr Tyr Asn Trp Gly Asp Asn Glu Thr 20 25 30 Asp Val Phe Leu Leu Asn Ser Thr Arg Pro Pro Arg Gly Ala Trp Phe 35 40 45 Gly Cys Thr Trp Met Asn Gly Thr 50 55 <210> 87 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 87 Gly Phe Thr Lys Thr Cys Gly Ala Pro Pro Cys Arg Ile Arg Lys Asp 1 5 10 15 Tyr Asn Ser Thr Ile Asp Leu Leu Cys Pro Thr Asp Cys Phe Arg Lys 20 25 30 His Pro Asp Ala Thr Tyr Leu Lys Cys Gly Ala Gly Pro Trp Leu Thr 35 40 45 Pro Arg Cys Leu Val Asp Tyr Pro 50 55 <210> 88 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 88 Thr Gly Cys Ile Ser Ile Ile Gly Arg Ile His Leu Asn Asp Gln Val 1 5 10 15 Val Val Ala Pro Asp Lys Glu Ile Leu Tyr Glu Ala Phe Asp Glu Met 20 25 30 Glu Glu Cys Ala Ser Lys Ala Ala Leu Ile Glu Glu Gly Gln Arg Met 35 40 45 Ala Glu Met Leu Lys Ser Lys Ile 50 55 <210> 89 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 89 Gly Ser Phe Ser Tyr Val Thr Gly Leu Thr Ser Asp Asn Leu Lys Val 1 5 10 15 Pro Cys Gln Val Pro Ala Pro Glu Phe Phe Ser Trp Val Asp Gly Val 20 25 30 Gln Ile His Arg Phe Ala Pro Val Pro Gly Pro Phe Phe Arg Asp Glu 35 40 45 Val Thr Phe Thr Val Gly Leu Asn 50 55 <210> 90 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 90 Ser Leu Val Val Gly Ser Gln Leu Pro Cys Asp Pro Glu Pro Asp Thr 1 5 10 15 Glu Val Leu Ala Ser Met Leu Thr Asp Pro Ser His Ile Thr Ala Glu 20 25 30 Thr Ala Ala Arg Arg Leu Ala Arg Gly Ser Pro Pro Ser Gln Ala Ser 35 40 45 Ser Ser Ala Ser Gln Leu Ser Ala 50 55 <210> 91 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 91 Thr Gly Ala Leu Ile Thr Pro Cys Ser Ala Glu Glu Glu Lys Leu Pro 1 5 10 15 Ile Ser Pro Leu Ser Asn Ser Leu Leu Arg His His Asn Leu Val Tyr 20 25 30 Ser Thr Ser Ser Arg Ser Ala Ser Gln Arg Gln Lys Lys Val Thr Phe 35 40 45 Asp Arg Leu Gln Val Leu Asp Asp 50 55 <210> 92 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 92 Ala Leu Ile Thr Pro Cys Ala Ala Glu Glu Glu Lys Leu Pro Ile Ser 1 5 10 15 Pro Leu Ser Asn Ser Leu Leu Arg His His Asn Leu Val Tyr Ser Thr 20 25 30 Ser Ser Arg Ser Ala Ala Gln Arg Gln Lys Lys Val Thr Phe Asp Arg 35 40 45 Leu Gln Val Leu Asp Asp His Tyr 50 55 <210> 93 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 93 Ile Asn Pro Leu Ser Asn Ser Leu Met Arg Phe His Asn Lys Val Tyr 1 5 10 15 Ser Thr Thr Ser Arg Ser Ala Ser Leu Arg Ala Lys Lys Val Thr Phe 20 25 30 Asp Arg Val Gln Val Leu Asp Ala His Tyr Asp Ser Val Leu Gln Asp 35 40 45 Val Lys Arg Ala Ala Ser Lys Val 50 55 <210> 94 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 94 Asn Thr Thr Leu Lys Glu Ile Lys Glu Leu Ala Ser Gly Val Lys Ala 1 5 10 15 Glu Leu Leu Ser Val Glu Glu Ala Cys Arg Leu Val Pro Ser His Ser 20 25 30 Ala Arg Ser Lys Phe Gly Tyr Gly Ala Lys Glu Val Arg Ser