WO2006085407A1 - Method for screening gene associated with hcv level - Google Patents

Method for screening gene associated with hcv level Download PDF

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WO2006085407A1
WO2006085407A1 PCT/JP2005/018573 JP2005018573W WO2006085407A1 WO 2006085407 A1 WO2006085407 A1 WO 2006085407A1 JP 2005018573 W JP2005018573 W JP 2005018573W WO 2006085407 A1 WO2006085407 A1 WO 2006085407A1
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gene
genes
virus group
low
virus
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PCT/JP2005/018573
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French (fr)
Japanese (ja)
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Mariko Esumi
Tadatoshi Takayama
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Nihon University
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/70—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving virus or bacteriophage
    • C12Q1/701—Specific hybridization probes
    • C12Q1/706—Specific hybridization probes for hepatitis
    • C12Q1/707—Specific hybridization probes for hepatitis non-A, non-B Hepatitis, excluding hepatitis D

Definitions

  • the present invention relates to a method for screening genes whose expression is increased in the high virus group of HCV RNA and genes whose expression is increased in the low virus group.
  • Hepatitis virus is a major cause of liver disease.
  • 80% of chronic liver diseases are caused by hepatitis c virus (HCV) infection.
  • 70-80% of HCV infections do not end with transient infections, but persistent infections are established. After that, it progresses to hepatocellular carcinoma over 20-30 years after chronic hepatitis and cirrhosis. Therefore, radical cure at the stage of chronic hepatitis C, which is a high-risk group for developing hepatocellular carcinoma, is desirable.
  • IFN interferon
  • IFN interferon
  • Hepatitis C in hepatitis C is caused by a host immune response that attempts to eliminate HCV. However, due to insufficient immune response, it is considered that HCV cannot be completely eliminated, leading to persistent infection. Even if HCV cannot be eliminated completely, if the viral load can be reduced, it should be possible to stop the progression of the disease. In general, HCV has a low ability to grow, but there are cases in which the amount of liver virus is 1000 times higher. It is not clear what causes this difference in the amount of liver virus. Disclosure of the invention
  • HCV hepatitis C virus
  • the present inventor selected a plurality of cases of high viral load and low viral load from human chronic liver inflammation cases, and the difference in gene expression between these two groups occurred. It was investigated by two methods. (1) When a virus infects cells, IFN is induced as a mechanism of virus elimination. The IFN induces various antiviral molecules and goes toward virus elimination. In order to investigate whether the strength of this host defense response is a factor that creates a high or low level of liver HCV, it is necessary to induce apoptosis through IFN downstream genes and two groups between two groups with different viral loads. The amount of Bcl2-associated X protein (BAX) involved was compared.
  • BAX Bcl2-associated X protein
  • the present invention is as follows.
  • a method for screening a gene whose expression is enhanced in a high virus group tissue containing a large amount of HCV comprising:
  • liver tissue derived from liver tissue derived from liver tissue with a value of 300 units or less divided by the 18S rRNA quantitative value per 50ng of liver tissue-derived cDNA was selected as the low virus group tissue.
  • liver tissue of 30000 units or more as a high virus group tissue Selecting a liver tissue of 30000 units or more as a high virus group tissue
  • liver tissue-derived cDNA (a) Divide the number of HCV copies per 50 ng of liver tissue-derived cDNA by the 18S rRNA quantitative value Select a liver tissue with a value of 300 units or less as a low virus group tissue, and select a liver tissue with a value of 30000 units or more as a high virus group tissue,
  • a test agent for a pathological condition associated with viral load comprising at least one gene selected from the following genes (a) to (:
  • a diagnostic agent for a disease state associated with the amount of virus comprising at least one gene selected from the following genes (a) to (! 1):
  • test drug described in any one of (7) to (10), which is in the form of a microarray. 'Brief description of the drawings
  • Fig. 1 is a diagram showing the mechanism of interferon action.
  • IFN interferon
  • ISGF transcription factor IFN-stimulated gene factor
  • ISG IFN-stimulated gene
  • MxA binds to viral RNA and inhibits RNA replication.
  • OAS and PKR suppress virus growth by shutting off host cell reactions.
  • p53 induces apoptosis of host cells via Bcl2_associated X protein (BAX) and suppresses viral growth. Control.
  • BAX Bcl2_associated X protein
  • the HCV protein counteracts the host's defense against viral infection with multiple mechanisms of inhibition. .
  • FIG. 2 shows the results of quantification of liver HCV RNA.
  • Low virus group (Low) 15 cases chronic hepatitis 9 cases, cirrhosis 6 cases
  • high virus group (High) 19 cases chronic hepatitis 9 cases, cirrhosis 10 cases.
  • the HCV genotype is shown below the graph bar. All cases not listed are lb type. “+ 2a” means double infection of type lb and type 2a. Black bars are for chronic hepatitis, hatched bars are for cirrhosis, and “” is used for oligonucleotide microarray analysis. Shows the column.
  • FIG. 3 is a diagram showing genes whose expression levels are different between the high virus group (High) and the low virus group (Low). Expression levels were compared using 14 cases of high virus group (5 cases of chronic hepatitis and 9 cases of cirrhosis) and 11 cases of low virus group (6 cases of chronic hepatitis and 5 cases of cirrhosis). Significant difference was tested by Mann Whitney U test (p 0.05). The horizontal line shows the median value of chronic hepatitis cases with significant differences. “ ⁇ ” indicates the gene expression level derived from patients with chronic hepatitis, and “ ⁇ ” indicates the gene expression level derived from patients with cirrhosis.
  • FIG. 4 is a diagram showing how to obtain genes having different expression levels between the high virus group and the low virus group.
  • 8 microarrays using 4 cases of the chronic hepatitis high virus group and 4 cases of the low virus group we searched for genes that were more than twice as differential in expression as compared between the two groups.
  • Each microarray used has 54,675 probes covering more than 47,000 genes.
  • Probes with expression expressed in at least one microarray were selected (28,505), and three types of parametric tests were performed by comparison between the two groups. The number of probes with significantly different expression levels was determined.
  • probes with a difference of more than 2 times between the two groups were selected, and probes with the expression of expression in the four groups with higher expression levels were selected.
  • the genes with high expression in the high virus group were selected as high virus genes, and those with high expression in the low virus group were selected as low virus genes.
  • Fig. 5 is a diagram showing a Condition tree by clustering analysis. Clustering of 8 microarrays was performed using 117 genes (A) that differed in expression level between the two groups and 28,505 probes (B) expressed in the liver. For the microarra, HI, H2, H3, and H4 were assigned in descending order of the viral load in the high virus group, and LI, L2, L3, and L4 were assigned in the low virus group in ascending order.
  • FIG. 6 shows the results of quantification of the expression of the endogenous control gene.
  • A The signals of GAPDH and RPL 34 were compared using 8 microarrays. The signal value after per gene normalization was used.
  • B The amounts of 18S rRNA, RPL 34, and GAPDH in 34 cases of liver cDNA were quantified using real-time PCR. The expression level was expressed as a corrected value with the median of each gene as 1. “ ⁇ ” indicates the low virus group, and “ ⁇ ” indicates the high virus group.
  • FIG. 7 is a diagram showing the results of quantification of the expression of high virus genes and low virus genes by real-time PGR.
  • Three high viral genes (A, B, C) and low viral genes (D, E, F) were quantified by real-time PGR.
  • Chronic hepatitis high virus group (High) 9 cases and low The virus group (Low) was compared with 9 cases.
  • Each of the 4 cases used in the microarray is indicated by a gray circle.
  • the gene expression level was corrected with 18S rRNA. Significant difference was tested by Mann Whitney U test (p ⁇ 0.05).
  • the horizontal line shows the median value of 9 cases of chronic hepatitis.
  • FIG. 8 is a diagram showing the position and classification of 117 probes on the gene structure.
  • a box ( ⁇ ) and a white arrow indicate a gene consisting of 5 exons and their direction.
  • the black arrow indicates the position and direction of the probe used for the microarray.
  • (5) shows the case where the transcript is proved in the region where the gene has not been identified.
  • the numbers on the right indicate the number of genes for each of the 78 high virus genes and 39 low virus genes.
  • FIG. 9 is a diagram showing an outline of analysis of gene expression level in chronic hepatitis.
  • FIG. 10 is a diagram showing an outline of analysis of gene expression levels in cirrhosis.
  • Figure 11 shows the results of analyzing the presence or absence of genes commonly expressed in chronic hepatitis and cirrhosis.
  • Figure 12 shows the results of clustering analysis.
  • Figure 13 shows the location and classification of the probes used in the microarray on the gene structure.
  • Fig. 14 shows the results of verification of the expression of high viral genes in chronic hepatitis.
  • Fig. 15 shows the results of verification of the expression of high viral genes in chronic hepatitis.
  • Fig. 16 shows the results of verification of the expression of low viral genes in cirrhosis.
  • FIG. 17 is a diagram showing the quantitative results of HCV levels in cancerous and non-cancerous parts.
  • FIG. 18 shows the results of measuring the expression level of receptor-related genes.
  • FIG. 19 shows the results of measuring the expression level of receptor-related genes.
  • the present inventor selected the target non-cancerous tissue of type C hepatocellular carcinoma into a high virus group with a high amount of HCV RNA and a low virus group with a low amount of HCV RNA.
  • the present invention provides a screening method for genes whose expression is enhanced in a high virus group having a high amount of HCV RNA, and a screening method for a gene whose expression is enhanced in a low virus group having a low amount of HCV RNA. Is.
  • the present invention also provides a diagnostic agent for a disease state associated with viral load, including a gene whose expression is increased in a high virus group or a low virus group. 2. High virus group and low virus group
  • the target for crystallization is classified into a high virus group or a low virus group according to the amount of HCV RNA.
  • the target tissue of the method of the present invention is a non-cancerous tissue of a patient with type C hepatocellular carcinoma. It may also be a tissue with chronic hepatitis or cirrhosis infected with hepatitis C virus. Tissues can be frozen in liquid nitrogen and stored at -80 ° C if the method of the present invention is not performed immediately after collection.
  • RNA is extracted from the tissue.
  • a method for extracting RNA from tissue can be appropriately selected by those skilled in the art.
  • rizol Invitrogen
  • rizol can be used.
  • the amount of HCV RNA can be measured by real time PCR.
  • real time PGR Rotor-Gene 3000 (Corbett Research, Mortalke, Australia) and ABI Prism 7000 Sequence Detection System (Applied Biosystems, Foster, CA) can be used.
  • Measurement of the amount of HCV RNA can be performed by synthesizing cDNA from the RNA obtained in 2. (1) by reverse transcriptase and using, for example, 50 ng of the obtained cDNA. At that time, as a primer, for example
  • 0.3 ⁇ ⁇ ⁇ may be used.
  • the amount of HCV RNA is represented by “tmit”. “Unit” means the value obtained by converting the amount of plasmid DNA used to create the calibration curve into the number of copies, calculating the number of HCV RNA copies per 50 ng of liver tissue-derived cDNA from the calibration curve, and dividing by the 18S rRNA quantitative value. To do.
  • 18S rRNA quantification value refers to 18S rRNA in cDNA (standard sample) derived from a liver. This is the amount of standard sample cDNA equivalent to 0.25 ng of liver tissue-derived cDNA when a standard curve is prepared by measuring real-time PCR. The amount of standard sample cDNA corresponding to 0.25 ng of cDNA derived from liver tissue can be obtained from a calibration curve. '
  • the “low virus group” means a case where the amount of 110 ⁇ 11 ⁇ is 300 1111 or less.
  • the “high virus group” means a case where the amount of HCV RNA is 30000 units or more.
  • the method of the present invention is characterized in that the analysis target is selected into the high virus group and the low virus group according to the amount of HCV RNA.
  • a high virus group and a low virus group can be selected by HCV genotype. That is, by nested PCR method, la type, lb type, 2a type,
  • the HCV genotype By performing 4 HCV genotype-specific PCR of type 2b, the HCV genotype can be clarified, and the expression level of the host gene can be analyzed focusing on the specific genotype of HCV.
  • an oligonucleotide microarray or real-time PCR can be used to measure the expression level of a gene.
  • the genes whose expression is enhanced in the high virus group or low virus group are further selected from these genes by real-time PCR. Can also be selected.
  • biotin-labeled cRNA is first synthesized from the total RNA obtained in 2. (1).
  • the synthesis can be performed, for example, by partially modifying the manual of Affymetrix Gene Chip expression analysis (see Example 2 (1)).
  • the obtained cRNA is appropriately purified and fragmented for use as a target gene sample. Purification and fragmentation can be easily performed by those skilled in the art.
  • the microarray is preferably a commercially available product such as Human Genome U133 Plus 2.0 array (Affymetrix), but is not limited thereto.
  • the prepared cRNA fragment is hybridized to the array as a target gene sample.
  • Devices such as Fluidics Station 450 (Asymetrix) can also be used for hybridization, washing, and staining.
  • a scanner for example, Scanner 3000 (Affymetrix)
  • software is preferably used, and examples of the software include Gene Spring version 7 (Silicon Genetics, Redwood, CA).
  • the contingency table test uses a two- test or Fisher's exact test.
  • the Marm-Whitney U test is preferably used for the significant difference test between the two groups.
  • a method for selecting a gene whose expression is increased in the high virus group and a method for selecting a gene whose expression is increased in the low virus group are shown below.
  • the gene corresponding to this probe is a gene expressed in the liver of a patient infected with HCV. '
  • probe means a part of a gene set in a microarray.
  • the “gene corresponding to the probe” means the gene that is the source of the probe.
  • a parametric test can then be performed to extract genes that have significant differences in expression between the two groups, the high virus group and the low virus group. For example, Student's t test assuming that the variance is the same in the two groups, Welch's t test assuming that the variance is not equal, or to estimate the population variance as accurately as possible from a small number of replicates, so it will converge when increasing replicate.
  • One example is the cross-gene error model parametric test that predicts the wax standard deviation.
  • one type of test or a plurality of types of test may be used, but it is preferable to perform a plurality of tests. When multiple tests are performed, it is preferable to prepare a Venn diagram in order to examine duplication of probes extracted by these tests.
  • the degree of expression enhancement between the two groups is more than doubled, that is, between the two groups.
  • Probes that differ by more than 2 times in the expression level in The difference in the degree of expression enhancement is preferably 2 times or more, more preferably 2.5 times or more, and further preferably 3 times or more.
  • the gene corresponding to the probe whose expression is increased in the high virus group is a gene whose expression is increased in the high virus group (hereinafter also referred to as “high virus gene”).
  • the gene corresponding to the probe whose expression is up-regulated is a gene whose expression is up-regulated in the low virus group (hereinafter also referred to as “low virus gene”).
  • probes can be extracted by focusing on the present flag in all of the plurality of microarrays or in all the microarrays of the high expression group.
  • polyA + RNA for example, rRNA
  • the present inventor was able to select a total of 117 genes, 78 (Table 5) as high viral genes and 39 (Table 6A) as low viral genes by the above method (Examples). 2). Of these, the genes that differed more than 2.5 times between the two groups are shown in Tables 3 and 4.
  • each of the high virus group and low virus group was classified into four groups by classifying into chronic hepatitis and cirrhosis, and as a result of analyzing the gene expression of each group, 66 genes were found as chronic hepatitis high virus genes (Table 10). ), 21 hepatitis low virus genes (Table 11), 27 cirrhosis high virus genes (Table 12), and 17 cirrhosis low virus genes (Table 13) (Example 5).
  • RNA obtained in 2. (1) above is appropriately treated with DNasel, purified, random primer and reverse transcriptase. And synthesize cDNA.
  • DNasel purified, random primer and reverse transcriptase.
  • synthesize cDNA For example, AMV reverse transcriptase XL (Life Sciences, Gaithersurg, MD) 3 ⁇ 4i! / I can do it.
  • Oligo (dT) primer can be used instead of random primer.
  • Measurement of gene expression by real-time PCR should be performed using commercially available equipment such as Rotor-Gene 3000 (Corbett Research, Moi'talke, Australia) or ABI Prism 7000 Sequence jDetection System (Applied Biosystems, Foster, CA). Can do.
  • the reaction is performed, for example, in a 25 1 reaction solution containing 10 ng of cDNA, SYBR Green PCR Master Mix (Applied Biosystems), 0.5 M of various gene primers, 95 ° C., 10 min preheat, and 95. C 15 sec, 60 ° C 60 sec can be performed for 45 cycles. At this time, housekeeping genes such as 18S rRNA can be quantified using, for example, 0.25 ng of cDNA. Those skilled in the art can appropriately design primers used for the reaction using software. The URL of typical software “primer 3” is shown below. (http://frodo.wi.mit.edu/cgi-bm/primer3/prirner3_www.cgi;
  • a calibration curve is prepared using a certain liver cDNA as a standard sample for quantification and used for quantification of various genes.
  • the liver cDNA showing the highest expression in each gene can be used as a standard sample, and the amount of the cDNA can be used as a quantitative value. If a sample of the sample cDNA to be measured is subjected to real-time PCR of gene X and the sample can be evaluated as 5 ng from the calibration curve, the sample should have the same amount as gene X mRNA contained in 5 ng of the standard sample cDNA. Gene X mRNA will be present.
  • the expression level of each gene is obtained by dividing the quantitative expression value of each gene in the measurement target sample obtained from the calibration curve by the endogenous control gene expression quantitative value (for example, the quantitative value of 18s rRNA in the measurement target sample). Relative value.
  • 18S rRNA glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal protein L34 (RPL34) can be used as the “endogenous control gene”, but the expression level is small. 18S rRNA is preferred.
  • the expression level of each gene in the host can be a value corrected with 18S rRNA.
  • the expression level of the low virus group is compared with the expression level of the high virus group.
  • a gene having a value obtained by dividing the median expression level of the high virus group by the median value of the low virus group is 2 or more, preferably 2.5 or more, more preferably 3 or more is selected as the high virus gene. be able to.
  • a gene of 2 or more, preferably 2.5 or more, more preferably 3 or more is selected as the low virus gene. can do.
  • High virus genes are considered to include genes that are induced beyond the ability of the host virus defense function of the high virus group to eliminate HCV. Therefore, there may be factors in the high viral genes that are expected to work in favor of growth on the HCV side.
  • the low viral genes there may be genes involved in creating an environment where HCV is difficult to propagate. That is, if the expression of a low viral gene screened by the present invention is enhanced, the growth of hepatitis C virus can be suppressed. It is expected to lead to the development of hepatitis C virus growth inhibitor and hepatitis c virus growth suppression method characterized by enhancing the expression of low viral genes.
  • the high virus gene and the low virus gene can be further classified into those derived from chronic hepatitis and those derived from cirrhosis, and the expression level can be analyzed.
  • patients can be classified into chronic hepatitis cases and cirrhosis cases as patient background factors, and comparison between the two groups can be performed for each item (sex, age, stage, etc.) using the viral load as an index.
  • the high virus gene and the low virus gene may be further classified into those derived from chronic hepatitis and those derived from cirrhosis, and after classification of the disease state (chronic hepatitis and cirrhosis), Classify viral genes and low viral genes
  • the order is not limited to the order. That is, in the gene expression analysis in the present invention, the gene group is a virus gene group in chronic hepatitis (CHH group), a low virus gene group in chronic hepatitis (CHL group), or a high virus gene group in cirrhosis (LCH group). As long as it is classified into 4 types of low viral gene group (LCL group) in cirrhosis and cirrhosis, the order of classification is not limited.
  • CHH group chronic hepatitis
  • CHL group chronic hepatitis
  • LCH group high virus gene group in cirrhosis
  • SEQ ID NO: 1 7 A gene that hybridizes under stringent conditions to a base sequence that is complementary to any of the base sequences represented by ⁇ 2 37 and that is highly expressed in the high virus group of chronic hepatitis
  • stringent conditions are washing conditions when nucleic acids are hybridized with each other, and are defined by the salt concentration and temperature of the buffer.
  • conditions of 37-52 ° C with concentrations of 0.5-2 X SSC and 0.1% SDS can be mentioned, and more stringent conditions include, for example, 65 ° C with 2 X SSC and 0.1% SDS.
  • the conditions include conditions such as 42 ° C at 0.5 X SSC and 0.1% SDS.
  • a person skilled in the art can set appropriate conditions by taking into consideration various conditions such as the concentration and length of other probes and reaction time in addition to the conditions such as the salt concentration and temperature of the buffer. it can.
  • the expression “enhanced expression” of a gene refers to a case where quantitative analysis is performed by real-time PCR, and the obtained quantitative value is higher than that of a group having different viral load to be compared.
  • Each gene belonging to the CHH gene group, the CHL gene group, the LCH gene group or the LCL gene group analyzed in the present invention becomes a viral load marker in chronic hepatitis for the CHH gene group and the CHL gene group.
  • Genes and LCL gene cluster can be a marker of viral load in cirrhosis. Therefore, by analyzing the expression levels of these genes from liver tissue obtained from patients, etc., how much virus is proliferating in which disease, how much hepatic function is maintained, and what kind of antiviral It can be judged whether a reaction can be induced.
  • the gene analyzed in the present invention is hybridized with a gene obtained from a liver tissue of a patient or the like, and is detected by hydration to determine which pathological condition is related to viral load. Judgment can be made. Hybridization conditions and labeling methods are well known to those skilled in the art, and any method other than those described herein can be employed.
  • the above gene can be used as a diagnostic agent for pathological conditions related to viral load.
  • gene expression level analysis can be performed easily and comprehensively.
  • the gene can be used in the form of a kit together with a buffer (for example, Tris buffer), a labeling reagent (for example, a fluorescent labeling reagent) and the like.
  • a buffer for example, Tris buffer
  • a labeling reagent for example, a fluorescent labeling reagent
  • a microarray carrying the above genes can also be included in the kit.
  • Non-cancerous tissues were isolated from cancer excision specimens of 59 patients with type C hepatocellular carcinoma, immediately frozen in liquid nitrogen and stored at -80 ° C. The use of specimens for research was obtained with the consent of each patient.
  • RNA 6000 nano assay chip from Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, Calif.) To evaluate the total RNA quality. DNase I treatment was performed to remove DNA mixed in the extracted RNA.
  • Total DNase I (Takara, Shiga, Japan) 10 units against 20 g of RNA, calorie-free, reacted at 37 ° C for 20 min in 50 ⁇ 1, and purified with rizol 9 RNA after DNase I treatment 10
  • random primer and 25 units of AMV reverse transcriptase XL (Life Sciences, Gaithersurg, MD) were added to synthesize cDNA in 1001.
  • Rotor-Gene 3000 Corbett Research, Mortalke, Australia
  • ⁇ Prism 7000 Sequence Detection System (Applied Biosystems, Foster, CA) were used for expression quantification by real-time PCR in the Examples.
  • HCV RNA was quantified using 50 ng of cDNA, and 18S rRNA was quantified using 0,25 ng of cDNA.
  • the HCV primer was used at 0.3 M.
  • plasmid DNA standard plasmid DNA
  • liver cDNA showing the highest expression for each gene was used as a standard sample
  • the cDNA was used to create a calibration curve for quantitative value calculation.
  • the quantitative amount of HCV RNA was calculated by converting the amount of standard plasmid DNA into the number of copies of the virus, obtaining the number of copies of HCV RNA per 50 ng of cDNA, and dividing the value by the quantitative value of 18S rRNA as “unit”.
  • endogenous control genes 18S rRNA, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and ribosomal protein L34 (RPL34) were used as endogenous control genes.
  • the expression level of each gene is determined by dividing the quantitative expression value of each gene by the quantitative expression value of the endogenous control gene. .wi. mit.edu/cgi-bin/primer3/primer3—use www.cgi)! I'm sorry. (table 1).
  • HCV quantitation HCV GACCAAGCTCAAACTCACTC 3 GCACGAGACAGGCTGTGATA 4
  • IFN-related genes PKR ACAATTGGCCGCTAAACTTG 16 GCGAGTGTGCTGGTCACTAA 17 p53 AACAACACCAGCTCCTCTCC 18 AACAACACCAGCTCCTCTCC 19
  • AW612461 a TGTGTAAGGCACAGGGTTTT 32 CAGCTGACTGTGGAAGGGTA 33
  • Microarray Low 154 a CACCTTGGATGACGAAACAA 42 GAGTTTCTGGGAAGGCAAAA 43
  • ENC1 GAAATCATTCCCAAGGCTGA 46 CTTTCGAGACCCCATTTTCA 47
  • HCV genotype-specific PCRs of la type, lb type, 2a type, and 2b type were performed by Okamoto's nested PCR method.
  • the first round PCR was performed using a consensus primer of 35 cycles in 20 ⁇ 1.
  • 35 cycles were carried out in a second front PCR 20 ⁇ 1 with a common forward primer and an additional U reverse primer.
  • the primer sequences used are shown in Table 1.
  • the PCR product 51 was subjected to 3% agarose gel electrophoresis, and the HCV genotype was determined from the size of the PCR product because the la type was 49 bp, the lb type was 144 bp, the 2a type was 174 bp, and the 2b type was 123 bp. (4) Selection of target cases
  • the quantification value was distributed in the range of 0 to 372,068 units. Cases with a viral load of 300 units or less were classified as a low virus group, and 30000 units or more were classified as a high virus group.
  • the low virus group was 15 cases, of which 9 were chronic hepatitis (CH) and 6 were cirrhosis (LC).
  • the high virus group consisted of 19 cases, consisting of 9 cases of chronic hepatitis and 10 cases of cirrhosis (Fig. 2).
  • CH chronic hepatitis
  • LC cirrhosis
  • High high virus group
  • Low low virus group
  • ICG-R15 indocyanine green IV rate after 15 minutes
  • Alb serum albumin
  • AST asparate aminotransferase
  • ALT alanine aminotransferase
  • T.bil total bilirubin
  • Table 2 in 34 cases (CH + LC), the percentage of cirrhosis (LC), sex ratio, age distribution, and hepatoma progression rate Divided by difference There was no difference between the two groups. Blood test results indicating liver function (“Liver function”) also show mild liver damage, but there was no significant difference between the two groups. Based on the above, using these 34 cases, it was considered possible to analyze the level of gene expression in livers that differ 1000-fold in viral load.
  • biotin-labeled cRNA was synthesized from total RNA as follows.
  • the manual of Affymetrix Gene Chip expression analysis was partially modified and performed as follows. First, 10 g of total RNA was used in the presence of RNase inhibitor42. First strand cDNA was synthesized at C and 2 hr. After synthesizing the second strand cDNA according to the manual, incubate the 43 1 reaction solution containing the following composition based on MEGAscript T7 kit (Ambion, Austin, TX) for 9 hr at 37 ° C. In vitro transcription was performed, and biotirrcRNA 3 ⁇ 4r was synthesized.
  • the expression of OAS, MxA, and BAX was significantly increased in the high virus group compared with 11 cases of chronic hepatitis ( ⁇ 0.05). There was no significant difference between the two groups in 14 cirrhosis cases or 25 cases in total. In addition, no significant difference was observed when comparing the 9 cases of HCV genotype lb alone. Thus, a significant difference was observed only in chronic hepatitis cases.
  • Fig. 3 show the measurement results of the expression level when 18S rRNA is used as the endogenous control gene.
  • 18S i'RNA Each gene expression level was evaluated as a trawl gene (described later).
  • Figure 8 Expression analysis by microarray was performed using the 8 cases indicated by “T” (4 cases of high virus group and 4 cases of low virus group in chronic hepatitis cases). Human Genome U133 Plus 2.0 airay (Affymetrix) was used, and 54,675 probes (probe) corresponding to more than 47,000 transcripts of humans were targeted. Figure 4 shows how to obtain genes that are significantly different in expression between 4 high virus groups and 4 low virus groups.
  • Fig. 4 (a) This is the gene expressed in the liver (specifically, the liver of chronic hepatitis).
  • three types of parametric tests were performed using 28,505 probes to extract genes with significant differences in expression between the two groups, the high virus group and the low virus group (Fig. 4 (b)). Student's t test, which is assumed to have the same variance in the two groups, extracted 1,710 probes, and Welch's t test, which assumes that the variances are not equal, extracted 1,327 probes.
  • FIG. 5A A clustering analysis of eight microarrays using these 117 genes was performed to create a Condition tree (Fig. 5A). Unlike the Condition tree with 28,505 probes (Fig. 5B), it was shown that the gene list can distinguish cases between the high virus group and the low virus group.
  • Tables 3 and 4 show the genes that were more than 2.5 times different between the two groups among 78 high virus genes and 39 low virus genes (Table 3) (Table 4).
  • proteasome proteasome (prosome, macropain)
  • alpha type, 8 (1) O is described in the gene whose expression was quantified by a real-time PCR.
  • the difference captured here is considered to be a transcript of a gene having a high homology with this probe.
  • Table 78 shows all 78 high virus genes and Table 6 shows all 39 low virus genes.
  • Example 2 found by comparison of 8 cases of microarray In order to investigate whether it was indeed correlated with the difference in HCV levels, we performed expression analysis by real-time PCR using 34 cases of liver cDNA. .
  • the housekeeping gene which is said to be expressed at a constant level per cell, is used as a control gene for evaluating the expression level of the gene.
  • j3 -actin and GAPDH genes are typical genes. However, when examining tissues and cells of various pathologies and conditions, it cannot be said that these genes are expressed constantly. Recently, 18S i'RNA has been used. In this example, we independently examined 8 microarrays of genes that are constantly expressed in the target hepatitis tissue.
  • the HG U133 Plus2.0 array used here lists 100 genes as control genes among the probes on it. Of these, 91 genes had present flags in all 8 microarrays. From these, we searched for genes that showed no difference in expression level among the 8 microarrays and that showed the same expression level as GAPDH. As a result, ribosomal protein L34 (RPL34) was selected. Compared to the GAPDH expression signal on the same microarray, RPL34 certainly had less variation in expression level (Figure 6A).
  • 18S rRNA cannot be evaluated by microarray analysis. Therefore, in order to clarify which of RPL34 and 18S rRNA is suitable as a control gene, the expression levels were compared by real-time PCR in all 34 cases.
  • Figure 6B shows a comparison of the expression levels of the 3 genes including GAPDH. Comparing the expression level of cDNA—quantitatively, the variation in the expression level of 18S rRNA was the smallest compared to PRL34 and GAPDH. Therefore, in this example, the following gene expression was evaluated using 18S rRNA as an endogenous control gene.
  • the comparison between the two groups was divided into 8 cases of chronic hepatitis (CH) and 18 cases of total chronic hepatitis (CH) and 16 cases of total cirrhosis (LC) used for microarray analysis.
  • As the expression level of the gene values corrected with 18S rRNA were used.
  • High virus group The number of low virus group is shown in parentheses. The result of 8 high virus genes is shown in the “High” column of Table 7, and the result of 5 low virus genes is shown in the “: Low” column of Table 7.
  • Fold change indicates the value when compared with the median of each group. For example, in the case of a high virus gene, the value obtained by dividing the median value of the high virus group of the gene by the median value of the low virus group is shown. In addition, the Mann Whitney U test was performed between the two groups, and the values of genes that had a significant difference (P ⁇ 0.05) were surrounded by a broken line. The reversible changes that showed a significant difference are enclosed in a solid line.
  • Figure 7 shows typical comparison results for chronic hepatitis.
  • the high virus genes shown in A to C of FIG. 7 were genes that clearly showed a significant difference in expression level between the virus group and the low virus group.
  • low virus genes showed similar results to microarray expression in 2 out of 5 genes, but after all, there was only 1 significant difference in chronic hepatitis (Table 7).
  • This heritable SELE showed a different tendency even in cirrhosis (Table 7).
  • the results of the above two genes SELE and FLJ461542 are shown in D and 3 ⁇ 4 of FIG.
  • N80145 was recognized as an opposite significant difference in chronic hepatitis, ie, a high viral gene (F).
  • the 117 genes that differed in expression extracted with Oligonucleotide microarra were classified according to the functions of known genes, unknown genes, and known genes.
  • (A) Structural classification Figure 8 shows the structural classification of 117 probes based on the latest gene information. There are five categories of gene classifications. .
  • (1) means the transcript of the relevant gene.
  • (2) may be a alternatively spliced transcript of the gene of interest or a new transcript.
  • (3) may be a transcript as an interfering RNA or a new transcript.
  • (4) may be a transcript of the gene of interest or a new transcript.
  • (5) is considered an unknown transcript.
  • INF-inducible genes were found as differential genes. Of the 239 genes known as INF-inducible genes, only 2 were among the high viral genes. This indicates that IFN is not working so strongly, even in high virus cases. In chronic hepatitis in which persistent infection was established, it was suggested that host genes other than IFN are involved in viral load control.
  • low viral genes there were genes with serine protease inhibitory active regions and genes related to the plugeothesome. This gene is expected to inhibit viral growth.
  • genes involved in inflammation other than high viral genes were also included.
