WO2008021163A2

WO2008021163A2 - Kits and methods for determining risk for primary liver cancer

Info

Publication number: WO2008021163A2
Application number: PCT/US2007/017690
Authority: WO
Inventors: Claus Fimmel; Yie-Hwa Chang
Original assignee: Saint Louis University
Priority date: 2006-08-09
Filing date: 2007-08-09
Publication date: 2008-02-21
Also published as: WO2008021163A3

Abstract

Methods and kits for diagnosing hepatocellular carcinoma are disclosed. The methods comprise detecting in a serum sample from a subject the quantity of at least one serum protein which is upregulated in patients with hepatocellular carcinoma. Kits of the present teachings include a capture antibody directed against a first epitope of a serum protein which is upregulated in patients with hepatocellular carcinoma, a detection antibody against a second epitope of the protein, and a labeled secondary protein directed against the detection antibody. The capture antibody can be immobilized on a solid support, such as a multiwell plate or a plastic bead.

Description

Kits and Methods for Determining Risk for Primary Liver

Cancer

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a non-provisional of Ser. No. 60/821,921 , filed August 9, 2006 which is incorporated herein by reference in its entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR

DEVELOPMENT Not Applicable

Background of the Invention

Filed of the invention

The invention is directed generally to medical diagnostics and specifically to diagnostic screens for primary liver cancer.

Brief Description of the Related Art

Hepatocellular carcinoma (HCC) is the fifth most common cancer in the world today, and the overall 5-year survival rate remains less than 5% (1). Although the incidence rate will likely fall with the institution of mass vaccination against the hepatitis B virus (2), major impacts will not be felt immediately as the age of presentation in most areas of the world is over 50 years long. More importantly, there is no immediate prospect of a vaccine against the hepatitis C virus on the market, the major aetiological factor for HCC in the US, Japan and Southern Europe (3, 4). Despite the absence of randomized clinical trials, there is strong evidence that surgical resection, liver transplantation or ablative therapies significantly improve survival (5, 6). Such approaches, however, are only applicable to those in whom the tumor is detected at an early stage — typically less than 3 cm in diameter without vascular involvement -- and tumors at these stages only rarely present symptoms (5-7). Early diagnosis has therefore become a priority. Surveillance of those with cirrhosis has been aided in the detection of small tumors, and there is emerging evidence that this early detection is correlated to improved survival rates (8). Currently, surveillance usually occurs at intervals of 6 month and involves both testing with serum alpha-fetoprotein (AFP) estimation and ultrasound scanning (7, 9). Although AFP may be a useful diagnostic serum marker in patients with advanced symptomatic disease, the technique's low sensitivity has rendered it much less useful in patients with early stage or small tumors (7-10). While ultrasound is far more sensitive (in the order of 80%), it is highly operator dependent (8, 9). More specific and sensitive serological tests, to complement ultrasound scanning, would therefore be of great clinical value.

A number of novel candidate markers have recently been introduced. Their discovery has been based on the identification of single proteins, complex proteomics features, or tumor-specific autoantibodies. The excitement about new candidate markers is tempered by the realization that none of them have yet met the most stringent criteria defined by the Early Detection Research Network (EDRN). Studies meeting the above criteria were systematically evaluated according to the guidelines established by EDRN (11). The guidelines are based on a 5-step process that reflects an increasing burden of proof, beginning with preclinical exploration of markers (11), the development and validation of a noninvasive clinical assay (12), a retrospective longitudinal testing of repository materials (13), the prospective screening of populations at risk (14), and studies to determine whether screening reduces the burden of cancer in the population (15). Markers meeting the latter goals would be considered the most valuable. Part of the results are shown in Table 1.

Table 1: E f HCC candidate serum markers

commerciablly available and FDA-approved.

² available in Japan and other Asian countries.

