WO2011038763A1

WO2011038763A1 - Method for biomolecular detection of human liver diseases compositions and kits used in said method

Info

Publication number: WO2011038763A1
Application number: PCT/EP2009/062716
Authority: WO
Inventors: Franco Maria Buonaguro; Luigi Buonaguro; Maria Lina Tornesello; Francesco Izzo; Francesco Marincola; Giuseppe Castello; Valeria De Giorgi
Original assignee: Franco Maria Buonaguro; Luigi Buonaguro; Maria Lina Tornesello; Francesco Izzo; Francesco Marincola; Giuseppe Castello; Valeria De Giorgi
Priority date: 2009-09-30
Filing date: 2009-09-30
Publication date: 2011-04-07

Abstract

The present invention identifies the global changes in gene expression associated with liver diseases progressing to cancer by examining gene expression in tissue from normal liver, Hepatitis C Virus (HCV) liver infection, primary hepatocellular carcinoma (including HCV- related malignancies) and metastatic malignant liver. The present invention also identifies expression profiles which can be used to complement current diagnostic techniques as well to monitor disease status and disease progression. The proposal is the preparation of a diagnostic/molecular kit based on a proper combination of weighted (balanced) quantities (in nanograms) of thirty specific oligomers (or multiple) for specific gene sequences, to develop a reliable and consistent diagnostic molecular tool [hepatochip™] able to identify and characterize, with high specificity and sensibility, liver tissue lesions. The gene chip is composed by a solid support covered by a specific nucleotide sequences miscellany/combination (oligomers) of the genes previously identified by the micro-array analysis. This rigid support will be involved in the reaction with the RNA extract from preneoplastic liver lesions. The identification of the lesions and the evaluation of their neoplastic progression will be based on the gene pattern expression on the gene-chip.

Description

METHOD FOR BIOMOLECULAR DETECTION OF HUMAN LIVER DISEASES COMPOSITIONS AND KITS USED IN SAID METHOD

DESCRIPTION BACKGROUND OF THE INVENTION

Hepatocellular carcinoma (HCC) is the most common liver malignancy and among the third leading causes of cancer death in the world (El-Serag HB et al, New Engl J Med 1999;340:745-50; Davila Jaet al J Clin Epidemiol 2003;56:487-93 El-Serag HB et al, Hepatology 2002;36 Suppl l :S74-83). As for other types of cancer, the etiology and carcinogenesis of HCC is multifactorial and multistage (Romeo R et al, Toxicology 2002; 181-182:39-42). The multistep process of HCC may be divided into chronic liver injury, inflammation, cell death, cirrhosis, regeneration, DNA damage, dysplasia and finally HCC. Different lesions have been suggested to represent hepatic preneoplastic stages. For instance, cirrhotic liver contains regenerative nodules and may contain dysplastic nodules as well as HCC (Schafer DF et al, Lancet 1999;353: 1253-1257; Kim JW et al, Carcinogenesis 2003;24:363-369). The principal risk factor for the development of HCC is hepatitis B virus (HBV) (Block TM et al, Oncogene 2003;22:5093-5107; Buendia MA et al, Biomed Pharmacother 1998;52:34-43), followed by hepatitis C virus (HCV) infection (Koike K et al, J Gastroenterol Hepatol 2002;17: 394-400), along with non viral causes. In particular, toxins and drugs (e.g., alcohol, aflatoxins, microcystin, anabolic steroids), metabolic liver diseases (e.g., hereditary haemochromatosis, a 1 -antitrypsin deficiency), steatosis (Ohata K et al, Cancer. 2003 Jun 15;97(12):3036-43) and non-alcoholic fatty liver diseases (Brunt EM Semin Liver Pis. 2004 Feb;24(l):3-20), diabetes (Davila JA et al, Gut. 2005 Apr;54(4):533-9), play a role in a minor number of cases. In general, HCCs are more frequent in men than in women and the incidence increases with age.

The molecular mechanism underlying HCC is currently unknown. Activation of cellular oncogenes, inactivation of tumor suppressor genes, overexpression of growth factors, and possibly telomerase activation and DNA mismatch repair defects may contribute to the development of HCC. Alterations in gene expression patterns accompanying different stages of growth, disease initiation, cell cycle progression, and responses to environmental stimuli provide important clues to these complex processes (Al-Sukhun S et al, Cancer 2003; 97 Suppl 8:2064-2075; Theodorescu D, Histol Histopathol 2003;18:259-274). In addition to primary liver cancer attributed to hepatocellular carcinoma, there are metastatic liver tumors as second locations of tumors in other parts of the body. These tumors most often metastasize from gastrointestinal organs, primarily colon and rectum, but metastatic liver cancers can represent secondary lesions from primary cancers throughout the body (Sitzman 1990, Groen 1999). These cancers can be treated using the routine therapies such as chemotherapy, radiotherapy, surgical resection, liver transplatation, chemoembolization, cryosurgery or a combination of therapies (Sitzman,(1990) in Nurs. 15, 48-57). The characterization of genes that are differentially expressed in tumorigenesis is an important step in identifying those that are intimately involved in the biological steps involved in the transformation process from normal tissue to cancer. Studies examining the gene expression of metastatic liver tumors and hepatocellular carcinomas in comparison with a set of normal liver tissues would produce data identifying genes that are not expressed in normal livers but have been switched on in tumors, as well as genes that have been completely turned off in these tumors during the progression from a normal to a malignant state. Such studies would also lead to the identification of genes that are expressed in tumor tissue at differing levels, but not expressed at any level in normal liver tissue. Several patents have been already deposited on molecular characterization of liver diseases, elaborating list of genes with altered expression and focusing on a specific stages of liver disease identifying genetic signatures specific for clinic classification of non-HCV related hepatocellular carcinoma HCC (WO2007/063118)), including the patent US 6,974,667 which is focused on differentially expressed genes in normal liver, metastasis and non-HCV- related HCC using standard Affimetrix system. Our claim is the identification, using an innovative {dedicated) microarray platform, of the minimal set of genes sufficient for the molecular signature and for developing the hepatochip™, with a dedicated instrument and related software, able to contribute or substitute the pathology diagnosis and to furnish a prognostic indication of progression risk, as well as responsivity to pharmacological treatment of HCV-associated hepatitis and their progression to cirrhosis/HCC.

SUMMARY OF THE INVENTION

The present invention relates to a method for bio molecular detection of human liver diseases and to a gene chip used in carrying out such method.

With microarray technology inventors carried out studies on the expression profile and regulation (activation or repression) of thousands of genes simultaneously. A specific set of genes with a peculiar cancer-related expression pattern was identified. This provides important molecular markers for diagnostic purposes.

The present invention identifies the global changes in gene expression associated with liver diseases, in particular liver cancer, by examining gene expression in tissue from normal liver, hepatocellular carcinoma (HCC), HCV-.related cirrhosis, and metastatic malignant liver. The present invention also identifies expression profiles which serve as useful diagnostic markers as well as markers that can be used to monitor disease states and disease progression.

The invention includes methods to diagnose the presence and type of liver diseases in patients comprising the step of detecting the level of expression in a tissue sample of 30 genes or multiples from Tables 1-4; where differential expression of all genes in Tables 1-4 is indicative of liver disease.