  • more than half of the low-viral genes were unknown genes whose functions were unknown.
  • transcripts that act as HCV interfering RNA were not included, or homology with the HCV 9.5 kb sequence was examined. However, there was no such sequence in the low viral gene.
  • Low viral genes may have genes involved in creating an environment in which HCV is difficult to grow.
  • HCV ' was quantified, and the number of cases was increased from Example 1 and 2 and divided into two pathological conditions, and the viral load was related.
  • the genes to be studied were examined. First, the amount of liver virus was quantified, and cases were selected. The method is shown below. The methods for total RNA extraction and real-time RT-PCR are the same as in Example 1. '
  • the amount of virus was determined by quantifying the virus gene. As materials, non-cancerous tissues of 59 cases of hepatocellular carcinoma were used, and I and II with the lowest hepatocellular carcinoma stage were selected as much as possible.
  • LC shows a case where the non-cancerous tissue has progressed to cirrhosis.
  • A indicates the case used for microarray analysis. Liver HCV levels ranged from 4 to 480000 units. Among them, 20 cases of 30000 units or more were assigned to the high virus group, and 15 cases of 300 units or less were assigned to the low virus group.
  • CH and LC showed different gene expression patterns. Therefore, in this example, genes related to viral load were examined by dividing into two disease states. did. Patient background factors were compared between the selected high virus group and low virus group. The patient background factors were divided into 18 cases of chronic hepatitis and 17 cases of cirrhosis, and each item was compared between two groups according to viral load. Table of significant difference test values
  • HCV RNA d (unit) 69,900 ⁇ 8,700 63 ⁇ 15 118,000 ⁇ 39,00C 158 ⁇ 42
  • the latest version of the oligonucleotide microarray was used to comprehensively examine the total mRNA expressed in liver tissue for differences in gene expression.
  • the GeneChip used has 54675 probes corresponding to about 47000 genes that are considered to be all human genes.
  • 5 cases of high virus group of chronic hepatitis and 5 cases of low virus group were newly added, and 7 cases of cirrhosis high virus group and 3 cases of low virus group were newly added.
  • a total of 20 microarrays were used, 10 for each disease state, and comparisons were made between two groups, 5: 5 for chronic hepatitis and 7: 3 for cirrhosis, to identify genes with differential expression.
  • Fig. 9 is a schematic diagram of a method for determining genes with different expression levels using microarray analysis results.
  • analysis was performed in 4 cases each for the high virus group and low virus group, but in this example, analysis was performed for 5 cases in each group.
  • Tables 10 to 13 list the chronic hepatitis high virus gene, chronic hepatitis low virus gene, cirrhosis high virus gene, and cirrhosis low virus gene, respectively.
  • ⁇ ⁇ A is the exon sequence of the gene
  • B is the gene.
  • Introri is the sequence in the same direction as the gene
  • C is the gene.
  • ⁇ ⁇ The sequence is in the opposite direction to the gene in intron
  • D is the sequence in the gene The contiguous arrangement in the same direction, E, indicates the sequence where the gene is not.
  • CHH-2 LCH-3 (Table 12) Table 1 1. Low viral genes in chronic hepatitis (CHL 21)
  • b A gene extracted by oligonucleotide microarray analysis in 8 cases of chronic hepatitis.
  • clustering analysis was performed to determine whether the expression pattern of the extracted gene is effective as a gene that can distinguish the difference in viral load.
  • the chronic hepatitis gene 87 gene was clustered into 66 high virus genes and 21 low virus genes, and 10 cases of chronic hepatitis were classified into low virus (L) and high virus (H) groups. It was shown that the cluster can be classified neatly (Fig. 12).
  • analysis of 10 cases of cirrhosis with 44 cirrhosis genes revealed a clean cluster classification of 2 groups of 3 and 7 cases.
  • the cluster classification of 10 cases could not be performed correctly when the cirrhosis cases were analyzed with the chronic hepatitis gene and when the chronic hepatitis cases were analyzed with the cirrhosis gene. Therefore, the genes related to viral load were shown to be different between chronic hepatitis and cirrhosis. '' Example 7
  • Table 14 shows the primer sequences used.
  • HCV type 2 accounts for about half of the low virus group. 4 of 9 cases with chronic hepatitis and 3 out of 6 cases with cirrhosis.
  • the low virus group was divided by HCV genotype and compared with the high virus group. Since there are only a few cases of genotype dependence, we narrowed down to only those that were graved on a boxplot. Some genes are analyzed by analyzing the cirrhosis high virus group in 9 cases. The ratio of the current dose in the high / less group and the low virus group was measured by the Mann-Whitney.U.test. The results of analysis for each of chronic hepatitis and cirrhosis are shown as' P values. 'P Blank indicates no measurement. The low virus group was divided by HCV genotype, and a comparison between the two groups was also performed.
  • the left panel compares the low virus group with high viral cancers divided into genotype 1 and type 2.
  • the right panel summarizes the entire low virus group compared to the high virus group.
  • the figure is a box-and-whisker plot, showing the distribution of measured values in each group. From the bottom, the lower end of the whiskers represents the 10th percentile, the lower end of the box represents the 25th percentile, the middle line of the box represents the 50th percentile, the upper end of the box represents the 75th percentile, and the upper end of the whiskers represents the 90th percentile.
  • the margin P value is The result of comparison between two groups of the amount of virus was based on the Mann- Whitney U test.
  • the left panel shows the results of dividing the low virus group into HCV genotypes 1 and 2 and comparing it to the high virus group.
  • OASL is a high virus gene commonly found in chronic hepatitis and cirrhosis. This gene was verified only in chronic hepatitis. SNAI2 was also verified as a chronic hepatitis high virus gene. All genes showed low expression in the low virus group regardless of the HCV genotype.
  • Figure 15 is an example of the chronic hepatitis high virus (CHH) gene.
  • CXCL6 expression was suppressed only in the HCV genotype 1b low virus group.
  • AK025967 was a low viral gene in cirrhosis.
  • Figure 16 shows an example of the cirrhosis low virus (LCL) gene.
  • LCL cirrhosis low virus
  • HCV is a single-stranded RNA virus with a positive strand RNA of approximately 9.6 kb. There are many genotypes in the HCV genome and so far it has been divided into more than 6 genotypes. HCV is a spherical virus with a diameter of 50-60 nm and has a structure in which the core particles are enveloped.
  • HCV adsorbs to hepatocytes via a receptor, enters the cytoplasm by endocytosis, and then sheds and releases RNA.
  • This RNA immediately binds to the ribosome as mRNA and a precursor protein consisting of about 3000 amino acids is translated.
  • Precursor proteins translated on the endoplasmic reticulum membrane are produced as three structural proteins and seven nonstructural proteins by cell signalases and two proteases encoded by the virus itself.
  • the synthesized viral RNA-dependent RNA polymerase causes the viral RNA to replicate one strand from the + strand and then the + strand.
  • the + strand RNA is taken up by the core protein, and particle formation occurs while covering the endoplasmic reticulum with an envelope.
  • Virus particles are thought to pass through the Golgi apparatus, reach the cell membrane, and be released out of the hepatocytes. In these processes, cell adsorption and invasion can be considered as the first step to control the viral load. Therefore, in this example, it was examined whether the difference in viral load was related to the expression of viral receptors and endocytosis-related genes. '
  • the method was as follows. First, the amount of visceral virus was quantified, and cases were selected. The method is shown below. The methods for total RNA extraction and real-time RT-PCR are the same as in Example 1.
  • the amount of virus was determined by quantifying the virus gene. As materials, I and II with the lowest hepatocellular carcinoma stage were selected as much as possible, using cancerous and non-cancerous tissues of 50 hepatocellular carcinoma cases.
  • Fig. 17 is a graph showing the results of liver HCV RNA quantification, with the ordinate indicating the amount of HCV in the cancerous part and the horizontal axis indicating the amount of HCV in the non-cancerous part.
  • the solid line shows the case where the amount of the cancerous part (T) is 1 with respect to the non-cancerous part (NT), and the dotted line shows 1 node 4 (T / NT, below the solid line) and 4 times (on the solid line).
  • Non-cancerous HCV is widely distributed from tens to hundreds of thousands.
  • HCV in the cancer area was the same amount or decreased, and it was found that 29 cases (58%) out of 50 cases were less than 1/4. In more than half of cases in the cancer area, it can be said that HCV is difficult to infect or increase. Therefore, regarding the difference in viral load, we examined not only differences among non-cancerous members but also differences among cancerous members.
  • CD81 and heparan sulfate are known as receptors that recognize HCV envelope proteins.
  • heparan sulfate three molecules of glycosyltransferase involved in heparan sulfate synthesis were measured.
  • Receptors that recognize the sugar chains of HCV envelope proteins include the C-type lectins DC-SIGN, L-SIGN, ASGR, and MBL2, and mannose and galactose are the recognition molecules. Since HCV particles bind to LDL and HDL in blood to form a complex, it is suggested that these receptors, LDLR and SCARB1, act as HCV receptors. SCARB1 is also thought to recognize E2 protein directly.
  • Endocytosis-related molecules include clathrin proteins and adapter proteins.
  • an adapter protein that exists in the vicinity of the receptor in the cell membrane, gathers around the receptor, which triggers the heavy chain (Clathrin) C) Trimer and light chain (Clathrin A)
  • the clathrin consisting of trimer comes together. By gathering a lot of clathrin, a clathrin-coated pit is created and a endome is formed.
  • TLR3, TICAM1, DDX58 Toll-like receptor-related signal molecules
  • Table 16 shows the primer sequences of each gene.
  • Table 17 shows the results of quantification by PCR.
  • Table 16 HCV receptor candidates and viral entry-related genes and their PCR primer sequences
  • **: The cDNA used for PGR is 25 ng. The other is 10ng.
  • NL low virus group
  • NH high virus group
  • Table 18 shows a comparison of background factors between the two groups.
  • HCV genotype (lb: lb + 2a: 2a: 2b) FE 6: 0: 2: 2 11: 3: 0: 0 0.0455 6: 0: 2: 2 6: 1: 0: 0 5: 2 6: 1
  • Count Average soil standard error, 'ICG, Indocyanine green 15 minutes after intravenous injection; Alb, serum albmin; AST, aspartate aminotransferase! AL ⁇ T, alanin aminotransferase; T.bill, total bilirubin; AFP, PIV, protein induced by vitamin K absence; HCVRNA, normalized by 18S rRNA; MW, Mann-Whitney's U test; FE, Fisher's sexact probability test
  • L-SIGN receptor gene
  • This high viral gene may contain factors that are expected to work favorably for HCV growth, so it is possible to suppress the expression of high viral genes. Can be inhibited.
  • This low viral gene may have a 3 ⁇ 4 gene that is involved in creating a circle in which HCV is difficult to grow.
  • HCV proliferation can be suppressed by enhancing the expression of the low virus gene.

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Abstract

A method for screening a gene whose expression is increased in a high virus group tissue containing a large amount of HCV comprising the following steps of: (a) selecting a liver tissue whose value obtained by dividing the copy number of HCV per 50 ng of liver tissue-derived cDNA by the quantitative value of 18S rRNA is not more than 300 units as a low virus group tissue and not more than 30000 units as a high virus group tissue; (b) measuring the gene expression level in the low virus group tissue and high virus group tissue; and (c) selecting a gene whose expression is increased in the high virus group tissue more than the low virus group tissue.

Description

明 細書  Specification
HCV量に関連する遺伝子のスクリーニング方法 技術分野 Methods for screening genes related to HCV levels
本発明は、 HCV RNAの高ウィルス群において発現亢進している遺伝子およぴ低 ウィルス群において発現亢進している遺伝子をスクリーニングする方法に関する。  The present invention relates to a method for screening genes whose expression is increased in the high virus group of HCV RNA and genes whose expression is increased in the low virus group.
背景技術 Background art
肝炎ウィルスは、 肝疾患の主な原因である。 特に、 慢性肝疾患の八割は c型 肝炎ウィルス (HCV)の感染が原因となっている。 HCVの感染の 70〜80%は、 一過性感染で終わらず持続感染が成立する。その後、慢性肝炎、肝硬変を経て、 20〜30年かけて肝細胞癌に進展する。 したがって、肝細胞癌発症の高危険群で ある、 C型慢性肝炎の段階での根治が望ましい。 現在、 抗ウィルス薬としてィ ンターフェロン (IFN)が認可され使用されてレヽる。 しかし、 約 30%にしか効果 がないため、 依然として有効な治療法はない状況である。  Hepatitis virus is a major cause of liver disease. In particular, 80% of chronic liver diseases are caused by hepatitis c virus (HCV) infection. 70-80% of HCV infections do not end with transient infections, but persistent infections are established. After that, it progresses to hepatocellular carcinoma over 20-30 years after chronic hepatitis and cirrhosis. Therefore, radical cure at the stage of chronic hepatitis C, which is a high-risk group for developing hepatocellular carcinoma, is desirable. Currently, interferon (IFN) is approved and used as an antiviral drug. However, only about 30% is effective, and there is still no effective treatment.
HCVそのものによる細胞障害性はほとんどないにも拘わらず、重篤な肝疾患 を引き起こすことが知られている。 C型肝炎の肝障害は、 HCVを排除しようと する宿主免疫反応により引き起こされている。 し力 し、 免疫応答が不十分なた め、 HCVを完全に排除することができず持続感染につながると考えられている。 たとえ、 HCVを完全に排除できなくとも、 ウィルス量を抑えることができれば 病態の進展を食い止めることができるはずである。 一般に HCVの増殖能は低 いが、 中には肝臓ウィルス量が 1000倍以上多い症例が存在する。 この肝臓ゥ ィルス量の違いが何に起因するかは明らかではない。 発明の開示  It is known to cause severe liver disease even though there is almost no cytotoxicity due to HCV itself. Hepatitis C in hepatitis C is caused by a host immune response that attempts to eliminate HCV. However, due to insufficient immune response, it is considered that HCV cannot be completely eliminated, leading to persistent infection. Even if HCV cannot be eliminated completely, if the viral load can be reduced, it should be possible to stop the progression of the disease. In general, HCV has a low ability to grow, but there are cases in which the amount of liver virus is 1000 times higher. It is not clear what causes this difference in the amount of liver virus. Disclosure of the invention
上記の通り、 C型肝炎ウィルス （HCV) のウィルス量は、 症例により違いがあ る。 本発明者は、 これらの違いが何によるものかを明らかにすれば、 自然経過にお ける抗ウィルス作用機構を知ることができるとともに、 抗ウィルス治療薬開発に 役立つ標的分子を明らかにできると考えた。 As mentioned above, the amount of hepatitis C virus (HCV) varies by case. By clarifying what these differences are, the present inventor can know the antiviral action mechanism in the natural course and develop antiviral therapeutics. We thought that useful target molecules could be clarified.
本発明者は、 上記課題を解決するために、 ヒト慢性肝.炎症例から、 高ウィルス 量と低ウィルス量の症例を複数選別し、 この 2群間でどのような遺伝子の発現 に差が生じているのかを、 2つの方法により調べた。 （1 ) 細胞にウィルスが感 染すると、 ウィルスの排除機構として IFNが誘導される。 その IFNは、 様々 な抗ウィルス作用分子を誘導してウィルス排除に向かう。 この宿主防御反応の 強弱が、 肝臓 HCV量の多い、 または、 少ない状況を作り出している要因であ るか調べるため、 ウィルス量の異なる 2群間で、 IFN下流遺伝子およびそれを 介しておこるアポトーシスに関与する Bcl2-associated X protein (BAX)の発 現量を比較した。 （2 ) ウィルス量のコントロールに関与する新規の遺伝子を探 し出すため、 高ウィルス群と低ウィルス群症例を各 4例選ぴ Oligonucleotide microarrayを用いた網羅的発現解析を行った。 鋭意研究の結果、 ヒト慢性肝炎 組織から高ウィルス量およぴ低ゥィルス量の症例を複数選び、ゥィルス側及ぴ宿主 側からの要因を検討することによって、高ウィルス量および低ウィルス量で高発現 する遺伝子を見出す方法の確立に成功し、 本発明を完成するに至った。  In order to solve the above problems, the present inventor selected a plurality of cases of high viral load and low viral load from human chronic liver inflammation cases, and the difference in gene expression between these two groups occurred. It was investigated by two methods. (1) When a virus infects cells, IFN is induced as a mechanism of virus elimination. The IFN induces various antiviral molecules and goes toward virus elimination. In order to investigate whether the strength of this host defense response is a factor that creates a high or low level of liver HCV, it is necessary to induce apoptosis through IFN downstream genes and two groups between two groups with different viral loads. The amount of Bcl2-associated X protein (BAX) involved was compared. (2) In order to search for new genes involved in the control of viral load, we selected four cases of high virus group and low virus group, respectively, and conducted comprehensive expression analysis using Oligonucleotide microarray. As a result of diligent research, we selected multiple cases with high viral load and low viral load from human chronic hepatitis tissues, and investigated the factors from the virus side and host side, thereby expressing high expression at high viral load and low viral load. The present inventors have succeeded in establishing a method for finding genes to be completed, and have completed the present invention.
すなわち、 本発明は以下の通りである。  That is, the present invention is as follows.
( 1 )多量の HCVを含む高ウィルス群組織において発現が亢進する遺伝子をスク リ一ユングする方法であって、  (1) A method for screening a gene whose expression is enhanced in a high virus group tissue containing a large amount of HCV, comprising:
(a)肝組織由来 cDNA 50ng当りの HCVのコピー数を 18S rRNA定量値で割つ た値が 300 unit 以下の肝組織を低ウィルス群組織として選択し、 当該値が (a) Liver tissue derived from liver tissue derived from liver tissue with a value of 300 units or less divided by the 18S rRNA quantitative value per 50ng of liver tissue-derived cDNA was selected as the low virus group tissue.
30000unit以上の肝組織を高ウィルス群組織として選択するステップ、 Selecting a liver tissue of 30000 units or more as a high virus group tissue,
(b) 前記低ゥィルス群組織および高ウイルス群組織における遺伝子の発現量を 測定するステップ、 並びに、  (b) measuring the expression level of the gene in the low virus group tissue and the high virus group tissue, and
(c) 前記低ウィルス群組織よりも高ウィルス群組織において発現が亢進する遺伝 子を選択するステップ  (c) selecting a gene whose expression is enhanced in a high virus group tissue than in the low virus group tissue
を含む前記方法。  Including said method.
( 2 )少量の HCVを含む低ウィルス群組織において発現が亢進する遺伝子をスク リーユングする方法であって、  (2) A method for screening a gene whose expression is enhanced in a low virus group tissue containing a small amount of HCV,
(a)肝組織由来 cDNA 50ng当りの HCVのコピー数を 18S rRNA定量値で割つ た値が 300 unit 以下の肝組織を低ウィルス群組織として選択し、 当該値が 30000unit以上の肝組織を高ウィルス群組織として選択.するステツプ、 (a) Divide the number of HCV copies per 50 ng of liver tissue-derived cDNA by the 18S rRNA quantitative value Select a liver tissue with a value of 300 units or less as a low virus group tissue, and select a liver tissue with a value of 30000 units or more as a high virus group tissue,
(b) 前記低ゥィルス群組織および高ウイルス群組織における遺伝子の発現量を 測定するステップ、 並びに、  (b) measuring the expression level of the gene in the low virus group tissue and the high virus group tissue, and
(c)前記高ウィルス群組織よりも低ウィルス群組織において発現が亢進する遺伝 子を選択するステップ  (c) selecting a gene whose expression is enhanced in the low virus group tissue than in the high virus group tissue
を含む前記方法。  Including said method.
( 3 ) 遺伝子の発現量の測定がマイクロアレイおよび/またはリアルタイム PCR を用いることを特徴とする、 （1 ) または （2 ) 記載の方法。  (3) The method according to (1) or (2), wherein the expression level of the gene is measured using a microarray and / or real-time PCR.
( 4 )高ウィルス群組織における遺伝子の発現量力 低ウィルス群における遺伝子 の発現量に対して 2倍以上発現亢進することを特徴とする、 （1 ) 記載の方法。 (4) The gene expression level in the high virus group tissue The method according to (1), wherein the gene expression level is increased two or more times with respect to the gene expression level in the low virus group.
( 5 )低ウィルス群組織における遺伝子の発現量が、高ウィルス群における遺伝子 の発現量に対して 2倍以上発現宂進することを特徴とする、 （2 ) 記載の方法。(5) The method according to (2), wherein the expression level of the gene in the low virus group tissue is more than twice as much as the expression level of the gene in the high virus group.
( 6 )低ウィルス群組織又は高ウィルス群組織を、 さらに慢性肝炎由来のもの及び 肝硬変由来のものに分類することを特徴とする （1 ) 〜 （5 ) のいずれか 1項に 記載の方法。 (6) The method according to any one of (1) to (5), wherein the low virus group tissue or the high virus group tissue is further classified into those derived from chronic hepatitis and those derived from cirrhosis.
( 7 ) 以下の (a)〜( の遺伝子から選ばれる少なくとも 1つの遺伝子を含有する、 ウィルス量に関連する病態の検査薬。  (7) A test agent for a pathological condition associated with viral load, comprising at least one gene selected from the following genes (a) to (:
(a)配列番号 5 4〜 1 3 1で表される塩基配列を含む遺伝子  (a) a gene comprising the nucleotide sequence represented by SEQ ID NOs: 5 4 to 1 3 1
(b) 配列番号 5 4〜 1 3 1で表される塩基配列に相補的な塩基配列にストリ ンジヱントな条件下でハイブリダィズし、 かつ、高ウィルス群において発現が亢 進する遺伝子  (b) A gene that hybridizes under stringent conditions to a base sequence complementary to the base sequence represented by SEQ ID NOs: 5 4 to 1 3 1 and whose expression is enhanced in a high virus group
(c)配列番号 1 3 2〜1 7 0で表される塩基配列を含む遺伝子  (c) a gene comprising the base sequence represented by SEQ ID NOs: 1 3 2 to 1 70
(d) 配列番号 1 3 2〜1 7 0で表される塩基配列に相補的な塩基配列にスト リンジェントな条件下でハイブリダィズし、 かつ、低ウィルス群において発現が 亢進する遺伝子  (d) A gene that hybridizes under stringent conditions to a base sequence complementary to the base sequence represented by SEQ ID NOs: 1 3 2 to 1 70 and has enhanced expression in the low virus group
( 8 ) 以下の (a)〜(！ 1)の遺伝子から選ばれる少なくとも 1つの遺伝子を含有する、 ゥィルス量に関連する病態の検査薬。  (8) A diagnostic agent for a disease state associated with the amount of virus, comprising at least one gene selected from the following genes (a) to (! 1):
(a)配列番号 1 7 1〜2 3 7で表されるいずれかの塩基配列を含む遺伝子 (b) 配列番号 1 7 1〜2 3 7で表されるいずれかの塩基配列に相補的な塩基 配列にストリンジェントな条件下でハイブリダィズし.、 かつ、慢性肝炎の高ウイ ルス群において発現が亢進する遺伝子 (a) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 1 7 1 to 2 3 7 (b) Hybridizes under stringent conditions to a base sequence complementary to any one of the base sequences represented by SEQ ID NOs: 1 1 to 2 3 7 and is expressed in the high virus group of chronic hepatitis Enhanced gene
(c)配列番号 2 3 8〜2 5 8で表されるいずれかの塩基配列を含む遺伝子 (d) 配列番号 2 3 8〜 2 5 8で表されるいずれかの塩基配列に相補的な塩基 配列にストリンジヱントな条件下でハイプリダイズし、 かつ、慢性肝炎の低ウイ ルス群において発現が亢進する遺伝子  (c) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 2 3 8 to 2 5 8 (d) a base complementary to any one of the nucleotide sequences represented by SEQ ID NOs: 2 3 8 to 2 5 8 A gene that is highly hybridized under stringent conditions in the sequence, and whose expression is enhanced in the low virus group of chronic hepatitis
(e)配列番号 2 5 9〜2 8 5で表されるいずれかの塩基配列を含む遺伝子 (£)配列番号 2 5 9〜2 8 5で表されるいずれかの塩基配列に相補的な塩基配 列にストリンジヱントな条件下でハイプリダイズし、 かつ、肝硬変の高ウィルス 群において発現が亢進する遺伝子  (e) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 2 5 9 to 2 85 (£) a base complementary to any one of the nucleotide sequences represented by SEQ ID NOs: 2 5 9 to 2 85 A gene that is highly hybridized under stringent conditions and is highly expressed in the high virus group with cirrhosis.
(g)配列番号 2 8 6〜3 0 2で表されるいずれかの塩基配列を含む遺伝子 (g) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 2 8 6 to 30 2
(h) 配列番号 2 8 6〜3 0 2で表されるいずれかの塩基配列に相補的な塩基 配列にストリンジェントな条件下でハイプリダイズし、 かつ、肝硬変の低ウィル ス群において発現が亢進する遺伝子 (h) Hyper-hybridized under stringent conditions to a base sequence complementary to any of the base sequences represented by SEQ ID NOs: 2 86 to 30 and enhanced expression in the low virus group with cirrhosis Genes
( 9 ) マイクロアレイの形態である、 （7 ) 〜 （1 0 ) のいずれか 1項に記载の検 査薬。 ' 図面の簡単な説明  (9) The test drug described in any one of (7) to (10), which is in the form of a microarray. 'Brief description of the drawings
図 1は、 インターフェロン作用機構を示す図である。 ウィルス感染によりィ ンターフヱロン (IFN) α / β が誘導されると、 Jak - Statシグナル伝達系を介 して転写因子 IFN-stimulated gene factor (ISGF) 3 が誘導される。 この転写 因ナ; 0 IFN-stimulated resoonse element (ISRE)に結合し、 IFN-stimulated gene (ISG)の転写が誘導される。 ここでは 4つの ISG - myxovirus resistance protein A (MxA), 2', 5'oligoadenylate synthetase (OAS), double -stranded RNA-dependent protein kinase (PKR), p53_の誘導を示す。 MxAはウィルス RNA に結合し、 RNA複製を阻害する。 OAS や PKR は宿主細胞内反応を shut-off することによりウィルス増殖を抑制する。 p53 は Bcl2_associated X protein (BAX )を介して宿主細胞のアポトーシスを誘導し、 ウィルス増殖を抑 制する。 これら宿主のウィルス感染防御反応に対し、 HCVタンパク質は複数 の抑制機構をもって対抗している。 . Fig. 1 is a diagram showing the mechanism of interferon action. When interferon (IFN) α / β is induced by viral infection, the transcription factor IFN-stimulated gene factor (ISGF) 3 is induced via the Jak-Stat signal transduction system. This transcription factor; 0 binds to IFN-stimulated response element (ISRE) and induces transcription of IFN-stimulated gene (ISG). Here, induction of four ISG-myxovirus resistance protein A (MxA), 2 ', 5'oligoadenylate synthetase (OAS), double-stranded RNA-dependent protein kinase (PKR), and p53_ is shown. MxA binds to viral RNA and inhibits RNA replication. OAS and PKR suppress virus growth by shutting off host cell reactions. p53 induces apoptosis of host cells via Bcl2_associated X protein (BAX) and suppresses viral growth. Control. The HCV protein counteracts the host's defense against viral infection with multiple mechanisms of inhibition. .
図 2は、 肝臓 HCV RNAの定量結果を示す図である。 低ウィルス群 （Low) 15 例 （慢性肝炎 9例、肝硬変 6例)、高ウィルス群 （High) 19例 （慢性肝炎 9例、 肝硬変 10例)の HCV RNA量を示した。グラフ棒の下に HCV遺伝子型を示す。 記載のない症例は、 すべて lb型である。 また 「+2a」 は、 lb型と 2a型との二 重感染を意味する。 黒棒は慢性肝炎、斜線棒は肝硬変、 「 」 は oligonucleotide microarray角军析に用レ、た；！ Εί列を示す。  FIG. 2 shows the results of quantification of liver HCV RNA. Low virus group (Low) 15 cases (chronic hepatitis 9 cases, cirrhosis 6 cases), high virus group (High) 19 cases (chronic hepatitis 9 cases, cirrhosis 10 cases). The HCV genotype is shown below the graph bar. All cases not listed are lb type. “+ 2a” means double infection of type lb and type 2a. Black bars are for chronic hepatitis, hatched bars are for cirrhosis, and “” is used for oligonucleotide microarray analysis. Shows the column.
図 3は、 高ウイルス群 (High)と低ウイルス群 (Low)とで発現量に差があった 遺伝子を示す図である。 高ウィルス群 14例 （慢性肝炎 5例と肝硬変 9例） と 低ウィルス群 11例 （慢性肝炎 6例と肝硬変 5例） とを用いて発現量を比較し た。 Mann Whitney U testにて有意差を検定した (pく 0.05)。 横線は有意差のあ つた慢性肝炎症例の中央値を示す。 「秦」は慢性肝炎患者由来の遺伝子発現量を 示し、 「〇」 は肝硬変患者由来の遺伝子発現量を示す。  FIG. 3 is a diagram showing genes whose expression levels are different between the high virus group (High) and the low virus group (Low). Expression levels were compared using 14 cases of high virus group (5 cases of chronic hepatitis and 9 cases of cirrhosis) and 11 cases of low virus group (6 cases of chronic hepatitis and 5 cases of cirrhosis). Significant difference was tested by Mann Whitney U test (p 0.05). The horizontal line shows the median value of chronic hepatitis cases with significant differences. “秦” indicates the gene expression level derived from patients with chronic hepatitis, and “◯” indicates the gene expression level derived from patients with cirrhosis.
図 4は、 高ウィルス群と低ウィルス群とで発現量に差のある遺伝子の求め方 を示す図である。 慢性肝炎高ウィルス群 4例と低ウィルス群 4例とを用いた 8 枚の microarrayについて、 二群間の比較で 2倍以上発現量に差のあった遺伝 子を探し出した。 用いた microarray 1枚には約 47，000遺伝子以上を網羅する 54,675 probeが載っている。 少なくとも 1枚の microarrayで発現有りの表記 がでた probeを選択し (28,505)、 2群間の比較で 3種類のパラメ トリック検定 を行った。 それぞれで有意に発現量が異なる probe 数を求めた。 いずれの検定 でも選ばれた共通 probe 683個について、 2群間で 2倍以上差のある probeを 選び、 さらに発現量の多い群 4枚とも発現有りの表記がでた probeを選んだ。 最終的には遺伝子として、高ウィルス群に発現優位のものを高ウィルス遺伝子、 低ウィルス群に発現優位のものを低ウィルス遺伝子とした。  FIG. 4 is a diagram showing how to obtain genes having different expression levels between the high virus group and the low virus group. For 8 microarrays using 4 cases of the chronic hepatitis high virus group and 4 cases of the low virus group, we searched for genes that were more than twice as differential in expression as compared between the two groups. Each microarray used has 54,675 probes covering more than 47,000 genes. Probes with expression expressed in at least one microarray were selected (28,505), and three types of parametric tests were performed by comparison between the two groups. The number of probes with significantly different expression levels was determined. For 683 common probes selected in any test, probes with a difference of more than 2 times between the two groups were selected, and probes with the expression of expression in the four groups with higher expression levels were selected. Eventually, the genes with high expression in the high virus group were selected as high virus genes, and those with high expression in the low virus group were selected as low virus genes.
図 5は、 クラスタリング解析による Condition treeを示す図である。 2群間 で発現量に差のあった遺伝子 117遺伝子 （A)と肝臓に発現していた 28,505 probe (B) とを用いて 8枚の microarrayのクラスタリングを行った。 microarra は、 高ウィルス群のなかでウィルス量の多い順に HI, H2, H3, H4 とし、 低ウィルス群でウィルス量の少ない順に LI, L2， L3， L4 とした。 Fig. 5 is a diagram showing a Condition tree by clustering analysis. Clustering of 8 microarrays was performed using 117 genes (A) that differed in expression level between the two groups and 28,505 probes (B) expressed in the liver. For the microarra, HI, H2, H3, and H4 were assigned in descending order of the viral load in the high virus group, and LI, L2, L3, and L4 were assigned in the low virus group in ascending order.
図 6は、 内在性コントロール遺伝子の発現定量の結果を示す図である。 （A) GAPDH と RPL 34のシグナルを 8枚の microarrayで比較した。 per gene normalization後のシグナル値を用いた。 （B) 34例の肝臓 cDNAにおける 18S rRNA, RPL 34, GAPDH量を real-time PCRを用いて定量した。 発現量は各 遺伝子の中央値を 1 とした捕正値で表した。 「〇」 は 低ウィルス群、 「譬」 は 高ウィルス群を示す。  FIG. 6 shows the results of quantification of the expression of the endogenous control gene. (A) The signals of GAPDH and RPL 34 were compared using 8 microarrays. The signal value after per gene normalization was used. (B) The amounts of 18S rRNA, RPL 34, and GAPDH in 34 cases of liver cDNA were quantified using real-time PCR. The expression level was expressed as a corrected value with the median of each gene as 1. “◯” indicates the low virus group, and “譬” indicates the high virus group.