Leu Ser 35 40 45 Ser Lys Ala Ile Asn His Ile Asn 50 55 <210> 95 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 95 Leu Val Pro Pro His Ser Ala Arg Ser Lys Phe Gly Tyr Ser Ala Lys 1 5 10 15 Asp Val Arg Ser Leu Ser Ser Lys Ala Ile Asn Gln Ile Arg Ser Val 20 25 30 Trp Glu Asp Leu Leu Glu Asp Thr Thr Thr Pro Ile Pro Thr Thr Ile 35 40 45 Met Ala Lys Asn Glu Val Phe Cys 50 55 <210> 96 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 96 Ser Ala Arg Leu Leu Thr Val Glu Glu Ala Cys Ala Leu Thr Pro Pro 1 5 10 15 His Ser Ala Lys Ser Arg Tyr Gly Phe Gly Ala Lys Glu Val Arg Ser 20 25 30 Leu Ser Arg Arg Ala Val Asn His Ile Arg Ser Val Trp Glu Asp Leu 35 40 45 Leu Glu Asp Gln His Thr Pro Ile 50 55 <210> 97 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 97 Ser Ala Arg Leu Leu Thr Leu Glu Glu Ala Cys Gln Leu Thr Pro Pro 1 5 10 15 His Ser Ala Arg Ser Lys Tyr Gly Phe Gly Ala Lys Glu Val Arg Ser 20 25 30 Leu Ser Gly Arg Ala Val Asn His Ile Lys Ser Val Trp Lys Asp Leu 35 40 45 Leu Glu Asp Pro Gln Thr Pro Ile 50 55 <210> 98 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 98 Ile Arg Ser Val Trp Glu Asp Leu Leu Glu Asp Thr Thr Thr Pro Ile 1 5 10 15 Pro Thr Thr Ile Met Ala Lys Asn Glu Val Phe Cys Val Asp Pro Ala 20 25 30 Lys Gly Gly Arg Lys Ala Ala Arg Leu Ile Val Tyr Pro Asp Leu Gly 35 40 45 Val Arg Val Cys Glu Lys Arg Ala 50 55 <210> 99 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 99 Ile Arg Ser Val Trp Glu Asp Leu Leu Glu Asp Thr Thr Thr Pro Ile 1 5 10 15 Pro Thr Thr Ile Met Ala Lys Asn Glu Val Phe Cys Val Asp Pro Ala 20 25 30 Lys Gly Gly Arg Lys Pro Ala Arg Leu Ile Val Tyr Pro Asp Leu Gly 35 40 45 Val Arg Val Cys Glu Lys Arg Ala 50 55 <210> 100 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 100 Glu Val Arg Ser Leu Ser Arg Arg Ala Val Asn His Ile Arg Ser Val 1 5 10 15 Trp Glu Asp Leu Leu Glu Asp Gln His Thr Pro Ile Asp Thr Thr Ile 20 25 30 Met Ala Lys Asn Glu Val Phe Cys Ile Asp Pro Thr Lys Gly Gly Lys 35 40 45 Lys Pro Ala Arg Leu Ile Val Tyr 50 55 <210> 101 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 101 Tyr Asp Thr Arg Cys Phe Asp Ser Thr Val Thr Glu Arg Asp Ile Arg 1 5 10 15 Thr Glu Glu Ser Ile Tyr Gln Ala Cys Ser Leu Pro Gln Glu Ala Arg 20 25 30 Thr Val Ile His Ser Leu Thr Glu Arg Leu Tyr Val Gly Gly Pro Met 35 40 45 Thr Asn Ser Lys Gly Gln Ser Cys 50 55 <210> 102 <211> 56 <212> PRT <213> Artificial sequence <220> <223> Synthetic peptide epitope <400> 102 Cys Lys Ala Ala Gly Ile Ile Ala Pro Thr Met Leu Val Cys Gly Asp 1 5 10 15 Asp Leu Val Val Ile Ser Glu Ser Gln Gly Thr Glu Glu Asp Glu Arg 20 25 30 Asn Leu Arg Ala Phe Thr Glu Ala Met Thr Arg Tyr Ser Ala Pro Pro 35 40 45 Gly Asp Pro Pro Arg Pro Glu Tyr 50 55