In one aspect, the invention includes methods of diagnosing liver progression to cirrhosis in patients comprising the step of detecting the level of expression in a tissue sample of 30 genes or multiples from Tables 1-4; where differential expression of the genes in Tables 2 and 4 is indicative of liver progression to cirrhosis.

In another aspect, the invention includes methods of diagnosing liver progression to hepatocellular carcinoma in patients comprising the step of detecting the level of expression in a tissue sample of 30 genes or multiples from Tables 1-4; where differential expression of the genes in Tables 1 and 4 is indicative of liver progression to hepatocellular carcinoma. In a further aspect, the invention includes methods of diagnosing metastatic liver cancer in patients comprising the step of detecting the level of expression in a tissue sample of 30 genes or multiples from Tables 1-4; where differential expression of the genes in Table 3 is indicative of metastatic liver cancer. The invention further includes compositions comprising oligonucleotides, where in each of the oligonucleotides comprises a sequence that specifically hybridizes to a gene in Tables 1-4 as well as solid supports comprising at least two probes, where each of the probes comprises a sequence that specifically hybridizes to a gene in Tables 1-4.

Preferably said compositions onto said support are in the form of a gene chip.

The invention further comprises kits useful for the practice of one or more of the methods of the invention. In some preferred embodiments, a kit may contain one or more solid supports having attached there to one or more oligonucleotides. The solid support may be a high- density oligonucleotide array. Kits may further comprise one or more reagents for use with the arrays, one or more signal detection and/or array-processing instruments, one or more gene expression databases and one or more analysis and database management software packages.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1 is a flow chart showing a schematic representation of the experimental protocol. Total RNAs prepared from biopsies are reverse transcribed to cDNAs and in vitro transcribed. Fluorescently labeled test and reference, combined R As were hybridised to oligochips (oligo-based microarray).

Arrays were scanned and images stored for all subsequent data analyses.

Figure 2 shows genes up regulated in the CTR and then completely lost HCV and/or HCC stages.

DETAILED DESCRIPTION

Many biological functions are accomplished by altering the expression of various genes through transcriptional (e.g., through control of initiation, provision of RNA precursors, RNA processing, etc.) and/or translational control. For example, fundamental biological processes such as cell cycle, cell differentiation and cell death, are often characterized by the variations in the expression levels of groups of genes.

Changes in gene expression also are associated with pathogenesis. For example, the lack of sufficient expression of functional tumor suppressor genes and/or the over expression of oncogene/protooncogenes could lead to tumorgenesis or hyperplastic growth of cells. Thus, changes in the expression levels of particular genes (e.g., oncogenes or tumor suppressors) serve as signature for the presence and progression of various diseases.

Monitoring changes in gene expression may also provide certain advantages during drug screening development. Often drugs are screened and prescreened for the ability to interact with a major target without regard to other effects the drugs have on cells. Often such other effects cause toxicity in the whole animal, which prevent the development and use of the potential drug. The present inventors have examined tissue samples from normal liver, metastatic malignant liver, HCV-. related cirrhosis, and hepatocellular carcinoma to identify the global changes in gene expression associated with liver cancer. These global changes in gene expression, also referred to as expression profiles, provide useful markers for diagnostic uses as well as markers that can be used to monitor disease states, disease progression, drug toxicity, drug efficacy and drug metabolism. The present invention provides compositions and methods to detect the level of expression of genes that may be differentially expressed dependent upon the state of the cell, i.e., normal versus cancerous. As used herein, the phrase "detecting the level expression" includes methods that quantitate expression levels as well as methods that determine whether a gene of interest is expressed at all. Thus, an assay which provides a yes or no result without necessarily providing quantification of an amount of expression is an assay that requires "detecting the level of expression" as that phrase is used herein. Assay Formats

The genes identified as being differentially expressed in liver cancer in comparison to normal as well as hepatitis/cirrhosis may be used in a variety of nucleic acid detection assays to detect or quantititate the expression level of a gene or multiple genes in a given sample. For example, traditional Northern blotting, nuclease protection, RT-PCR and differential display methods may be used for detecting gene expression levels. Those methods are useful for some embodiments of the invention. However, methods and assays of the invention are most efficiently designed with array or chip hybridization-based methods for detecting the expression of a large number of genes.

Any hybridization assay format may be used, including solution-based and solid support- based assay formats. Solid supports containing oligonucleotide probes for differentially expressed genes of the invention can be filters, polyvinyl chloride dishes, silicon or glass based chips, etc. Such wafers and hybridization methods are widely available, for example, those disclosed by Beattie (WO 95/11755) or those recently disclosed by Wang, Marincola, Miller (WO/2001/073134). Any solid surface to which oligonucleotides can be bound, either directly or indirectly, either covalently or non-covalently, can be used. A preferred solid support is a high density array or DNA chip. These contain a particular oligonucleotide probe in a predetermined location on the array. Each predetermined location may contain more than one molecule of the probe, but each molecule within the predetermined location has an identical sequence. Such predetermined locations are termed features. There may be, for example, about 2, 10, 100, 1000 to 10,000; 100,000 or 400,000 of such features on a single solid support. The solid support, or the area within which the probes are attached may be on the order of a square centimeter.

Oligonucleotide probe arrays for expression monitoring can be made and used according to any techniques known in the art (see for example, Lockhart et al., (1996) Nat. Biotechnol. 14, 1675-1680; McGall et al, (1996) Proc. Nat. Acad. Sci. USA 93, 13555-13460). Such probe arrays may contain at least two or more oligonucleotides that are complementary to or hybridize to two or more of the genes described herein. Such arrays may also contain oligonucleotides that are complementary or hybridize to at least about 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 50, 70, 100 or or more the genes described herein.

The genes which are assayed according to the present invention are typically in the form of mRNA or reverse transcribed mRNA. The genes may be cloned or not and the genes may be amplified or not. The cloning itself does not appear to bias the representation of genes within a population. However, it may be preferable to use polyA +RNA as a source, as it can be used with less processing steps.

The sequences of the expression marker genes to be used in the hepatochip™ is based on a limited number of genes (30 or multiples), present in public databases, able to identify different stages of liver diseases, including HCV -related hepatitis and progression to HCC. Tables 1-4 provide the GenBank accession number for the genes. The sequences of the genes in GenBank are expressly incorporated by reference as are equivalent and related sequences present in GenBank or other public databases. The column labeled "SEQ ID" refers to the sequence identification number correlating the listed gene to its sequence information as provided within the sequence listing of this application.

Probes based on the sequences of the genes described herein may be prepared by any commonly available method. Oligonucleotide probes for assaying the tissue or cell sample are preferably of sufficient length to specifically hybridize only to appropriate, complementary genes or transcripts. Typically the oligonucleotide probes will be at least 10, 12, 14, 16, 18, 20 or 25 nucleotides in length. In some cases longer probes of at least 30, 40, or 50 nucleotides will be desirable. As used herein, oligonucleotide sequences that are complementary to one or more of the genes described herein, refers to oligonucleotides that are capable of hybridizing under stringent conditions to at least part of the nucleotide sequence of said genes. Such hybridizable oligonucleotides will typically exhibit at least about 75% sequence identity at the nucleotide level to said genes, preferably about 80% or 85% sequence identity or more preferably about 90% or 95% or more sequence identity to said genes.