図 7は、 高ウィルス遺伝子および低ウィルス遺伝子の real-time PGRによる 発現定量の結果を示す図である。 各 3つの高ウィルス遺伝子 (A, B, C)と低ウイ ルス遺伝子 (D， E, F)について、 real-time PGRにより発現定量を行い、 慢性肝 炎高ウイルス群 (High) 9例と低ウイルス群 (Low) 9例とで比較した。  FIG. 7 is a diagram showing the results of quantification of the expression of high virus genes and low virus genes by real-time PGR. Three high viral genes (A, B, C) and low viral genes (D, E, F) were quantified by real-time PGR. Chronic hepatitis high virus group (High) 9 cases and low The virus group (Low) was compared with 9 cases.
microarrayに用いた各 4例は、灰色丸で示した。遺伝子の発現量は、 18S rRNA で補正した値を用いた。 Mann Whitney U testにて有意差を検定した (p<0.05)。 横線は慢性肝炎 9症例の中央値を示す。 Each of the 4 cases used in the microarray is indicated by a gray circle. The gene expression level was corrected with 18S rRNA. Significant difference was tested by Mann Whitney U test (p <0.05). The horizontal line shows the median value of 9 cases of chronic hepatitis.
図 8は、 117 probeの遺伝子構造上の位置と分類を示す図である。 ボックス (□) と白矢印により、 exon 5個からなる遺伝子とその方向を示す。 黒矢印は microarrayに使用された probeの位置とその方向を示す。 （5) は遺伝子が同定 されていない領域に、 転写産物が証明されている場合を示す。 右の数字は、 高 ウィルス遺伝子 78個と低ウィルス遺伝子 39個の各分類別遺伝子数を示す。 図 9は、 慢性肝炎における遺伝子発現量の解析の概要を示す図である。  FIG. 8 is a diagram showing the position and classification of 117 probes on the gene structure. A box (□) and a white arrow indicate a gene consisting of 5 exons and their direction. The black arrow indicates the position and direction of the probe used for the microarray. (5) shows the case where the transcript is proved in the region where the gene has not been identified. The numbers on the right indicate the number of genes for each of the 78 high virus genes and 39 low virus genes. FIG. 9 is a diagram showing an outline of analysis of gene expression level in chronic hepatitis.
図 1 0は、 肝硬変における遺伝子発現量の解析の概要を示す図である。  FIG. 10 is a diagram showing an outline of analysis of gene expression levels in cirrhosis.
図 1 1は、 慢性肝炎と肝硬変において共通に発現する遺伝子の有無を解析し た結果を示す図である。  Figure 11 shows the results of analyzing the presence or absence of genes commonly expressed in chronic hepatitis and cirrhosis.
図 1 2は、 クラスタリング解析結果を示す図である。  Figure 12 shows the results of clustering analysis.
図 1 3は、 microarrayに使用された probeの遺伝子構造上の位置と分類を示 す図である。  Figure 13 shows the location and classification of the probes used in the microarray on the gene structure.
図 1 4は、 慢性肝炎における高ウィルス遺伝子について発現の検証を行った 結果を示す図である。 図 1 5は、 慢性肝炎における高ウィルス遺伝子について発現の検証を行った 結果を示す図である。 Fig. 14 shows the results of verification of the expression of high viral genes in chronic hepatitis. Fig. 15 shows the results of verification of the expression of high viral genes in chronic hepatitis.
図 1 6は、 肝硬変における低ウィルス遺伝子について発現の検証を行った結 果を示す図である。 '  Fig. 16 shows the results of verification of the expression of low viral genes in cirrhosis. '
図 1 7は、 癌部と非癌部における HCV量の定量結果を示す図である。  FIG. 17 is a diagram showing the quantitative results of HCV levels in cancerous and non-cancerous parts.
図 1 8は、 受容体関連遺伝子の発現量を測定した結果を示す図である。  FIG. 18 shows the results of measuring the expression level of receptor-related genes.
図 1 9は、 受容体関連遺伝子の発現量を測定した結果を示す図である。 発明を実施するための最良の形態  FIG. 19 shows the results of measuring the expression level of receptor-related genes. BEST MODE FOR CARRYING OUT THE INVENTION
以下、本発明を詳細に説明する。 以下の実施の形態は、 本発明を説明するため の例示であり、 本発明をこの実施の形態にのみ限定するものではない。  The present invention will be described in detail below. The following embodiment is an illustration for explaining the present invention, and the present invention is not limited to this embodiment.
なお、 本明細書において引用された全ての先行技術文献および公開公報、 特 許公報その他の特許文献は、 参照として本明細書に組み込むものとする。 1 . 本発明の概要  It should be noted that all prior art documents, publications, patent gazettes and other patent documents cited in the present specification are incorporated herein by reference. 1. Summary of the present invention
HCVに感染した慢性肝炎、 肝硬変肝組織において、 ウィルス量の多い症例と少 ない症例が存在することが知られている。本発明者は、 このウィルス量の違いが宿 主側の何に起因するかを明らかにする目的で、ヒト慢性肝炎組織のさまざまな遺伝 子の発現レベルを調べ、 ウィルス増殖に関連する宿主側要因を検討した。  In chronic hepatitis and cirrhotic liver tissues infected with HCV, it is known that there are cases with high and low viral load. The present inventor investigated the expression levels of various genes in human chronic hepatitis tissues in order to clarify what causes the difference in viral load on the host side, and the host side factors related to virus growth. It was investigated.
具体的には、本発明者は、対象症例である C型肝細胞癌の非癌部組織を、 HCV RNA量の多い高ウィルス群と、 HCV RNA量の少ない低ウィルス群とに選別し、 この 2群間での遺伝子の発現レベルを解析し、 それぞれの群において発現が亢 進している遺伝子を見出した。  Specifically, the present inventor selected the target non-cancerous tissue of type C hepatocellular carcinoma into a high virus group with a high amount of HCV RNA and a low virus group with a low amount of HCV RNA. We analyzed gene expression levels between the two groups, and found genes whose expression was enhanced in each group.
したがって、 本発明は、 HCV RNA量の多い高ウィルス群において、 発現亢進 している遺伝子のスクリーニング方法、および、 HCV RNA量の少ない低ウィルス 群において、発現亢進している遺伝子のスクリーニング方法を提供するものである。 また、本発明は、高ウィルス群又は低ウィルス群において発現亢進している遺伝 子を含む、 ウィルス量に関連する病態の検査薬を提供する。 2 . 高ウィルス群および低ウィルス群 Therefore, the present invention provides a screening method for genes whose expression is enhanced in a high virus group having a high amount of HCV RNA, and a screening method for a gene whose expression is enhanced in a low virus group having a low amount of HCV RNA. Is. The present invention also provides a diagnostic agent for a disease state associated with viral load, including a gene whose expression is increased in a high virus group or a low virus group. 2. High virus group and low virus group
本発明の方法の好ましい態様においては、 まず、 角析対象を HCV RNA量に よって、 高ウィルス群または低ウィルス群に分類する。  In a preferred embodiment of the method of the present invention, first, the target for crystallization is classified into a high virus group or a low virus group according to the amount of HCV RNA.
( 1 ) 試料 ' '  (1) Sample ''
本発明の方法の対象となる組織は、 C型肝細胞癌患者の非癌部組織である。また、 C型肝炎ウィルスに感染した慢性肝炎、肝硬変の組織であってもよい。組織は採取 後すぐに本発明の方法を実施しない場合は、液体窒素で凍結して、 -80°Cにて保存 することもできる。  The target tissue of the method of the present invention is a non-cancerous tissue of a patient with type C hepatocellular carcinoma. It may also be a tissue with chronic hepatitis or cirrhosis infected with hepatitis C virus. Tissues can be frozen in liquid nitrogen and stored at -80 ° C if the method of the present invention is not performed immediately after collection.
続いて、 組織から total RNAを抽出する。 組織から RNAを抽出する方法は、 当 業者であれば適宜選択することができるが、 例えば rizol (Invitrogen)を用いるこ とができる。  Subsequently, total RNA is extracted from the tissue. A method for extracting RNA from tissue can be appropriately selected by those skilled in the art. For example, rizol (Invitrogen) can be used.
( 2 ) HCV RNA量の測定  (2) Measurement of HCV RNA level
HCV RNA量は、 real time PCRによつて測定することができる。 real time PGR には、 列えば、 Rotor-Gene 3000 (Corbett Research, Mortalke, Australia) と ABI Prism 7000 Sequence Detection System (Applied Biosystems, Foster, CA)を用いることができる。  The amount of HCV RNA can be measured by real time PCR. For real time PGR, Rotor-Gene 3000 (Corbett Research, Mortalke, Australia) and ABI Prism 7000 Sequence Detection System (Applied Biosystems, Foster, CA) can be used.
HCV RNA量の測定は、 2 . ( 1 ) で得られた RNAから逆転写酵素によって cDNAを合成し、 得られた cDNAの例えば 50ng相当を用いて実施することが できる。 そのとき、 プライマーとしては、 例えば  Measurement of the amount of HCV RNA can be performed by synthesizing cDNA from the RNA obtained in 2. (1) by reverse transcriptase and using, for example, 50 ng of the obtained cDNA. At that time, as a primer, for example
Forward (5'-3')： GACCAAGCTCAAACTCACTC (配列番号 1 ) Forward (5'-3 '): GACCAAGCTCAAACTCACTC (SEQ ID NO: 1)
Reverse (5'-3')： GCACGAGACAGGCTGTGATA (配列番号 2 ) Reverse (5'-3 '): GCACGAGACAGGCTGTGATA (SEQ ID NO: 2)
を 0.3 ί Μ用いてもよい。  0.3 ί よ い may be used.
HCV全長を組み込んだプラスミド DNAを用いて検量線を作成し、 HCV RNA 量の定量に用いる。  Create a standard curve using plasmid DNA incorporating the full length of HCV and use it to quantify the amount of HCV RNA.
本発明において、 HCV RNA量は、 「tmit」 で表す。 「unit」 は、 検量線作成に 用いたプラスミ ド DNA量を copy数に換算し、検量線から肝組織由来の cDNA 50ng当りの HCV RNAコピー数を求め、 18S rRNA定量値で割った値を意味 する。  In the present invention, the amount of HCV RNA is represented by “tmit”. “Unit” means the value obtained by converting the amount of plasmid DNA used to create the calibration curve into the number of copies, calculating the number of HCV RNA copies per 50 ng of liver tissue-derived cDNA from the calibration curve, and dividing by the 18S rRNA quantitative value. To do.
「18S rRNA定量値」は、ある肝臓由来の cDNA (標準サンプル）中の 18S rRNA をリアルタイム PCRで測定して、 標準サンプル cDNAに対する検量線を作成 したときの、 肝組織由来の cDNA0.25ng相当における標準サンプル cDNA量 を意味する。 肝組織由来の cDNA0.25ng相当における標準サンプル cDNA量 は検量線から求めることができる。 ' “18S rRNA quantification value” refers to 18S rRNA in cDNA (standard sample) derived from a liver. This is the amount of standard sample cDNA equivalent to 0.25 ng of liver tissue-derived cDNA when a standard curve is prepared by measuring real-time PCR. The amount of standard sample cDNA corresponding to 0.25 ng of cDNA derived from liver tissue can be obtained from a calibration curve. '
例えば、 肝組織由来の cDNA 50n 当りの HCV RNAコピー数が 8000であ り、 肝組織由来の cDNA 0.25ng当りの 18S rRNA定量値が 0.2ngのときは、 40000 unitとなる (8000 X 1/0.2 = 40000)。  For example, if the number of HCV RNA copies per 50n of liver tissue-derived cDNA is 8000 and the quantification value of 18S rRNA per 0.25ng of liver tissue-derived cDNA is 0.2ng, then 40000 units (8000 X 1 / 0.2 = 40000).
( 3 ) 対象症例の選別  (3) Selection of target cases
本発明において、 「低ウィルス群」 とは、 11〇¥ 11^量が 300 1111 以下の症例 を意味する。  In the present invention, the “low virus group” means a case where the amount of 110 ¥ 11 ^ is 300 1111 or less.
本発明において、 「高ウィルス群」 とは、 HCV RNA量が 30000 unit以上の 症例を意味する。  In the present invention, the “high virus group” means a case where the amount of HCV RNA is 30000 units or more.
3 . 遺伝子の発現量の測定 3. Measurement of gene expression level
本発明の方法は、 HCV RNA量によって、 解析対象を前記の高ウィルス群と 低ウィルス群とに選別して行うことを特徴とする。  The method of the present invention is characterized in that the analysis target is selected into the high virus group and the low virus group according to the amount of HCV RNA.
さらに、本発明は、高ウィルス群および低ウィルス群を HCV遺伝子型によって 選別することもできる。すなわち、 nested PCR法により、 la型、 lb型、 2a型、 Furthermore, according to the present invention, a high virus group and a low virus group can be selected by HCV genotype. That is, by nested PCR method, la type, lb type, 2a type,
2b型の 4つの HCV遺伝子型特異的 PCRを行うことで HCV遺伝子型を明らか にし、 HCVの特定の遺伝子型に注目して、宿主遺伝子の発現量解析を行うこと もできる。 By performing 4 HCV genotype-specific PCR of type 2b, the HCV genotype can be clarified, and the expression level of the host gene can be analyzed focusing on the specific genotype of HCV.
また、 高ウィルス群および低ウィルス群から慢性肝炎または肝硬変の症例の みを抽出して、 宿主遺伝子の発現量解析を行うこともできる。  It is also possible to extract only the cases of chronic hepatitis or cirrhosis from the high virus group and low virus group and analyze the expression level of the host gene.
本発明の遺伝子スクリーユング方法において、 遺伝子の発現量の測定にはォ リゴヌクレオチドマイクロアレイまたはリアルタイム PCR を用いることがで きる。  In the gene screening method of the present invention, an oligonucleotide microarray or real-time PCR can be used to measure the expression level of a gene.
また、 高ウィルス群または低ウィルス群で発現亢進する遺伝子をオリゴヌク レオチドマイクロアレイで選択した後、 これらの遺伝子の中から高ウィルス群 または低ウィルス群で発現亢進する遺伝子をリアルタイム PCRでさらに絞つ て選択することもできる。 In addition, after selecting genes whose expression is enhanced in the high virus group or low virus group using the oligonucleotide microarray, the genes whose expression is enhanced in the high virus group or low virus group are further selected from these genes by real-time PCR. Can also be selected.
( 1 ) オリゴヌクレオチドマイクロアレイ  (1) Oligonucleotide microarray
( a ) 発現解析方法 '  (a) Expression analysis method ''
宿主の遺伝子の発現量を測定するために、 まず、 2 . ( 1 ) で得られた total RNAから biotin-標識 cRNAを合成する。合成は、例えば、 Affymetrix Gene Chip expression analysisのマニュアルを一部改変して実施することができる （実施 例 2 ( 1 ) 参照）。 得られた cRNAは、 標的遺伝子サンプルとして使用するた めに、 適宜精製し、 断片化する。 精製、 断片化は、 当業者であれば容易に実施 することができる。  In order to measure the expression level of the host gene, biotin-labeled cRNA is first synthesized from the total RNA obtained in 2. (1). The synthesis can be performed, for example, by partially modifying the manual of Affymetrix Gene Chip expression analysis (see Example 2 (1)). The obtained cRNA is appropriately purified and fragmented for use as a target gene sample. Purification and fragmentation can be easily performed by those skilled in the art.
マイクロアレイは、 Human Genome U133 Plus 2.0 array (Affymetrix)など の市販品を用いることが好ましいが、 これに限定されるわけではない。  The microarray is preferably a commercially available product such as Human Genome U133 Plus 2.0 array (Affymetrix), but is not limited thereto.
次に、 作製した cRNA断片を標的遺伝子サンプルとしてアレイにハイブリダ ィズさせる。 ハイブリ ダィズ、 洗浄、 染色には、 Fluidics Station 450 (Asymetrix)などの機器を用いることもできる。 ハイプリダイズ、 洗浄、 染色 の方法は、市販アレイであれば、添付のマニュアルにしたがうことが好ましい。 続いて、 スキャナー （たとえば、 Scanner 3000 (Affymetrix)) にて遺伝子発 現のシグナルを読み取り、 解析する。 遺伝子発現シグナルの解析には、 ソフ ト ウェアを用いることが好ましく、 ソフトウェアには、 例えば、 Gene Spring version 7 (Silicon Genetics, Redwood, CA)を挙げることができる。  Next, the prepared cRNA fragment is hybridized to the array as a target gene sample. Devices such as Fluidics Station 450 (Asymetrix) can also be used for hybridization, washing, and staining. As for the method of hypridizing, washing, and staining, it is preferable to follow the attached manual for commercially available arrays. Subsequently, the gene expression signal is read and analyzed with a scanner (for example, Scanner 3000 (Affymetrix)). For analysis of gene expression signals, software is preferably used, and examples of the software include Gene Spring version 7 (Silicon Genetics, Redwood, CA).
シグナル値の補正は、 マイクロアレイ毎に中央値を 1 とする 「 per chip normalization J を行レヽ、 つづレヽて、 逾伝子毋に中央値を 1とする 「per gene noraialization」 ^行つこと »好ましい。  To correct the signal value, set the median value to 1 for each microarray “Per chip normalization J” and then set it to “per gene noraialization” with the median value of 1 .
( b ) 統計学的解析  (b) Statistical analysis
本発明において、 分割表の検定は、 2検定またはフィ ッシャーの直接確率 検定を用いる。 また、 2群間の有意差検定は、 Marm- Whitney U検定を用いる ことが好ましい。 In the present invention, the contingency table test uses a two- test or Fisher's exact test. In addition, the Marm-Whitney U test is preferably used for the significant difference test between the two groups.
( c ) 発現解析手順  (c) Expression analysis procedure
高ウィルス群において発現亢進している遺伝子を選択する方法、およぴ低ウィル ス群において発現亢進している遺伝子を選択する方法を以下に示す。 同時に複数試料で発現解析を行う場合は、まず、複数枚のマイクロアレイのうち、 少なくとも 1枚で発現の確認された （「present flag」 の.出た） プローブを抽出する ことができる。 このプローブに対応する遺伝子が、 HCVに感染した患者の肝臓に 発現している遺伝子である。 ' A method for selecting a gene whose expression is increased in the high virus group and a method for selecting a gene whose expression is increased in the low virus group are shown below. When performing expression analysis on multiple samples at the same time, it is possible to first extract a probe whose expression has been confirmed (from the “present flag”) in at least one of the multiple microarrays. The gene corresponding to this probe is a gene expressed in the liver of a patient infected with HCV. '
ここで「プローブ」は、マイクロアレイにセットした、遺伝子の一部を意味する。 「プローブに対応する遺伝子」 とは、 プローブの元となった遺伝子を意味する。 次に、 高ウィルス群と低ゥ'ィルス群との 2群間で発現に有意な差がある遺伝 子を抽出するために、 パラメ トリック検定を行うことができる。 例えば、 2群 で分散が等しいと仮定する Student's t test、 分散が等しくないと仮定する Welch's t test, あるいは、 少ない replicateからできるだけ正確な母分散を見 積もるため、 replicateを増やした時に収束するであろう標準偏差を予測計算す る Cross-gene error modelのパラメ トリック検定が挙げられる。 本発明におい て、検定は 1種類でもよいし、複数種類でもよいが、複数行うことが好ましい。 複数の検定を行う場合は、 これらの検定で抽出されたプローブの重複を調べ るために、 Venn diagramを作製することが好ましい。  Here, “probe” means a part of a gene set in a microarray. The “gene corresponding to the probe” means the gene that is the source of the probe. A parametric test can then be performed to extract genes that have significant differences in expression between the two groups, the high virus group and the low virus group. For example, Student's t test assuming that the variance is the same in the two groups, Welch's t test assuming that the variance is not equal, or to estimate the population variance as accurately as possible from a small number of replicates, so it will converge when increasing replicate. One example is the cross-gene error model parametric test that predicts the wax standard deviation. In the present invention, one type of test or a plurality of types of test may be used, but it is preferable to perform a plurality of tests. When multiple tests are performed, it is preferable to prepare a Venn diagram in order to examine duplication of probes extracted by these tests.
続いて、 1種類の検定で抽出されたプローブ、 または複数の検定で共通に抽 出されたプローブを対象にして、 2群間で発現亢進の程度が 2倍以上、 すなわ ち、 2群間での発現量に 2倍以上差のあるプローブを選択できる。 発現亢進の 程度の差は、 好ましくは 2倍以上、 より好ましくは 2.5倍以上、 さらに好まし くは 3倍以上である。 選択されたプローブのうち、 高ウィルス群において発現 亢進しているプローブに対応する遺伝子が、 高ウィルス群において発現亢進し ている遺伝子 （以下 「高ウィルス遺伝子」 ともいう） であり、 低ウィルス群に おいて発現亢進しているプローブに対応する遺伝子が、 低ウィルス群において 発現亢進している遺伝子 （以下 「低ウィルス遺伝子」 ともいう） である。  Subsequently, with respect to probes extracted by one type of test or probes extracted in common by multiple tests, the degree of expression enhancement between the two groups is more than doubled, that is, between the two groups. Probes that differ by more than 2 times in the expression level in The difference in the degree of expression enhancement is preferably 2 times or more, more preferably 2.5 times or more, and further preferably 3 times or more. Among the selected probes, the gene corresponding to the probe whose expression is increased in the high virus group is a gene whose expression is increased in the high virus group (hereinafter also referred to as “high virus gene”). The gene corresponding to the probe whose expression is up-regulated is a gene whose expression is up-regulated in the low virus group (hereinafter also referred to as “low virus gene”).
また、 場合によっては、 さらに、 複数枚のマイクロアレイのすべてにおいて、 または高発現群のマイクロアレイのすべてにおいて present flagのついているも のに絞って、 プローブを抽出することもできる。 また、 プローブの対応する遺伝子 が同一であり重複するものや、 polyA+RNA としては測定できない遺伝子 （例え ば、 rRNAなど）を除くこともできる。このように選択されるプローブにおいても、 高ウィルス群において発現亢進しているプローブに対応する遺伝子が髙ウィル ス遺伝子であり、 低ウィルス群において発現亢進しているプローブに対応する 遺伝子が低ウィルス遺伝子である。 Further, in some cases, probes can be extracted by focusing on the present flag in all of the plurality of microarrays or in all the microarrays of the high expression group. In addition, it is possible to exclude genes that have the same and overlapping probes, or genes that cannot be measured as polyA + RNA (for example, rRNA). Even in the probe selected in this way, The gene corresponding to the probe whose expression is increased in the high virus group is the 髙 virus gene, and the gene corresponding to the probe whose expression is increased in the low virus group is the low virus gene.
本発明者は、 上記方法により、 高ウィルス遺伝子として 78個 （表 5 )、 および 低ウィルス遺伝子として 39個 （表 6 A) の、 計 117個の遺伝子を選択するこ とができた （実施例 2 )。 そのうち、 2群間で 2.5倍以上差のあった遺伝子をさ らに表 3および表 4に示す。  The present inventor was able to select a total of 117 genes, 78 (Table 5) as high viral genes and 39 (Table 6A) as low viral genes by the above method (Examples). 2). Of these, the genes that differed more than 2.5 times between the two groups are shown in Tables 3 and 4.
また、 高ウィルス群及び低ウィルス群のそれぞれについて、 慢性肝炎と肝硬 変に分類して 4つの群とし、 それぞれの群の遺伝子発現を解析した結果、 慢性 肝炎高ウィルス遺伝子として 66個（表 10)、慢性肝炎低ウィルス遺伝子として 21個 （表 11)、 肝硬変高ウィルス遺伝子として 27個 （表 12)、 肝硬変低ウイ ルス遺伝子として 17個 （表 13) を得た （実施例 5 )。  In addition, each of the high virus group and low virus group was classified into four groups by classifying into chronic hepatitis and cirrhosis, and as a result of analyzing the gene expression of each group, 66 genes were found as chronic hepatitis high virus genes (Table 10). ), 21 hepatitis low virus genes (Table 11), 27 cirrhosis high virus genes (Table 12), and 17 cirrhosis low virus genes (Table 13) (Example 5).
( 2 ) リアルタイム PCR  (2) Real-time PCR
( a ) 発現解析方法  (a) Expression analysis method
本発明において、リアルタイム PCRを用いて遺伝子の発現量を測定する場合は、 まず、 上記 2 . ( 1 ) で得られた RNAを、 適宜 DNasel処理し、 精製して、 ラン ダムプライマーと逆転写酵素とで cDNAを合成する。逆転写酵素は、例えば AMV reverse transcriptase XL (Life Sciences, Gaithersurg, MD) ¾i用！ /、ることカで きる。 また、 ランダムプライマーの代わりに Oligo(dT)プライマーを用いるこ ともできる。  In the present invention, when measuring the expression level of a gene using real-time PCR, first, the RNA obtained in 2. (1) above is appropriately treated with DNasel, purified, random primer and reverse transcriptase. And synthesize cDNA. For example, AMV reverse transcriptase XL (Life Sciences, Gaithersurg, MD) ¾i! / I can do it. Also, Oligo (dT) primer can be used instead of random primer.
リアルタイム PCRによる遺伝子の発現量の測定は、 Rotor-Gene 3000 (Corbett Research, Moi'talke, Australia) や ABI Prism 7000 Sequence jDetection System (Applied Biosystems, Foster, CA)などの市販の機器を用いて行うこと ができる。  Measurement of gene expression by real-time PCR should be performed using commercially available equipment such as Rotor-Gene 3000 (Corbett Research, Moi'talke, Australia) or ABI Prism 7000 Sequence jDetection System (Applied Biosystems, Foster, CA). Can do.
反応は例えば、 10ng相当の cDNA、 SYBR Green PCR Master Mix (Applied Biosystems), 0.5 Mの各種遺伝子プライマーを含む 25 1反応液中で、 95°C、 10 min の preheat後、 95。C 15 sec、 60°C 60 secを 45 cycle行うことができ る。 このとき、 18S rRNAなどのハウスキーピング遺伝子の定量には、 例えば 0.25ng相当の cDNAを用いて行うことができる。 反応に用いるプライマーは、 当業者であればソフトウエアを用いて適宜設計 することができる。代表的なソフトウエア「primer 3」 の URLを下記に示す。 (http://frodo.wi.mit.edu/cgi-bm/primer3/prirner3_www.cgi; The reaction is performed, for example, in a 25 1 reaction solution containing 10 ng of cDNA, SYBR Green PCR Master Mix (Applied Biosystems), 0.5 M of various gene primers, 95 ° C., 10 min preheat, and 95. C 15 sec, 60 ° C 60 sec can be performed for 45 cycles. At this time, housekeeping genes such as 18S rRNA can be quantified using, for example, 0.25 ng of cDNA. Those skilled in the art can appropriately design primers used for the reaction using software. The URL of typical software “primer 3” is shown below. (http://frodo.wi.mit.edu/cgi-bm/primer3/prirner3_www.cgi;
primer 3を用いて設計したプライマーの例を下記の表 1に示す。  Examples of primers designed using primer 3 are shown in Table 1 below.
ある肝臓 cDNAを定量用の標準サンプルに用いて検量線を作成し、 各種遺伝子 の定量に用いる。 例えば、 各遺伝子で最も高い発現を示す肝臓 cDNAを標準サン プルとし、 その cDNAの量を定量値に用いることができる。 測定対象のサンプ ルの cDNAを一定量、 遺伝子 Xのリアルタイム PCRにかけて、 そのサンプル が検量線から 5 ngと評価できれば、そのサンプルには標準サンプル cDNAの 5 ngに含まれる遺伝子 X mRNAと等量の遺伝子 X mRNAが存在することにな る。  A calibration curve is prepared using a certain liver cDNA as a standard sample for quantification and used for quantification of various genes. For example, the liver cDNA showing the highest expression in each gene can be used as a standard sample, and the amount of the cDNA can be used as a quantitative value. If a sample of the sample cDNA to be measured is subjected to real-time PCR of gene X and the sample can be evaluated as 5 ng from the calibration curve, the sample should have the same amount as gene X mRNA contained in 5 ng of the standard sample cDNA. Gene X mRNA will be present.
本発明において、 各遺伝子発現量は、 検量線から得られた測定対象サンプル 中の各遺伝子発現定量値を内在性コントロール遺伝子発現定量値 （例えば上記 測定対象サンプル中の 18s rRNAの定量値） で除した相対値で表すことができ る。  In the present invention, the expression level of each gene is obtained by dividing the quantitative expression value of each gene in the measurement target sample obtained from the calibration curve by the endogenous control gene expression quantitative value (for example, the quantitative value of 18s rRNA in the measurement target sample). Relative value.
( b ) 内在性コント口ール遺伝子  (b) Endogenous control gene
本発明において 「内在性コ ン ト ロ ール遺伝子」 は、 18S rRNA, glyceraldehyde- 3 -phosphate dehydrogenase (GAPDH), ribosomal protein L34 (RPL34)を用いることができるが、 発現量のばらつきが小さい点で 18S rRNAが好ましい。  In the present invention, 18S rRNA, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal protein L34 (RPL34) can be used as the “endogenous control gene”, but the expression level is small. 18S rRNA is preferred.
( c ) 発現解析手順  (c) Expression analysis procedure
上記のように、宿主の各遺伝子の発現量は、 18S rRNAで補正した値を用いる ことができる。 補正の後、 低ウィルス群の発現量と高ウィルス群の発現量とを 比較する。 例えば、 高ウィルス群の発現量の中央値を低ウィルス群の中央値で 割ったときの値が、 2以上、 好ましくは 2.5以上、 より好ましくは 3以上の遺 伝子を高ウィルス遺伝子として選択することができる。 逆に、 低ウィルス群の 中央値を高ウィルス群の発現量の中央値で割ったときの値が、 2以上、 好まし くは 2.5以上、 より好ましくは 3以上の遺伝子を低ウィルス遺伝子として選択 することができる。 また、 このとき、 2群間で Mann Whitney U検定を行い、 上記遺伝子の中 でも、 有意差 (P<0.05)の遺伝子を選択することがより好ましい。 As described above, the expression level of each gene in the host can be a value corrected with 18S rRNA. After correction, the expression level of the low virus group is compared with the expression level of the high virus group. For example, a gene having a value obtained by dividing the median expression level of the high virus group by the median value of the low virus group is 2 or more, preferably 2.5 or more, more preferably 3 or more is selected as the high virus gene. be able to. Conversely, if the median of the low virus group is divided by the median of the expression level of the high virus group, a gene of 2 or more, preferably 2.5 or more, more preferably 3 or more is selected as the low virus gene. can do. At this time, it is more preferable to perform a Mann Whitney U test between the two groups and select a gene having a significant difference (P <0.05) among the above genes.
4 . 高ウィルス遺伝子おょぴ低ウィルス遺伝子 4. High virus gene Oppi low virus gene
( 1 ) 高ウィルス遺伝子  (1) High viral gene
高ウィルス遺伝子では、 HCVを排除しようとする高ウィルス群の宿主防御機 能の能力を超えて誘導された遺伝子が含まれていると考えられる。したがって、 高ウイルス遺伝子の中には、 HCV側にとつて増殖有利に働くと予想される因子 が存在する可能性がある。  High virus genes are considered to include genes that are induced beyond the ability of the host virus defense function of the high virus group to eliminate HCV. Therefore, there may be factors in the high viral genes that are expected to work in favor of growth on the HCV side.
すなわち、 本発明によってスクリーニングされる高ウィルス遺伝子の発現を 抑制すれば、 C型肝炎ウィルスの増殖を抑制することが可能となるだろう。 高 ウィルス遺伝子の発現を抑制することを特徴とする C型肝炎ウィルス増殖抑制 剤や c型肝炎ゥィルス増殖抑制方法の開発につながることが予想される。  That is, if the expression of a high viral gene screened by the present invention is suppressed, it will be possible to suppress the growth of hepatitis C virus. High Expected to lead to the development of hepatitis C virus growth inhibitor and hepatitis c virus growth suppression method characterized by suppressing the expression of viral genes.
( 2 ) 低ウィルス遺伝子  (2) Low viral genes
低ウィルス遺伝子の中には、 HCVが増殖しにくい環境作りに関与する遺伝子 が存在する可能性がある。 すなわち、 本発明によってスクリーニングされる低 ウィルス遺伝子の発現を亢進すれば、、 C型肝炎ウィルスの増殖を抑制すること が可能となる。 低ウィルス遺伝子の発現を亢進することを特徴とする C型肝炎 ウィルス増殖抑制剤や c型肝炎ウィルス増殖抑制方法の開発につながることが 期待できる。  Among the low viral genes, there may be genes involved in creating an environment where HCV is difficult to propagate. That is, if the expression of a low viral gene screened by the present invention is enhanced, the growth of hepatitis C virus can be suppressed. It is expected to lead to the development of hepatitis C virus growth inhibitor and hepatitis c virus growth suppression method characterized by enhancing the expression of low viral genes.