Plasma/serum proteomics: Traditionally, serum proteomics studies have been based on two-dimensional gel electrophoresis, though this method does not appear to be sufficiently sensitive for the detection of low-abundance marker proteins. A number of such studies have been performed in HCC patients. Steel and coworkers performed 2-dimensional gel electrophoresis of sera from HBV-infected patients with and without HCC (16). Two protein signals were consistently less abundant in HCC patients as compared to HBV-negative controls and HBV-carriers (17). They were identified by mass spectroscopy as fragments of C3 complement and apolipoprotein A1, respectively. However, similar decreases in the serum levels of the two proteins were also observed in HCC-negative patients with chronic hepatitis, suggesting that the observed changes were not cancer-specific. A recent study by the same group suggests that a decrease in a serum pre-amyloid P fragment may correlate with HCC (18). Similar reports based on this method have been published by several authors. It is doubtful that subtle changes in the levels of highly abundant proteins will be sufficiently sensitive and specific for diagnostic purposes.

More recently, surface-enhanced laser desorption/ionization - time of flight spectrometry (SELDI-TOF) has been advocated as a superior method for the identification of unique serum protein fragments. Poon and colleagues used this approach to study 38 HCC patients and 20 control patients with chronic hepatitis (19). The patients' sera were processed by anion-exchange fractionation, followed by absorption to protein chip arrays, and time-of-flight mass spectrometry. The data were analyzed using mathematical algorithms previously validated for gene array data, including SAM ("significant analysis of microarray") filtering. Using artificial neural networks, the authors identified 250 differential "serum proteomic features" which reportedly allowed the detection of HCC with sensitivity and specificity in the 90% range. This level of performance exceeds that of any known single serum marker reported to date. Since the publication of this study, four groups have reported their findings using SELDI- TOF-based analyses: Ward and colleagues reported their data obtained on 182 patients with HCV-related liver disease. Their neural network approach resulted in a set of protein peaks with 94% sensitivity and 86% specificity (20). Of note, the authors identified the two most informative SELDI peaks, and determined that they represented k and I immunoglobulin light chains. This result was confirmed by Western blotting, and indicated a modest (approximately 50%) increase. This study was noteworthy for its careful documentation of the reproducibility of the analyses and description of the SELDI methods.

In a study of Chinese patients with poorly characterized chronic liver disease and HCC, Wang and colleagues reported two sets of distinct SELDI peaks that allowed differentiation between HCC and normal subjects or patients with cirrhosis, respectively (21). The identity of the four protein peaks was not determined, however, and the sensitivity and specificity of the informative peaks were not fully reported. Drake and colleagues analyzed SELDI-TOF data alone or in combination with measurements of AFP, DCP, and GP73 in 170 patients with HCV-related liver disease. They identified 38 proteomic "features" that distinguished cirrhotics with and without cancer with a sensitivity and specificity of 61% and 76%, respectively. Combining the proteomics features with the serum levels of AFP₁ DCP, and GP73 improved the sensitivity and specificity to 75% and 92%, respectively (22). These results are less impressive than those obtained by Poon, but still represent a significant improvement over single marker measurements. Paradis and colleagues studied 82 French patients with liver cirrhosis from a variety of causes, and identified six SELDI peaks that distinguished HCC and non-HCC patients in 90% of the cases (23). The most informative protein peak was identified as a C-terminal vitronectin fragment. The authors provided in vitro evidence suggesting that this fragment may be generated by cleavage of the intact molecule by a metalloprotease activity, suggesting a biologically plausible mechanism for the appearance of the fragment in serum. Of note, the hepatic expression of vitronectin was not increased in HCC, supporting the notion that the serum peak was not simply due to a transcriptional upregulation of its expression. This study demonstrates the potential of the proteomics approach to reveal candidate markers that would be missed by tissue proteomics or gene array analysis.

The quality of serum SELDI data has recently come into question. Drawbacks of the method include the limited dynamic range of measurable protein fragments, the lack of identification of protein fragments of interest, and its unproven reproducibility (24, 25). It is highly likely that the improved accuracy of immunoassays over SELDI 'quantitation¹ could improve the performance of biomarkers originally identified by SELDI. The use of multiple carefully chosen markers should enhance both the sensitivity and specificity of HCC screening.