As used herein a "probe" is defined as a nucleic acid, capable of binding to a target nucleic acid of complementary sequence through one or more types of chemical bonds, usually through complementary base pairing, usually through hydrogen bond formation. As used herein, a probe may include natural (i.e., A, G, U, C or T) or modified bases (7- deazaguanosine, inosine, etc.). In addition, the bases in probes may be joined by a linkage other than a phosphodiester bond, so long as it does not interfere with hybridization. Thus, probes may be peptide nucleic acids in which the constituent bases are joined by peptide bonds rather than phosphodiester linkages.

The similarity between two nucleic acid sequences, or two amino acid sequences, is expressed in terms of the similarity between the sequences, otherwise referred to as sequence identity. Sequence identity is frequently measured in terms of percentage identity (or similarity or homology) ; the higher the percentage, the more similar the two sequences are. Homo logs or orthologs of nucleic acid or amino acid sequences will possess a relatively high degree of sequence identity when aligned using standard methods. This homology will be more significant when the orthologous proteins or nucleic acids are derived from species which are more closely related (e. g., human and chimpanzee sequences), compared to species more distantly related (e. g., human and C. elegans sequences). Typically, orthologs are at least 50% identical at the nucleotide level and at least 50% identical at the amino acid level when comparing human orthologous sequences.

Methods of alignment of sequences for comparison are well known. Various programs and alignment algorithms are described in : Smith & Waterman, Adv. AppL Math. 2 : 482, 1981 ; Needleman & Wunsch, J. Mol. Biol. 48 : 443, 1970 ; Pearson & Lipman, Proc. Natl. Acad. Sci. USA 85 : 2444, 1988 ; Higgins & Sharp, Gene, 73 : 237-44, 1988 ; Higgins & Sharp, CABIOS 5 : 151-3, 1989 ; Corpet et al, Nuc. Acids Res. 16 : 10881-90, 1988 ; Huang et al. Computer Appls. Biosci. 8, 155-65, 1992 ; and Pearson et al, Metl. Mol. Bio. 24 : 307-31 , 1994. Altschul et al, J. Mol. Biol. 215 : 403-10, 1990, presents a detailed consideration of sequence alignment methods and homology calculations. The NCBI Basic Local Alignment Search Tool (BLAST) (Altschul et al, J. Mol. Biol. 215 : 403-10, 1990) is available from several sources, including the National Center for Biotechnology Information (NCBI, Bethesda, MD) and on the Internet, for use in connection with the sequence analysis programs blastp, blastn, blastx, tblastn and tblastx. Each of these sources also provides a description of how to determine sequence identity using this program.

Homologous sequences are typically characterized by possession of at least 60%>, 70%>, 75%>, 80%), 90%o, 95%) or at least 98%> sequence identity counted over the full length alignment with a sequence using the NCBI Blast 2. 0, gapped blastp set to default parameters. Queries searched with the blastn program are filtered with DUST (Hancock and Armstrong, Comput. AppL Biosci. 10 : 67-70, 1994). It will be appreciated that these sequence identity ranges are provided for guidance only ; it is entirely possible that strongly significant homo logs could be obtained that fall outside of the ranges provided.

Probe Design

One of skill in the art will appreciate that an enormous number of array designs are suitable for the practice of this invention. The high density array will typically include a number of probes that specifically hybridize to the sequences of interest. See WO 99/32660 for methods of producing probes for a given gene or genes. In addition, in a preferred embodiment, the array will include one or more control probes. High density array chips of the invention include "test probes." Test probes may be oligonucleotides that range from about 5 to about 500 or about 5 to about 50 nucleotides, more preferably from about 10 to about 40 nucleotides and most preferably from about 15 to about 40 nucleotides in length. In other particularly preferred embodiments the probes are about 20 to 25 nucleotides in length. In another preferred embodiment, test probes are double or single strand DNA sequences. DNA sequences are isolated or cloned from natural sources or amplified from natural sources using natural nucleic acid as templates. These probes have sequences complementary to particular subsequences of the genes whose expression they are designed to detect. Thus, the test probes are capable of specifically hybridizing to the target nucleic acid they are to detect.

In addition to test probes that bind the target nucleic acid(s) of interest, the high density array can contain a number of control probes. The control probes fall into three categories referred to herein as (1) normalization controls; (2) expression level controls; and (3) mismatch controls.

Normalization controls are oligonucleotide or other nucleic acid probes that are complementary to labeled reference oligonucleotides or other nucleic acid sequences that are added to the nucleic acid sample. The signals obtained from the normalization controls after hybridization provide a control for variations in hybridization conditions, label intensity, "reading" efficiency and other factors that may cause the signal of a perfect hybridization to vary between arrays. In a preferred embodiment, signals (e.g., fluorescence intensity) read from all other probes in the array are divided by the signal (e.g., fluorescence intensity) from the control probes thereby normalizing the measurements.

Virtually any probe may serve as a normalization control. However, it is recognized that hybridization efficiency varies with base composition and probe length. Preferred normalization probes are selected to reflect the average length of the other probes present in the array, however, they can be selected to cover a range of lengths. The normalization contra l(s) can also be selected to reflect the (average) base composition of the other probes in the array, however in a preferred embodiment, only one or a few probes are used and they are selected such that they hybridize well (i.e., no secondary structure) and do not match any target-specific probes.

Expression level controls are probes that hybridize specifically with constitutively expressed genes in the biological sample. Virtually any constitutively expressed gene provides a suitable target for expression level controls. Typical expression level control probes have sequences complementary to subsequences of constitutively expressed "housekeeping genes" including, but not limited to the .beta.-actin gene, the transferrin receptor gene, the GAPDH gene, and the like.

Mismatch controls may also be provided for the probes to the target genes, for expression level controls or for normalization controls. Mismatch controls are oligonucleotide probes or other nucleic acid probes identical to their corresponding test or control probes except for the presence of one or more mismatched bases. A mismatched base is a base selected so that it is not complementary to the corresponding base in the target sequence to which the probe would otherwise specifically hybridize. One or more mismatches are selected such that under appropriate hybridization conditions (e.g., stringent conditions) the test or control probe would be expected to hybridize with its target sequence, but the mismatch probe would not hybridize (or would hybridize to a significantly lesser extent). Preferred mismatch probes contain a central mismatch. Thus, for example, where a probe is a twenty-mer, a corresponding mismatch probe will have the identical sequence except for a single base mismatch (e.g., substituting a G, a C or a T for an A) at any of positions 6 through 14 (the central mismatch).

Mismatch probes thus provide a control for non-specific binding or cross hybridization to a nucleic acid in the sample other than the target to which the probe is directed. Mismatch probes also indicate whether a hybridization is specific or not. For example, if the target is present the perfect match probes should be consistently brighter than the mismatch probes. In addition, if all central mismatches are present, the mismatch probes can be used to detect a mutation. The difference in intensity between the perfect match and the mismatch probe (IBM)-I(MM)) provides a good measure of the concentration of the hybridized material.