( 3 ) 疾患別に発現する遺伝子  (3) Genes expressed by disease
本発明においては、上記高ウィルス遺伝子と低ウィルス遺伝子を、 さらに慢性肝 炎由来のもの及び肝硬変由来のものに分類して発現量の解析を行うことができる。 例えば、 患者背景因子として慢性肝炎症例と肝硬変症例に分類し、それぞれの項目 (性別、年齢、病期等）についてウィルス量を指標として 2群間の比較を行うことができ る。  In the present invention, the high virus gene and the low virus gene can be further classified into those derived from chronic hepatitis and those derived from cirrhosis, and the expression level can be analyzed. For example, patients can be classified into chronic hepatitis cases and cirrhosis cases as patient background factors, and comparison between the two groups can be performed for each item (sex, age, stage, etc.) using the viral load as an index.
なお、本発明においては高ウィルス遺伝子と低ウィルス遺伝子を、 さらに慢性肝 炎由来のもの及ぴ肝硬変由来のものに分類するという順序でもよく、病態（慢性肝 炎由来及び肝硬変）を分類した後に高ウイルス遺伝子と低ウイルス遺伝子を分類す るという順序でもよく、順序に限定されるものではない。 すなわち、本発明におけ る遺伝子発現解析は、 遺伝子群が、 慢性肝炎における ウィルス遺伝子群 （CHH 群)、 慢性肝炎における低ウィルス遺伝子群 （CHL群）、 肝硬変における高ウィル ス遺伝子群 （LCH群）、 及び肝硬変における低ウィルス遺伝子群 （LCL群） の 4 通りに分類されている限り、 分類の順序は問わないものとする。 In the present invention, the high virus gene and the low virus gene may be further classified into those derived from chronic hepatitis and those derived from cirrhosis, and after classification of the disease state (chronic hepatitis and cirrhosis), Classify viral genes and low viral genes The order is not limited to the order. That is, in the gene expression analysis in the present invention, the gene group is a virus gene group in chronic hepatitis (CHH group), a low virus gene group in chronic hepatitis (CHL group), or a high virus gene group in cirrhosis (LCH group). As long as it is classified into 4 types of low viral gene group (LCL group) in cirrhosis and cirrhosis, the order of classification is not limited.
( 4 ) 解析された遺伝子  (4) Analyzed genes
本発明において解析された遺伝子を以下に示す。  The genes analyzed in the present invention are shown below.
<高ウィルス遺伝子 > (表 5 )  <High virus gene> (Table 5)
(a)配列番号 5 4〜1 3 1で表されるいずれかの塩基配列を含む遺伝子 (b) 配列番号 5 4〜 1 3 1で表されるいずれかの塩基配列に相補的な塩基配 列にストリンジェントな条件下でハイブリダイズし、 かつ、高ウィルス群におい て発現が亢進する遺伝子  (a) a gene containing any one of the nucleotide sequences represented by SEQ ID NOs: 5 4 to 1 3 1 (b) a nucleotide sequence complementary to any one of the nucleotide sequences represented by SEQ ID NOs: 5 4 to 1 3 1 Genes that hybridize under stringent conditions and have enhanced expression in the high virus population
<低ウィルス遺伝子 > (表 6 )  <Low virus gene> (Table 6)
(c)配列番号 1 3 2〜1 7 0で表されるいずれかの塩基配列を含む遺伝子 (d) 配列番号 1 3 2〜1 7 0で表されるいずれかの塩基配列に相補的な塩基 配列にストリンジヱントな条件下でハイブリダィズし、 かつ、低ウィルス群にお いて発現が亢進する遺伝子  (c) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 1 3 2 to 1700 (d) a base complementary to any one of the nucleotide sequences represented by SEQ ID NOs: 1 3 2 to 1 70 A gene that hybridizes under stringent conditions to the sequence and is highly expressed in the low virus group
また、 疾患別に分類したときの遺伝子群を以下に示す。  In addition, the gene groups classified by disease are shown below.
(i) CHH遺伝子群 （表 10)  (i) CHH genes (Table 10)
(a)配列番号 1 7 1〜 2 3 7で表されるいずれかの塩基配列を含む遺伝子 (a) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 1 7 1 to 2 3 7
(b) 配列番号 1 7 ：！〜 2 3 7で表されるいずれかの塩基配列に相補的な塩基 配列にストリンジェントな条件下でハイブリダィズし、 かつ、慢性肝炎の高ウイ ルス群において発現が亢進する遺伝子 (b) SEQ ID NO: 1 7! A gene that hybridizes under stringent conditions to a base sequence that is complementary to any of the base sequences represented by ~ 2 37 and that is highly expressed in the high virus group of chronic hepatitis
(ii) CHL遺伝子群） （表 11)  (ii) CHL genes) (Table 11)
(c)配列番号 2 3 8〜 2 5 8で表されるいずれかの塩基配列を含む遺伝子 (c) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 2 3 8 to 2 5 8
(d) 配列番号 2 3 8〜2 5 8で表されるいずれかの塩基配列に相補的な塩基 配列にストリンジヱントな条件下でハイプリダイズし、 つ、慢性肝炎の低ウイ ルス群において発現が亢進する遺伝子 (d) Hyperhybridized under stringent conditions to a base sequence complementary to any of the base sequences represented by SEQ ID NOs: 2 3 8 to 2 5 8 and enhanced expression in the low virus group of chronic hepatitis Genes
(iii) LCH遺伝子群 （表 12) (e)配列番号 2 5 9〜2 8 5で表されるいずれかの塩基配列を含む遺伝子(iii) LCH gene group (Table 12) (e) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 2 5 9 to 2 8 5
( ) 配列番号 2 5 9〜2 8 5で表されるいずれかの塩基配列に相補的な塩基配 列にストリンジェントな条件下でハイブリダィズし、 かつ、肝硬変の高ウィルス 群において発現が充進する遺伝子 ' () Hybridizes under stringent conditions to a base sequence complementary to any of the base sequences represented by SEQ ID NOs: 2 5 9 to 2 85, and promotes expression in a high virus group with cirrhosis Gene ''
(iv) LCL遺伝子群 （表 13)  (iv) LCL genes (Table 13)
(g)配列番号 2 8 6〜3 0 2で表されるいずれかの塩基配列を含む遺伝子 (g) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 2 8 6 to 30 2
(h) 配列番号 2 8 6〜3 0 2で表されるいずれかの塩基配列に相補的な塩基 配列にストリンジェントな条件下でハイプリダイズし、 かつ、肝硬変の低ウィルス 群において発現が亢進する遺伝子 (h) It is hybridized under stringent conditions to a base sequence complementary to any of the base sequences represented by SEQ ID NOs: 2 8 6 to 30 2, and expression is enhanced in the low virus group with cirrhosis Gene
上記各遺伝子'において、 「ストリンジェントな条件」 とは、核酸同士がハイプリ ダイズしたときの洗浄条件であってバッファ一の塩濃度と温度により規定され る条件である。 例えば、 0.5〜2 X SSC及ぴ 0.1%SDSの濃度で 37〜52°Cの条件 を挙げることができ、 よりストリンジェン卜な条件としては、 例えば 2 X SSC 及び 0.1%SDSで 65°Cの条件、 0.5 X SSC及ぴ 0.1%SDSで 42°Cの条件等の条件を 挙げることができる。 当業者であれば、 このようなバッファーの塩濃度、 温度 等の条件に加えて、 その他のプローブの濃度や長さ、 あるいは反応時間等の諸 条件を加味し、 適切な条件を設定することができる。  In each of the above genes, “stringent conditions” are washing conditions when nucleic acids are hybridized with each other, and are defined by the salt concentration and temperature of the buffer. For example, conditions of 37-52 ° C with concentrations of 0.5-2 X SSC and 0.1% SDS can be mentioned, and more stringent conditions include, for example, 65 ° C with 2 X SSC and 0.1% SDS. The conditions include conditions such as 42 ° C at 0.5 X SSC and 0.1% SDS. A person skilled in the art can set appropriate conditions by taking into consideration various conditions such as the concentration and length of other probes and reaction time in addition to the conditions such as the salt concentration and temperature of the buffer. it can.
ハイプリダイゼーション法の詳細な手順については、 「Molecular Cloning, A For details on the hypridization method, see “Molecular Cloning, A
Laboratory Manual 2nd ed.J (Cold Stmng Harbor Laboratory Press (1989)、 「 Current Protocols in Molecular Biology」 （John Wiley & Sons (1987-1997) 等を参照することができる。 Reference can be made to Laboratory Manual 2nd ed. J (Cold Stmng Harbor Laboratory Press (1989), “Current Protocols in Molecular Biology” (John Wiley & Sons (1987-1997)).
本発明において遺伝子が 「発現が亢進する」 とは、 リアルタイム PCRにより定 量解析を行い、得られた定量値が比較したいウィルス量の異なる群よりも高い場 合を言う。  In the present invention, the expression “enhanced expression” of a gene refers to a case where quantitative analysis is performed by real-time PCR, and the obtained quantitative value is higher than that of a group having different viral load to be compared.
5 . 病態検査薬 5. Pathologic testing agents
本発明において解析された、 CHH遺伝子群、 CHL遺伝子群、 LCH遺伝子群ま たは LCL遺伝子群に属するそれぞれの遺伝子は、 CHH遺伝子群及び CHL遺伝子 群については慢性肝炎におけるウィルス量のマーカーとなり、 LCH遺伝子群及び LCL遺伝子群は肝硬変におけるウィルス量のマーカーとなり得る。 したがって、 患者等から得られた肝組織からこれらの遺伝子の発現量 解析することで、どの疾 患でどの程度ウィルスが増殖している病態力、 どの程度肝機能を維持し、 どのよう な抗ウィルス反応を惹起できるかなどを判断することができる。 Each gene belonging to the CHH gene group, the CHL gene group, the LCH gene group or the LCL gene group analyzed in the present invention becomes a viral load marker in chronic hepatitis for the CHH gene group and the CHL gene group. Genes and LCL gene cluster can be a marker of viral load in cirrhosis. Therefore, by analyzing the expression levels of these genes from liver tissue obtained from patients, etc., how much virus is proliferating in which disease, how much hepatic function is maintained, and what kind of antiviral It can be judged whether a reaction can be induced.
また、本発明において解析された遺伝子は、患者等の肝組織から得られた遺伝子 とのハイブリダイゼーションを行い、ハイプリダイゼーションによってシグナノレを 検出することで、ウィルス量に関連したどの病態にあるかを判断することができる。 ハイブリダィゼーシヨン条件および標識方法は、 当業者に周知であり、本明細書に 記載の方法のほか、 任意の方法を採用することができる。  In addition, the gene analyzed in the present invention is hybridized with a gene obtained from a liver tissue of a patient or the like, and is detected by hydration to determine which pathological condition is related to viral load. Judgment can be made. Hybridization conditions and labeling methods are well known to those skilled in the art, and any method other than those described herein can be employed.
従って、上記遺伝子は、 ウィルス量に関連する病態の検査薬として使用すること ができる。上記遺伝子をマイクロアレイに搭載することで、簡易かつ網羅的に遺伝 子の発現量解析を行うことが可能である。  Therefore, the above gene can be used as a diagnostic agent for pathological conditions related to viral load. By mounting the above genes on a microarray, gene expression level analysis can be performed easily and comprehensively.
本発明において、 上記遺伝子は緩衝液 （例えば Tris緩衝液）、 標識試薬 （例えば 蛍光標識試薬）等とともにキットの形態で使用することができる。上記遺伝子が搭 載されたマイクロアレイをキットに含めることもできる。  In the present invention, the gene can be used in the form of a kit together with a buffer (for example, Tris buffer), a labeling reagent (for example, a fluorescent labeling reagent) and the like. A microarray carrying the above genes can also be included in the kit.
以下、本発明を具体的な例を挙げて説明するが、本発明はこれらの例に限定され るものではない。 実施例 1  Hereinafter, the present invention will be described with specific examples, but the present invention is not limited to these examples. Example 1
( 1 ) 肝臓組織  (1) Liver tissue
59例の C型肝細胞癌患者の癌切除術検体より非癌部組織を分離し、 速やか に液体窒素で凍結し- 80°C にて保存した。 検体の研究使用に関しては、 各患者 より同意を得て行った。  Non-cancerous tissues were isolated from cancer excision specimens of 59 patients with type C hepatocellular carcinoma, immediately frozen in liquid nitrogen and stored at -80 ° C. The use of specimens for research was obtained with the consent of each patient.
( 2 ) RNA抽出と RNA発現定量  (2) RNA extraction and RNA expression quantification
約
Figure imgf000018_0001
0&1：81^(1, 0 )を 2 1111加ぇ、 ポリ ト ロンでホモゲナイズ後、 取り扱い説明書に従い total RNAを抽出した。 Total RNAの質的評価を行うため、 Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, CA)の RNA 6000 nano assay chipを用いて電気泳動解析を行った。 抽出した RNAに混在する DNAを除くため、 DNase I 処理を行った。 Total RNA 20 β gに対し DNase I (Takara, Shiga, Japan) 10 unitをカロ免、 50 μ 1中 で 37°C, 20 min反応後、 rizolにて RNAを精製した 9 DNase I処理後の RNA 10 At g を用レヽて、 random primer と AMV reverse transcriptase XL (Life Sciences, Gaithersurg, MD) 25 unitを加え 100 1中で cDNAを合成した。 実施例中の Real-time PCRによる発現定量は、 Rotor-Gene 3000 (Corbett Research, Mortalke, Australia) と ΑβΙ Prism 7000 Sequence Detection System (Applied Biosystems, Foster, CA)を用いた。 lOn 相当の cDNA、SYBR Green PCR Master Mix (Applied Biosystems), 0.5 μ Mの各種遺伝子 primer を含む 25 1反応液中で、 95°C、 10 min の preheat後、 95°C 15 sec、 60°C 60 secを 45 cycle行つた。 Real-time PCRにおいて、 HCV RNAの定量は 50ng 相当の cDNAを用いて行い、 18S rRNAの定量は 0,25ng相当の cDNAを用い て行った。 また、 HCV primerは 0.3 Mで行つた。 about
Figure imgf000018_0001
0 & 1: 81 ^ (1, 0) was added to 21111, homogenized with polytron, and total RNA was extracted according to the instruction manual. Electrophoretic analysis was performed using an RNA 6000 nano assay chip from Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, Calif.) To evaluate the total RNA quality. DNase I treatment was performed to remove DNA mixed in the extracted RNA. Total DNase I (Takara, Shiga, Japan) 10 units against 20 g of RNA, calorie-free, reacted at 37 ° C for 20 min in 50 μ1, and purified with rizol 9 RNA after DNase I treatment 10 Using At g, random primer and 25 units of AMV reverse transcriptase XL (Life Sciences, Gaithersurg, MD) were added to synthesize cDNA in 1001. Rotor-Gene 3000 (Corbett Research, Mortalke, Australia) and ΑβΙ Prism 7000 Sequence Detection System (Applied Biosystems, Foster, CA) were used for expression quantification by real-time PCR in the Examples. lOn equivalent cDNA, SYBR Green PCR Master Mix (Applied Biosystems), 0.5 μM of various gene primers in 25 1 reaction solution, 95 ° C, 10 min preheat, 95 ° C 15 sec, 60 ° C It took 45 seconds for 60 sec. In Real-time PCR, HCV RNA was quantified using 50 ng of cDNA, and 18S rRNA was quantified using 0,25 ng of cDNA. The HCV primer was used at 0.3 M.
定量用標準サンプルは、 肝臓 cDNAおよび HCV全長を組み込んだプラスミ ド DNA (標準プラスミ ド DNA) を 5倍の系列希釈で 5点用意し、 検量線を作 成後、 得られた検量線を絶対定量解析に用いた。 各遺伝子毎に、 最も高い発現 を示した肝臓 cDNAを標準サンプルとし、その cDNAを定量値算出用の検量線 作成に用いた。 HCV RNA定量値は、標準プラスミ ド DNA量をウィルスの copy 数に換算し、 cDNA 50ng当りの HCV RNA copy数を求め、 18S rRNA定量値 で割った値を 「unit」 として表記した。 内在性コントロール遺伝子として、 3 つのノヽウスキーピング遺伝子、 18S rRNA, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal protein L34 (RPL34)を用いた。 子 発現量は、 各遺伝子発現定量値を内在性コントロール遺伝子発現定量値で除し 7こネ日文 T iiで 3¾ し 7こ 用 ヽ 7こ lDrimer 配列の一部 は、 primer 3 (http：〃 frodo.wi. mit.edu/cgi-bin/primer3/primer3— www.cgi)を用！/ヽてァ ir ン した。 （表 1)。 表 1 用いたプライマー配列 For the standard sample for quantification, prepare 5 samples of plasmid DNA (standard plasmid DNA) incorporating liver cDNA and the full length of HCV in 5-fold serial dilution, create a calibration curve, and then absolute quantify the resulting calibration curve Used for analysis. The liver cDNA showing the highest expression for each gene was used as a standard sample, and the cDNA was used to create a calibration curve for quantitative value calculation. The quantitative amount of HCV RNA was calculated by converting the amount of standard plasmid DNA into the number of copies of the virus, obtaining the number of copies of HCV RNA per 50 ng of cDNA, and dividing the value by the quantitative value of 18S rRNA as “unit”. Three endogenous control genes, 18S rRNA, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and ribosomal protein L34 (RPL34) were used as endogenous control genes. The expression level of each gene is determined by dividing the quantitative expression value of each gene by the quantitative expression value of the endogenous control gene. .wi. mit.edu/cgi-bin/primer3/primer3—use www.cgi)! I'm sorry. (table 1). Table 1 Primer sequences used
Lxoenment Gene Lxoenment Gene
Forward (5'-3*) Nob Reverse (5'-3') Nob Forward (5'-3 *) No b Reverse (5'-3 ') No b
HCV quantitation HCV GACCAAGCTCAAACTCACTC 3 GCACGAGACAGGCTGTGATA 4 HCV quantitation HCV GACCAAGCTCAAACTCACTC 3 GCACGAGACAGGCTGTGATA 4
(1st PGR) CGCGCGACDAGGAAGACTTC 5 ATGTACCCCATGAGGTCGGC 6  (1st PGR) CGCGCGACDAGGAAGACTTC 5 ATGTACCCCATGAGGTCGGC 6
AGGAAGACTTCSGAGCGRTC 7 TGCCTTGGGGATAGGCTGAC (la) 8 AGGAAGACTTCSGAGCGRTC 7 TGCCTTGGGGATAGGCTGAC (la) 8
HCV genotyping GAGCCATCCTGCCCACCCCA (lb) 9 HCV genotyping GAGCCATCCTGCCCACCCCA (lb) 9
(2nd PCR)  (2nd PCR)
CCAAGAGGGACGGGAACCTC (2a) 10 ACCCTCGTTTCCGTACAGAG (2b) 11 CCAAGAGGGACGGGAACCTC (2a) 10 ACCCTCGTTTCCGTACAGAG (2b) 11
MXA GTGCATTGCAGAAGGTCAGA 12 CTGGTGATAGGCCATCAGGT 13MXA GTGCATTGCAGAAGGTCAGA 12 CTGGTGATAGGCCATCAGGT 13
OAS TCAGCGAGGCCAGTAATCTT 14 GTTTCGTGAGCTGCCTTCTC 15OAS TCAGCGAGGCCAGTAATCTT 14 GTTTCGTGAGCTGCCTTCTC 15
IFN-related genes PKR ACAATTGGCCGCTAAACTTG 16 GCGAGTGTGCTGGTCACTAA 17 p53 AACAACACCAGCTCCTCTCC 18 AACAACACCAGCTCCTCTCC 19IFN-related genes PKR ACAATTGGCCGCTAAACTTG 16 GCGAGTGTGCTGGTCACTAA 17 p53 AACAACACCAGCTCCTCTCC 18 AACAACACCAGCTCCTCTCC 19
BAX ATGGAGCTGCAGAGGATGAT 20 CAGTTGAAGTTGCCGTCAGA 21BAX ATGGAGCTGCAGAGGATGAT 20 CAGTTGAAGTTGCCGTCAGA 21
OASL CGTGGCAGAAGGGTACAGAT 22 AAGGGTTCACGATGAGGTTG 23OASL CGTGGCAGAAGGGTACAGAT 22 AAGGGTTCACGATGAGGTTG 23
CXCL6 TGTTTACGCGTTACGCTGAG 24 GACAAACTTGCTTCCCGTTC 25CXCL6 TGTTTACGCGTTACGCTGAG 24 GACAAACTTGCTTCCCGTTC 25
MAP1B CTGGATGACATCAGCAATGG 26 AGGGGTTCGTGTTGTCTTTG 27MAP1B CTGGATGACATCAGCAATGG 26 AGGGGTTCGTGTTGTCTTTG 27
U4PRSS2 CACTGTGCATCACCTTGACC 28 ACACACCGATTCTCGTCCTC 29U4PRSS2 CACTGTGCATCACCTTGACC 28 ACACACCGATTCTCGTCCTC 29
Microarray High Microarray High
TACSTD ACCTCCAAGTGTCTGCTGCT 30 GTCGTAGAGGCCATCGTTGT 31 TACSTD ACCTCCAAGTGTCTGCTGCT 30 GTCGTAGAGGCCATCGTTGT 31
AW612461 a TGTGTAAGGCACAGGGTTTT 32 CAGCTGACTGTGGAAGGGTA 33AW612461 a TGTGTAAGGCACAGGGTTTT 32 CAGCTGACTGTGGAAGGGTA 33
CXCL10 ACCGTACGCTGTACCTGCAT 34 TCTTGATGGCCTTCGATTCT 35CXCL10 ACCGTACGCTGTACCTGCAT 34 TCTTGATGGCCTTCGATTCT 35
LIN7C ACAGAAGAGGGCCTTGGATT 36 CCCCCATGTCTATCAGCAAT 37LIN7C ACAGAAGAGGGCCTTGGATT 36 CCCCCATGTCTATCAGCAAT 37
FU461542 GGCTGAGGTTGATTTGTCGT 38 CCATCCCCATTTTTGTATGC 39FU461542 GGCTGAGGTTGATTTGTCGT 38 CCATCCCCATTTTTGTATGC 39
SELE GCCAACGTGTAAAGCTGTGA 40 AACTGGGATTTGCTGTGTCC 41SELE GCCAACGTGTAAAGCTGTGA 40 AACTGGGATTTGCTGTGTCC 41
Microarray Low 議 154 a CACCTTGGATGACGAAACAA 42 GAGTTTCTGGGAAGGCAAAA 43 Microarray Low 154 a CACCTTGGATGACGAAACAA 42 GAGTTTCTGGGAAGGCAAAA 43
RAPHl GGATCCGCATTGCAAAGTAT 44 CTCTGGGATGCTGGAAGAAC 45 RAPHl GGATCCGCATTGCAAAGTAT 44 CTCTGGGATGCTGGAAGAAC 45
ENC1 GAAATCATTCCCAAGGCTGA 46 CTTTCGAGACCCCATTTTCA 47ENC1 GAAATCATTCCCAAGGCTGA 46 CTTTCGAGACCCCATTTTCA 47
18SrRNA AAACGGCTACCACATCCAAG 48 CCTCCAATGGATCCTCGTTA 4918SrRNA AAACGGCTACCACATCCAAG 48 CCTCCAATGGATCCTCGTTA 49
Control GAPDH GGTCGGAGTCAACGGATTTG 50 GGATCTCGCTCCTGGAAGAT 51 Control GAPDH GGTCGGAGTCAACGGATTTG 50 GGATCTCGCTCCTGGAAGAT 51
RPL34 AGCACCAAAATCTGCATGTG 52 GCCCTGCTGACATGTTTCTT 53  RPL34 AGCACCAAAATCTGCATGTG 52 GCCCTGCTGACATGTTTCTT 53
"Accession No.で記載。 b配列番号。 "Described in Accession No. b Sequence number.
( 3 ) HCV遺伝子型の決定 (3) Determination of HCV genotype
cDNA 100ngを用いて、 岡本らの nested PCR法により、 la型、 lb型、 2a 型、 2b型の 4つの HCV遺伝子型特異的 PCRを行つた。第一ラウンド PCRは、 共通配列 primerで 20 μ 1中 35 cycle PCRを行った。その反応液 1 μ 1を用いて 共通 forward primerと 型另 U reverse primerで第二フゥント PCR 20 μ 1 中で 35 cycle行った。用いた primer配列を表 1に示す。 PCR産物 5 1を 3% ァガロースゲル電気泳動にかけ、 PCR産物の大きさより la型が 49bp、 lb型 が 144bp、 2a型が 174bp、 2b型が 123bpであることから、 HCV遺伝子型を 決定した。 ( 4 ) 対象症例の選別 Using 100 ng of cDNA, four HCV genotype-specific PCRs of la type, lb type, 2a type, and 2b type were performed by Okamoto's nested PCR method. The first round PCR was performed using a consensus primer of 35 cycles in 20 µ1. Using 1 μ 1 of the reaction solution, 35 cycles were carried out in a second front PCR 20 μ 1 with a common forward primer and an additional U reverse primer. The primer sequences used are shown in Table 1. The PCR product 51 was subjected to 3% agarose gel electrophoresis, and the HCV genotype was determined from the size of the PCR product because the la type was 49 bp, the lb type was 144 bp, the 2a type was 174 bp, and the 2b type was 123 bp. (4) Selection of target cases
59例の肝臓 HCV RNAを定量した結果、 定量値は、. 0~372，068 unitの範囲 で分布した。 ウィルス量が、 300 unit以下の症例を低ウィルス群とし、 30000 unit以上を高ウィルス群として、 59例を群分けした。  As a result of quantification of 59 cases of liver HCV RNA, the quantification value was distributed in the range of 0 to 372,068 units. Cases with a viral load of 300 units or less were classified as a low virus group, and 30000 units or more were classified as a high virus group.
その結果、 低ウィルス群は 15例で、 その内訳は慢性肝炎 (CH)9例と肝硬変 (LC)6例であった。 高ウィルス群は 19例で、 その内訳は慢性肝炎 9例と肝硬 変 10例であった （図 2)。  As a result, the low virus group was 15 cases, of which 9 were chronic hepatitis (CH) and 6 were cirrhosis (LC). The high virus group consisted of 19 cases, consisting of 9 cases of chronic hepatitis and 10 cases of cirrhosis (Fig. 2).
選別した 34例 （CH+LC) とその中の慢性肝炎症例 （CH) 18例について、 患者の背景因子を高ウィルス群と低ウィルス群 で比較した （表 2)。 表 2 病態に関わる患者背景因子の、高ウィルス群と低ウィルス群での比較 a In 34 selected cases (CH + LC) and 18 chronic hepatitis cases (CH), the background factors of patients were compared between the high virus group and the low virus group (Table 2). Patient background factors relating to Table 2 condition, compared a at high virus group and the low virus group
CH + LC (34) CH (18  CH + LC (34) CH (18
High (19) Low (15) P High (9) Low (9) P High (19) Low (15) P High (9) Low (9) P
CH / LC 9 / 10 9 / 6 0.464 CH / LC 9/10 9/6 0.464
Male / female 10 / 9 13 / 2 0.064 5 / 4 9 / 0 0.082 Male / female 10/9 13/2 0.064 5/4 9/0 0.082
Age (range) 67.8 (60-78) 63.6 (50-73) 0.119 68.9 (60-77) 62.6 (50-70) 0.102 · Age (range) 67.8 (60-78) 63.6 (50-73) 0.119 68.9 (60-77) 62.6 (50-70) 0.102
I 10 5 2 2 I 10 5 2 2
Stage b II 9 8 0.206 7 6 0.757 Stage b II 9 8 0.206 7 6 0.757
ΠΙΑ 0 2 0 1 ΠΙΑ 0 2 0 1
Liver function (mean ±SD) Liver function (mean ± SD)
ICG-R15 (%) (く 10) 20.4±14.1 . 17.8±10.8 0.675 14.1±7.61 11.6±5.79 0.501 ICG-R15 (%) (く 10) 20.4 ± 14.1 .17.8 ± 10.8 0.675 14.1 ± 7.61 11.6 ± 5.79 0.501
Alb (g/dl) (6.7-8.3) 3.83±0.43 3.95±0.55 0.466 4.02±0.47 4.06±0.53 0.825Alb (g / dl) (6.7-8.3) 3.83 ± 0.43 3.95 ± 0.55 0.466 4.02 ± 0.47 4.06 ± 0.53 0.825
AST (IU/1) (8-38) 65.4±47.1 48.8±27.8 0.282 62.1±59.0 36.3±16.4 0.354AST (IU / 1) (8-38) 65.4 ± 47.1 48.8 ± 27.8 0.282 62.1 ± 59.0 36.3 ± 16.4 0.354
ALT (IU/1) (40-44) 55.1±37.1 43.3±29.5 0.282 52.0±42.7 41.9±36.1 0.508ALT (IU / 1) (40-44) 55.1 ± 37.1 43.3 ± 29.5 0.282 52.0 ± 42.7 41.9 ± 36.1 0.508
T.bil (mg/dl) (0.3-1.2) 0.83±0.43 0.70±0.31 0.405 0.78±0.51 0.57±0.24 0.289T.bil (mg / dl) (0.3-1.2) 0.83 ± 0.43 0.70 ± 0.31 0.405 0.78 ± 0.51 0.57 ± 0.24 0.289
HCV genotype HCV genotype
lb 15 8 7 5  lb 15 8 7 5
lb+2a 4 0 2 0  lb + 2a 4 0 2 0
0.001 0.082 2a 0 5 0 3  0.001 0.082 2a 0 5 0 3
2b 0 2 0 1 a有意差検定は次のように行った。 CH LCは χ2検定; Male/femaleおよび HCV genotypeはフィッシャーの直 接確率検定； Age, Stage, Liver fbnctionは Mann Whitney U検定. 2b 0 2 0 1 a Significance test was performed as follows. CH LC for χ2 test; Male / female and HCV genotype for Fisher's exact test; Age, Stage, Liver fbnction for Mann Whitney U test.
b肝細胞癌の Stage分類は、 TOM分類（ref)に従った。 b Stage classification of hepatocellular carcinoma was in accordance with TOM classification (ref).
c各値の正常値を括弧内に示した。 c Normal values for each value are shown in parentheses.
CH,慢性肝炎； LC,肝硬変; High,高ウィルス群； Low,低ウィルス群； ICG-R15, indocyanine green静注 15 分後の 率； Alb, serum albumin; AST, asparate aminotransferase; ALT, alanine aminotransferase; T.bil, total bilirubin 表 2に示すように、 34例 （CH+LC) において、肝硬変 （LC) の割合、性比、 年齢の分布、 肝細胞癌の進行度の分布については、 ウィルス量の違いでわけた 2群間に差はなかった。 肝機能を表す血液検査結果 （「： Liver function」） も、 軽 度の肝障害を示す値であるが、 2群間で有意差は認め れなかった。以上より、 この 34症例を用いてウィルス量が 1000倍異なる肝臓で、どのような遺伝子発 現レベルの違いがあるのか、 解析することが可能と考えた。 CH, chronic hepatitis; LC, cirrhosis; High, high virus group; Low, low virus group; ICG-R15, indocyanine green IV rate after 15 minutes; Alb, serum albumin; AST, asparate aminotransferase; ALT, alanine aminotransferase; T.bil, total bilirubin As shown in Table 2, in 34 cases (CH + LC), the percentage of cirrhosis (LC), sex ratio, age distribution, and hepatoma progression rate Divided by difference There was no difference between the two groups. Blood test results indicating liver function (“Liver function”) also show mild liver damage, but there was no significant difference between the two groups. Based on the above, using these 34 cases, it was considered possible to analyze the level of gene expression in livers that differ 1000-fold in viral load.
ただし、 34例における HCV遺伝子型の分布（「HCV genotype」 ）は、 2群間 で有意に異なり、 2型 HCVが低ウィルス群に偏っていたことから (p=0.001)、 一部 HCV遺伝子型の違いによる差が反映されることを考慮する必要がある。 そこで、 以下の実施例 （実施例 3 ( 1 ) を除く） では、 lb型の 23例で比較解 祈を行うことにした。  However, the distribution of HCV genotypes in 34 cases (“HCV genotype”) was significantly different between the two groups, and because type 2 HCV was biased toward the low virus group (p = 0.001), some HCV genotypes It is necessary to consider that the difference due to the difference of Therefore, in the following examples (excluding Example 3 (1)), we decided to make a comparative prayer in 23 cases of the lb type.