Serum qlvcoproteomics: Cancer-specific changes in the glycosylation of serum proteins have been previously reported in several types of cancer. Mehta and colleagues recently reported significant increases in the core- fucosylation of several serum proteins in woodchucks with HBV-related HCC, and introduced lectin affinity purification methods to identify and quantitate such proteins (26). The authors subsequently extended their analysis to patients with HBV-related liver disease, and documented similar changes in a number of highly-abundant proteins (including hemopexin, alpha-acid glycoprotein, alpha-1- antichymotrypsin, alpha-1 -antitrypsin, and haptoglobin) as well as AFP and GP73, two previously described HCC markers. Strikingly, the differences in fucosylation were observed even when the overall abundance of the marker proteins were similar in cancer patients and controls (26). Another interesting feature of these studies was that the HCC-specific fucosylation changes were observed in patients with normal and increased AFP levels, suggesting that the two marker categories might be complementary.

Tissue proteomics: Proteomics studies on liver tissues have traditionally utilized a combination of two-dimensional gel electrophoresis and mass spectrometry analysis. Li and colleagues performed a comprehensive liver proteomics analysis of patients with HBV-related HCC, comparing the profiles of cancer tissue with that of surrounding non-cancerous tissue (27). They identified 80 proteins with differential expression in HCC (43 upregulated in HCC, 37 downregulated) by peptide mass spectrometry, and assigned them to several functional categories. A few candidates, including proliferating cell antigen and stathmin 1, were confirmed by Western blotting analysis. Um identified 21 proteins with significant changes in expression in cirrhotic livers with HCC (28). Several previously identified candidate markers were upregulated, including the heat shock protein HSP70RY and nucleophosmin, whereas protein disulfide isomerase (PDI) levels were reduced. In a similar study, Kim identified 12 consistently up- and 2 downregulated proteins in HCC as compared to adjacent non-cancerous tissues (29), and confirmed the increase in nucleophosmin serum levels previously described by Lim. In contrast, a similar study by Kim identified the A3 isoform of PDI as consistently upregulated in HCC (30). The reason for the discrepancies between published data are unclear, although variability in serum composition is likely to account for at least some of the differences. The sensitivity and specificity of the reported alterations in tissue protein profiles have not been formally evaluated, and it remains to be seen whether the tissue data can be exploited for the purpose of serum diagnostics. More recently, MeIIe and coworkers performed laser capture microdissection studies of hepatocellular cancer cells and adjacent, noncancerous hepatocytes (31), and identified proteins with different abundance by proteomics analysis. The only distinguishing peak was identified as hemoglobin, most likely a reflection of the hypovascularity of hepatocellular cancers as compared to surrounding, cirrhotic tissues. No other candidate peaks were identified. The unimpressive results of this study, despite its use of the most sophisticated cell isolation and proteomics techniques, highlight the potential pitfalls of HCC tissue proteomics.

HCC-specific auto-antibodies: An extensive body of literature has documented the presence of tumor-derived autoantibodies (TAA) in the sera of HCC patients. They include some of the earliest TAAs, such as anti-p53 (32), as well as newer members (such as anti-telomerase (33)). In some cases, TAAs may be markers of the malignant transformation, since their occurrence appears to be triggered by the abnormal processing of antigenic cellular proteins during the process of hepatic carcinogenesis (34). Evidence for such a sequence of events has recently been presented for P62 (nucleophosmin), a nuclear protein that had previously been found to be present at elevated levels in the serum of HCC patients. Increased cellular nucleophosmin expression and abnormal protein processing may trigger the formation of a cell- or antibody-mediated autoimmune response (35). A common feature of HCC-TAAs is their low apparent sensitivity - positive serum reactivities are typically found in less than one fifth of all cases (36). Furthermore, the reported sensitivities were typically obtained in comparing HCC patients and healthy subjects, whereas there are few studies on cirrhotic patients who represent a more relevant target population. On the other hand, current data suggest that the "cancer specificity" of certain TAAs may be quite high (approaching 90% in some cases) - a feature that would compare favorably to many of the conventional serum markers (37). One potential limitation may be the lack of liver- specificity, since the same TAAs may occur in different malignancies. At present, none of the individual TAAs has been subjected to a rigorous prospective analysis in HCC cohorts (see table 1).

The following references are cited parenthetically as numbers throughout this disclosure. The references are incorporated herein by reference. Applicant reserves the right to challenge the veracity of any statements made therein.

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Summary of the Invention

In view of the need for alternative methods for the diagnosis and/or prediction of risk of hepatocellular carcinoma (HCC), the present inventors have developed methods and kits .