Nucleic Acid Samples

As is apparent to one of ordinary skill in the art, nucleic acid samples used in the methods and assays of the invention may be prepared by any available method or process. Methods of isolating total mRNA are also well known to those of skill in the art. For example, methods of isolation and purification of nucleic acids are described in detail in Chapter 3 of Laboratory Techniques in Biochemistry and Molecular Biology: Hybridization With Nucleic Acid Probes, Part I Theory and Nucleic Acid Preparation, Tijssen, (1993) (editor) Elsevier Press. Such samples include RNA samples, but also include cDNA synthesized from a mRNA sample isolated from a cell or tissue of interest. Such samples also include DNA amplified from the cDNA, and an RNA transcribed from the amplified DNA. One of skill in the art would appreciate that it is desirable to inhibit or destroy RNase present in homogenates before homogenates can be used. Biological samples may be of any biological tissue or fluid or cells from any organism as well as cells raised in vitro, such as cell lines and tissue culture cells. Frequently the sample will be a "clinical sample" which is a sample derived from a patient. Typical clinical samples include, but are not limited to, sputum, blood, blood-cells (e.g., white cells), tissue or fine needle biopsy samples, urine, peritoneal fluid, and pleural fluid, or cells therefrom.

Biological samples may also include sections of tissues, such as frozen sections or formalin fixed sections taken for histological purposes.

Forming High Density Arrays

Methods of forming high density arrays of oligonucleotides with a minimal number of synthetic steps are known. Though the nucleic acids being deposited are different than in traditional microarray technology, the techniques described for these traditional systems are equally applicable to deposition of the herein disclosed nucleic acid preparation to gene profiling arrays. For instance, arrays can be formed on non-porous surfaces (such as glass) by robotic micropipetting of nano liter quantities of DNA to predetermined positions on a non- porous glass surface (as in Schena et aL, Science 270 : 467-470, 1995, and WO 95/35505). This is a"spotting"technique. Generally, in a spotting technique, the target molecules are delivered by directly depositing (rather than flowing) relatively small quantities of them in selected regions. For instance, a dispenser can move from address to address, depositing only as much target as necessary at each stop. Typical dispensers include an ink-jet printer or a micropipette to deliver the target in solution to the substrate, and a robotic system to control the position of the micropipette with respect to the substrate. In other embodiments, the dispenser includes a series of tubes, a manifold, an array of pipettes, or the like so that the target polypeptides can be delivered to the reaction regions simultaneously.

In addition the oligonucleotide analogue array can be synthesized by a light-directed chemical coupling, (see Pirrung et aL, (1992) U.S. Pat. No. 5,143, 854; Fodor et al, (1998) U.S. Pat. No. 5,800,992; Chee et al, (1998) U.S. Pat. No. 5,837,832 .

In brief, the light-directed combinatorial synthesis of oligonucleotide arrays on a glass surface proceeds using automated phosphoramidite chemistry and chip masking techniques. In one specific implementation, a glass surface is derivatized with a silane reagent containing a functional group, e.g., a hydroxyl or amine group blocked by a photolabile protecting group. Photolysis through a photolithogaphic mask is used selectively to expose functional groups which are then ready to react with incoming 5' photoprotected nucleoside phosphoramidites. The phosphoramidites react only with those sites which are illuminated (and thus exposed by removal of the photolabile blocking group). Thus, the phosphoramidites only add to those areas selectively exposed from the preceding step. These steps are repeated until the desired array of sequences have been synthesized on the solid surface. Combinatorial synthesis of different oligonucleotide analogues at different locations on the array is determined by the pattern of illumination during synthesis and the order of addition of coupling reagents.

Hybridization

Nucleic acid hybridization simply involves contacting a probe and target nucleic acid under conditions where the probe and its complementary target can form stable hybrid duplexes through complementary base pairing (see Lockhart et al., (1999) WO 99/32660). The nucleic acids that do not form hybrid duplexes are then washed away leaving the hybridized nucleic acids to be detected, typically through detection of an attached detectable label. It is generally recognized that nucleic acids are denatured by increasing the temperature or decreasing the salt concentration of the buffer containing the nucleic acids.

Under low stringency conditions (e.g., low temperature and/or high salt) hybrid duplexes (e.g., DNA-DNA, RNA-RNA or RNA-DNA) will form even where the annealed sequences are not perfectly complementary.

Thus specificity of hybridization is reduced at lower stringency. Conversely, at higher stringency (e.g., higher temperature or lower salt) successful hybridization requires fewer mismatches. One of skill in the art will appreciate that hybridization conditions may be selected to provide any degree of stringency. In a preferred embodiment, hybridization is performed at low stringency, in this case in 4x SSC at 42° C (0.4% SDS ) to ensure hybridization and then subsequent washes are performed at higher stringency (e.g., 2x SSC with 0.1% SDS at RT) to eliminate mismatched hybrid duplexes. Successive washes may be performed at increasingly higher stringency (lx SSC, 0.2x SSC and 0.05xSSC, sequentially for 1 min each..) until a desired level of hybridization specificity is obtained. Stringency can also be increased by addition of agents such as formamide. Hybridization specificity may be evaluated by comparison of hybridization to the test probes with hybridization to the various controls that can be present (e.g., expression level control, normalization control, mismatch controls, etc.).

In general, there is a tradeoff between hybridization specificity (stringency) and signal intensity. Thus, in a preferred embodiment, the wash is performed at the highest stringency that produces consistent results and that provides a signal intensity greater than approximately 10% of the background intensity. Thus, in a preferred embodiment, the hybridized array may be washed at successively higher stringency solutions and read between each wash. Analysis of the data sets thus produced will reveal a wash stringency above which the hybridization pattern is not appreciably altered and which provides adequate signal for the particular oligonucleotide probes of interest.

Signal Detection.

The data generated by assaying a gene profiling array can be analyzed using known computerized systems. For instance, the array can be read by a computerized "reader" or scanner and quantification of the binding of probe to individual addresses on the array carried out using computer algorithms. Likewise, where a control probe has been used, computer algorithms can be used to normalize the hybridization signals in the different spots of the array. Such analyses of an array can be referred to as "automated detection" in that the data is being gathered by an automated reader system. In the case of labels that emit detectable electromagnetic wave or particles, the emitted light (e. g., fluorescence or luminescence) or radioactivity can be detected by very sensitive cameras, confocal scanners, image analysis devices, radioactive film or a Phosphoimager, which capture the signals (such as a color image) from the array. A computer with image analysis software detects this image, and analyzes the intensity of the signal for each probe location in the array. Signals can be compared between spots on a single array, or between arrays (such as a single array that is sequentially probed with multiple different probe molecules), or between the labels of different probes on a single array. Computer algorithms can also be used for comparison between spots on a single array or on multiple arrays. In addition, the data from an array can be stored in a computer readable form. Certain examples of automated array readers (scanners) will be controlled by a computer and software programmed to direct the individual components of the reader (e. g., mechanical components such as motors, analysis components such as signal interpretation and background subtraction). Optionally software may also be provided to control a graphic user interface and one or more systems for sorting, categorizing, storing, analyzing, or otherwise processing the data output of the reader. To"read" an array, an array that has been assayed with a detectable probe to produce binding (e. g., a binding pattern) can be placed into (or onto, or below, etc., depending on the location of the detector system) the reader and a detectable signal indicative of probe binding detected by the reader. Those addresses at which the probe has bound to an immobilized nucleic acid mixture provide a detectable signal, e. g., in the form of electromagnetic radiation. These detectable signals could be associated with an address identifier signal, identifying the site of the "positive" hybridized spot. The reader gathers information from each of the addresses, associates it with the address identifier signal, and recognizes addresses with a detectable signal as distinct from those not producing such a signal. Certain readers are also capable of detecting intermediate levels of signal, between no signal at all and a high signal, such that quantification of signals at individual addresses is enabled. Certain readers that can be used to collect data from the arrays, especially those that have been probed using a fluorescently tagged molecule, will include a light source for optical radiation emission. The wavelength of the excitation light will usually be in the UV or visible range, but in some situations may be extended into the infra-red range. A beam splitter can direct the reader emitted excitation beam into the object lens, which for instance may be mounted such that it can move in the x, y and z directions in relation to the surface of the array substrate. The objective lens focuses the excitation light onto the array, and more particularly onto the (polypeptide) targets on the array. Light at longer wavelengths than the excitation light is emitted from addresses on the array that contain fluorescently-labeled probe molecules (i. e., those addresses containing a nucleic acid molecule within a spot containing a nucleic acid molecule to which the probe binds). In certain embodiments, the array may be movably disposed within the reader as it is being read, such that the array itself moves (for instance, rotates) while the reader detects information from each address. Alternatively, the array may be stationary within the reader while the reader detection system moves across or above or around the array to detect information from the addresses of the array (see 2001 WO 01/73134).