また明らかに病態が進行している肝硬変の影響も考慮する必要があると考え、 慢性肝炎 （CH) 18例で ウィルス量の違いも独立して解析することにした。 実施例 2  We also considered that it is necessary to consider the effects of liver cirrhosis, which is clearly progressing, and decided to independently analyze the difference in viral load in 18 patients with chronic hepatitis (CH). Example 2
、丄 ) Oligonucleotide microarrayによる発現角军析方法  ,)) Expression angle analysis method using Oligonucleotide microarray
慢性肝炎症例の高ウィルス群、低ウィルス群より各 4例を選別し、 total RNA より biotin-標識 cRNA を以下のように合成した。 Affymetrix Gene Chip expression analysisのマニュアルを一部改変して次のように行った。 まず、 10 gの total RNAを用いて RNase inhibitor存在下、 42。C， 2 hrにて first strand cDNAを合成した。 マニュアルに従って second strand cDNAを合成後、 半分 量を用いて MEGAscript T7 kit (Ambion, Austin, TX)を基本にした以下の組成 の反応液を含む 43 1 の反応液を 37°C で 9 hr インキュベートし、 in vitro transcriptionを行レヽ、 biotirrcRNA ¾r合成した。  Four cases each were selected from the high virus group and low virus group of chronic hepatitis cases, and biotin-labeled cRNA was synthesized from total RNA as follows. The manual of Affymetrix Gene Chip expression analysis was partially modified and performed as follows. First, 10 g of total RNA was used in the presence of RNase inhibitor42. First strand cDNA was synthesized at C and 2 hr. After synthesizing the second strand cDNA according to the manual, incubate the 43 1 reaction solution containing the following composition based on MEGAscript T7 kit (Ambion, Austin, TX) for 9 hr at 37 ° C. In vitro transcription was performed, and biotirrcRNA ¾r was synthesized.
75 mM ATP, GTP各 4 /Π、  75 mM ATP, GTP 4 / Π each
75 mM CTP、 UTP各 3 μ 1、  75 mM CTP, UTP each 3 μ1,
T7 10x reaction buffer 4 μ 1、  T7 10x reaction buffer 4 μ 1,
T7 enzyme 4 μ 1、  T7 enzyme 4 μ 1,
10 mM biotin- 11-CTP (PerkinElmer Life Sciences, Boston, MA) 7.5 μ 1、 10 mM biotin- 16-UTP (Roche Diagnostics, Basel, Switzerland) 7.5 μ 1、 200 unit/ 1 T7 RNA polymerase (Ambion) 1 μ 1、  10 mM biotin-11-CTP (PerkinElmer Life Sciences, Boston, MA) 7.5 μ1, 10 mM biotin-16-UTP (Roche Diagnostics, Basel, Switzerland) 7.5 μ1, 200 unit / 1 T7 RNA polymerase (Ambion) 1 μ 1,
40 unit/ μ 1 RNase inhibitor Ι ΐ その後、 biotin-cRNAは RNeasy MiniElute cleanup kit (Qiagen, Hilden, Germany)を用いて精製した。 cRNAの fragmentationはマニュアルにしたが つた。 ' 40 unit / μ 1 RNase inhibitor Ι ΐ Biotin-cRNA was then purified using the RNeasy MiniElute cleanup kit (Qiagen, Hilden, Germany). cRNA fragmentation was according to the manual. '
Human Genome U133 Plus 2.0 array (Affymetrix, Santa Clara, CA)を 8枚 用いて、 マニュアルに従って Fluidics Station 450 (Affymetrix)によりハイブ リダィゼーシヨン、 洗浄、 染色を行い、 Scanner 3000 (Affymetrix)にて読みと りを行った。 各遺伝子発現シグナルは、 Gene Spring version 7 (Silicon Genetics, Redwood, CA)を用いて解析した。 シグナル値の補正は、 microarray ごとに中央値を 1とする per chip normalizationを行い、 その後遺伝子ごとに 中央値を 1とする per gene normalizationを行った。  Using eight Human Genome U133 Plus 2.0 arrays (Affymetrix, Santa Clara, CA), perform hybridization, washing and staining with Fluidics Station 450 (Affymetrix) according to the manual, and read with Scanner 3000 (Affymetrix) It was. Each gene expression signal was analyzed using Gene Spring version 7 (Silicon Genetics, Redwood, CA). The signal value was corrected by performing per chip normalization with a median of 1 for each microarray, and then performing per gene normalization with a median of 1 for each gene.
( 2 ) インターフヱロン下流遺伝子の発現解析  (2) Expression analysis of interferon downstream genes
IFN作用機構がうまく働いているかいないかでウィルス量に差が出るの力、 を調べるために、 抗ウィルス作用を示す 5 ·つの遺伝子 （MxA、 OAS, PKR、 p53、 BAX) (図 1) の発現量を高ウィルス群と低ウィルス群の 2群間で比較し た。  In order to investigate the difference in viral load depending on whether or not the IFN action mechanism works well, the five genes showing antiviral action (MxA, OAS, PKR, p53, BAX) (Fig. 1) Expression levels were compared between the high virus group and the low virus group.
図' 3に示すように、慢性肝炎 11例で比較すると高ウィルス群において、 OAS、 MxA、 BAXの発現が有意に上がっていた ( <0.05)。 肝硬変 14例や全体 25例 では 2群間の有意差は認められなかった。 また、 HCV遺伝子型 lb単独の 9例 で比較しても、 有意差は認められなかった。 このように慢性肝炎症例だけで有 意差がみられた。  As shown in Fig. 3, the expression of OAS, MxA, and BAX was significantly increased in the high virus group compared with 11 cases of chronic hepatitis (<0.05). There was no significant difference between the two groups in 14 cirrhosis cases or 25 cases in total. In addition, no significant difference was observed when comparing the 9 cases of HCV genotype lb alone. Thus, a significant difference was observed only in chronic hepatitis cases.
図 3からも明らかなように、 高ウィルス群の症例のなかに、 3遺伝子につい て特に発現が上がっているものが存在した。 この症例を除くと、 いずれの遺伝 子についても有意差は認められなかった。 このことより、 サンプリングエラー による有意差も考えられ、 慢性肝炎症例数を増やし、 再現性を確かめる必要が あると考える。  As is clear from FIG. 3, among the cases of the high virus group, there were those in which the expression of 3 genes was particularly increased. Except for this case, there was no significant difference for any gene. Based on this, there is a significant difference due to sampling errors, and it is necessary to increase the number of chronic hepatitis cases and confirm reproducibility.
図 3の結果は、 内在性コントロール遺伝子として 18S rRNAを用いたときの 発現量の測定結果である。 よく用いられる GAPDHと 18S I'RNAとで、 一定 cDNA量あたりの発現量を比較したところ、 GAPDHでは症例間に差が大きく、 18SrRNAの方が症例間の差が少なかった （図 6B)。 よって 18S i'RNAをコン トロール遺伝子として各遺伝子発現量を評価した （後述）。 The results in Fig. 3 show the measurement results of the expression level when 18S rRNA is used as the endogenous control gene. When the expression level per certain amount of cDNA was compared between GAPDH and 18S I'RNA, which are commonly used, the difference between GAPDH was larger between cases, and the difference between 18S rRNA was smaller between cases (Fig. 6B). Therefore, 18S i'RNA Each gene expression level was evaluated as a trawl gene (described later).
上記の結果では、予想外にも慢性肝炎高ウィルス群 IFN誘導性遺伝子の発 現が増加していた。 これはウィルス量が多いため、 結果的に IFN及ぴ IFN下 流の遺伝子が誘導されたことによると考えられる。 本実施例の系においては、 IFN下流の抗ウイルス作用関連遺伝子がゥィルス量の抑制に関与しているわけ ではなく、 宿主細胞の他の因子がウィルス量制御に関与していることが示唆さ れた。  In the above results, the expression of IFN-inducible genes for chronic hepatitis high virus group was unexpectedly increased. This is thought to be due to the induction of IFN and IFN downstream genes due to the large amount of virus. In the system of this example, it is suggested that the antiviral action-related gene downstream of IFN is not involved in the suppression of viral load, and that other factors of the host cell are involved in viral load control. It was.
そこで、 既知の抗ウィルス作用因子ではなく、 何がウィルス量の低下に関与 しているのかを知る目的で、 下記の （3 ) oligonucleotide microarray を用い た網羅的発現解析により、HCVのウィルス量に関連する宿主遺伝子の検討を行 つた。  Therefore, for the purpose of knowing what is involved in the reduction of viral load, not known antiviral agents, the following (3) comprehensive expression analysis using oligonucleotide microarray is used to relate to the viral load of HCV. We examined the host genes to be used.
( 3 ) Oligonucleotide microarrayの発現解析結果  (3) Results of Oligonucleotide microarray expression analysis
図 2 「T」 印に示した 8例 （慢性肝炎症例の高ウィルス群 4例と低ウィルス 群 4例）を用いて、 microarrayによる発現解析を行った。 Human Genome U133 Plus 2.0 airay (Affymetrix)を用い、 ヒ トの約 47,000個以上の転写産物に相当 する 54,675 プローブ （probe) を対象とした。 高ウィルス群 4枚と低ウィルス 群 4枚とで発現が有意に異なる遺伝子の求め方を図 4に示す。  Figure 8 Expression analysis by microarray was performed using the 8 cases indicated by “T” (4 cases of high virus group and 4 cases of low virus group in chronic hepatitis cases). Human Genome U133 Plus 2.0 airay (Affymetrix) was used, and 54,675 probes (probe) corresponding to more than 47,000 transcripts of humans were targeted. Figure 4 shows how to obtain genes that are significantly different in expression between 4 high virus groups and 4 low virus groups.
まず、 8枚の microarrayのうち少なくとも 1枚で発現ありの表記 (present flag)が出た probeを抽出した。その結果 28,505 probeが選ばれた（図 4 (a))。 こ れが、肝臓（詳しくは慢性肝炎の肝臓）に発現している遺伝子である。 さらに、 28,505 probeより、 高ウィルス群と低ウィルス群との 2群間で発現に有意な差 がある遺伝子を抽出するため、 3種類のパラメ トリック検定を行った (図 4 (b))。 2群で分散が等しいと仮定する Student's t testでは 1,710 probesが抽出され、 分散が等しくないと仮定する Welch's t testでは 1,327 probesが抽出された。 また、少ない replicateからできるだけ正確な母分散を見積もるため、 replicate を増やした時に収束するであろう標準偏差を予測計算する Cross-gene error modelのパラメ トリック検定では、 1,069 probesが抽出された。これらの probe の重複を調べるために、 Venn diagramを作製した （図 4)。 Welch's t testの 1,327 probeは、 すべて Student's t testの 1,710 probeに含まれていた。 そし て、 3種類の検定で共通に抽出された 683 probesを対象に、 2群間で 2倍以上 発現に差がある probeを選んだ (図 4 (c))。 その結果、 .高ウィルス群に発現が 2 倍以上増加していた probeは 158個、低ウイルス群で有意に発現が 2倍以上増 加していた probeは 136個であった（図 4 ( d ))。 さらに、 発現量の多い群 4枚 ともに present flagがついている probeを絞った（図 4 (e))。 それぞれ 80個と 41個になり、これらの中で、 probeが同一遺伝子として重複するものや polyA+ RNAとしては測定できないはずの遺伝子を除いた。 First, we extracted probes with a present flag on at least one of the eight microarrays. As a result, 28,505 probe was selected (Fig. 4 (a)). This is the gene expressed in the liver (specifically, the liver of chronic hepatitis). In addition, three types of parametric tests were performed using 28,505 probes to extract genes with significant differences in expression between the two groups, the high virus group and the low virus group (Fig. 4 (b)). Student's t test, which is assumed to have the same variance in the two groups, extracted 1,710 probes, and Welch's t test, which assumes that the variances are not equal, extracted 1,327 probes. In addition, in order to estimate the population variance as accurately as possible from a small number of replicates, 1,069 probes were extracted in the parametric test of the cross-gene error model that predicts and calculates the standard deviation that will converge when the number of replicates is increased. In order to investigate the overlap of these probes, a Venn diagram was created (Fig. 4). All 1,327 probes of Welch's t test were included in 1,710 probes of Student's t test. And Thus, 683 probes extracted in common by the three types of tests were selected, and probes with expression differences of 2 times or more between the two groups were selected (Fig. 4 (c)). As a result, there were 158 probes whose expression increased more than 2-fold in the high virus group, and 136 probes whose expression increased significantly more than 2-fold in the low virus group (Fig. 4 (d) )). In addition, probes with present flags were narrowed down in four groups with high expression levels (Fig. 4 (e)). There were 80 and 41, respectively. Of these, genes with duplicate probes and genes that should not be measured as polyA + RNA were excluded.
結局、 高ウィルス群で発現亢進している遺伝子 （髙ウィルス遺伝子） として 78 個、 低ウィルス群で発現亢進している遺伝子 （低ウィルス遺伝子） として 39個が選ばれた（図 4 (f))。  Eventually, 78 genes were selected that were highly upregulated in the high virus group (髙 virus gene), and 39 genes were selected that were upregulated in the low virus group (low virus gene) (Fig. 4 (f)). .
この 117個の遺伝子で 8枚の microarrayのクラスタリング解析を行い、 Condition treeを作成した （図 5 A)。 28,505 probeによる Condition tree (図 5 B)とは異なり、 高ウィルス群と低ウィルス群に症例を区別できる遺伝子リス トであることが示された。  A clustering analysis of eight microarrays using these 117 genes was performed to create a Condition tree (Fig. 5A). Unlike the Condition tree with 28,505 probes (Fig. 5B), it was shown that the gene list can distinguish cases between the high virus group and the low virus group.
肝臓で発現する遺伝子全体では感染したウィルス量と関連する特徴は捉える ことはできず、 限られた遺伝子だけが感染したウィルス量に関連することがわ かった。 表 3と表 4に、 高ウィルス遺伝子 78個と低ウィルス遺伝子 39個のう ち、 2群間で 2.5倍以上差のあった遺伝子を示す （表 3 ) (表 4 )。 In the whole gene expressed in the liver, characteristics related to the amount of infected virus could not be captured, and it was found that only a limited number of genes were related to the amount of infected virus. Tables 3 and 4 show the genes that were more than 2.5 times different between the two groups among 78 high virus genes and 39 low virus genes (Table 3) (Table 4).
表 3 高ウィルス遺伝子 Table 3 High viral genes
ProbeProbe
Accession No. Gene symbol FC Gene title Function Validation3 Accession No. Gene symbol FC Gene title Function Validation 3
locationb 匪— 003733 OASL 3.780 2'-5'-0ugoadenylate svnthetase-like O (1) location b匪 — 003733 OASL 3.780 2'-5'-0ugoadenylate svnthetase-like O (1)
Immune response  Immune response
丽— 002993 CXCL6 3.692 Chemokine (C-X-C motif) ligand 6 0029— 002993 CXCL6 3.692 Chemokine (C-X-C motif) ligand 6
Inflammation O (1) Inflammation O (1)
AI763378 EHF 3.433 Ets homologous factor Transcription (4)AI763378 EHF 3.433 Ets homologous factor Transcription (4)
AK025180 3.418 (2)AK025180 3.418 (2)
AA554833 MAP1B 3.399 Microtubule-associated protein IB Structural protein O (1) AA554833 MAP1B 3.399 Microtubule-associated protein IB Structural protein O (1)
Homo sapiens, clone  Homo sapiens, clone
BF513121 3.317 (5)  BF513121 3.317 (5)
IMAGE:4794726, mKNA  IMAGE: 4794726, mKNA
AI660243 TMPRSS2 3.124 Transmembrane protease, serine 2 Proteolysis 〇 (1) AI660243 TMPRSS2 3.124 Transmembrane protease, serine 2 Proteolysis 〇 (1)
BF700086 IRS2 2.999 Insulin receptor substrate 2 Cell proliferation (1) BF700086 IRS2 2.999 Insulin receptor substrate 2 Cell proliferation (1)
Tumor-associated calcium signal  Tumor-associated calcium signal
J04152 TACSTD2 2.919 Cell proliferation  J04152 TACSTD2 2.919 Cell proliferation
transducer 2 O (1) transducer 2 O (1)
Homo sapiens mRNA; cDNA Homo sapiens mRNA; cDNA
BE157991 2.768 (2)  BE157991 2.768 (2)
DKFZp686D0581  DKFZp686D0581
Homo sapiens cDNA FLJ23860  Homo sapiens cDNA FLJ23860
AK074440 2.728 (2) fis, clone LNG08308  AK074440 2.728 (2) fis, clone LNG08308
Homo sapiens mRNA; cDNA  Homo sapiens mRNA; cDNA
AW025579 2.703  AW025579 2.703
DKFZp564B222 (2) DKFZp564B222 (2)
Homo sapiens transcribed Homo sapiens transcribed
AW612461 2.698  AW612461 2.698
sequences O (2)  sequences O (2)
Immune response  Immune response
Chemokine (C-X-C motif) ligand  Chemokine (C-X-C motif) ligand
雇—001565 CXCL10 2.696 Antiviral 〇 Employment—001565 CXCL10 2.696 Antiviral 〇
10 (1) response  10 (1) response
AV733347 LOC56902 2.613 Putatative 28 kDa protein (4)  AV733347 LOC56902 2.613 Putatative 28 kDa protein (4)
Homo sapiens cDNA FLJ 10263  Homo sapiens cDNA FLJ 10263
AW301393 2.563 (2) fis, clone HEMBB 1000991.  AW301393 2.563 (2) fis, clone HEMBB 1000991.
應—018362 LIN7C 2.553 Lin-7 homolog C (C. elegans) O (1) --018362 LIN7C 2.553 Lin-7 homolog C (C. elegans) O (1)
Homo sapiens transcribed  Homo sapiens transcribed
AI475680 2.543 sequence with strong similarity to (5) protein pdb: lBGM (E. coli)  AI475680 2.543 sequence with strong similarity to (5) protein pdb: lBGM (E. coli)
AI765383 2.537 KIAA1466 protein (5)  AI765383 2.537 KIAA1466 protein (5)
Homo sapiens cDNA FLJ42409  Homo sapiens cDNA FLJ42409
AI733124 2.536  AI733 124 2.536
fis, clone BLADE2000866 (5) a real-time PCRによる発現定量を行った遺伝子に Oを記載。 fis, clone BLADE2000866 (5), wherein the O gene was performed expression quantification by a real-time PCR.
b図 8の probeの構造上分類を記載。 b Describes the structural classification of the probe in Figure 8.
表 4 低ウィルス遺伝子 Table 4 Low viral genes
ProbeProbe
Accession No. Gene symbol FC Gene title Function Validation a Accession No. Gene symbol FC Gene title Function Validation a
location13 location 13
Homo sapiens full length insert Homo sapiens full length insert
AF086134 9.210 (5) cDNA clone ZA88B06  AF086134 9.210 (5) cDNA clone ZA88B06
BF514098 4.502 (5)  BF514098 4.502 (5)
Homo sapiens transcribed sequence  Homo sapiens transcribed sequence
Signaling  Signaling
T55506 FU46154 4.376 with weak similarity to protein  T55506 FU46154 4.376 with weak similarity to protein
cascade 〇 (1) ref:NP  cascade ○ (1) ref: NP
t 一 060265.1 (H.sapiens)  t one 060265.1 (H.sapiens)
Homo sapiens full length insert  Homo sapiens full length insert
AI580142 4.043 (5) cDNA clone YI46G04  AI580142 4.043 (5) cDNA clone YI46G04
protein  protein
M27830 28S rRNA c 4.026 Human 28S ribosomal RNA gene (5) biosynthesis M27830 28S rRNA c 4.026 Human 28S ribosomal RNA gene (5) biosynthesis
Selectin E (endothelial adhesion Inflammation  Selectin E (endothelial adhesion Inflammation
丽— 000450 SELE 3.334 〇 丽 — 000450 SELE 3.334 〇
molecule 1) Cell adhesion ■ (i) molecule 1) Cell adhesion ■ (i)
AI740788 3.215 (5) 画 145 3.026 Homo sapiens transcribed sequences O (5) AI740788 3.215 (5) 145 3.026 Homo sapiens transcribed sequences O (5)
Ras association (RalGDS/AF6) and Structural  Ras association (RalGDS / AF6) and Structural
雇—025252 RAPH1 2.999 〇 Employment—025252 RAPH1 2.999 〇
pleckstrin homology domain 1 (1) protein  pleckstrin homology domain 1 (1) protein
AW975324 2.941 Homo sapiens transcribed sequences (4)  AW975324 2.941 Homo sapiens transcribed sequences (4)
Ectoderm al-neural cortex (with  Ectoderm al-neural cortex (with
AF010314 ENC1  AF010314 ENC1
BTB-like domain) O (1) BTB-like domain) O (1)
Homo sapiens cDNA FLJ41455 fis, Homo sapiens cDNA FLJ41455 fis,
AA018404 2.836 (5) clone BRSTN2012284  AA018404 2.836 (5) clone BRSTN2012284
NM—001187 BAGE 2.709 B melanoma antigen Tumor antigen (1)  NM—001187 BAGE 2.709 B melanoma antigen Tumor antigen (1)
Homo sapiens cDNA FLJ12835 fis,  Homo sapiens cDNA FLJ12835 fis,
AK022897 2.625 (3) clone NT2RP2003165.  AK022897 2.625 (3) clone NT2RP2003165.
Homo sapiens, clone  Homo sapiens, clone
AA417117 ' 2.615 (5)  AA417117 '2.615 (5)
IMAGE:5300025, mRNA  IMAGE: 5300025, mRNA
proteasome (prosome, macropain)  proteasome (prosome, macropain)
AI001156 PSMA8 2.551 Proteasome  AI001156 PSMA8 2.551 Proteasome
subunit, alpha type, 8 (1) a real-time PCRによる発現定量を行った遺伝子に Oを記載。 subunit, alpha type, 8 (1) O is described in the gene whose expression was quantified by a real-time PCR.
b図 8の probeの構造上分類に従い遺伝子を分類した。 b The genes were classified according to the structural classification of the probe in Fig. 8.
0この遺伝子は cRNA合成の原理上、定量解析できない遺伝子である。 0 This gene cannot be quantitatively analyzed due to the principle of cRNA synthesis.
ここでとらえられた差は、この probeとホモロジ一の高い遺伝子の転写産物と考える。 The difference captured here is considered to be a transcript of a gene having a high homology with this probe.
この probe配列にホモロジ一の高い遺伝子は、複数見つかる。 Several genes with high homology in this probe sequence are found.
また、 高ウィルス遺伝子 78個すベてを表 5に、 低ウィルス遺伝子 39個すベ てを表 6に示した。 Table 78 shows all 78 high virus genes and Table 6 shows all 39 low virus genes.
表 5およぴ表 6 (1)、 （2)において、 「a」 は microarrayの probeが由来する遺 伝子で、 発現変化した遺伝子そのものではない場合もあることを、 「b」 は、 遺 伝子の構造上の probeの位置より、 5つのカテゴリーに分類したことを、 「c」 は、 この probe配列とホモロジ一のある他の遺伝子が検出されてことを示して いる。 また、 「A」 は遺伝子の exon配列を、 「B」 は遺伝子の intronで遺伝子と 同方向の配列を、 「C」 は遺伝子の intronで、 遺伝子と反対方向の配列を、 「D」 は遺伝子に隣接する同方向の配列を、 「E」 は遺伝子の.ないところの配列を示し ている。 表 5高ウィルス遺伝子 （78) In Tables 5 and 6 (1) and (2), “a” is a gene derived from the probe of the microarray, and “b” “C” indicates that another gene that is homologous to this probe sequence has been detected. “A” is the exon sequence of the gene, and “B” is the gene intron. The sequence in the same direction, `` C '' is the intron of the gene, the sequence in the opposite direction to the gene, `` D '' is the sequence in the same direction adjacent to the gene, `` E '' is the sequence where the gene is not present ing. Table 5 High virus genes (78)
Seq  Seq
No. Fold change Accesion No.' Category No. Fold change Accesion No.1 CategoryNo. Fold change Accesion No. 'Category No. Fold change Accesion No. 1 Category
1 3.780 丽 003733 54 Al 41 2.198 AF400600 94 A161 3.780 0037 003733 54 Al 41 2.198 AF400 600 94 A16
2 3.692 NM 002993 55 A2 42 2.186 AI285970 95 B122 3.692 NM 002993 55 A2 42 2.186 AI285970 95 B12
3 3.433 AI763378 56 Dl 43 2.184 M63310 96 A173 3.433 AI763378 56 Dl 43 2.184 M63310 96 A17
4 3.418 AK025180 57 Bl 44 2.162 AB040914 97 A184 3.418 AK025180 57 Bl 44 2.162 AB040914 97 A18
5 3.399 AA554833 58 A3 45 2.153 NM_016323 98 A195 3.399 AA554833 58 A3 45 2.153 NM_016323 98 A19
6 3.317 BF513121 59 El 46 2.149 AI762431 99 C26 3.317 BF513121 59 El 46 2.149 AI762431 99 C2
7 3.124 AI660243 60 A4 47 2.148 AA557324 100 A207 3.124 AI660243 60 A4 47 2.148 AA557324 100 A20
8 2.999 BF700086 61 A5 48 2.144 AA026666 101 El l8 2.999 BF700086 61 A5 48 2.144 AA026666 101 El l
9 2.919 J04152 62 A6 49 2.141 BF984830 102 A219 2.919 J04152 62 A6 49 2.141 BF984830 102 A21
10 2.768 BE157991 63 B2 50 2.133 NM 002125 103 A2210 2.768 BE157991 63 B2 50 2.133 NM 002125 103 A22
11 2.728 AK074440 64 B3 51 2.123 BF055144 104 B1311 2.728 AK074440 64 B3 51 2.123 BF055144 104 B13
12 2.698 AW612461 65 B4 52 2.121 NM 006206 105 A2312 2.698 AW612461 65 B4 52 2.121 NM 006206 105 A23
13 2.696 NM 001565 66 A7 53 2.107 AA588854 106 A2413 2.696 NM 001565 66 A7 53 2.107 AA588854 106 A24
14 2.613 AV733347 67 D2 54 2.100 BE501712 107 C314 2.613 AV733347 67 D2 54 2.100 BE501712 107 C3
15 2.563 AW301393 68 B5 55 2.098 NM 001096 108 A2515 2.563 AW301393 68 B5 55 2.098 NM 001096 108 A25
16 2.553 NM一 018362 69 A8 56 2.096 AV715309 109 D416 2.553 NM 018362 69 A8 56 2.096 AV715309 109 D4
17 2.543 AI475680 70 E2 57 2.090 AI741188 110 D517 2.543 AI475 680 70 E2 57 2.090 AI741188 110 D5
18 2.537 AI765383 71 E3 58 2.088 AL096776 111 A2618 2.537 AI765383 71 E3 58 2.088 AL096776 111 A26
19 2.536 AI733124 72 E4 59 2.087 AF055024 112 A2719 2.536 AI733 124 72 E4 59 2.087 AF055024 112 A27
20 2.485 AV699047 73 E5 60 2.085 NM— 173829 113 A2820 2.485 AV699047 73 E5 60 2.085 NM— 173829 113 A28
21 2.479 AK026659 74 E6 61 2.085 NM 017631 114 A2921 2.479 AK026659 74 E6 61 2.085 NM 017631 114 A29
22 2.441 BC035120 75 B6 62 2.084 AI432713 115 A3022 2.441 BC035 120 75 B6 62 2.084 AI432 713 115 A30
23 2.440 AK091504 76 B7 63 2.083 Z24727 116 A3123 2.440 AK091504 76 B7 63 2.083 Z24727 116 A31
24 2.435 AA937109 77 B8 64 2.081 AW629515 117 A3224 2.435 AA937 109 77 B8 64 2.081 AW629515 117 A32
25 2.431 AU145679 78 E7 65 2.077 AU147926 118 B1425 2.431 AU145679 78 E7 65 2.077 AU147926 118 B14
26 2.409 All 10886 79 A9 66 2.073 AB046808 119 A3326 2.409 All 10886 79 A9 66 2.073 AB046808 119 A33
27 2.409 BU685917 80 D3 67 2.062 AA903184 120 C427 2.409 BU685917 80 D3 67 2.062 AA903184 120 C4
28 2.385 AA148507 81 A10 68 2.048 AF229069 121 E1228 2.385 AA148507 81 A10 68 2.048 AF229069 121 E12
29 2.385 BC017579 82 E8 69 2.046 AA772278 122 A3429 2.385 BC017579 82 E8 69 2.046 AA772278 122 A34
30 2.359 AL 136727 83 Al l 70 2.045 NM一 138337 123 A3530 2.359 AL 136 727 83 Al l 70 2.045 NM 1 138 337 123 A35
31 2.356 BF590303 84 B9 71 2.036 AL049435 124 E1331 2.356 BF590303 84 B9 71 2.036 AL049435 124 E13
32 2.354 NM— 004420 85 A12 72 2.034 AA115933 125 A3632 2.354 NM— 004420 85 A12 72 2.034 AA115 933 125 A36
33 2.306 AI806747 86 E9 73 2.024 AU147194 126 B1533 2.306 AI806747 86 E9 73 2.024 AU147194 126 B15
34 2.274 AL021786 87 A13 74 2.022 AL044078 127 C534 2.274 AL021786 87 A13 74 2.022 AL044078 127 C5
35 2.267 AW242409 88 E10 75 2.015 AL157471 128 A3735 2.267 AW242409 88 E10 75 2.015 AL157471 128 A37
36 2.263 AF311312 89 A14 76 2.012 AL161725 129 A3836 2.263 AF311312 89 A14 76 2.012 AL161725 129 A38
37 2.263 AF275800 90 B10 77 2.011 N90755 130 A3937 2.263 AF275 800 90 B10 77 2.011 N90755 130 A39
38 2.226 丽 030751 91 A15 78 2.009 AL136820 131 B1638 2.226 丽 030751 91 A15 78 2.009 AL136820 131 B16
39 2.219 AI017983 92 Bl l 39 2.219 AI017983 92 Bl l
40 2.199 AU145365 93 CI 6(1)低ウィルス遺伝子 (39) 表 6 (2) 40 2.199 AU145365 93 CI 6 (1) Low viral genes (39) Table 6 (2)
No. Fold change Accesion No.3 ID Category*5 117遺伝子のカテゴリ一別分類No. Fold change Accesion No. 3 ID Category * 5
1 9.210 AF086134 132 El 局ゥ ル 低ゥ ル1 9.210 AF086134 132 El station
2 4.502 BF514098 133 Ε2 ス遺伝子 ス遺伝十2 4.502 BF514098 133 Ε2 gene
3 4.376 Τ55506 134 Al 39 103 4.376 Τ55 506 134 Al 39 10
4 4.043 AI580142 135 E3 6 04 4.043 AI580 142 135 E3 6 0
5 4.026 M27830c 136 E4 25 4.026 M27830 c 136 E4 2
6 3.334 丽 000450 137 A2 26 3.334 0004 000450 137 A2 2
7 3.215 ΑΙ740788 138 E5 3 257 3.215 ΑΙ740 788 138 E5 3 25
8 3.026 N80145 139 E6 Total 78 398 3.026 N80145 139 E6 Total 78 39
9 2.999 丽 025252 140 A3 9 2.999 丽 025 252 140 A3
10 2.941 AW975324 141 Dl  10 2.941 AW975324 141 Dl
11 2.877 AF010314 142 A4  11 2.877 AF010314 142 A4
12 2.836 AA018404 143 E7  12 2.836 AA018404 143 E7
13 2.709 ΝΜ一 001187 144 A5  13 2.709 Keiichi 001187 144 A5
14 2.625 ΑΚ022897 145 CI  14 2.625 ΑΚ022897 145 CI
15 AA417117 146 E8  15 AA417 117 146 E8
16 2.551 AI00 156 147 A6  16 2.551 AI00 156 147 A6
17 2.492 ΑΙ349737 148 E9  17 2.492 ΑΙ349737 148 E9
18 2.452 AL049437 149 E10  18 2.452 AL049437 149 E10
19 2.440 Ν74530 150 El l  19 2.440 Ν74530 150 El l
20 2.424 BC022234 151 E12 A D B c E  20 2.424 BC022234 151 E12 A D B c E
21 2.395 BC022380 152 E13  21 2.395 BC022380 152 E13
22 2.360 AI804210 153 E14  22 2.360 AI804 210 153 E14
23 2.302 BC038210 154 E15  23 2.302 BC038210 154 E15
24 2.195 ΑΚ096893 155 E16 24 2.195 ΑΚ096893 155 E16
Figure imgf000029_0001
Figure imgf000029_0001
26 2.185 AL049997 157 E17  26 2.185 AL049997 157 E17
27 2.177 AK021494 158 Dl  27 2.177 AK021494 158 Dl
28 2.162 AY010114 159 E18  28 2.162 AY010 114 159 E18
29 2.156 ΑΚ023827 160 E19  29 2.156 ΑΚ023827 160 E19
30 2.155 BF511381 161 C2  30 2.155 BF511381 161 C2
31 2.126 BC029472 162 E20  31 2.126 BC029472 162 E20
32 2.125 ΝΜ—020398 163 A8  32 2.125 ΝΜ—020398 163 A8
33 2.119 AW340004 164 E21  33 2.119 AW340004 164 E21
34 2.095 BC043200 165 E22  34 2.095 BC043200 165 E22
35 2.093 AL137028 166 E23  35 2.093 AL137028 166 E23
36 2.048 BF593928 167 E24  36 2.048 BF593928 167 E24
37 U19518 168 A9  37 U19518 168 A9
38 2.038 AU147598 169 E25  38 2.038 AU147598 169 E25
39 2.002 AL137266 170 A10 実施例 3  39 2.002 AL137266 170 A10 Example 3
real-time PGRによる発現量解析 Expression level analysis by real-time PGR
8症例の microarrayの比較で見いだされた遺伝子 117個 （実施例 2 ) が 確かに HCV量の違いに相関するものかを調べるために、 34症例の肝臓 cDNA を用いて real-time PCRによる発現量解析を行った。 . 117 genes (Example 2) found by comparison of 8 cases of microarray In order to investigate whether it was indeed correlated with the difference in HCV levels, we performed expression analysis by real-time PCR using 34 cases of liver cDNA. .