In various embodiments, the present teachings include methods for diagnosing hepatocellular carcinoma in a subject. In various aspects, these methods include a) obtaining a serum sample from a subject, and b) quantifying, in the serum sample, at least one protein that is differentially upregulated in patients diagnosed with HCC. A subject can be diagnosed with HCC if the quantity of at least one of the proteins is determined to be elevated relative to control levels. Examples of serum proteins that can be differentially upregulated in a subject with HCC can be, without limitation, apolipoprotein E₁ Trypsin precursor, KIAA0284, Apolipoprotein A-I precursor, v-kit (c-kit homologue), c-kit and Apolipoprotein C-III precursor. In various aspects of the present teachings, an assay for measuring the amount of a protein which is upregulated in HCC can be an aptamer-based assay, an antibody-based assay, a mass spectroscopy assay, or a high performance liquid chromatography assay. In some configurations, an antibody-based assay can be an ELISA, a radioimmunoassay or a Western blot.

In some aspects or the present teachings, the methods can further include removing at least one high-abundance serum protein from the serum sample prior to analyzing a serum sample for the quantity of a protein diagnostic for HCC. Such high-abundance proteins include albumin, IgG₁ antitrypsin, IgA₁ transferrin and haptoglobin. In some aspects, all six of these proteins can be removed from the serum sample prior to the analysis.

In various embodiments of the present teachings, the inventors disclose kits for diagnosing hepatocellular carcinoma. A kit of these embodiments can include, without limitation, a capture antibody directed against a first epitope of an HCC serum biomarker, a solid support upon which the capture antibody is immobilized, a detection antibody directed against a second epitope of the HCC serum biomarker; and a labeled secondary antibody directed against the detection antibody. In some aspects, the solid support can comprise at least one plastic bead or a multiwell plate such as an ELISA plate well known to skilled artisans. In various aspects, an HCC serum biomarker can be, without limitation, a protein such as an apolipoprotein E₁ a Trypsin precursor, a KIAA0284, a Apolipoprotein A-I precursor, a v-kit (c-kit homologue), a c-kit or an Apolipoprotein C-III precursor. In some additional aspects, a labeled secondary antibody comprised by a kit can include a label such as a fluorophore, an enzyme or a radioisotope.

Brief Description of the Drawings

Figure 1 illustrates the 2D gel image of c-kit protein from a cirrhosis serum sample and an HCC serum sample.

Figure 2 illustrates the 2D gel image of Apo E protein from a cirrhosis serum sample and an HCC serum sample.

Figure 3 illustrates a Western blot analysis of serum samples using anti-kit antibodies.

Figure 4 illustrates a Western blot analysis of serum samples using anti-ApoE antibodies

Figure 5 illustrates fractionation of serum proteins using the PF-2D LC system. Detailed Description

Early diagnosis of hepatocellular carcinoma (HCC) is the key to the delivery of effective therapies. There is a long felt need to identify novel serum markers of hepatocellular cancer (HCC). Applicants have established serum banks from patients with hepatitis C virus infection and HCV-related HCC at Saint Louis University Medical Center and the Saint Louis VA. In a recent pilot study using agilent affinity-column to remove 6 abundant proteins followed by 2 dimensional gel electrophoresis and mass spectroscopy (MS), applicants identified several new candidate serum biomarkers.

The inventors made the surprising discovery that various proteins are differentially found in the serum of patients at risk for or having HCC. Those proteins and their exemplary GenBank accession numbers are listed in Table 2. Thus, in one embodiment, the invention is directed to a method for determining the risk of a patient having or acquiring hepatocellular carcinoma ("HCC"), the steps comprising obtaining a serum sample from a patient, detecting and/or quantifying any one or more of the biomarkers listed in Table 2, alone or in combination with one or more known HCC serum biomarkers, and determining the patient's risk for having or acquiring HCC. The detecting step may be any one of myriad well-known methods in the art, including for example aptamer- based assays, antibody-based assays (e.g., ELISA, RIA, western), mass spec, HPLC, and the like. Preferably, the detection method is an antibody-based ELISA, as is currently the preference in the medical diagnostics art. The preferred determining step is quantifying the signal generated by the detection of the one of more the biomarkers of Table 2 in the test sample (e.g., serum of an individual suspected of having risk factors for HCC) and comparing that signal quantity to a control sample. A difference between the test and control values for the biomarkers can be interpreted to assess whether the test individual is at risk for HCC and/or needs additional testing and/or therapy.