Databases

The present invention includes relational databases containing sequence information, for instance for the genes of Tables 1-4, as well as gene expression information in various liver tissue samples. Databases may also contain information associated with a given sequence or tissue sample such as descriptive information about the gene associated with the sequence information, or descriptive information concerning the clinical status of the tissue sample, or the patient from which the sample was derived. The database may be designed to include different parts, for instance a sequences database and a gene expression database. Methods for the configuration and construction of such databases are widely available, for instance, see Akerblom et al, (1999) U.S. Pat. No. 5,953,727, which is herein incorporated by reference in its entirety.

The databases of the invention may be linked to an outside or external database. In a preferred embodiment, as described in Tables 1-4, the external database is GenBank and the associated databases maintained by the National Center for Biotechnology Information (NCBI).

Any appropriate computer platform may be used to perform the necessary comparisons between sequence information, gene expression information and any other information in the database or provided as an input. For example, a large number of computer workstations are available from a variety of manufacturers, such has those available from Silicon Graphics. Client-server environments, database servers and networks are also widely available and appropriate platforms for the databases of the invention.

The databases of the invention may be used to produce, among other things, electronic Northerns to allow the user to determine the cell type or tissue in which a given gene is expressed and to allow determination of the abundance or expression level of a given gene in a particular tissue or cell.

The databases of the invention may also be used to present information identifying the expression level in a tissue or cell of a set of genes comprising at least one gene in Tables 1-4 comprising the step of comparing the expression level of at least one gene in Tables 1-4 in the tissue to the level of expression of the gene in the database. Such methods may be used to predict the physiological state of a given tissue by comparing the level of expression of a gene or genes in Tables 1-4 from a sample to the expression levels found in tissue from normal liver, metastatics liver or HCV related hepatocellular carcinoma. Such methods may also be used in the drug or agent screening assays as described below.

Kits

The invention further includes kits combining, in different combinations, high-density oligonucleotide arrays, reagents for use with the arrays, signal detection and array-processing instruments, gene expression databases and analysis and database management software described above. The kits may be used, for example, to predict or model the toxic response of a test compound, to monitor the progression of liver disease states, to identify genes that show promise as new drug targets and to screen known and newly designed drugs as discussed above.

The databases packaged with the kits are a compilation of expression patterns from human or laboratory animal genes and gene fragments (corresponding to the genes of Table 1-4). Data is collected from a repository of both normal and diseased animal tissues and provides reproducible, quantitative results, i.e., the degree to which a gene is up-regulated or down- regulated under a given condition.

The kits may used in the pharmaceutical industry, where the need for early drug testing is strong due to the high costs associated with drug development, but where bioinformatics, in particular gene expression informatics, is still lacking. These kits will reduce the costs, time and risks associated with traditional new drug screening using cell cultures and laboratory animals. The results of large-scale drug screening of pre-grouped patient populations, pharmacogenomics testing, can also be applied to select drugs with greater efficacy and fewer side-effects. The kits may also be used by smaller biotechnology companies and research institutes who do not have the facilities for performing such large-scale testing themselves. Databases and software designed for use with use with microarrays is discussed in Balaban et al, U.S. Pat. No. Nos. 6,229,911, a computer-implemented method for managing information, stored as indexed tables, collected from small or large numbers of microarrays, and U.S. Pat. No. 6,185,561, a computer-based method with data mining capability for collecting gene expression level data, adding additional attributes and reformatting the data to produce answers to various queries. Chee et al, U.S. Pat. No. 5,974,164, disclose a software-based method for identifying mutations in a nucleic acid sequence based on differences in probe fluorescence intensities between wild type and mutant sequences that hybridize to reference sequences.

Diagnostic Uses for the Liver Cancer Markers

As described above, the genes and gene expression information provided in Tables 1-4 may be used as diagnostic markers for the prediction or identification of the malignant state of the liver tissue. For instance, a liver tissue sample or other sample from a patient may be assayed by any of the methods described above, and the expression levels from a gene or genes from the Tables, in particular the genes in Tables 1-4, may be compared to the expression levels found in normal liver tissue, tissue from metastatic liver cancer or HCV-related hepatocellular carcinoma tissue. Expression profiles generated from the tissue or other sample that substantially resemble an expression profile from normal or diseased liver tissue may be used, for instance, to aid in disease diagnosis. Comparison of the expression data, as well as available sequence or other information may be done by researcher or diagnostician or may be done with the aid of a computer and databases as described above.

Use of the Liver Cancer Markers for Monitoring Disease Progression

As described above, the genes and gene expression information provided in Tables 1-4 may also be used as markers for the monitoring of disease progression, for instance, the development of liver cancer. For instance, a liver tissue sample or other sample from a patient may be assayed by any of the methods described above, and the expression levels in the sample from a gene or genes from Tables 1-4 may be compared to the expression levels found in normal liver tissue, tissue from metastatic liver cancer or HCV- related-hepatocellular carcinoma tissue. Comparison of the expression data, as well as available sequence or other information may be done by researcher or diagnostician or may be done with the aid of a computer and databases as described above. Assays to monitor the expression of a marker or markers as defined in Tables 1-4 may utilize any available means of monitoring for changes in the expression level of the nucleic acids of the invention. As used herein, an agent is said to modulate the expression of a nucleic acid of the invention if it is capable of up- or down-regulating expression of the nucleic acid in a cell. In one assay format, gene chips containing probes to at least 30 genes from Tables 1-4 may be used to directly monitor or detect changes in gene expression in the treated or exposed cell as described in more detail above. In another format, cell lines that contain reporter gene fusions between the open reading frame and/or the 3' or 5' regulatory regions of a gene in Tables 1-4 and any assayable fusion partner may be prepared. Numerous assayable fusion partners are known and readily available including the firefly luciferase gene and the gene encoding chloramphenicol acetyltransferase (Alam et al., (1990) Anal. Biochem. 188, 245-254). Cell lines containing the reporter gene fusions are then exposed to the agent to be tested under appropriate conditions and time. Differential expression of the reporter gene between samples exposed to the agent and control samples identifies agents which modulate the expression of the nucleic acid.