(1) 内在性コントロール遺伝子  (1) Endogenous control gene
遺伝子の発現量の評価に用いるコントロール遺伝子として、 細胞あたり一定 量発現するといわれている housekeeping gene が用いられる。 j3 -actin や GAPDH遺伝子が代表的な遺伝子である。 しかし、 様々な病態や状態の組織、 細胞を調べると、 必ずしもこれらの遺伝子が一定発現するとはいえない。 最近 では 18S i'RNAなどが用いられるようになつている。 本実施例では、 対象とす る肝炎組織で一定発現する遺伝子を、 8例の microarrayから独自に検討してみ た。  The housekeeping gene, which is said to be expressed at a constant level per cell, is used as a control gene for evaluating the expression level of the gene. j3 -actin and GAPDH genes are typical genes. However, when examining tissues and cells of various pathologies and conditions, it cannot be said that these genes are expressed constantly. Recently, 18S i'RNA has been used. In this example, we independently examined 8 microarrays of genes that are constantly expressed in the target hepatitis tissue.
今回用いた HG U133 Plus2.0 arrayには、これに載っている probeのうち、 コントロール遺伝子として 100個の遺伝子がリス トされている。 そのうち 8枚 の microarray全て に present flagの付いている遺伝子は 91個であった。 こ の中から、 8枚の microarrayで発現レベルに差がなく、 なおかつ GAPDHと 同様の発現レベルを示す遺伝子を探した。 その結果 ribosomal protein L34 (RPL34)が選ばれた。 同じ microarray上の GAPDH発現シグナルと比較する と、 RPL34の方が確かに発現レベルのバラつきが少なかった （図 6 A)。  The HG U133 Plus2.0 array used here lists 100 genes as control genes among the probes on it. Of these, 91 genes had present flags in all 8 microarrays. From these, we searched for genes that showed no difference in expression level among the 8 microarrays and that showed the same expression level as GAPDH. As a result, ribosomal protein L34 (RPL34) was selected. Compared to the GAPDH expression signal on the same microarray, RPL34 certainly had less variation in expression level (Figure 6A).
microarray解析では 18S rRNA の評価をすることができない。 そこで、 RPL34と 18S rRNAとではどちらがコントロール遺伝子として適しているか を明らかにするために、全 34症例で real-time PCRにより発現量を比較した。 図 6Bに GAPDHも含めて 3遺伝子の発現量の比較を示す。 cDNA—定量あた りの発現量を比較したところ、 18S rRNA の発現量のばらつきが、 PRL34 と GAPDHと比較して最も小さかった。 よって本実施例では、 内在性コントロー ル遺伝子として 18S rRNAを用いて、 以下の遺伝子発現の評価を行った。  18S rRNA cannot be evaluated by microarray analysis. Therefore, in order to clarify which of RPL34 and 18S rRNA is suitable as a control gene, the expression levels were compared by real-time PCR in all 34 cases. Figure 6B shows a comparison of the expression levels of the 3 genes including GAPDH. Comparing the expression level of cDNA—quantitatively, the variation in the expression level of 18S rRNA was the smallest compared to PRL34 and GAPDH. Therefore, in this example, the following gene expression was evaluated using 18S rRNA as an endogenous control gene.
(2) 高ウイルス遺伝子と低ウイルス遺伝子の発現定量比較 (2) Quantitative comparison of high and low viral genes
高ウィルス遺伝子 8 個、 低ウィルス遺伝子 5 個を選び、 慢性肝炎 18 例 (microarrayに用いた 8例を含む） と肝硬変 16例を対象に、 高ウィルス群と 低ウィルス群との間で発現量の比較を行った。 表 7にその結果を示す。 Real-time PCRによる発現定量解析と二群間比較 Select 8 high virus genes and 5 low virus genes, and in 18 cases of chronic hepatitis (including 8 cases used for microarray) and 16 cases of cirrhosis, the expression level between high virus group and low virus group A comparison was made. Table 7 shows the results. Real-time PCR quantitative analysis and comparison between two groups
Microarray (CH 4:4) Real-time PCR Microarray (CH 4: 4) Real-time PCR
Gene Raw signal CH (4 4) CH (9 9) LC (10 : 6)  Gene Raw signal CH (4 4) CH (9 9) LC (10: 6)
High Low FC P FC P P  High Low FC P FC P P
High  High
OASL 3.78 255.9 77.4 16.33 0.0209 9.47 0.0007 0.1931 OASL 3.78 255.9 77.4 16.33 0.0209 9.47 0.0007 0.1931
CXCL6 3.692 134.7 41.1 3.89 0.0209 3.34 0.0305 0.4477CXCL6 3.692 134.7 41.1 3.89 0.0209 3.34 0.0305 0.4477
MAP1B 3.399 62.5 23.5 2.43 0.0209 2.47 0.0054 0.8283MAP1B 3.399 62.5 23.5 2.43 0.0209 2.47 0.0054 0.8283
TMPRSS2 3.124 118 46.7 2.42 0.0433 2.66 0.0023 >0.9999TMPRSS2 3.124 118 46.7 2.42 0.0433 2.66 0.0023> 0.9999
TACSTD 2.919 153.2 54.6 3.38 0.0209 3.35 0.0041 0.6644TACSTD 2.919 153.2 54.6 3.38 0.0209 3.35 0.0041 0.6644
AW612461 a 2.703 55.2 26.1 2.19 0.0833 3.11 0.0031 0.1931AW612461 a 2.703 55.2 26.1 2.19 0.0833 3.11 0.0031 0.1931
CXCL10 2.698 . 698 342.4 2.93 0.0209 i 3.22 0.0118 0.9136CXCL10 2.698 .698 342.4 2.93 0.0209 i 3.22 0.0118 0.9136
LIN7C 2.553 104 49 1.64 0.3865 2.22 0.0305 0.7449LIN7C 2.553 104 49 1.64 0.3865 2.22 0.0305 0.7449
Low Low
FLJ461542 4.376 7 29.9 3.09 0.0209 0.87 0.3538 0.7449 FLJ461542 4.376 7 29.9 3.09 0.0209 0.87 0.3538 0.7449
SELE 3.334 15.3 50.4 6.69 0.0209 2.19 0.0703 0.0509 漏 145 a 3.026 29.2 96.6 0.55 0.1489 0.33 0.0198 0.9136SELE 3.334 15.3 50.4 6.69 0.0209 2.19 0.0703 0.0509 Leakage 145 a 3.026 29.2 96.6 0.55 0.1489 0.33 0.0198 0.9136
RAPH1 2.999 123.5 418 0.80 0.5637 0.96 0.1023 0.7449RAPH1 2.999 123.5 418 0.80 0.5637 0.96 0.1023 0.7449
ENC1 2.877 37.1 124.3 1.22 0.5637 0.82 0.8253 0.6644 a Accession No.で 載。 ENC1 2.877 37.1 124.3 1.22 0.5637 0.82 0.8253 0.6644 a Listed in Accession No.
二群間比較は、 マイクロアレイ解析に用いた慢性肝炎 (CH)8例と全慢性肝炎 (CH)18 .例'と全肝硬変 (LC) 16 例とにわけて行つ'た。 遺伝子の発現暈は、 18S rRNAで.補正した値を用いた。 高ウィルス群：低ウィルス群の例数を括弧内に 示す。 表 7の 「High」 の欄に高ウィルス遺伝子 8個の結果を、 表 7の 「： Low」 の欄に低ウィルス遺伝子 5個の結果を示した。 The comparison between the two groups was divided into 8 cases of chronic hepatitis (CH) and 18 cases of total chronic hepatitis (CH) and 16 cases of total cirrhosis (LC) used for microarray analysis. As the expression level of the gene, values corrected with 18S rRNA were used. High virus group: The number of low virus group is shown in parentheses. The result of 8 high virus genes is shown in the “High” column of Table 7, and the result of 5 low virus genes is shown in the “: Low” column of Table 7.
Fold change (FC)は、 各群中央値で比較したときの値を示す。 例えば、 高ゥ ィルス遺伝子であれば、 当該遺伝子の高ウィルス群の中央値を低ウィルス群の 中央値で除した値を示している。 また、 2群間で Mann Whitney U検定を 行い、 有意差 (P<0.05)のあった遺伝子の値は破線で囲んだ。 逆転変化で有意差 を示したものは、 実線で囲んだ。  Fold change (FC) indicates the value when compared with the median of each group. For example, in the case of a high virus gene, the value obtained by dividing the median value of the high virus group of the gene by the median value of the low virus group is shown. In addition, the Mann Whitney U test was performed between the two groups, and the values of genes that had a significant difference (P <0.05) were surrounded by a broken line. The reversible changes that showed a significant difference are enclosed in a solid line.
表 7に示すように、 real-time PCRによる発現量解析において、 高ウィルス 遺伝子は、 microarrayによる発現解析結果とほぼ一致し、 慢性肝炎 （CH) 18 例においては 8遺伝子とも高ウィルス遺伝子として有意差を認めた (表 7 )。 し かし肝硬変 （LC) では発現量に差は認められなかった。 これらの遺伝子は、 低 ウィルス症例で発現が減少していなかつたためである。 このことから、 感染し ているウィルス量が少ない慢性肝炎と肝硬変とでは、 ウィルス量を制御する機 構は異なり、 共通のメカニズムを単純には追跡できないことがわかった。 As shown in Table 7, in the expression level analysis by real-time PCR, The genes were almost identical to the results of microarray expression analysis, and in 18 patients with chronic hepatitis (CH), all 8 genes were significantly different as high viral genes (Table 7). However, no difference in the expression level was observed in cirrhosis (LC). This is because the expression of these genes was not reduced in the low virus cases. From this, it was found that the mechanism of controlling the viral load differs between chronic hepatitis and cirrhosis with low viral load, and it is not possible to simply follow a common mechanism.
図 7には慢性肝炎での代表的な比較結果を示す。 図 7の A〜Cに示す高ウイ ルス遺伝子は、図 3に示した IFN下流の遺伝子とは異なり、髙ウィルス群と低 ウィルス群とで明らかに発現量の有意差を認める遺伝子であった。 しかし、 低 ウィルス遺伝子は、 microarrayの発現結果と同様の結果が 5個中 2個に認めら れるが、 結局慢性肝炎で有意に差を認めるのは 1個となった (表 7 )。 この遺伝' 子 SELEは肝硬変でも差のある傾向を示した （表 7 )。 図 7の Dおよび ¾に上 記 2つの遺伝子 SELEおよび FLJ461542の結果を示す。 また、 N80145は慢 '性肝炎で逆の有意差、すなわち高ウィルス遺伝子として認められた（F)。 SELE 以外の遺伝子では、 肝硬変症例で有意に差のある遺伝子は見出されなかった。 低ウイルス遺伝子の中には、 microarra の発現解析の 8例では差のある遺伝 子として抽出されても、 慢性肝炎' 18例では差のある遺伝子とはいえない遺伝 子が含まれている可能性が示唆された。 また、 一部の低ウィルス遺伝子では、 microarray と real-time PGRとで同じような有意差を示すことができない遺 '.伝子も存在した。 設計した primer.では効率よく PCRできない、 microarray . • 'の probeにクロスハイブリダ'ィゼーシヨンする遺伝子があるなどの可能性が考 えられる。 実施例 4  Figure 7 shows typical comparison results for chronic hepatitis. Unlike the genes downstream of IFN shown in FIG. 3, the high virus genes shown in A to C of FIG. 7 were genes that clearly showed a significant difference in expression level between the virus group and the low virus group. However, low virus genes showed similar results to microarray expression in 2 out of 5 genes, but after all, there was only 1 significant difference in chronic hepatitis (Table 7). This heritable SELE showed a different tendency even in cirrhosis (Table 7). The results of the above two genes SELE and FLJ461542 are shown in D and ¾ of FIG. In addition, N80145 was recognized as an opposite significant difference in chronic hepatitis, ie, a high viral gene (F). For genes other than SELE, no significantly different genes were found in cirrhosis cases. The low viral genes may contain genes that were extracted as differential genes in 8 cases of microarra expression analysis but could not be said to be different genes in 18 cases of chronic hepatitis Was suggested. In addition, for some low-viral genes, there were also genes that could not show the same significant difference between microarray and real-time PGR. There is a possibility that PCR cannot be performed efficiently with the designed primer, or that there is a gene that cross-hybridizes in the microarray. Example 4
117遺伝子の分類 '  117 gene classification ''
Oligonucleotide microarra で抽 |±}された発現に差のある遺伝子 117個につ いて、 既知の遺伝子、 未知の遺伝子、 ざらに既知遺伝子の機能について分類し た。  The 117 genes that differed in expression extracted with Oligonucleotide microarra were classified according to the functions of known genes, unknown genes, and known genes.
(A).構造分類 図 8に、 最新遺伝子情報にもとづく 117 probeの構造上の分類を示す。 遺伝 子の分類は次の 5つのカテゴリーが考えられる。 . (A) Structural classification Figure 8 shows the structural classification of 117 probes based on the latest gene information. There are five categories of gene classifications. .
(1) 同定済みの遺伝子または遺伝子として予想されている配列が probeの場合、 (1) If the identified gene or the sequence predicted as a gene is probe,
(2) 遺伝子領域内であるが、 イントロン配列が probeの場合、 (2) Within the gene region, but the intron sequence is probe,
(3) 上記 (2)の probeの相補鎖が probeの場合、 (3) If the complementary strand of probe in (2) above is probe,
(4) 遺伝子に隣接する外側の配列が probeの場合、  (4) If the outer sequence adjacent to the gene is probe,
(5) 遺伝子が想定されていない領域が probeの場合  (5) When the region where no gene is assumed is probe
である。（1)は該当遺伝子の転写産物を意味する。（2)は該当遺伝子の選択的ス プライシング転写産物か、 あるいは新たな転写産物の可能性がある。 （3)はその 干渉 RNAとしての転写産物か、 あるいは新たな転写産物の可能性がある。 （4) は該当遺伝子の転写産物か、 新たな転写産物の可能性がある。 （5)は未知の転写 産物と考えられる。  It is. (1) means the transcript of the relevant gene. (2) may be a alternatively spliced transcript of the gene of interest or a new transcript. (3) may be a transcript as an interfering RNA or a new transcript. (4) may be a transcript of the gene of interest or a new transcript. (5) is considered an unknown transcript.
高ウィルス遺伝子 78個と低ウィルス遺伝子 39個を、 これらのカテゴリーに 従って分類した （図 8)。  78 high viral genes and 39 low viral genes were classified according to these categories (Figure 8).
高ウィルス遺伝子の半数は遺伝子転写産物で、 8割が遺伝子関連領域の転写 産物であった。 低ウィルス遺伝子は逆に遺伝子未同定の領域の転写産物が 6割 を占めていた。 これら未知の転写産物が数多く発現増強していることが、 ウイ ルス抑制状態と関連するかどう力、 興味深いところである。 (B) 機能分類  Half of the high viral genes were gene transcripts, and 80% were gene-related region transcripts. On the other hand, transcripts from unidentified regions accounted for 60% of low-viral genes. It is interesting to note that the expression of many of these unknown transcripts is related to the virus suppression state. (B) Function classification
まず、 INF誘導性遺伝子が差のある遺伝子として見いだされているかを検討 した。 INF誘導性遺伝子として知られている 239個の遺伝子のうち、 2個だけ が高ウィルス遺伝子の中に存在した。 このことは高ウィルス症例でさえ、 IFN がそれほど強く作動していないことを示している。 持続感染が成立してしまつ た慢性肝炎では、 IFN以外の宿主遺伝子がウィルス量のコントロールに関与し ていることが示唆された。  First, it was examined whether INF-inducible genes were found as differential genes. Of the 239 genes known as INF-inducible genes, only 2 were among the high viral genes. This indicates that IFN is not working so strongly, even in high virus cases. In chronic hepatitis in which persistent infection was established, it was suggested that host genes other than IFN are involved in viral load control.
既知の高ウィルス遺伝子 36個の中で、 6個は、 T細胞活性、 免疫細胞やリン パ球の増殖、 リンパ球の走化性などの炎症反応、 免疫反応を増強する遺伝子で あった。 このような遺伝子が発現していることは、 HCVを排除しようとする宿 主防御反応が働いていることを示すものである。 これらは、 ウィルス量が多い 結果、 誘導された遺伝子と考えられる。 しかし、 それにも拘わらずウィルスは 排除されず、 宿主はウィルス量の多い状態を保っている。 髙ウィルス遺伝子の 中には、 HCV側にとつて増殖有利に働くと予想される因子が存在する可能性が ある。 Of the 36 known high viral genes, 6 were genes that enhance T cell activity, immune cell and lymphocyte proliferation, inflammatory responses such as lymphocyte chemotaxis, and immune responses. The expression of such a gene means that HCV is excluded It indicates that the main defense reaction is working. These are considered to be induced genes as a result of the high viral load. However, the virus has never been eliminated, and the host remains in a high viral load state. There is a possibility that there are factors in the 増 殖 virus gene that are expected to have a growth advantage on the HCV side.
低ウィルス遺伝子では、 セリンプロテアーゼ阻害活性領域を持つ遺伝子、 プ 口テオソームに関与する遺伝子が存在した。 ウィルス増殖阻害が予想される遺 伝子である。 また、 高ウィルス遺伝子とは別の.炎症に関与する遺伝子も含まれ ていた。 しかし、 低ウィルス遺伝子では機能のわからない未知遺伝子が半分以 上占めていた。 これらの中に、 HCVの干渉 RNAとして働く転写産物が含まれ ていないか、 HCV9.5 kbの配列との相同性を調 てみた。 しかし、 低ウィルス 遺伝子にはそのような配列は存在しなかった。 低ウィルス遺伝子には、 HCV が増殖しにくい環境作りに関与する遺伝子が存在する可能性がある。  Among the low viral genes, there were genes with serine protease inhibitory active regions and genes related to the plugeothesome. This gene is expected to inhibit viral growth. In addition, genes involved in inflammation other than high viral genes were also included. However, more than half of the low-viral genes were unknown genes whose functions were unknown. Among these, transcripts that act as HCV interfering RNA were not included, or homology with the HCV 9.5 kb sequence was examined. However, there was no such sequence in the low viral gene. Low viral genes may have genes involved in creating an environment in which HCV is difficult to grow.
ここで見出された遺伝子には、 ウィルス量に関わる原因遺伝子と結果遺伝子 とが両方存在すると考えられる。 どの遺伝子がウィルス量のコントロールに関 与している原因遺伝子であるかは、 HCV感染増殖実験系を用いて、遺伝子が実 際ウィルス量に影響するかどう力 \ 因果関係を明らかにしていく必要がある。 実施例 5  The genes found here are considered to have both causative genes and resulting genes related to viral load. To determine which genes are responsible for controlling viral load, it is necessary to clarify the force / causal relationship of whether genes actually affect viral load using the HCV infection growth experiment system There is. Example 5
本率¾例では、 .実施例.1及び 2と同様に. HCV'の定量を行い、 .また実施例 1 . 及ぴ 2よりも症例数を増やして 2つの病態に分けてウィルス量と関連する遺伝 子を検討した。 まず肝臓ウィルス量を定量し、症例の選別を行った。方法を以下に示す。なお、 total RNA抽出とリアルタイム RT-PCRの方法は、実； 例.1と同様である。 '  In this rate example, as in Examples 1 and 2, HCV 'was quantified, and the number of cases was increased from Example 1 and 2 and divided into two pathological conditions, and the viral load was related. The genes to be studied were examined. First, the amount of liver virus was quantified, and cases were selected. The method is shown below. The methods for total RNA extraction and real-time RT-PCR are the same as in Example 1. '
ウィルス量は、ウィルス遺伝子の定量で求めた。材料は、肝細胞癌症例 59例の非 癌部組織を用い、なるべく肝細胞癌ステージの低い I,および IIを選択した。  The amount of virus was determined by quantifying the virus gene. As materials, non-cancerous tissues of 59 cases of hepatocellular carcinoma were used, and I and II with the lowest hepatocellular carcinoma stage were selected as much as possible.
組織から Total RNAを抽出し、 DNAの混在を除くため DNase l処理をおこなった。 その後、ランダムプライマーにより. cDNAを合成しリアルタイム PCRにて遺伝子定量 をおこなった。 HCV RNAの定量は、 HCVの遺伝子配列が保存されていて、効率よく PCRがかかった、 3'端に近い領域を用いた。また肝臓 mRNAの定量も同様の方法で 行った。 HCV RNA量や mRNA量は、細胞あたりの量に標準化するために 18S の定量も行い、この値で除した値を各 RNA量とした。 HCV RNA定量の結果を 表 8に示す。 Total RNA was extracted from the tissue and DNase treatment was performed to remove DNA contamination. Then, synthesize cDNA using random primers and quantitate genes by real-time PCR I did it. For the quantification of HCV RNA, a region close to the 3 'end where the HCV gene sequence was conserved and PCR was efficiently performed was used. Liver mRNA was also quantified in the same manner. In order to standardize the amount of HCV RNA and mRNA to the amount per cell, 18S was also quantified, and the value divided by this value was used as the amount of each RNA. The results of HCV RNA quantification are shown in Table 8.
表 8 C型肝細胞癌症例の背景因子と非癌部肝組織における HCV RNA Table 8 Background factors of hepatoma type C and HCV RNA in non-cancerous liver tissue
Figure imgf000035_0001
Figure imgf000035_0001
109 71 M Π lb 47110 A 109 71 M Π lb 47110 A
117 60 F Π lb 58349 117 60 F Π lb 58349
119 77 F Π lb 62246  119 77 F Π lb 62246
107 69 M Π lb+2a 68446 A 107 69 M Π lb + 2a 68446 A
114 74 M Π lb 88748 114 74 M Π lb 88748
78 66 F I lb 108180 A 78 66 F I lb 108 180 A
4 65 M I lb 109124 A 高ウィルス 81 69 F I LC lb 37545 群 20例 31 60 M I LC lb 38579 A 4 65 M I lb 109 124 A High virus 81 69 F I LC lb 37545 Group 20 cases 31 60 M I LC lb 38579 A
106 78 M I LC lb+2a 45558  106 78 M I LC lb + 2a 45558
62 66 M I LC lb 46203 A 62 66 M I LC lb 46203 A
15 68 M Π LC lb 66864 A15 68 M Π LC lb 66864 A
26 70 M I LC lb 70061 26 70 M I LC lb 70061
17 54 M I LC lb 74664 A 17 54 M I LC lb 74664 A
103 61 F I LC lb 81365 A103 61 F I LC lb 81365 A
3 71 F I LC lb 168169 3 71 F I LC lb 168 169
110 69 M I LC lb+2a 197867 A 110 69 M I LC lb + 2a 197867 A
77 65 F I LC lb 476467 A a:非癌部組織が肝硬変に進展している症例を LCで示す。 77 65 F I LC lb 476467 A a: LC shows a case where the non-cancerous tissue has progressed to cirrhosis.
b :HCV RNA定量値を内在性コントロール遗伝子 18S rRNA定量値で補正した値。 ( )の値は 遺伝子型 2型 HCVのため少なめに定量されている。  b: Value obtained by correcting the quantitative value of HCV RNA with the quantitative value of endogenous control gene 18S rRNA. Values in () are quantified slightly because of genotype 2 HCV.
c：マイクロアレイ解析に用いた症例を Aで示す。 肝臓 HCV量は、 4〜480000 unitの範囲で分布した。その中から、 30000 unit以上の 20症例を高ウイ.ルス群とし、 300 unit以下の 15症例を低ウィルス群とした。 c: A indicates the case used for microarray analysis. Liver HCV levels ranged from 4 to 480000 units. Among them, 20 cases of 30000 units or more were assigned to the high virus group, and 15 cases of 300 units or less were assigned to the low virus group.
実施例 2において行ったインターフェロン下流の遺伝子の発現解析から、 CHと LC では異なる遺伝子発現パターンを示したことより、本実 ½例では、 2つの病態に分けて、 ウィルス量と関連する遺伝子を検討した。選別した高ウィルス群と低ウィルス群とで患 者背景因子を比較した。患者背景因子として慢性肝炎 18例、肝硬変 17例に分けて、 それぞれの項目についてウィルス量による 2群間で比較を行った。有意差検定値を表 Based on the expression analysis of genes downstream of interferon performed in Example 2, CH and LC showed different gene expression patterns. Therefore, in this example, genes related to viral load were examined by dividing into two disease states. did. Patient background factors were compared between the selected high virus group and low virus group. The patient background factors were divided into 18 cases of chronic hepatitis and 17 cases of cirrhosis, and each item was compared between two groups according to viral load. Table of significant difference test values
9の「 」の欄に示す。 Shown in “” column of 9.
表 9 病態に関わる患者背景因子の、高ウィルス群と低ウィルス群での比較 a Patient background factors involved in Table 9 pathology, comparing a at high virus group and the low virus group
CH (18) LC (19)  CH (18) LC (19)
High (9) Low (9) P High (11) Low (6) P High (9) Low (9) P High (11) Low (6) P
Male 1 female 5 / 4 ' 9 / 0 7 / 4 4 /2 >0.999 Age (range) 68.9 (60-77) 62.6 (50-70) 66.5 (54-78) 65.2(56 73) . 0.5795 o o o Male 1 female 5/4 '9/0 7/4 4/2> 0.999 Age (range) 68.9 (60-77) 62.6 (50-70) 66.5 (54-78) 65.2 (56 73) .0.5795 o o o
I 2 2 9 2 I 2 2 9 2
Stage b H 7 6 2 3 0.042 Stage b H 7 6 2 3 0.042
ΠΙΑ 0 1 0 1  ΠΙΑ 0 1 0 1
Liver function 0 (mean±SE) Liver function 0 (mean ± SE)
ICG-R15 (% (く 10) 14.1±2.53 11.6±2.04 23.3±5.21 26.0±4.35  ICG-R15 (% (10) 14.1 ± 2.53 11.6 ± 2.04 23.3 ± 5.21 26.0 ± 4.35
Alb (g/dl) (6.7-8.3) 4.02±0.16 4.06±0.18 3.80±0.08 3.80±0.24  Alb (g / dl) (6.7-8.3) 4.02 ± 0.16 4.06 ± 0.18 3.80 ± 0.08 3.80 ± 0.24
AST (謹） (8-38) 62.1土 19.7 36.3±5.48 55.1±3.64 67.5±13.1  AST (謹) (8-38) 62.1 Sat 19.7 36.3 ± 5.48 55.1 ± 3.64 67.5 ± 13.1
ALT (IU/1) (40-44) 52.0±14.2 41.9±12.0 50.9±4.84 45.5±7.52  ALT (IU / 1) (40-44) 52.0 ± 14.2 41.9 ± 12.0 50.9 ± 4.84 45.5 ± 7.52
T.bil (mg/dl) (0.3-1.2) 0.79±0.17 0.56±0.08 0.80±0.11 0.80±0.13  T.bil (mg / dl) (0.3-1.2) 0.79 ± 0.17 0.56 ± 0.08 0.80 ± 0.11 0.80 ± 0.13
HCV RNAd (unit) 69,900±8,700 63±15 118,000±39,00C 158±42 HCV RNA d (unit) 69,900 ± 8,700 63 ± 15 118,000 ± 39,00C 158 ± 42
HCV genotype  HCV genotype
o o o o lb 7 5 9 3  o o o o lb 7 5 9 3
lb+2a 2 0 2 0  lb + 2a 2 0 2 0
0.082  0.082
2a . · · 0 . . 3： ' 0 . .2  2a... 3: '0 ..2
• : 2b ■ 0 • 1 0 1' .  •: 2b ■ 0 • 1 0 1 '.
a:有意差検定は次のように行った。 CH/LCは c2検定； Male/femaleおよび HCV genotypeはフ イツシヤーの直接確率検定； Age, Stage, Liver function, HCV RNA量は Mann Whitney U検定. b :肝細胞癌の Stage分類は、 TNM分類 に従った。  a: Significant difference test was performed as follows. CH / LC for c2 test; Male / female and HCV genotype for Fisher's direct probability test; Age, Stage, Liver function, HCV RNA levels for Mann Whitney U test. I followed.
c：各値の正常値を括弧内に示した。  c: Normal values for each value are shown in parentheses.
d : cDNA 50 ng当たりの HCV RNA copy数を求め、 18S rRNA定量値で割った値を unitとして 表記した。  d: The number of HCV RNA copies per 50 ng of cDNA was determined, and the value divided by the 18S rRNA quantitative value was expressed as unit.
CH,慢性肝炎； LC，肝硬変; High,高ウィルス群； Low,低ウィルス群； ICG-R15, indocyanine green青争注 15分後の停 率； Alb, serum albumin; AST, asparate aminotransferase; ALT, alanine aminotransferase: T.bil, total bilirubin 肝硬変の高ウィルス群 は肝細胞癌の進展度が低い症例が多くみられたが、 肝機能レベルなど他は 2·群間に有意差はなかった。 ウィルスの遺伝子型につい ては低ウィルス群側に 2型の HCVが偏って分布した。 従って HCVの遺伝子 型の違いも考慮に入れる必要があると考え、 遺伝子発現量を比較する際には遺 伝子型別解析も平行して行つた。 CH, Chronic hepatitis; LC, Cirrhosis; High, High virus group; Low, Low virus group; ICG-R15, indocyanine green Blue 15% after withdrawal; Alb, serum albumin; AST, asparate aminotransferase; ALT, alanine aminotransferase: T.bil, total bilirubin In the high virus group with cirrhosis, there were many cases with low progression of hepatocellular carcinoma, but there were no significant differences between the two groups except for liver function level. About virus genotypes In particular, type 2 HCV was unevenly distributed on the low virus group side. Therefore, we considered that it was necessary to take into account the differences in HCV genotypes, and when comparing gene expression levels, we performed gene-type analysis in parallel.
遺伝子発現の違いを肝臓組織に発現する全 mRNAを対象に網羅的に調べる ため、 最新バージョンのオリゴヌクレオチドマイクロアレイを用いた。  The latest version of the oligonucleotide microarray was used to comprehensively examine the total mRNA expressed in liver tissue for differences in gene expression.
方法は、 実施例 2と同様にして行った。  The method was performed in the same manner as in Example 2.
用いた GeneChip(Affymetrix)には、 ヒ ト全遺伝子と思われる約 47000遺伝 子に相当する 54675プローブが張り付いている。 本実施例では、 慢性肝炎の高 ウィルス群を 5例、 低ウィルス群を 5例とし、 また、 新たに肝硬変高ウィルス 群 7例、低ウィルス群 3例を加えた。 各病態で 10枚ずつ合計 20枚のマイクロ アレイを使い、 慢性肝炎では 5:5、 肝硬変では 7:3の 2群間比較を行い、 発現 に差のある遺伝子を同定した。  The GeneChip (Affymetrix) used has 54675 probes corresponding to about 47000 genes that are considered to be all human genes. In the present example, 5 cases of high virus group of chronic hepatitis and 5 cases of low virus group were newly added, and 7 cases of cirrhosis high virus group and 3 cases of low virus group were newly added. A total of 20 microarrays were used, 10 for each disease state, and comparisons were made between two groups, 5: 5 for chronic hepatitis and 7: 3 for cirrhosis, to identify genes with differential expression.