Claims

1. Use of antibodies against multiple viral epitopes for the preparation of reagents for use in a method for identifying a subject with early hepatocellular carcinoma (HCC), the method comprising: (i) detecting the presence or absence of antibodies against a plurality of viral epitopes in a sample obtained from the subject, wherein the plurality of viral epitopes include epitopes from 61 viruses listed in Table 5A, wherein the amino acid sequences of the viral epitopes are shown in SEQ ID NOs: 1-61; (ii) determining the presence of a viral exposure signature (VES) in a sample obtained from the subject when: (a) antibodies specific to epitopes of the following viruses are detected in the sample: hepatitis C virus (HCV) genotype 3b, Tr-Kj isolate; HCV genotype 1b, isolate from Taiwan, China; HCV genotype 1a, 1 isolate; human cytomegalovirus, AD169 strain; HCV genotype 6g, JK046 isolate; HCV genotype 1b, BK isolate; HCV genotype 1c, HC-G9 isolate; HCV genotype 1b, HC-J4 strain; HCV genotype 4a, ED43 isolate; hepatitis D virus; HCV genotype 5a, isolate EUH1480; human cytomegalovirus; Crimean-Congo hemorrhagic fever virus, Nigeria / IbAr10200 / 1970 strain; HCV genotype 1b, isolate HC-J1; influenza A virus, A / USSR / 90 / 1977 H1N1 strain; influenza A virus, A / Bangkok / 1 / 1979 H3N2 strain; HCV genotype 1c, Indian isolate; and Chapare virus, human / Bolivia / 810419 / 2003 isolate; and (b) antibodies specific for epitopes of the following viruses were not detected in the sample: Epstein-Barr virus, strain B95-8; human rhinovirus 23; HCMV, strain Towne; human herpesvirus 2 (HHV-2), strain HG52; human herpesvirus 3; varicella-zoster virus, strain Dumas; simian herpesvirus 16; Human adenovirus C serotype 2; human astrovirus-1; human respiratory syncytial virus; human herpesvirus 6B, strain Z29; human herpesvirus 7, strain JI; human rhinovirus 14; Lordsdale virus, strain GII / human / UK / Lordsdale / 1993; human herpesvirus 1, strain KOS; human metapneumovirus, strain CAN97-83; coxsackievirus A16, strain G-10; Epstein-Barr virus, AG876 strain; vaccinia virus; human herpesvirus 1, 17 strains; human adenovirus E serotype 4; human adenovirus F serotype 40; Tanapox virus; human adenovirus C serotype 5; rhinovirus B; human herpesvirus 8; human herpesvirus 6A, Uganda-1102 strain; human rhinovirus A serotype 89, 41467-Gallo strain; norovirus MD145, GII / human / USA / MD145-12 / 1987 strain; Molluscum contagiosum virus subtype 1; vaccinia virus, Copenhagen strain; poliovirus type 1, Sabin strain; aphthous stomatitis virus; HHV-2, strain 333; hepatitis B virus; Epstein-Barr virus, strain GD1; human parainfluenza virus 3, strain Wash / 47885 / 57; HHV-2; human enterovirus 71, strain BrCr; human herpesvirus 6A, strain GS; simian herpesvirus 1; influenza B virus, strain B / Yamagata / 16 / 1988; and influenza A virus, strain A / Philippines / 2 / 1982H3N2; and (iii) identifying that the subject has early-stage HCC when the VES is present.

2. The use according to claim 1, wherein the plurality of viral epitopes consists of epitopes of 61 viruses listed in Table 5A.

3. The use according to claim 1, wherein the sample is a blood or serum sample.

4. The method according to claim 1, wherein the antibody is detected by phage immunoprecipitation, immunoblotting or enzyme-linked immunosorbent assay.

5. The use according to claim 1, further comprising administering an appropriate therapy for preventing or treating HCC.

6. The use according to claim 5, wherein the appropriate therapy comprises vaccination against HBV, vaccination against HCV, administration of antiviral drugs, lifestyle changes or dietary adjustments.

7. The use according to claim 6, wherein the antiviral drug is a nucleoside analog, interferon or lamivudine.

8. The use according to claim 6, wherein the lifestyle or dietary changes include reducing or eliminating intravenous drug use, reducing or eliminating alcohol consumption, reducing aflatoxin exposure, or reducing iron overload.

9. The use according to claim 5, wherein the appropriate therapy comprises liver transplantation or liver resection.

10. The use according to claim 9, the method further comprising radiofrequency ablation.

11. The use according to claim 1, further comprising performing diagnostic monitoring on the subject with early-stage HCC every 3 months or every 6 months.

12. The use according to claim 11, wherein diagnostic monitoring comprises ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), or a combination thereof.

13. The use according to claim 1, wherein the subject has not been previously diagnosed with one or more of liver disease, hepatitis B virus (HBV) infection, hepatitis C virus (HCV) infection, hepatitis D virus (HDV) infection, non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), and hepatocellular carcinoma (HCC).

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