Additional assay formats may be used to monitor the ability of the agent to modulate the expression of a gene identified in Tables 1-4. For instance, as described above, mRNA expression may be monitored directly by hybridization of probes to the nucleic acids of the invention. Cell lines are exposed to the agent to be tested under appropriate conditions and time and total RNA or mRNA is isolated by standard procedures such those disclosed in Sambrook et al., (1989) Molecular Cloning—A Laboratory Manual, Cold Spring Harbor Laboratory Press).

The following working examples therefore, specifically point out the preferred embodiments of the present invention, and are not to be construed as limiting in any way the remainder of the disclosure.

EXAMPLES

Tissue Samples Acquisition and Preparation

Thirty-three HCV-related HCCs and fifteen metastatic liver tissue along with their respective normal control tissue from the same patients, as well as thirteen normal tissue samples from patients with non-preneoplastic liver disease, were obtained with informed consent from sixty-one patients enrolled at the liver unit of the INT "Pascale"-Naples (Italy). Liver tumor tissues and adjacent non-tumor tissues were excised and stored in RNA Later® at -80C° (Ambion,Austin,TX). The sample set was composed of (a) thirty-three samples of HCV- correlated hepatocellular-carcinoma with their corresponding HCV-positive non cancerous liver tissue; (b) fifteen metastatic liver tissues with their corresponding non cancerous liver tissue; and (c) thirteen normal liver tissues from patients subjected to laparoscopic cholecystectomy. Histopatho logical classification of liver diseases was performed according to the Edmondson grading system; clinical stages were determined according to the tumor- node-metastasis (TNM) staging. Liver histology for the control patients confirmed the absence of any pathology, moreover all thirteen patients were seronegative for hepatitis C virus antibodies (HCV Ab).

Samples used for RNA isolation and amplification were fresh collected and stored in RNA Later at -80°C. Sample processing included several steps. In particular, samples were homogenized in disposable tissue grinders (Kendall, Precision) and total RNA was extracted using TRIzol (Life Technologies, Rockville, MD). The purity of the RNA preparation was tested by the A260:280nm ratio (range, 1.8-2.0) with NanoDrop. Integrity of RNA after extraction was checked using Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA) to identify the 28S and 18S ribosomal RNA bands. The good quality of RNA was evaluated on the basis of 28S/18S rRNA ratios equal or close to 2. In addition, phenol contamination was checked and A260:230nm ratios greater than 1.9 were considered acceptable.

cDNA was prepared from 3μg of Total RNA (T-RNA) in 9μ1 DEPC -treated H₂0 using Superscript II (Invitrogen) with a T7-(dT15) oligonucleotide primer. cDNA synthesis was completed at 42°C for lh. Full-length ds-cDNA, during the removal of the primer RNA, was synthesized from the ss-cDNAby adding 106μ1 of DNase-free water, 15μ1 Advantage PCR buffer (Clontech), 3μ1 lOmM dNTP, Ιμΐ RNase-H (Promega), 3μ1 Advantage cDNA Polymerase (Clontech). Double-strand cDNA was extracted with phenol-chloroform-isoamyl and precipitated with ethanol in the presence of Ιμΐ linear acrylamide (0.1 μg/μl, Ambion, Austin, TX). The amplified RNA (aRNA), mRNA equivalent, was transcribed using Ambion' s T7 MegaScript in Vitro Transcription Kit (Ambion, Austin, TX). A RNA recovery and removal of template DNA was achieved by TRIzol purification. For the second round of amplification aliquots of ^g of the synthesized aRNA were reverse transcribed into cDNA using Ιμΐ of random hexamer under the conditions used in the first round. Second-strand cDNA synthesis was initiated by ^g oligo-dT-T7 primer. In vitro transcription of aRNA was carried out as for the first round (Ena Wang et al, Nature Biotechnology Vol 18 April 2000). 6μg of aRNA was used for probe preparation; test samples were labeled with USL-Cy5 (Kreatech) and pooled with the same amount of reference sample (normal donor peripheral blood mononuclear cells, PBMC) labeled with USL-Cy3 (Kreatech). The two labeled aRNA probes were separated from uncorporated nucleotides by filtration, fragmented, mixed and co- hybridized to a costum-made 36K oligoarrays at 42C° for 24h. The oligo-chips were printed at the Immunogenetics Section Department of Transfusion Medicine, Clinical Center , National Institutes of Health (Bethesda, MD). After hybridization the slides were washed with 2x SSC/0.1% SDS for lmin, lx SSC for lmin, 0.2x SSC for lmin, 0.05x SSC for lOsec, and dried by centrifugation.

Hybridized arrays were scanned at ΙΟμιη resolution on a GenePix 4000 scanner (Axon Instruments) at variable PMT voltage to obtain maximal signal intensities with less than 1% probe saturation. Resulting jpeg and data files were deposited at microarray data base (mAdb) http://nciarray.nci.nih.gov and retrieved after median centered, filtering of intensity (>200) and spot elimination (bad and no signal). Data were further analyzed using Cluster and Tree View software and Partek Pro software (Partek).

Statistical Analysis

Supervised class comparison utilized the BRB Array Tool developed at NCI, Biometric Research Branch, Division of Cancer Treatment and Diagnosis. Three subsets of genes were explored. That subset included genes upregulated in:

• cirrhotic samples from HCV-positive patients compared to normal liver samples from HCV-negative non-liver-cancer subjects (controls);

• hepatocellularcarcinoma samples in HCV-positive subjects compared to controls;

• metastatic liver tissue compared to controls

All analyses were tested for univariate significance threshold set at p- value < 0.01 or p< 0.001. Gene clusters identified by the univariate t-test were challenged with two alternative additional tests: univariate permutation test (PT) and global multivariate PT. The multivariate PT was calibrated to restrict the false discovery rate to 10%. Genes, identified by univariate t- test as differentially expressed, were considered truly differentially regulated when PT significance was <0.05. Gene function was assigned based on two Databases: (a) Genontology and (b) Annotation, Visualization and Integrated Discovery (DAVID).

EXAMPLE 1: Strategy of transcriptional analysis of Liver samples

Tumors and samples, clinical data

A series of 33 HCV-related-hepatocellular carcinomas, 15 metastasis with their corresponding non-tumor tissues and 13 control liver biopsies were collected from 61 patients enrolled at the liver unit of the INT "Pascale", Naples, Italy from 2004 to 2008. For all cases included in this study, full clinical data at enrollement and subsequent follow up are available. The sex ratio (M:F) was 3: 1 and the mean age of the patients was 68 years (range 56-80 yr) in HCV-related HCC patients. The sex ratio (M:F) was 1 :2 and the mean age of the patients was 57 years (range 39-75 yr) in Metastasis. In Controls the sex ratio (M:F) was 1 : 1 and the mean age of the patients was 53 years (range 30-77 yr). The patients were Caucasian born in Italy. The histological grade of tumor differentiation was assigned according to the Edmondson and Steiner grading system The study was approved by the local Ethics Committee, and informed consent was obtained in accordance with Italian legislation.