図 9は、 マイクロアレイ解析結果を用いて発現量に差のある遺伝子を求める 方法の概要図である。 実施例 2では高ウィルス群、 低ウィルス群各 4症例で解 析したが、 本実施例では、 各群 5症例にして解析した。  Fig. 9 is a schematic diagram of a method for determining genes with different expression levels using microarray analysis results. In Example 2, analysis was performed in 4 cases each for the high virus group and low virus group, but in this example, analysis was performed for 5 cases in each group.
その結果、 54675プローブのうち、 10枚中 1枚でも発現有りと表記された probeを選び出すと、 29070 probeであった。 この 29070 probe力 月干臓に発 現している遺伝子と考えられる。  As a result, out of 54675 probes, one probe out of 10 was selected to have 29070 probe. This 29070 probe force is thought to be a gene expressed in the moon's debris.
次に 2群間で有意に差のある遺伝子を抽出するため、 3種類のパラメ トッリ ク検定を行った。 2群間で分散が等しいと仮定ずる Student's t testで 1637 probe, 2群間で分散が等しくないと仮定する Welch's t testで 1367 probeが 抽出された。 また少ないレプリケートからできるだけ正確な母分散を見積もる ため、 レプリケートを増やした時に収束するであろ'う標準偏差を予測計算した Cross gene error model適用のノ ラメ トリック検定を行レヽ 982 probeを抽出し た。 この 3種類の検定で重複した 714 probe力 S、 信頼性の高い差のある probe と考えた。 さらに、 この 714 probeのうち、 2群間で発現量が 2倍以上差のあ る probeを求めたところ、 高ウィルス群側に 2倍以上発現の高くなつている probeは 143個で、更に高ウィルス群の全てのアレイに発現有りと表記された、 遺伝子発現が明確なプローブだけにすると、高ウィルス遺伝子として 69 probe となった。 遺伝子として整理すると 66遺伝子となり（表 10)、 これらを高ウイ ルス遺伝子と呼ぶ。 同様の操作により、 低ウィルス遺伝子は 21遺伝子となつ た (表 11)。 これら 93probe、 87遺伝子が、 ウィルス量に関連して発現変化を示 した遺伝子となる。 ' Next, three types of parametric tests were performed to extract genes that were significantly different between the two groups. 1637 probes were extracted by Student's t test assuming that the variance was equal between the two groups, and 1367 probes were extracted by Welch's t test assuming that the variance was not equal between the two groups. In addition, in order to estimate the population variance as accurately as possible from a small number of replicates, a 982 probe was extracted using a cross gene error model applying a cross gene error model that predicted and calculated the standard deviation that would converge when the number of replicates was increased. The 714 probe force S was duplicated in these three types of tests, and the probe had a highly reliable difference. Furthermore, of these 714 probes, the number of probes whose expression levels differed by a factor of 2 or more between the two groups was determined. As a result, there were 143 probes whose expression was more than twice as high on the high virus group side. If only a probe with a clear gene expression, which is marked as being expressed in all arrays of viruses, is identified as a high virus gene, 69 probe It became. When organized as genes, it becomes 66 genes (Table 10), and these are called high virus genes. The same procedure resulted in 21 low viral genes (Table 11). These 93probe and 87 genes are genes that show altered expression in relation to viral load. '
表 1 0〜1 3に、 それぞれ慢性肝炎高ウィルス遺伝子、 慢性肝炎低ウィルス 遺伝子、 肝硬変高ウィルス遺伝子、 肝硬変低ウィルス遺伝子をリス トした。 Tables 10 to 13 list the chronic hepatitis high virus gene, chronic hepatitis low virus gene, cirrhosis high virus gene, and cirrhosis low virus gene, respectively.
慢性肝炎における高ウィルス遺伝子（CHH 66) High viral gene in chronic hepatitis (CHH 66)
SEQ IDSEQ ID
. Accession No. NO Gene symbol Fold change Category3 Overlapb 画一 002122 171 HLA-DQA1 4.17 Accession No. NO Gene symbol Fold change Category 3 Overlap b Standard 002122 171 HLA-DQA1 4.17
丽— 003733 172 OASL 3.87  丽 — 003733 172 OASL 3.87
丽— 005909 173 MAP1B 3.30  丽 — 005909 173 MAP1B 3.30
丽—005656 174 TMPRSS2 3.29  0056—005656 174 TMPRSS2 3.29
NM_002993 175 CXCL6 3.21  NM_002993 175 CXCL6 3.21
丽一 003311 176 PHLDA2 3.09  Junichi 003311 176 PHLDA2 3.09
AI763378 177 EHF 3.07  AI763378 177 EHF 3.07
BC042028 178 2.99  BC042028 178 2.99
BE675995 179 SPEC2 2.99  BE675995 179 SPEC2 2.99
， 雇—020240 180 SPEC2 , Hiring—020240 180 SPEC2
AK025180 181 ― 2.97 B o1 BC089425 182 LOC129607 2.92 A  AK025180 181 ― 2.97 B o1 BC089425 182 LOC129607 2.92 A
NM— 003068 183 SNAI2 2.88 A8  NM—003068 183 SNAI2 2.88 A8
丽— 006403 184 NEDD9 2.84 A9  丽 — 006403 184 NEDD9 2.84 A9
丽ー 001549 185 IFIT3/IFIT4 2.83 A10 ー 001549 185 IFIT3 / IFIT4 2.83 A10
5 丽—002353 186 TACSTD2 2.79 Al l o6 丽— 001001887 187 IFIT1 2.78 A125 丽 —002353 186 TACSTD2 2.79 Al l o6 丽 — 001001887 187 IFIT1 2.78 A12
7 丽— 002354 188 TACSTD1 2.75 A137 丽 — 002354 188 TACSTD1 2.75 A13
8 雇一 006417 189 IFI44 2.72 A ,12423 61 111-4 8 Hired 006417 189 IFI44 2.72 A, 12423 61 111-4
雇— 001565 190 CXCL10 2.61 A15 o 丽— 002303 191 LEPR 2.52 A16 Employment— 001565 190 CXCL10 2.61 A15 o 丽 — 002303 191 LEPR 2.52 A16
1 BF724558 192 2.52 D3 o o o o〇〇0000 000 o 000000 丽一 152878 193 MAFF 2.48 A171 BF724 558 192 2.52 D3 o o o o 000000 000 o 000000 Junichi 152878 193 MAFF 2.48 A17
3 丽— 004030 194 IRF7 2.47 A18 3 丽 — 004030 194 IRF7 2.47 A18
丽— 003749 195 IRS2 2.37 A19 丽 — 003749 195 IRS2 2.37 A19
5 NM_017631 196 FU20035 2.37 A205 NM_017631 196 FU20035 2.37 A20
6 AV699047 197 —- 2.37 El6 AV699047 197 —- 2.37 El
7 AI475680 198 —- 2.34 E27 AI475680 198 —- 2.34 E2
8 AA937109 199 FNBP1 2.32 A218 AA937109 199 FNBP1 2.32 A21
9 AW954199 200 2.32 E39 AW954199 200 2.32 E3
0 AK025967 201 —- 2.31 E40 AK025967 201 —- 2.31 E4
1 画— 016323 202 HERC5 2.28 A22 1 stroke— 016323 202 HERC5 2.28 A22
NM—139266 203 STAT1 2.27 A23  NM—139266 203 STAT1 2.27 A23
NM_002581 204 PAPPA 2.27 A24  NM_002581 204 PAPPA 2.27 A24
丽一 005242 205 F2RL1 2.26 A25 Junichi 005242 205 F2RL1 2.26 A25
5 BX647703 206 ― 2.24 B25 BX647703 206 ― 2.24 B2
6 A腿 1801 207 2.23 E56 A thigh 1801 207 2.23 E5
7 AK001 125 208 2.23 B37 AK001 125 208 2.23 B3
8 AV733347 209 LOC56902 2.22 D4 8 AV733347 209 LOC56902 2.22 D4
NM—004420 210 DUSP8 2.21 A26  NM—004420 210 DUSP8 2.21 A26
AK026659 211 2.21 E6 (表 10の続き). AK026659 211 2.21 E6 (Continued from Table 10).
SEQ ID  SEQ ID
No. Accession No. NO Gene symbol Fold change Categorya Over No. Accession No. NO Gene symbol Fold change Category a Over
41 NM—033260 212 FOXQ1 A27  41 NM—033260 212 FOXQ1 A27
42 丽— 005139 213 ANXA3 A28  42 丽 — 005139 213 ANXA3 A28
43 BE671038 214 LRRC16 C2  43 BE671038 214 LRRC16 C2
44 BF590263 215 CSPG2 E7  44 BF590263 215 CSPG2 E7
45 NM一 018362 216 LIN7C A29  45 NM 018362 216 LIN7C A29
46 NM— 004117 217 FKBP5 2.15 A30  46 NM— 004117 217 FKBP5 2.15 A30
47 丽— 003045 218 SLC7A1 2.13 A31  47 丽 — 003045 218 SLC7A1 2.13 A31
48 AK074440 219 —- 2.13 B4  48 AK074440 219 —- 2.13 B4
49 画—004864 220 GDF15 2.12 A32  49 Stroke—004864 220 GDF15 2.12 A32
50 AV715309 221 —- 2.11 D5  50 AV715309 221 —- 2.11 D5
51 丽— 005257 222 GATA6. 2.10 A33  51 丽 — 005257 222 GATA6. 2.10 A33
52 AK091504 223 SFX3 2.10 A34  52 AK091504 223 SFX3 2.10 A34
53 画一 001122 224 ADFP 2.10 A35  53 Uniform 001122 224 ADFP 2.10 A35
54 匪— 030674 225 SLC38A1 09 A36  54 匪 — 030674 225 SLC38A1 09 A36
55 NM—004867 226 ITM2A 07 A37 〇  55 NM—004867 226 ITM2A 07 A37 ○
56 丽— 001547 227 IFIT2 07 A38  56 丽 — 001547 227 IFIT2 07 A38
57 NM一 004244 228 CD163 03 A39  57 NM I 004244 228 CD163 03 A39
58 NM_032964 229 CCL15 03 A40  58 NM_032964 229 CCL15 03 A40
59 丽— 0161 14 230 ASB1 02 A41  59 丽 — 0161 14 230 ASB1 02 A41
60 AL049435 231 02 D6  60 AL049435 231 02 D6
61 丽ー025074( 232 FRAS1 A42  61 丽 ー 025074 (232 FRAS1 A42
62 U73936 233 JAG1 . A43 〇〇 o o〇 〇〇〇〇 o  62 U73936 233 JAG1 .A43 〇 ○ o o〇 〇〇〇〇 o
63 雇— 015066 234 TRIM35 A44  63 Hire— 015066 234 TRIM35 A44
64 AK000850 235 B5  64 AK000850 235 B5
65 AW297731 236 B6  65 AW297731 236 B6
66 AI806747 237 2 D7  66 AI806747 237 2 D7
. . a：遣.伝干の構造上の probeの位置より、 .5つのカテゴリーに分類した（図 13を参照）。 ' · . · Aは遺伝子の exon配列、 Bは遺伝子 . introriで遽伝子ど同方向の配列、 Cは遺伝子の.. . · intronで遺伝子と反対方向の配列、 Dは遗伝子に瞵接する同方向の配列、 Eは造伝子の'な 5 いところの配列を示す。  . a: Based on the position of the probe on the transmission structure, it was classified into five categories (see Figure 13). '· · · A is the exon sequence of the gene, B is the gene. Introri is the sequence in the same direction as the gene, C is the gene.. · · The sequence is in the opposite direction to the gene in intron, D is the sequence in the gene The contiguous arrangement in the same direction, E, indicates the sequence where the gene is not.
b ：慢性肝炎 8例を対象として行ったオリゴヌクレオチドマイクロアレイ解析で、 抽出 されていた遺伝子。  b: Gene extracted by oligonucleotide microarray analysis in 8 patients with chronic hepatitis.
遺伝子の重複： CHH-2=LCH-3 (表 12) 表 1 1慢性肝炎における低ウィルス遺伝子（CHL 21) Gene duplication: CHH-2 = LCH-3 (Table 12) Table 1 1. Low viral genes in chronic hepatitis (CHL 21)
SEQ ID SEQ ID
No. Accession Wo. Gene Symbol NO Fold change Category— Overlap' No. Accession Wo. Gene Symbol NO Fold change Category—Overlap '
1 AK096893 238 6.03 E1 1 AK096893 238 6.03 E1
2 丽ー 198462 FLJ46154 239 4.14 A1  2 丽 ー 198462 FLJ46154 239 4.14 A1
3 丽— 021614 KCNN2 240 3.65 A2  3 丽 — 021614 KCNN2 240 3.65 A2
4 丽— 000567 CRP 241 3.53 A3  4 丽 — 000567 CRP 241 3.53 A3
5 丽—000450 SELE 242 3.45 A4  5 丽 —000450 SELE 242 3.45 A4
6 BF514098 243 3.44 E2  6 BF514098 243 3.44 E2
7 AI580142 244 3.24 E3  7 AI580 142 244 3.24 E3
245  245
8 N80145 3.23 E4  8 N80145 3.23 E4
9 M27830 246 3.08 E5  9 M27830 246 3.08 E5
10 AW975324 247 2.97 D1  10 AW975324 247 2.97 D1
11 AA018404 248 2.81 E6  11 AA018404 248 2.81 E6
12 AK022897 249 2.53 C1  12 AK022897 249 2.53 C1
13 丽—003633 ENC1 250 2.37 A5  13 丽 —003633 ENC1 250 2.37 A5
14. 丽ー 213589 RAPH1 251 2.34 A6  14. 丽 ー 213589 RAPH1 251 2.34 A6
15 AL049437 252 2.31 E7  15 AL049437 252 2.31 E7
16 丽ー 001187 BAGE 253 2.30 E8  16 丽 ー 001187 BAGE 253 2.30 E8
17 BC022380 FLJ00310 254 2.20 E9  17 BC022380 FLJ00310 254 2.20 E9
18 AI650260 255 2.13 E10  18 AI650 260 255 2.13 E10
19 AK000674 LOC134145 256 2.09 A7  19 AK000674 LOC134145 256 2.09 A7
257  257
20 AB019490 RABGAP1L 2.04 A8  20 AB019490 RABGAP1L 2.04 A8
〇 o 〇〇〇〇〇〇〇〇〇〇〇〇〇〇  〇 o 0000 000 000 000 000 000 000
21 BF511381 HMGA2 258 2.01 C 〇  21 BF511381 HMGA2 258 2.01 C ○
a :遗伝子の構造上の probeの位置より、 5つのカテゴリ一に分類した（図 13を参照）。 A〜Eの意味は表 10と同様である。  a: Classified into five categories according to the probe position on the structure of the gene (see Fig. 13). The meanings of A to E are the same as in Table 10.
b ：慢性肝炎 8例を対象として行つたォリゴヌクレオチドマイクロアレイ解析で、 抽出 されていた遗伝子。 b: A gene extracted by oligonucleotide microarray analysis in 8 cases of chronic hepatitis.
表 12肝硬変における高ウィルス遺伝子（LCH 27) Table 12 High viral genes in cirrhosis (LCH 27)
SEQ ID  SEQ ID
No. Accession No. Gene symooi NO Fold change Categorya No. Accession No. Gene symooi NO Fold change Category a
1 BC020750 SDS 259 8.09 Al  1 BC020750 SDS 259 8.09 Al
2 NM 005101 G1P2 260 3.58 A2  2 NM 005101 G1P2 260 3.58 A2
3 丽ー 003733 OASL 261 3.55 A3  3 丽 ー 003733 OASL 261 3.55 A3
4 雇— 001300 KLF6 262 3.30 A4  4 Hiring — 001 300 KLF6 262 3.30 A4
5 雇— 024786 ZDHHC11 263 3.20 A5  5 Hire—024786 ZDHHC11 263 3.20 A5
6 AK093529 ——― 264 3.08 Bl  6 AK093529 ——— 264 3.08 Bl
7 N55072 ― 265 3.03 B2  7 N55072 ― 265 3.03 B2
8 NM—006887 ZFP36L2 266 2.67 A6  8 NM—006887 ZFP36L2 266 2.67 A6
9 NM一 015675 GADD45B 267 2.45 A7  9 NM 015675 GADD45B 267 2.45 A7
10 BC020765 268 2.45 B3  10 BC020765 268 2.45 B3
11 NM—005542 INSIG1 269 2.36 A8  11 NM—005542 INSIG1 269 2.36 A8
12 画— 032527 ZGPAT 270 2.32 A9  12 strokes — 032527 ZGPAT 270 2.32 A9
13 顧一 002462 MX1 271 2.27 A10  13 Keiichi 002462 MX1 271 2.27 A10
14 NM— 001065 TNFRSF1A 272 2.27 Al l  14 NM— 001065 TNFRSF1A 272 2.27 Al l
15 BF528646 273 2.22 El  15 BF528646 273 2.22 El
16 AW612461 ―— 274 2.10 B4  16 AW612461 ―― 274 2.10 B4
17 NM— 001001924 MTSG1 275 2.07 A12  17 NM— 001001924 MTSG1 275 2.07 A12
18 NM—005243 EWSR1 276 2.06 A13  18 NM—005243 EWSR1 276 2.06 A13
19 NM_018584 CaMKIINalpha 277 2.06 A14  19 NM_018584 CaMKIINalpha 277 2.06 A14
20 NM一 000505 F12 278 2.03 A15  20 NM 000505 F12 278 2.03 A15
21 應— 002616 PERI 279 2.02 A16  21-002616 PERI 279 2.02 A16
22 U62733 CPT1B 280 2.02 A17  22 U62733 CPT1B 280 2.02 A17
23 丽ー 030582 COL18A1 281 2.01 A18  23 丽 ー 030582 COL18A1 281 2.01 A18
24 画—005178 BCL3 282 2.00 A19 24 stroke—005178 BCL3 282 2.00 A19
•25:； ；. AA777349 —二- 283 2.00 B5 • 25 :;;. AA777349 —2-283 2.00 B5
26 BC006435 ― ' '284 2.00 E2' 26 BC006435 ― '' 284 2.00 E2 '
27 NM_019063 EML4 285 2.00 A20 a：遺伝子の構造上の probeの位置より、 5つのカテゴリーに分類した（図 13を参照）。 A〜Eの意味は表 10と同様である。 27 NM_019063 EML4 285 2.00 A20 a: Classified into 5 categories based on the position of the probe on the gene structure (see Figure 13). The meanings of A to E are the same as in Table 10.
遣伝子の重複： LCH-3=CHH-2 (表 10) 表 13肝硬変における低ウィルス遺伝子（LCL 17) Overlapping genes: LCH-3 = CHH-2 (Table 10) Table 13 Low viral genes in cirrhosis (LCL 17)
SEQ ID  SEQ ID
No. Accession No. Gene symbol NO Fold change Category—  No. Accession No. Gene symbol NO Fold change Category—
1 NM— 002432 應 DA 286 2.83 Al  1 NM— 002432 AE DA 286 2.83 Al
DKFZp586G012  DKFZp586G012
2 丽— 016613 3/SLC25A24 287 2.44 A2  2 丽 — 016613 3 / SLC25A24 287 2.44 A2
3 NM_197947 CLECSF12 288 2.33 A3  3 NM_197947 CLECSF12 288 2.33 A3
4 AL833097 289 2.31 El  4 AL833097 289 2.31 El
5 AI741439 SLC8A1 290 2.29 Dl  5 AI741439 SLC8A1 290 2.29 Dl
6 画一 016613 DKFZp434L142 291 2.25 A4  6 Uniform 016613 DKFZp434L142 291 2.25 A4
7 NM— 007115 TNFAIP6 292 2.24 A5  7 NM—007115 TNFAIP6 292 2.24 A5
8 BG231961 293 2.22 E2 '  8 BG231961 293 2.22 E2 '
9 AI799128 294 2.14 E3  9 AI799128 294 2.14 E3
10 BF438173 FST 295 2.11 D2  10 BF438173 FST 295 2.11 D2
11 丽— 003916 AP1S2 296 2.10 A6  11 丽 — 003916 AP1S2 296 2.10 A6
12 AI743207 297 2.07 E4  12 AI743207 297 2.07 E4
13 AI732988 298 2.04 E5  13 AI732988 298 2.04 E5
14 丽一 020117 LARS 299 2.02 A7  14 Junichi 020117 LARS 299 2.02 A7
15 AI743123 300 2.02 Bl  15 AI743123 300 2.02 Bl
16 丽 015173 TBC1D1 301 2.02 A8  16 015 015173 TBC1D1 301 2.02 A8
17 AI949827 NFE2L3 302 2.01 D3  17 AI949827 NFE2L3 302 2.01 D3
a：遺伝子の構造上の probeの位置より、 5つのカテゴリ一に分類した  a: Classified into five categories according to the probe position on the gene structure
(図 13を参照）。 A〜Eの意味は表 10と同様である。 実施例 2の解析結果と比較したところ、高ウィルス遺伝子は 35probeが重複してお り、低ウィルス遺伝子では 19 probeが重複していた。これらの重複した遺伝子は、症 例を増やすことで発現量の差が 2倍にも満たなくなることから、症例を増やすことで、よ り信頼性の高い遺伝子として抽出されたものであると考えられる。なお表 10及び 11の 「Overlap」の欄にこれら重複遺伝子をマークした。  (See Figure 13). The meanings of A to E are the same as in Table 10. When compared with the analysis results of Example 2, 35 probes were duplicated in the high virus gene, and 19 probes were duplicated in the low virus gene. These duplicated genes are considered to have been extracted as more reliable genes by increasing the number of cases because the difference in expression level is less than doubled by increasing the number of cases. . These duplicated genes are marked in the “Overlap” column of Tables 10 and 11.
肝硬変において高ウィルス群 7例、低ウィルス群 3例で,同様の解析をした。その結 果、高ウィルス遺伝子は、 27遺伝子、低ウィルス遺伝子は 17遺伝子が抽出された（図 10)。  The same analysis was performed in 7 cases of high virus group and 3 cases of low virus group in cirrhosis. As a result, 27 genes were extracted from the high virus genes and 17 genes from the low virus genes (Fig. 10).
慢性肝炎と肝硬変からそれぞれ抽出されたウィルス量に関連する遺伝子には、共 通なものがあるかを検討した。その結果、高ウィルス遺伝子に 1遺伝子の重複があつ た（図 11)。他は、重複が認められなかった。 実施例 6 We examined whether there are common genes related to viral load extracted from chronic hepatitis and cirrhosis. As a result, there was one gene duplication in the high virus gene (Fig. 11). Others were not duplicated. Example 6
本実施例では、 抽出された遺伝子の発現パターンが、 ウィルス量の違いを見 分ける遺伝子として有効であるか、 クラスタリング解析を行った。 特にサンプ ルの近縁関係がどのように解析されるかに注目した。  In this example, clustering analysis was performed to determine whether the expression pattern of the extracted gene is effective as a gene that can distinguish the difference in viral load. In particular, we focused on how the relationship between samples is analyzed.
その結果、 慢性肝炎遺伝子 87遺伝子は、 高ウィルス遺伝子 66個と低ウィル ス遺伝子 21個にクラスター分類されており、慢性肝炎 10症例も低ウイルス (L) 群と高ウィルス (H)群とに、きれいにクラスター分類できることが示された (図 1 2 )。 また、 同様に肝硬変遺伝子 44遺伝子で肝硬変 10症例を解析すると 3 例と 7例の 2群のきれいにクラスター分類できた。 しかし、 慢性肝炎遺伝子で 肝硬変症例を解析した場合と肝硬変遺伝子で慢性肝炎症例を解析した場合では、 10症例のクラスター分類は正しく行うことができなかった。従って、 ウィルス 量に関連する遺伝子は慢性肝炎と肝硬変とでは異なることが示された。 ' 実施例 7  As a result, the chronic hepatitis gene 87 gene was clustered into 66 high virus genes and 21 low virus genes, and 10 cases of chronic hepatitis were classified into low virus (L) and high virus (H) groups. It was shown that the cluster can be classified neatly (Fig. 12). Similarly, analysis of 10 cases of cirrhosis with 44 cirrhosis genes revealed a clean cluster classification of 2 groups of 3 and 7 cases. However, the cluster classification of 10 cases could not be performed correctly when the cirrhosis cases were analyzed with the chronic hepatitis gene and when the chronic hepatitis cases were analyzed with the cirrhosis gene. Therefore, the genes related to viral load were shown to be different between chronic hepatitis and cirrhosis. '' Example 7
抽出した遺伝子（表 10〜13)が、ウィルス量関連遺伝子であることを検証するため に、その一部の遺伝子を適宜選択してリアルタイム PCRによる mRNAの発現定量を 行った。  In order to verify that the extracted genes (Tables 10 to 13) are viral load-related genes, some of the genes were selected as appropriate, and mRNA expression quantification was performed by real-time PCR.
表 14に、用いたプライマー配列を示す。 Table 14 shows the primer sequences used.
Figure imgf000045_0001
Figure imgf000045_0001
一 • •  One • •
一  One
• • • •
• •• •
▲▲
▲ ▲
一 • •  One • •
• •
▲ • ▲ •
一 ▲  One ▲
▲ •▲ •
• • • •
a :遺伝子の構造上の probeの位置より、 5つのカテゴリーに分類した (図 13を参照）。 A〜Eの意味は表 10と同様である。 a: Classified into five categories based on the probe position on the gene structure (see Fig. 13). The meanings of A to E are the same as in Table 10.
b :検証できたもの（PO.05)に「攀」、検証できる傾向にあったもの (0.05<P<0.07)に「▲」' をつけた。 なお HCV遺伝子型 lbに依存の場合は 「· ¾」 ， 「▲¾」、 HCV遺伝子型 2 型に依存の場合は 「·2」 ， 「 2」 とした。 なお、 追加して検証できた遺伝子分類を右端 に付記した。 検証し得た抽出遺伝子の評価を表 15に示す。 b: “攀” is added to those that can be verified (PO.05), and “▲” is added to those that tend to be verified (0.05 <P <0.07). In addition, “· ¾” and “▲ ¾” were used when dependent on HCV genotype lb, and “· 2” and “2” were used when dependent on HCV genotype 2. In addition, the gene classification that could be additionally verified was added to the right end. Table 15 shows the evaluation of the extracted genes that could be verified.
表 15リアルタイム RT-PCIUこよる発現解析と 2群間比較 Table 15 Real-time RT-PCIU expression analysis and comparison between two groups
Figure imgf000046_0001
Figure imgf000046_0001
低ウィルス群には HCV 2型が約半数を占める。 慢性肝炎で 9例中 4例、 肝硬変で 6例 中 3例である。 低ウィルス群を HCV遺伝子型別にわけ高ウィルス群との 2群間比較も行 い、 P値を記載した。 遺伝子型依存であるかは、 例数が少ないので、 箱ひげ図に墓づき明 らかのものだけに絞った。 一部の遺伝子は肝硬変高ウィルス群を 9例で解析して ヽる。 高ウイ. /レス群と低ウィルス群での^現量比 を Mann-Whitney.U .testにて 行った。 慢性肝炎と肝硬変のそれぞれで解析できた結果を' P値で示す。 ' P 空欄は未測定であることを示す。 低ウィルス群を HCV遺伝子型別に分け、 2 群間比較も行った。  HCV type 2 accounts for about half of the low virus group. 4 of 9 cases with chronic hepatitis and 3 out of 6 cases with cirrhosis. The low virus group was divided by HCV genotype and compared with the high virus group. Since there are only a few cases of genotype dependence, we narrowed down to only those that were graved on a boxplot. Some genes are analyzed by analyzing the cirrhosis high virus group in 9 cases. The ratio of the current dose in the high / less group and the low virus group was measured by the Mann-Whitney.U.test. The results of analysis for each of chronic hepatitis and cirrhosis are shown as' P values. 'P Blank indicates no measurement. The low virus group was divided by HCV genotype, and a comparison between the two groups was also performed.
検証結果の例を図 1 4 〜 1 6に示す。 左パネルは、 低ウィルス群を遺伝子型 1型と 2型にわけて高ウィルス癌と比較した図である。 右パネルは、 低ウィル ス群全体をまとめて高ウィルス群と比較した図である。図は、箱ひげ図であり、 各群における測定値の分布を示している。 下からひげ下端が 10パーセンタイ ル、 箱下端が 2 5パーセンタイル、 箱の中線が 5 0パーセンタイル、 箱上端が 7 5パーセンタイル、 ひげ上端が 9 0パーセンタイルを表す。 欄外 P値は、 ゥ ィルス量の 2群間比較の結果で Mann- Whitney U検定による。 左パネルは、 低ウィルス群を HCV遺伝子型 1型と 2型に分け、 高ウィルス群との比較を行 つた結果を示す。 Examples of verification results are shown in Figs. The left panel compares the low virus group with high viral cancers divided into genotype 1 and type 2. The right panel summarizes the entire low virus group compared to the high virus group. The figure is a box-and-whisker plot, showing the distribution of measured values in each group. From the bottom, the lower end of the whiskers represents the 10th percentile, the lower end of the box represents the 25th percentile, the middle line of the box represents the 50th percentile, the upper end of the box represents the 75th percentile, and the upper end of the whiskers represents the 90th percentile. The margin P value is The result of comparison between two groups of the amount of virus was based on the Mann- Whitney U test. The left panel shows the results of dividing the low virus group into HCV genotypes 1 and 2 and comparing it to the high virus group.
図 1 4において、 OASLは、 慢性肝炎と肝硬変で共通に見いだされた高ウイ ルス遺伝子である。 この遺伝子は、 慢性肝炎でのみ検証された。 SNAI2も慢性 肝炎高ウィルス遺伝子として検証できた。 いずれの遺伝子も. HCV遺伝子型に よらず、 低ウィルス群では低発現を示した。  In Fig. 14, OASL is a high virus gene commonly found in chronic hepatitis and cirrhosis. This gene was verified only in chronic hepatitis. SNAI2 was also verified as a chronic hepatitis high virus gene. All genes showed low expression in the low virus group regardless of the HCV genotype.
図 1 5は、慢性肝炎高ウィルス（CHH)遺伝子の例である。図 1 5において、 CXCL6は HCV遺伝子型 1 b型低ウィルス群でのみ発現抑制がみられた。  Figure 15 is an example of the chronic hepatitis high virus (CHH) gene. In FIG. 15, CXCL6 expression was suppressed only in the HCV genotype 1b low virus group.
AK025967は、 肝硬変では低ウィルス遺伝子であった。 AK025967 was a low viral gene in cirrhosis.
図 1 6は、 肝硬変低ウィルス （LCL) 遺伝子の例である。 図 1 6において、 両遺伝子共、 肝硬変低ウィルス遺伝子として検証できたが、 慢性肝炎では高ゥ ィルス遺伝子であった。 実施例 8  Figure 16 shows an example of the cirrhosis low virus (LCL) gene. In Figure 16 both genes were verified as cirrhosis low virus genes, but in chronic hepatitis they were high virus genes. Example 8
HCVは約 9.6kbのプラス鎖 RNAを持つ一本鎖 RNAウィルスである。 HCV ゲノムには多くの遺伝子型が存在しており、 現在までに 6種類以上の遺伝子型 に分けられている。 また HCVは直径 50〜60nmの球状のウィルスでコア粒子 をエンベロープが包み込む構造をとつている。  HCV is a single-stranded RNA virus with a positive strand RNA of approximately 9.6 kb. There are many genotypes in the HCV genome and so far it has been divided into more than 6 genotypes. HCV is a spherical virus with a diameter of 50-60 nm and has a structure in which the core particles are enveloped.
HCVは肝細胞に受容体を介して吸着し、細胞質にエンドサイトーシスで侵入 したあと脱殻して RNAを放出する。 この RNAはすぐに mRNAとしてリボゾ ームと結合し約 3000アミノ酸からなる前駆体蛋白質が翻訳される。 小胞体膜 上で翻訳された前駆体タンパク質は、 細胞のシグナラーゼとウィルス自身がコ 一ドする 2種類のプロテアーゼによって 3種の構造蛋白質と 7種の非構造蛋白 質として産生される。合成されたウィルス由来の RNA依存性 RNAポリメラー ゼによって、 ウィルス RNAは +鎖から一鎖が複製され、 さらに +鎖が複製さ れる。 +鎖 RNAはコアタンパク質に取り込まれ、 小胞体内に向かってェンべ ロープをかぶりながら粒子形成が起こる。 ウィルス粒子はゴルジ装置を通って 細胞膜に達し、 肝細胞の外へ放出されると考えられている。 これらの過程で、. ウィルス量を制御する第一ステップとして細胞への吸着と 侵入過程が考えられる。 そこで、 本実施例では、 ウィルス量の違いがウィルス 受容体発現およびエンドサイトーシス関連遺伝子発現と関連するかどうか、 検 討した。 ' HCV adsorbs to hepatocytes via a receptor, enters the cytoplasm by endocytosis, and then sheds and releases RNA. This RNA immediately binds to the ribosome as mRNA and a precursor protein consisting of about 3000 amino acids is translated. Precursor proteins translated on the endoplasmic reticulum membrane are produced as three structural proteins and seven nonstructural proteins by cell signalases and two proteases encoded by the virus itself. The synthesized viral RNA-dependent RNA polymerase causes the viral RNA to replicate one strand from the + strand and then the + strand. The + strand RNA is taken up by the core protein, and particle formation occurs while covering the endoplasmic reticulum with an envelope. Virus particles are thought to pass through the Golgi apparatus, reach the cell membrane, and be released out of the hepatocytes. In these processes, cell adsorption and invasion can be considered as the first step to control the viral load. Therefore, in this example, it was examined whether the difference in viral load was related to the expression of viral receptors and endocytosis-related genes. '
方法は、 .以下の通り行った。 まず奸臓ウィルス量を定量し、 症例の選別を行 つた。 方法を以下に示す。 なお、 total RNA抽出とリアルタイム RT-PCRの方 法は、 実施例 1と同様である。  The method was as follows. First, the amount of visceral virus was quantified, and cases were selected. The method is shown below. The methods for total RNA extraction and real-time RT-PCR are the same as in Example 1.