In another embodiment, the invention is directed to a diagnostic kit for determining the risk of an individual for having or getting HCC. The preferred kit is based upon the ELISA immunodetection method, but the skilled artisan in the practice of this invention would recognize that other methods to which the kit can be based upon are available and applicable. In the ELISA-based kit, the kit comprises a substrate to which a capture antibody is fixed, a detection antibody, and a detectable moiety antibody. The preferred substrate for example may be a plastic bead or surface of a multiwell plate. The preferred capture antibody recognizes a first epitope on a HCC serum biomarker. The preferred detection antibody recognizes a second epitope on the HCC serum biomarker. The preferred detectable moiety antibody recognizes the detection antibody and has a detection moiety such as for example a fluorophore, chemiluminescence molecule, enzyme, or the like.

Table 2: Proteins Differentially Found in Serum of HCC Patients

Examples

The methods described herein utilize laboratory techniques well known to skilled artisans, and guidance can be found in laboratory manuals such as Sambrook, J., et al., Molecular Cloning: A Laboratory Manual, 3rd ed. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY, 2001; Spector, D. L. et al., Cells: A Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY₁ 1998; and Harlow, E., Using Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY₁ 1999.

Example 1. Identification of Biomaker candidates using 2-D gel approaches followed by MS analysis

Patients with HCV-related chronic liver disease were enrolled at the Johns Cochran VA Hospital and Saint Louis University Health Sciences Center. For the initial pilot study using two-dimensional gel electrophoresis methods, two groups of male patients with proven, compensated liver cirrhosis were studied, one without evidence of hepatocellular cancer, the other with biopsy-proven small HCC (<3 cm) that were discovered by surveillance imaging studies. Serum samples were obtained from patients after an overnight fast. None of the patients were receiving treatment for their HCC at the time of the blood draw. The clinical characteristics of the two groups are provided in Table 3.

Table 3: Clinical Characteristics

Patients in the two groups were comparable with regard to their age, MELD score, and serum AFP values. Of note, none of the HCC patients had AFP levels above the upper limit of normal (20mg/L), the most commonly used cutoff of HCC screening studies (12).

To analyze the low-abundant serum proteins, the Agilent spin cartridge was used to remove six high-abundant proteins from the serum pooled from three patients. These six proteins include albumin, IgG, antitrypsin, IgA, transferrin, and haptoglobin according to manufacturer's procedures. Specific removal of six high- abundant proteins can deplete approximately 85%-88% of total protein mass from human serum.

To remove the six abundant serum proteins, we first diluted 10 μL of pooled serum with Buffer A to a final volume of 200 μL and load it onto the spin cartridge that has been equilibrated with 4 ml of Buffer A into syringe. We then centrifuge for 1.5 minutes at 100xg to collect the flow through fraction (F1), followed by washing the column with 400 μL of Buffer A by spin for 2.5 minutes at 100xg. The flow-through fraction was collected into the same F1 collection tube. This procedure was repeated once and this fraction was collected into the F2 collection tube. Next, we used 2 ml of Buffer B to elute the bound abundant proteins. The column was re-equilibrated with Buffer A and the procedure was repeated with pooled serum samples. Each fraction was then analyzed separately by 1D SDS-PAGE to ensure the reproducibility of the depletion procedure. After the confirmation, all F1 and F2 fractions obtained from the same pooled sera were pooled and concentrated by 5KDa MWCO spin concentrators. The buffer was exchanged to 0.1 M ammonium bicarbonate separated into two aliquots and lyophilized. Protein pellet from one aliquot was re-suspended in PBS and the protein concentration was determined with Bradford method using BSA as standards.

An important consideration in the measurement of quantitative changes in protein expression is the consistency of the observations for a given technique as well as the reproducibility of the experiment. Several techniques are available for measuring changes in protein expression including gel-based approaches and shotgun proteomic methods. High-resolution 2-DE based separation of protein mixtures followed by image analysis for relative protein quantitation and mass spectrometric analysis for identification is a hallmark method in proteomics [1 ,2]. One of the benefits of the 2-DE approach is that the same separation technology is used both to measure protein expression changes as well as to purify proteins for subsequent MS analysis. The development of pre-and post separation fluorescent stains has facilitated reliable measures of changes in spot intensity [3,4 ].