RNA extraction

Samples used for RNA isolation and amplification has been fresh collected and stored at in RNA Later at -80C°. Sample processing included several steps. In particular, samples were homogenized in disposable tissue grinders (Kendall, Precision) and total RNA was extracted using TRIzol (Life Technologies, Rockville, MD). The purity of the RNA preparation was tested by the A260:280nm ratio (range, 1.8-2.0) with NanoDrop. Integrity of RNA after extraction was checked using Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA) to identify the 28S and 18S ribosomal RNA bands. The good quality of RNA was evaluated on the basis of 28S/ 18S rRNA ratios equal or close to 2. In addition, phenol contamination was checked and A260:230nm ratios greater than 1.9 were considered acceptable.

Basic transcriptome analysis

cDNA was prepared from 3μg of Total RNA (T-RNA) in 9μ1 DEPC -treated H₂0 using Superscript II (Invitrogen) with a T7-(dT15) oligonucleotide primer. cDNA synthesis was completed at 42°C for lh. Full-length ds-cDNA, during the removal of the primer RNA, was synthesized from the ss-cDNAby adding 106 μΐ of DNase-free water, 15 μΐ Advantage PCR buffer (Clontech), 3 μΐ 10 mM dNTP, 1 μΐ RNase-H (Promega), 3 μΐ Advantage cDNA Polymerase (Clontech). Double-strand cDNA was extracted with phenol-chloroform-isoamyl and precipitated with ethanol in the presence of Ιμΐ linear acrylamide (0.1 μ /μ1, Ambion, Austin, TX). The amplified RNA (aRNA), mRNA equivalent, was transcribed using Ambion's T7 MegaScript in Vitro Transcription Kit (Ambion, Austin, TX). aRNA recovery and removal of template DNA was achieved by TRIzol purification. For the second round of amplification aliquots of ^g of the synthesized aRNA were reverse transcribed into cDNA using Ιμΐ of random hexamer under the conditions used in the first round. Second-strand cDNA synthesis was initiated by ^g oligo-dT-T7 primer. In vitro transcription of aRNA was carried out as for the first round (Ena Wang et al, Nature Biotechnology Vol 18 April 2000). 6μg of aRNA was used for probe preparation; test samples were labeled with USL-Cy5 (Kreatech) and pooled with the same amount of reference sample (normal donor peripheral blood mononuclear cells, PBMC) labeled with USL-Cy3 (Kreatech). The two labeled aRNA probes were separated from uncorporated nucleotides by filtration, fragmented, mixed and co- hybridized to a costum-made 36K oligoarrays at 42C° for 24h. The oligo-chips were printed at the Immunogenetics Section Department of Transfusion Medicine, Clinical Center , National Institutes of Health (Bethesda, MD). After hybridization the slides were washed with 2x SSC/0.1% SDS for lmin, lx SSC for lmin, 0.2x SSC for lmin, 0.05x SSC for lOsec, and dried by centrifugation.

Hybridized arrays were scanned at ΙΟμιη resolution on a GenePix 4000 scanner (Axon Instruments) at variable PMT voltage to obtain maximal signal intensities with less than 1% probe saturation. Resulting jpeg and data files were deposited at microarray data base (mAdb) htt ://nciarray.nci.nih . ov and retrieved after median centered, filtering of intensity (>200) and spot elimination (bad and no signal). Data were further analyzed using Cluster and Tree View software and Partek Pro software (Partek). A total of 33.827 genes were generated for further analyses.

EXAMPLE 2: Analysis of gene expression profiles

Determination of the specific HCC subgroup differentially expressed genes and subsequent GO analyses

All univariate t- and -tests were performed using BRB ArrayTools (v3.2) on the log²- transformed intensity values for the 33.827 genes. A nominal significance level of each univariate test of p< 0.001, as well as 90% confidence limits of less than 10 false discoveries, was designated based on multivariate test using 1,000 permutations. Genes identified by univariate t-test as differentially expressed (p-value <0.001 and p-value <0.01) and PT significance <0.05 were considered truly differentially expressed. Gene function was assigned based on the Databases for (a) Annotation, Visualization and Integrated Discovery (DAVID) and (b) Genontology.

Tree subsets of genes were explored. The first subset included genes upregulated in HCV- related HCC compared to control liver samples, the second subset included genes upregulated in HCV-positive cirrhotic liver tissue samples compared to control liver samples, the third subset included genes upregulated in metastatic tissue compared to controls.

EXAMPLE 3: Prognosis of HCV-related HCC

Material and methods

Microarray analysis was performed as described in basic transcriptome analysis section of Example 1.

Association of HVC-related HCC with specific Gene expression

Supervised analysis, performed as described in Analysis of gene expression profiles section of Example 2, identified 825 genes differentially expressed using unpaired Student t-test with a cut-off set at p- value < 0.01. Among them, 465 genes were shown to be up-regulated and 360 genes down-regulated in HCV-related HCC. These groups of genes can be used to differentiate between HCV-positive liver tumor samples from liver samples of subjects with chronic hepatitis/cirrhosis as well as from normal liver samples of control subjects.

In addition the gene subsets of Table 1 can, therefore, be used to identify the presence of a malignant tumor in liver tissue from chronic hepatitis and cirrhosis patients, to monitor the progression liver diseases.

EXAMPLE 4: Prognosis of HCV-related Cirrhosis

Material and methods

Association of HVC-related Cirrhosis with specific Gene expression

Supervised analysis, performed as described in Analysis of gene expression profiles section of Example 2, identified 151 genes differentially expressed setting unpaired Student t-test at p- value < 0.001. Among them, 127 genes were shown to be up-regulated and 24 genes down- regulated in HCV-related Cirrhosis.

These groups of genes can be used to differentiate between liver tumor samples from subjects with chronic hepatitis and Cirrhosis and normal liver samples without pathology.

In addition the gene subsets of Table 2 can be used to identify markers that can indicate a poor prognosis with high progression risk to HCC of cirrhotic and HCV-positive liver tissues even when non-tumor cells are present in the study sample. EXAMPLE 5: Prognosis of Liver Metastasis

Material and methods

Association of Liver Metastasis with specific Gene expression

Supervised analysis, performed as described in Analysis of gene expression profiles section of

Example 2, identified 967 genes differentially expressed using unpaired Student t-test with a cut-off set at p < 0.01. Among them, 547 genes were shown to be up-regulated and 420 genes down-regulated in metastatic samples. These groups of genes can be used to differentiate between liver metastasis samples and normal liver samples without pathology.

In addition the gene subsets of Table 3 can be used to identify markers that can indicate the presence of metastasis in liver tissues.

EXAMPLE 6: Identification of Progression Markers

Material and methods

Identification of molecular progression marker

A time course analysis was performed to find a markers of tumoral progression between normal liver samples, HCV-related Cirrhosis and HCC liver samples. For this analysis, CTR were taken as the early time point, cirrhosis the intermedian point and the HCC the last time point. The time course analysis identified 49 genes differentially expressed according to the different tissue point.

10 out of 49 were up regulated in the CTR and then completely lost in the HCC. 26 were switched off in the control and progressively upregulated in the HCC. Two genes GLUL1 and Spinkl are not expressed at all in CTR and HVC and up-regulated in HCC. The gene subsets of Table 4 can be used to identify markers that can indicate the progression of HCC.

EXAMPLE 7: In silico Hepatochip™ Macroarray Analysis

Material and methods

In silico Hepatochip™ Analysis has bee performed by aligning hybridization results of first 30 genes for each of the 4 listed tables..