ウィルス量は、 ウィルス遺伝子の定量で求めた。 材料は、 肝細胞癌症例 50 例の癌部および非癌部組織を用い、なるべく肝細胞癌ステージの低い I， および IIを選択した。  The amount of virus was determined by quantifying the virus gene. As materials, I and II with the lowest hepatocellular carcinoma stage were selected as much as possible, using cancerous and non-cancerous tissues of 50 hepatocellular carcinoma cases.
組織から Total RNAを抽出し、 DNAの混在を'除くため DNase I処理をお こなった。 その後、 ランダムプライマーにより cDNAを合成し、 リアルタイム PCRにて遺伝子定量をおこなった。 HCV RNAの定量は、 HCVの遺伝子配列 が保存されていて、 効率よく PCR増幅ができた、 3'端に近い領域を用いた。 ま た肝臓 mRNAの定量も同様の方法で行った。 HCV RNA量や mHNA量は、 細 胞あたりの量に標準化するために <¾9_Γ ?Λ の定量も行い、 この値で除した値 を各 RNA量とした。  Total RNA was extracted from the tissues and treated with DNase I to remove DNA contamination. Subsequently, cDNA was synthesized with random primers and gene quantification was performed by real-time PCR. For the quantification of HCV RNA, the region close to the 3 'end where the HCV gene sequence was conserved and PCR amplification was efficiently performed was used. The liver mRNA was also quantified by the same method. To standardize the amount of HCV RNA and mHNA to the amount per cell, quantification of <¾9_Γ? Λ was performed, and the value divided by this value was used as the amount of each RNA.
その結果、 ウィルス量の違いは、 非癌部肝組織だけでなく、 癌部でも多様で あることが分かった '(図 1 7 )。 図 1 7は、 肝臓 HCV RNA定量の結果につい て.、縦軸に.癌部の HCV量、.横軸に非癌部の. HCV量をとつてあらわ.レたグラフ である。  As a result, it was found that the difference in viral load varied not only in non-cancerous liver tissues but also in cancerous areas' (Fig. 17). Fig. 17 is a graph showing the results of liver HCV RNA quantification, with the ordinate indicating the amount of HCV in the cancerous part and the horizontal axis indicating the amount of HCV in the non-cancerous part.
実線は非癌部 (NT)に対し癌部 (T)の量が 1の場合を示し、点線は 1ノ 4 (T/NT、 実線の下側） と 4倍 （実線の上側） を表す。 非癌部 HCVは数十から数十万単 位まで幅広く分布している。 これに対し、 癌部 HCVは同量かもしくは低下が 見られ、' 1 / 4以下になる症例が 50症例中 29例 (58%) 存在することが分か つた。癌部では半分以上の症例で、 HCVが感染しにくいか増えにくいと言える。 そこで、 ウィルス量の違いについて、 非癌部同志の違いだけでなく、 癌部同志 での違いについても検討した。 非癌部 ·癌部ともにウィルス量が多い症例が 7 例 （領域 1の症例）、 癌部のウィルス量が非癌部の 100分の 1.以下になる症例 が 7例 （領域 2の症例）、 非癌部 ·癌部ともにウィルス量が少ない症例が 11例 (領域 3 ) について、 ウィルス受容体おょぴその関連遺伝子について発現量を 比較した。 The solid line shows the case where the amount of the cancerous part (T) is 1 with respect to the non-cancerous part (NT), and the dotted line shows 1 node 4 (T / NT, below the solid line) and 4 times (on the solid line). Non-cancerous HCV is widely distributed from tens to hundreds of thousands. On the other hand, HCV in the cancer area was the same amount or decreased, and it was found that 29 cases (58%) out of 50 cases were less than 1/4. In more than half of cases in the cancer area, it can be said that HCV is difficult to infect or increase. Therefore, regarding the difference in viral load, we examined not only differences among non-cancerous members but also differences among cancerous members. 7 cases with high viral load in both non-cancerous and cancerous cases (region 1 cases), and cases where the viral load in the cancerous part is less than 1/100 of non-cancerous part 7 cases (region 2 cases) and 11 cases (region 3) with low viral load in both non-cancerous and cancerous regions (region 3) were compared for the expression level of the virus receptor and related genes.
なお、 図 1 7において、 HCV遺伝子型別については、 「拿」 は lb、 「〇」 は 2a、 「◊」 は 2b、 「麗」 は lb と 2aの重感染を示す。  In Figure 17, for HCV genotypes, “拿” indicates lb, “◯” indicates 2a, “◊” indicates 2b, “Re” indicates lb and 2a co-infection.
受容体のリガンド別に分類すると、HCVエンベロープタンパク質を認識する 受容体として CD81、へパラン硫酸が知られている。へパラン硫酸については、 へパラン硫酸合成に関わる糖転移酵素の 3分子を測定した。 HCVエンベロープ タンパク質の糖鎖を認識する受容体として、 C型レクチンの DC-SIGN, L-SIGN, ASGR及び MBL2があり、 それぞれマンノースやガラク トースなど が認識分子となっている。 HCV粒子が血中の LDL、 HDLと結合し複合体形成 をしているため、 これらの受容体である LDLR及び SCARB1が HCV受容体 として働くことも示唆されている。 また、 SCARB1は E2蛋白を直接認識し ているとも考えられている。  When classified by receptor ligand, CD81 and heparan sulfate are known as receptors that recognize HCV envelope proteins. As for heparan sulfate, three molecules of glycosyltransferase involved in heparan sulfate synthesis were measured. Receptors that recognize the sugar chains of HCV envelope proteins include the C-type lectins DC-SIGN, L-SIGN, ASGR, and MBL2, and mannose and galactose are the recognition molecules. Since HCV particles bind to LDL and HDL in blood to form a complex, it is suggested that these receptors, LDLR and SCARB1, act as HCV receptors. SCARB1 is also thought to recognize E2 protein directly.
そこで、 発現量については、 8個の受容体候補に関連して 11分子の mRNA を測定した。 エンドサイ トーシス関連分子には、 クラスリンタンパク質とアダプタータン パク質がある。 リガンドが受容体に結合すると、 細胞膜内で受容体の近くに存 在しているアダプタータンパク質である AP2が受容体の周りに集まり、それが きっかけとなり受容体とアダプタータンパク質の周りに重鎖 （Clathrin C) 三 量体と軽鎖 (Clathrin A)三量体からなるクラスリンが集まって来る。 クラスリ ンがたくさん集まることによってクラスリン被覆ピッ ト （Clathrin-coated pit) が出来上がり、 ェンドゾームが形成される。  Therefore, for the expression level, 11 molecules of mRNA were measured in relation to 8 receptor candidates. Endocytosis-related molecules include clathrin proteins and adapter proteins. When the ligand binds to the receptor, AP2, an adapter protein that exists in the vicinity of the receptor in the cell membrane, gathers around the receptor, which triggers the heavy chain (Clathrin) C) Trimer and light chain (Clathrin A) The clathrin consisting of trimer comes together. By gathering a lot of clathrin, a clathrin-coated pit is created and a endome is formed.
本実施例では、 上記エンドサイ トーシス関連分子として CLTC， CLTA及ぴ AP2M1の 3分子を測定した。  In this example, three molecules of CLTC, CLTA and AP2M1 were measured as the above-mentioned endocytosis-related molecules.
なお、感染に伴い起こるシグナル伝達の 1つである Toll-like receptor関連の シグナル分子 (TLR3, TICAM1, DDX58)も測定した。 表 1 6に各遺伝子のプライマー配列を示す。 リアルタイム: PCRにて定量し た結果を表 1 7に示す。 表 16 HCV受容体候補およびウィルス侵入関連遗伝子とその PCRプライマ一配列 We also measured Toll-like receptor-related signal molecules (TLR3, TICAM1, DDX58), one of the signal transduction associated with infection. Table 16 shows the primer sequences of each gene. Real-time: Table 17 shows the results of quantification by PCR. Table 16 HCV receptor candidates and viral entry-related genes and their PCR primer sequences
一  One
二 Two
二  Two
一 Ό一 o o  O ichi o o
*： PGRのァニーリングと伸長反応を 65°Cで行一■一■03っ 0M 4 9 -た。 他は 60°Cで行った c *: PGR annealing and extension reaction were performed at 65 ° C. Others were carried out at 60 ° C c
**： PGRに用いた cDNAは 25ngである。 他は 10ngである。  **: The cDNA used for PGR is 25 ng. The other is 10ng.
リアルタイム RT-PCRによる定量結果  Quantitative results by real-time RT-PCR
Nontumor Tumor  Nontumor tumor
2群間比較（11:14) ~~ HCV量との相関 2群間比較 * HCV*∑の顯 Comparison between 2 groups (11:14) ~~ Correlation with HCV level Comparison between 2 groups * HCV * ∑ 顯
Gene Gene
Spearman Mann- Whitney U test Spearman Spearman Mann- Whitney U test Spearman
Mann- Whitney U test - p P Low:High (l l:7)Low:ffigh (7:7) P PMann- Whitney U test-p P Low: High (l l: 7) Low: ffigh (7: 7) P P
CD81 0.6222 -0.113 0.5796 0.079 0.3379 -0.137 0.503CD81 0.6222 -0.113 0.5796 0.079 0.3379 -0.137 0.503
LDLR 0.4767 0.132 0.5193 0.9639 0.1417 -0.002 0.9938LDLR 0.4767 0.132 0.5193 0.9639 0.1417 -0.002 0.9938
SCARB1 0.547 -0.067 0.743 0.6184 -0.041 0.8426SCARB1 0.547 -0.067 0.743 0.6184 -0.041 0.8426
ASGR2 0.8695 0.057 0.7803 0.4414 -0.079 0.6984ASGR2 0.8695 0.057 0.7803 0.4414 -0.079 0.6984
ASGR1 0.7426 . 0.012 0.9519 0.497 0.21 0.303ASGR1 0.7426 .0.012 0.9519 0.497 0.21 0.303
EXT1 0.9128 -0.053 0.7948 0.7513 0.6547 0.084 0.6812EXT1 0.9128 -0.053 0.7948 0.7513 0.6547 0.084 0.6812
ΕΧΓ2 0.3811. 0.167 0.4135 0.1891 0.848 -0.133 0.5155ΕΧΓ2 0.3811.0.167 0.4135 0.1891 0.848 -0.133 0.5155
EXTL2 . 0.6222 0.186 0.3618 0.2215. 0.2248 -0.178 0.3831EXTL2.0.6222 0.186 0.3618 0.2215.0.2248 -0.178 0.3831
CD209 0.6614 0.145 0.4763 0.8919. 0.034 0.8686CD209 0.6614 0.145 0.4763 0.8919. 0.034 0.8686
CLEC4M 0.9563 -0.125 0.539 0.47 CLEC4M 0.9563 -0.125 0.539 0.47
MBL2 0.8267 . 0.049 0.8094 0.6547 0.259 0.2043 MBL2 0.8267 .0.049 0.8094 0.6547 0.259 0.2043
CLTC 0.5112 0.129 0.5267 ¾.00¾¾；:: ! S0j l81 -0.482 0.0181CLTC 0.5112 0.129 0.5267 ¾.00¾¾; :: ! S0j l81 -0.482 0.0181
CLTA 0.2503 0.227 0.2663 0.0007 0.0476 -0,675 0.0009CLTA 0.2503 0.227 0.2663 0.0007 0.0476 -0,675 0.0009
AP2M1 0.1711 0.358 0.0791 0.0043 '0 .扉瞧1 ¾ -0.536 0.0086AP2M1 0.1711 0.358 0.0791 0.0043 '0 .Door 瞧 1 ¾ -0.536 0.0086
TLR3 0.4115 0.204 0.2338 0.1604 6.1797 0.176 0.3048TLR3 0.4115 0.204 0.2338 0.1604 6.1797 0.176 0.3048
TICAM1 0.547 0.112 0.5135 0.8919 0.7494 0.008 0.9618TICAM1 0.547 0.112 0.5135 0.8919 0.7494 0.008 0.9618
DDX58 0.7426 0.036 0.8331 0.2976 0.9491 -0.049 0.7731DDX58 0.7426 0.036 0.8331 0.2976 0.9491 -0.049 0.7731
* 11:7, 非癌部低ウィルス症例の癌部 11例と非癌部髙ウィルス '癌部高ウィルス症例の 癌部 7例との比較 * 11: 7, 11 non-cancerous low-virus cases of cancer and 11 non-cancerous gonorrhea virus' cancerous high-virus cases of cancer 7
7:7, 非癌部高ウィルス ·癌部低ウィルス症例の癌部 7例と非癌部高ウィルス ·癌部高 ウィルス症例の癌部 7例との比較 表 1 7の癌部 （Tumor) の 「2群間比較」 の欄において、 網掛けをした部分 の結果を図 1 8及び図 1 9に示す。 図 1 8及び図 1 9は、 有意差のでた受容体 関連遺伝子の結果である。 7: 7, Comparison of 7 non-cancerous high-virus cancer cases in low-cancerous cancer cases and 7 non-cancerous high-virus cancer cases in 7 cancerous cases Figures 18 and 19 show the results of the shaded areas in the “Comparison between two groups” column of Tumor in Table 17. Figures 18 and 19 show the results for receptor-related genes with significant differences.
なお、 表 1 7における CLEC4Mは、 L-SIGNと同義である。  In Table 17, CLEC4M is synonymous with L-SIGN.
非癌部のウィルス量から、低ウィルス群 （NL)ll例、 高ウィルス群 (NH) 1 4 例に分け、 NHについては、さらに癌部で依然として高ウィルスである（NHTH) 7例と低ウィルスとなる (NHTL) 7例とに分けて、 比較した。  Based on the amount of virus in the non-cancerous part, it was divided into low virus group (NL) ll cases and high virus group (NH) 1 4 cases. (NHTL) It was divided into 7 cases and compared.
なお、 2群間比較における背景因子の比較を、 表 1 8に示す。  Table 18 shows a comparison of background factors between the two groups.
表 ウィルス量の違いにおける背 a因子の比較 Table Comparison of dorsal a factor in difference in viral load
StaQsbca 非癌部 癌部 非癌部 Kウィルス症例の癌部 StaQsbca Non-cancerous part Cancerous part Non-cancerous part Cancerous part of K virus case
Variable Variable
1 analysis  1 analysis
Low (n=ll) High(n=14) Low (n=ll) High fn=7) Low (n=7) High(n=7) Low (n = ll) High (n = 14) Low (n = ll) High fn = 7) Low (n = 7) High (n = 7)
Age MW 64.4±2,0 67.1±1.S 64.4±2.0 66.7±2.7 67.6±2.5 66.7±2.7Age MW 64.4 ± 2,0 67.1 ± 1.S 64.4 ± 2.0 66.7 ± 2.7 67.6 ± 2.5 66.7 ± 2.7
Sex (M:F) FE 9:2 8:6 9:2 Sex (M: F) FE 9: 2 8: 6 9: 2
Tumor stage ( I :Π :ΠΙΑ) FE 3:6:2 : 7:0 3:6:2  Tumor stage (I: Π: ΠΙΑ) FE 3: 6: 2: 7: 0 3: 6: 2
Non tumor (LC:CH) FE 3:7 6:8 3:7  Non tumor (LC: CH) FE 3: 7 6: 8 3: 7
ICG 15.9±3.7 22.3±4.3 15.9±3.7  ICG 15.9 ± 3.7 22.3 ± 4.3 15.9 ± 3.7
Alb MW 4.02±0.16 3.96±0.12 4.02 0.16 4.07±0.16 3.84±0.1 4.07±0.16  Alb MW 4.02 ± 0.16 3.96 ± 0.12 4.02 0.16 4.07 ± 0.16 3.84 ± 0.1 4.07 ± 0.16
o  o
AST MW 36.6±5.0 63.0±12.3 0.0427 36.6±5.0 73.6±23.6 •o 52.4±8.1 73.6±23.6 AST MW 36.6 ± 5.0 63.0 ± 12.3 0.0427 36.6 ± 5.0 73.6 ± 23.6 o 52.4 ± 8.1 73.6 ± 23.6
ALT MW 34.2±7.8 54.5±9.12 34.2±7.8 62.0±17.2 47.0±7.2 62.0 17.2ALT MW 34.2 ± 7.8 54.5 ± 9.12 34.2 ± 7.8 62.0 ± 17.2 47.0 ± 7.2 62.0 17.2
T.bil MW 0.61±0.07 0.90±0.12 0.61±0.07 0.99±0.19 . 0.81±0.17 0.99±0.19T.bil MW 0.61 ± 0.07 0.90 ± 0.12 0.61 ± 0.07 0.99 ± 0.19 .0.81 ± 0.17 0.99 ± 0.19
AFP MW 356±185 206±95.3 356±185 79.5±33.2 332±182 79.5±33.2AFP MW 356 ± 185 206 ± 95.3 356 ± 185 79.5 ± 33.2 332 ± 182 79.5 ± 33.2
PIV MW 568±356 216±148 (7:11) 568±356 20.5±10.8 (7:7) 55.9 m cn±372 20.5±10.8 0.037(4:7)PIV MW 568 ± 356 216 ± 148 (7:11) 568 ± 356 20.5 ± 10.8 (7: 7) 55.9 m cn ± 372 20.5 ± 10.8 0.037 (4: 7)
HCV genotype (lb:lb+2a:2a:2b) FE 6:0:2:2 11:3:0:0 0.0455 6:0:2:2 6:1:0:0 5:2 6:1 HCV genotype (lb: lb + 2a: 2a: 2b) FE 6: 0: 2: 2 11: 3: 0: 0 0.0455 6: 0: 2: 2 6: 1: 0: 0 5: 2 6: 1
HCVRNA MW 80.mi 112000±30700 <0.0001 18±14 31600±5900 0.0002 330 70 31600±5900 0.002 HCVRNA MW 80.mi 112000 ± 30700 <0.0001 18 ± 14 31600 ± 5900 0.0002 330 70 31600 ± 5900 0.002
Count,Average土 standard error,' ICG, Indocyanine green静脈注射後 15分後の血中 停滞率 ； Alb, serum albmin; AST, aspartate aminotransferase! AL^T, alanin aminotransferase； T.bill, total bilirubin; AFP, alphafetoprotein; PIV, proteins induced by vitamin K absence; HCVRNA, normalized by 18S rRNA; MW, Mann-Whitney's U test; FE, Fis er'sexact probability test 以上の結果より、 次のことが分かった。 Count, Average soil standard error, 'ICG, Indocyanine green 15 minutes after intravenous injection; Alb, serum albmin; AST, aspartate aminotransferase! AL ^ T, alanin aminotransferase; T.bill, total bilirubin; AFP, PIV, protein induced by vitamin K absence; HCVRNA, normalized by 18S rRNA; MW, Mann-Whitney's U test; FE, Fisher's sexact probability test
(1) 非癌部でゥィルス量に相関する受容体関連遺伝子はなかった。  (1) There was no receptor-related gene that correlated with viral load in non-cancerous areas.
(2) 癌部ではウィルス量に相関する受容体遺伝子 （L-SIGN) が 1つみつかつ た。 ウィルス量が多い癌では L-SIGNが高発現していた。  (2) In the cancer department, there was one receptor gene (L-SIGN) that correlated with viral load. L-SIGN was highly expressed in cancers with high viral load.
(3) 癌部でウィルス量に逆相関する遺伝子が 3つ （エンドサイトーシス関連 遺伝子の 3つ） がみつかった。 ウィルスが少ない癌ではエンドサイト シス関 連分子が高発現していた。  (3) Three genes (3 of endocytosis-related genes) that were inversely correlated with viral load were found in the cancer site. In cancers with few viruses, endocytosis-related molecules were highly expressed.
(4) 非癌部が高ウィルスであるにも拘わらず、 癌部ではウィルス低下が見ら れる症例には上記の変化に加え、 SCARBl, ASGR及び DC-SIGNの低下が顕 著であった。 (4) In addition to the above changes, SCARBl, ASGR, and DC-SIGN decreased in cases where the virus decreased in the non-cancerous part even though the non-cancerous part was high virus. It was a book.
以上より、これら受容体関連遺伝子において、非癌.部のウィルス量には関連 ないが、 癌部ウィルス量には関連する分子が存在した。 非癌部のウィルス量は これら受容体関連遺伝子の発現量とは無関係なところで制御されている。 しか し癌細胞のウィルス量はこれら受容体およぴ関連分子の発現量に依存しており、 1つにウィルスェン 1、リ一ステップでウィルス量が制御されていると考えられ た。  Based on the above, in these receptor-related genes, there were molecules that were not related to the viral load of the non-cancerous part but related to the viral load of the cancerous part. The amount of virus in the non-cancerous part is controlled in a manner independent of the expression level of these receptor-related genes. However, the viral load of cancer cells depends on the expression levels of these receptors and related molecules, and it is thought that the viral load is controlled by virus 1 in one step and by one step.
また癌細胞におけるウィルス低下がエンドサイ ト一シス亢進と関連する可能 性が示唆された。 特に L-SIGNの発現抑制、 CLTCの発現促進は、 癌部低ウイ ルス群に顕著であり、 非癌部レベルと比べても明らかな特徴である。 従って、 L-SIGNの発現抑制、 CLTCの発現促進をすることが、 HCV感染防御に有効な' 戦略を示すものと思われる。 産業上の利用可能性  In addition, it was suggested that virus reduction in cancer cells may be associated with increased endocytosis. In particular, the suppression of L-SIGN expression and the promotion of CLTC expression are prominent in the low-virus cancer group, and are clear features compared to the non-cancerous level. Therefore, suppressing L-SIGN expression and promoting CLTC expression may represent an effective strategy for protecting against HCV infection. Industrial applicability
本発明により、高ウィルス群で発現亢進している遺伝子をスクリーニングするこ とが可能となる。 そして、 この高ウィルス遺伝子の中には、 HCVが増殖するの に有利に働くと予想される因子が存在する可能性があるため、 高ウィルス遺伝 子の発現を抑制することによつ.て HCVの増殖を抑制することができる。  According to the present invention, it is possible to screen a gene whose expression is increased in a high virus group. This high viral gene may contain factors that are expected to work favorably for HCV growth, so it is possible to suppress the expression of high viral genes. Can be inhibited.
また、 本発明により、 低ウィルス群で発現亢進している遺伝子をスクリーニン グする:ととが可能となる。 そして、 この低ウィルス遺伝子に.は、 HCVが増殖し にくい環 ^作りに関与する ¾伝子が存在する可能性がある。 すなわち、 低ウイ ルス遺伝子の発現を亢進することによって HCV の増殖を抑制することができ る。  Further, according to the present invention, it is possible to screen a gene whose expression is enhanced in the low virus group. This low viral gene may have a ¾ gene that is involved in creating a circle in which HCV is difficult to grow. In other words, HCV proliferation can be suppressed by enhancing the expression of the low virus gene.
すなわち、 本発明の方法を用いて見出された遺伝子の発現を調節することに よって、 HCVの発現量の調節を行うことができるため、 本発明によって HCV の治療剤、 治療方法の開発を行うことができる。 配列表フリーテキスト  That is, since the expression level of HCV can be regulated by regulating the expression of the gene found using the method of the present invention, the therapeutic agent and treatment method for HCV are developed according to the present invention. be able to. Sequence listing free text
配列番号 1〜 5 3 ：プライマー 配列番号 303〜404 ：プライマー Sequence number 1-5 3: Primer Sequence number 303-404: Primer

Claims

請求 の 範 囲 The scope of the claims
1 . 多量の HCVを含む高ウィルス群組織において発現が亢進する遺伝子をスクリ 5 一二ングする方法であって、 1. A method of screening a gene whose expression is enhanced in a high virus group tissue containing a large amount of HCV, comprising:
(a)肝組織由来 cDNA 50ng当りの HCVのコピー数を 18S rRNA定量値で割 つた値が 300 unit以下の肝組織を低ウィルス群組織として選択し、 当該値が 30000unit以上の肝組織を高ウィルス群組織として選択するステップ、  (a) Liver tissue-derived liver tissue with a value of 300 units or less divided by the 18S rRNA quantitative value per 50 ng of HCV copy per 50 ng of cDNA is selected as a low virus group tissue, and liver tissue with a value of 30000 units or more is high virus. Selecting as a group organization,
(b) 前記低ゥィルス群組織および高ウイルス群組織における遺伝子の発現量 10 を測定するステップ、 並びに、  (b) measuring the expression level 10 of the gene in the low virus group tissue and the high virus group tissue, and
(c) 前記低ウィルス群組織よりも高ウィルス群組織において発現が亢進する遺 伝子を選択するステップ  (c) selecting a gene whose expression is enhanced in a high virus group tissue than in the low virus group tissue
を含む前記方法。  Including said method.
2 . 少量の HCVを含む低ウィルス群組織において発現が亢進する遺伝子をスクリ 15 一二ングする方法であって、  2. A method for screening a gene whose expression is increased in a low virus group tissue containing a small amount of HCV, comprising:
(a) 肝組織由来 cDNA 50ng当りの HCVのコピー数を 18S rRNA定量値で割 つた値が 300 unit以下の肝組織を低ウィルス群組織として選択し、 当該値が 30000unit以上の肝組織を高ウィルス群組織として選択するステップ、  (a) Liver tissue derived from liver tissue cDNA 50 ng divided by 18S rRNA quantitative value, liver tissue with a value of 300 units or less is selected as a low virus group tissue, and liver tissue with a value of 30000 units or more as a high virus Selecting as a group organization,
(b) 前記低ゥィルス群組織および高ウイルス群組織における遺伝子の発現量 20. .を測定するステップ、 並びに、  (b) measuring the gene expression level 20. in the low virus group tissue and the high virus group tissue, and
(c) 前記高ウィルス群組 ょりも低ウィルス群組織において発現が亢進する遺 伝子を選択するステップ  (c) selecting a gene whose expression is enhanced in the high virus group tissue as well as in the low virus group tissue
を含む前記方法。  Including said method.
3 . 遺伝子の発現量の測定がマイクロアレイおよび Zまたはリアルタイム PCRを 25 用いることを特徴とする、 請求項 1または 2記載の方法。  3. The method according to claim 1 or 2, wherein the gene expression level is measured using microarray and Z or real-time PCR.
4 . 高ウィルス群組織における遺伝子の発現量が、低ウィルス群における遺伝子の 発現量に対して 2倍以上発現亢進することを特徴とする、 請求項 1記載の方法。 4. The method according to claim 1, wherein the expression level of the gene in the high virus group tissue is more than twice as high as the expression level of the gene in the low virus group.
5 . 低ウィルス群組織における遺伝子の発現量が、高ウィルス群における遺伝子の 発現量に対して' 2倍以上発現亢進することを特徴 :とする、 請求項 2記載の方法。 . 5 low expression level of the gene in the virus group tissue, characterized in that 'enhancing least twice expression relative to the expression level of genes in high virus groups: that method of claim 2 wherein.
.低ウィルス群組織又は高ウィルス群組織を、 さらに慢性肝炎由来のもの及ぴ肝 硬変由来のものに分類することを特徴とする請求項 1〜 5のいずれか 1項に記 載の方法。The method according to any one of claims 1 to 5, wherein the low virus group tissue or the high virus group tissue is further classified into those derived from chronic hepatitis and those derived from cirrhosis.
. 以下の (a)〜(d)の遺伝子から選ばれる少なくとも 1つの遺伝子を含有する、 ゥ ィルス量に関連する病態の検査薬。 A test agent for pathological conditions related to the amount of virus, comprising at least one gene selected from the following genes (a) to (d):
(a)配列番号 5 4〜1 3 1で表されるいずれかの塩基配列を含む遺伝子 (a) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 5 4 to 1 3 1
(b) 配列番号 5 4〜1 3 1で表されるいずれかの塩基配列に相補的な塩基配 列にストリンジヱントな条件下でハイブリダィズし、 かつ、高ウィルス群におい て発現が亢進する遺伝子 (b) A gene that hybridizes under stringent conditions to a base sequence complementary to any one of the base sequences represented by SEQ ID NOs: 5 4 to 1 31 and has enhanced expression in the high virus group
(c)配列番号 1 3 2〜 1 7 0で表される！/、ずれかの塩基配列を含む遺伝子 (c) represented by SEQ ID NOs: 1 3 2 to 1 70! /, A gene containing any base sequence
(d) 配列番号 1 3 2〜1 7 0で表されるいずれかの塩基配列に相補的な塩基 配列にストリンジェントな条件下でハイブリダイズし、 かつ、低ウィルス群にお レ、て発現が亢進する遺伝子(d) It hybridizes under stringent conditions to a base sequence complementary to any of the base sequences represented by SEQ ID NOs: 1 3 2 to 1700, and is expressed in a low virus group. Enhanced gene
. 以下の (a)〜(！ 1)の遺伝子から選ばれる少なくとも 1つの遺伝子を含有する、 ゥ ィルス量に関連する病態の検查薬。 1. A diagnostic agent for a disease state related to the amount of virus, comprising at least one gene selected from the genes (a) to (! 1) below.
(a)配列番号 1 7 1〜2 3 7で表されるいずれかの塩基配列を含む遺伝子 (a) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 1 7 1 to 2 3 7
(b) .配列番号 1 7 1〜2 3 7で表されるいずれかの塩基配列に相補的な塩基 配列にストリンジェントな条件下でハイブリダィズし、 かつ、慢性肝炎の高ウイ ルス群において発現が亢進する遺伝子 (b) Hybridizes under stringent conditions to a base sequence complementary to any one of the base sequences represented by SEQ ID NOs: 1 1 to 2 37 and is expressed in a group of chronic hepatitis viruses Enhanced gene
(c)配列番号 2 3 8〜 2 5 8で表されるいずれかの塩基配列を含む遺伝子 (c) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 2 3 8 to 2 5 8
(d) 配列番号 2 3 8〜2 5 8で表されるいずれかの塩基配列に相補的な塩基 配列にストリンジェントな条件下でハイブリダィズし、 かつ、慢性肝炎の低ウイ ルス群において発現が亢進する遺伝子 (d) Hybridizes under stringent conditions to a base sequence complementary to any of the base sequences represented by SEQ ID NOs: 2 3 8 to 2 5 8 and enhances expression in the low virus group of chronic hepatitis Genes
(e)配列番号 2 5 9〜2 8 5で表されるいずれかの塩基配列を含む遺伝子 (£)配列番号 2 5 9〜 2 8 5で表されるいずれかの塩基配列に相補的な塩基配 列にストリンジヱントな条件下でハイブリダィズし、 かつ、肝硬変の高ウィルス 群において発現が亢進する遺伝子  (e) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 2 5 9 to 2 85 (£) a base complementary to any one of the nucleotide sequences represented by SEQ ID NOs: 2 5 9 to 2 85 A gene that hybridizes under stringent conditions to the sequence and is highly expressed in the high virus population with cirrhosis
(g)配列番号 2 8 6〜3 0 2で表されるいずれかの塩基配列を含む遺伝子 (g) a gene comprising any one of the nucleotide sequences represented by SEQ ID NOs: 2 8 6 to 30 2
(h) 配列番号 2 8 6〜3 0 2で表されるいずれかの塩基配列に相補的な塩基 配列にストリンジヱントな条件下でハイブリダィズし、 かつ、 肝硬変の低ウィル ス群において発現が亢進する遺伝子(h) a base complementary to any one of the base sequences represented by SEQ ID NOs: 2 8 6 to 30 2 A gene that hybridizes under stringent conditions to the sequence and is highly expressed in the low virus group of cirrhosis
. マイクロアレイの形態である、 請求項 7又は 8に記載の検査薬。 The test agent according to claim 7 or 8, which is in the form of a microarray.
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