We used 200 mg of each sample for the 2D gel analysis. Protein pellets were resuspended in a mixture containing 80 ul of 8M urea, 4% CHAPS, 65 mM DTT in 66.7 mM Tris and 300 ul of 8M urea, 4%CHAPS,65 mM DTT,1% ampholytes for in-gel rehydration. IEF and SDS-PAGE were performed by standard procedures. IEF was performed on 18 cm, 3-10 nonlinear IPG strips (GE Amersham Biosciences, Piscataway, NJ₁ USA) using the following program: 1 250V 20 min linear, 2 8000V 2.5 h linear and 3 8000V to 20,000V Rapid. SDS- PAGE was performed on a 12%T slab gels with an agarose overlay. Gels were fixed, stained with SYPRO Ruby (Molecular Probes, Eugene, OR₁USA) and destained according to the manufacturer's protocol.

Gel images are acquired with a Typhoon 9410 imager (Amersham Biosciences). Gel images are then analyzed using Phoretix 2D Evolution gel analysis software (Nonlinear Dynamics Ltd.). Automatic spot detection was performed with default parameters; spot editing and removal of artifacts were performed manually. Subsequent data analyses were performed on the MS- identified spots and manually matched among the gels. The normalized spot volume relative to the total volume of all detected spots in a gel (%vol) was used to calculate averages and CV between gels of replicate samples for individual spots. Microsoft Excel's STDEV function was used to calculate the SD for a given spot. A propagation of errors calculation was used to calculate the SD of expression ratios, which was subsequently used to calculate a CV for expression ratios.

Following image analysis, interesting proteins were excised from gels by GelPix (Genetix Inc.) and digested by an automated digester with trypsin, the MultiProbe Il workstation (PerkinElmer Inc.). Digests were de-salted and concentrated with C18 ZipTips (Millipore, Bedford, MA, USA) following the manufacturer's instructions and spotted onto a MALDI target plate and analyzed by a QSTAR XL mass spectrometer (Applied Biosystems). MS peak lists were submitted for automatic precursor ion selection excluding common trypsin autolysis peaks. Up to four of the most intense peaks were selected from each MS spectrum for MS/MS The acquired data are automatically submitted to database searching and protein identification by MASCOT v1.9 database searching engine. Searches were restricted to 50 ppm MS mass tolerance, and 0.3 Da MS/MS mass tolerance. Search results were ranked by protein score confidence interval% (Cl%), a GPS calculation based on Mascot score with the significance threshold removed to normalize results across different databases. Protein hits with protein score Cl% between 95 and 100 were accepted for identifications.

By comparing the 2D gel image of the sirrororis serum sample and that of the HCC serum sample, we found 30 down regulated protein spots and 7 up- regulated protein spots in HCC serum. The seven protein spots were analyzed as described above and the proteins were identified. Among these seven proteins upregulated in HCC serum samples, one is c-kit (Figure 1, 3h) and two are ApoE spots (Figure 2 1h and 2h). Example 2. Verification of the first candidate, c-kit

To further confirm that the above identified identified proteins (table 1 ) are up-regulated in HCC samples, we performed Western blot analysis of many more serum samples using anti-kit antibodies. The results are shown in Figure 3.

Example 3 Verification of a second candidate, phosphorylated ApoE

Since two spots are identified as ApoE, it is possible that they are ApoE isoforms or phosphorylated ApoE. To test whether they are phosphorylated ApoE, we first treated the serum samples with the phosphoprotein enrichment kit (Clontech) and performed western blot analysis using anti-ApoE antibodies to find out whether the phorphorylated form of ApoE is upregulated in HCC sera. 15 ul of human serum samples were diluted to 1 ml with buffer A provided in the kit and loaded to the phosphoryprote in affinity column. After washing the bound proteins were eluted with buffer B. Protein concentration in the eluate was determined by Bio-Rad protein assay. 0.5 ug of total protein was used for western blot analysis as shown in Figure 4.