Evaluation of diagnostic/prognostic efficacy of the virtual gene-chip

All tissue samples from patient cohort, listed in Figure 2, have been blinded analyzed several times to verify the virtual chip efficacy to identify the clinical stage of the enrolled patients. The in silico analysis showed a 71.2% of specificity and 87.3% sensitivity. These results support the feasibility to develop a reliable diagnostic and prognostic tool, which will need to be confirmed on a large number of biological samples (>3'000) along with the possible optimization of sets of genes.

The set of genes in each group, along with their relative expression levels, creates a profile for the diseases examined, chronic hepatitis and cirrhosis with hepatic carcinoma and metastatic liver cancer.

TABLE 1

RBP7 145 M 13755.1 retinol binding protein 7, cellular 1 16362 v-rel reticuloendotheliosis viral oncogene

homolog B, nuclear factor of kappa light

RELB 146 M83221.1 5971 polypeptide gene enhancer in B-cells 3

(avian)

RNF31 147 AY256461.1 ring finger protein 31 55072

RRAGD 145 NM_052960.2 Ras-related GTP binding D 58528 serpin peptidase inhibitor, clade B

SERPINB1 153 NM_030666.2 1992

(ovalbumin), member 1

SWI/SNF related, matrix associated, actin

SMARCC2 156 BT009924.1 dependent regulator of chromatin, subfamily 6601 c, member 2

SQSTM1 159 BC005857.2 sequestosome 1 8878

T6 (alpha-N-acetyl-neuraminyl-2,3-beta- galactosyl-1 , 3)-N-acetylgalactosaminide

ST6GALNAC4 160 BC036705.2 27090 alpha-2,6-sialyltransferase 4, transcript

variant 2,

telomeric repeat binding factor (NIMA-

TERF1 164 U40705.1 7013 interacting) 1 , transcript variant 2

TK1 165 NM_003258.4 thymidine kinase 1 , solubile 7083

TMEM106C 170 BC107792.1 transmembrane protein 106C 79022

TXN 173 BC054866.1 thioredoxin 7295

TYK2 174 BC014243.2 tyrosine kinase 2 7297 ubiquitin specific peptidase 14 (tRNA-

USP14 175 X57361 .1 guanine transglycosylase), transcript variant 9097

2

USP3 176 BC050461.1 ubiquitin specific peptidase 3 9960

VWF 180 BC022258.1 von Willebrand factor 7450

WBP5 181 AF125535.1 WW domain binding protein 5 51 186

ZBTB17 183 BC126163.1 zinc finger and BTB domain containing 17 7709

ZNF580 184 BC017698.1 zinc finger protein 580, transcript variant 2 51 157

ZNF652 185 BC139779.1 zinc finger protein 652 22834

ZNF706 186 BC068524.1 zinc finger protein 706, transcript variant 3 51 123

TABLE 2

TABLE 3

NAD(P)H dehydrogenase, quinone 1 ,

NQ01 1 18 AY281093.1 1728 transcript variant 3

NUP93 120 BC034346.1 nucleoporin 93kDa 9688

OGT 124 U77413.1 O-linked N-acetylglucosamine 8473 olfactory receptor, family 2, subfamily T,

OR2T10 125 BC136940.1 127069 member 10

progestin and adipoQ receptor family member

PAQR8 126 BC030664.2 85315

VIII

pleckstrin homology-like domain, family A,

PHLDA2 127 AF001294.1 7262 member 2

PKM2 129 M23725.1 pyruvate kinase, muscle, transcript variant 1 5315 prothymosin, alpha (gene sequence 28),

PTMA 139 AY169282.1 5757 transcript variant 2

protein tyrosine phosphatase type IVA,

PTP4A3 140 BT007303.1 1 1 156 member 3 , transcript variant 2

PYGB 142 J03544.1 phosphorylase, glycogen; brain 5834 ral guanine nucleotide dissociation stimulator,

RALGDS 143 BC059362.1 5900 transcript variant 1

S100A10 148 M81457.1 S100 calcium binding protein A10 6281

S100A1 1 149 M81457.1 S100 calcium binding protein A1 1 6282

S100A6 150 BT006965.1 S100A6-S100 calcium binding protein A6 6277

S100P 151 BT007289.1 S100P-S100 calcium binding protein P 6286 serpin peptidase inhibitor, clade B (ovalbumin),

SERPINB1 154 BT006928.1 1992 member 1

SWI/SNF related, matrix associated, actin

SMARCA4 155 U29175.1 dependent regulator of chromatin, subfamily a, 6597 member 4

small nuclear ribonucleoprotein polypeptides B

SNRPB 157 BC080516.1 6628 and B1 , transcript variant 2

serine/threonine kinase 24 (STE20 homolog,

STK24 161 BC065378.1 8428 yeast), transcript variant 1

STMN3 162 BC025234.1 stathmin-like 3 50861

SYK 163 L28824.1 spleen tyrosine kinase 6850

TFDP1 166 BC01 1685.2 transcription factor Dp-1 7027

TIMP1 167 BC007097.1 TIMP metallopeptidase inhibitor 1 7076

TK1 168 BT006941.1 thymidine kinase 1 , soluble 7083 transmembrane emp24 protein transport

TMED3 169 AY358974.1 24423 domain containing 3

TMSB10 171 M92381.1 thymosin, beta 10 9168 ubiquitously transcribed tetratricopeptide

UTX 177 BC093868.1 7403 repeat, X chromosome

VASP 178 BC026019.1 VASP-vasodilator-stimulated phosphoprotein 7408 vitamin D (1 ,25- dihydroxyvitamin D3)

VDR 179 BC060832.1 7421 receptor, transcript variant 1

tyrosine 3-monooxygenase/tryptophan 5-

YWHAZ 182 M86400.1 monooxygenase activation protein, zeta 7534 polypeptide, transcript variant 1 TABLE 4

Claims

1. Method for biomolecular detection of human liver diseases comprising the step of detecting the level of expression in a tissue sample of 30 genes or multiples from Tables 1-4; where differential expression of the genes in Tables 1-4 is indicative of liver disease.

2. Method according to claim 1, characterized by comprising the step of detecting the level of expression in a tissue sample of 30 genes or multiples from Tables 1-4; where differential expression of the genes in Tables 2 and 4 is indicative of liver progression to cirrhosis.

3. Method according to claim 1, characterized by comprising the step of detecting the level of expression in a tissue sample of 30 genes or multiples from Tables 1-4; where differential expression of the genes in Tables 1 and 4 is indicative of liver progression to hepatocellular carcinoma.

4. Method according to claim 1, characterized by comprising the step of detecting the level of expression in a tissue sample of 30 genes or multiples from Tables 1-4; where differential expression of the genes in Table 3 is indicative of metastatic liver cancer.

5. Composition comprising oligonucleotides, where each of the oligonucleotides comprises a sequence that specifically hybridizes to a gene in Tables 1-4.

6. Composition according to claim 5, comprising a solid support comprising at least two probes, where each of the probes comprises a sequence that specifically hybridizes to a gene in Tables 1-4.

7. Composition according to claim 5 or 6, in the form of a gene chip.

8. Kit for the practice of the method according to any of claims 1-4, comprising one or more solid supports having attached 30 or multiples oligonucleotides and one or more reagents for use in said method.

9. Kit according to claim 8, characterized by comprising one or more signal detection and/or array-processing instruments, one or more gene expression databases and one or more analysis and database management software packages for use in said method.