Example 4. Fractionation of serum proteins using PF-2D LC system from Beckman Coulter.

Briefly, serum protein with six abundant proteins depleted as described was used and the buffer was exchanged to the starting buffer provided by the ProteomeLab PF 2D kit. 1 mg of the normal serum protein were resolved using the default method, and proteins were collected by interval of 0.3 pH unit from the first dimension separation using the ProteomeLab PF 2D fractionation system (Beckman Coulter). Twenty fractions were generated and each fraction was further separated by the C18 column with a linear gradient of 0%-100% ACN. The results are analyzed by proteovue program from Beckman Coulter Fractionation of serum proteins using PF-2D LC system from Beckman Coulter as shown in Figure 5.

Claims

ClaimsWhat is claimed is:

1. A method of diagnosing hepatocellular carcinoma in a subject, the method comprising: a) obtaining a serum sample from the subject; b) quantifying, in the serum sample, at least one protein that is differentially upregulated in patients diagnosed with HCC, whereby the subject is diagnosed with HCC if the quantity of at least one of the proteins is elevated relative to control levels.

2. A method of diagnosing hepatocellular carcinoma in accordance with claim 1 , wherein the at least one protein is selected from the group consisting of apolipoprotein E, Trypsin precursor, KIAA0284, Apolipoprotein A-I precursor, v-kit (c- kit homologue), c-kit and Apolipoprotein C-III precursor.

3. A method of diagnosing hepatocellular carcinoma in accordance with claim 1 , wherein the at least one protein is apolipoprotein E.

4. A method of diagnosing hepatocellular carcinoma in accordance with claim 1 , wherein the at least one protein is trypsin precursor.

5. A method of diagnosing hepatocellular carcinoma in accordance with claim 1 , wherein the at least one protein is KIAA0284.

6. A method of diagnosing hepatocellular carcinoma in accordance with claim 1 , wherein the at least one protein is Apolipoprotein A-I precursor.

7. A method of diagnosing hepatocellular carcinoma in accordance with claim 1 , wherein the at least one protein is v-kit (c-kit homologue).

8. A method of diagnosing hepatocellular carcinoma in accordance with claim 1, wherein the at least one protein is c-kit.

9. A method of diagnosing hepatocellular carcinoma in accordance with claim 1, wherein the at least one protein is Apolipoprotein C-IIl precursor.

10. The method according to Claim 1, wherein the quantifying comprises performing an assay selected from the group consisting of an aptamer-based assay, an antibody-based assay, a mass spectroscopy assay, and a high performance liquid chromatography assay.

11. The method according to claim 10, wherein the antibody-based assay is selected from the group consisting of a radioimmunoassay, an ELISA and a Western blot.

12. A method of diagnosing hepatocellular carcinoma in accordance with claim 1, further comprising removing at least one high-abundance serum protein from the serum sample prior to the quantifying.

13. A method of diagnosing hepatocellular carcinoma in accordance with claim 12, wherein the at least one high-abundance serum protein is selected from the group consisting of albumin, IgG, antitrypsin, IgA, transferrin and haptoglobin.

14. A method of diagnosing hepatocellular carcinoma in accordance with claim 12, wherein the removing at least one high-abundance serum protein comprises removing six high-abundance serum proteins.

15. A kit for diagnosing hepatocellular carcinoma, comprising: a capture antibody directed against a first epitope of an HCC serum biomarker; a solid support upon which the capture antibody is immobilized; a detection antibody directed against a second epitope of the HCC serum biomarker; and a labeled secondary antibody directed against the detection antibody.

16. The diagnostic kit of Claim 15 wherein the solid support comprises at least one plastic bead.

17. The diagnostic kit of Claim 15 wherein the solid support comprises a multiwell plate.

18. The diagnostic kit of Claim 15 wherein the hepatocellular carcinoma serum biomarker is selected from the group consisting of apolipoprotein E₁ Trypsin precursor, KIAA0284, Apolipoprotein A-I precursor, v-kit (c-kit homologue), c-kit and Apolipoprotein C-III precursor.

19. The diagnostic kit of Claim 15 wherein the labeled secondary antibody comprises a label selected from the group consisting of a fluorophore, an enzyme and a radioisotope.