KR20150081633A - Biomarker for predicting and diagnosing drug-induced liver injury - Google Patents

Abstract

The present invention relates to a biomarker for predicting and diagnosing a drug-induced liver injury. The biomarker of the present invention means genes, which are sensitively reactive to a drug-induced liver injury, selected based on transcriptomics. The biomarker of the present invention may be usefully used in the prediction and diagnosis of a drug-induced liver injury and in particular, may be usefully used in the analysis of the type of the liver injury. In addition, the biomarker of the present invention has the advantage of diagnosing and predicting a toxicity caused by a drug promptly and accurately at an early stage, and may be able to prevent side effects caused by the toxicity caused by a drug at an early stage.

Description

≪ Desc / Clms Page number 1 > Biomarker for predicting and diagnosing drug-induced liver injury &

The present invention relates to a biomarker for predicting and diagnosing liver damage caused by a drug, and more particularly, to a biomarker for predicting and diagnosing liver damage caused by exposure to a drug, Markers.

Hepatic toxicity is defined as liver damage, such as hepatic dysfunction caused by exposure to drugs or other non-infectious agents. Hepatotoxicity can also be defined as drug-induced hepatitis, including not only hepatic damage caused by drugs or other chemicals, but also certain types of side effects induced by other drugs. Although the term for such hepatotoxicity varies, one of the most commonly used terms is DILI (drug-induced liver injury). DILI is known to be a major cause of acute liver failure in liver transplant recipients and is a major concern for clinicians and pharmacists, and it is very common for drugs already approved to withdraw from the market due to drug-induced liver damage. According to the US acute hepatic dysfunction study group, drugs such as acetaminophen account for more than 50% of the main causes of acute liver failure. Rats exposed to liver toxic agents such as acetaminophen or carbon tetrachloride have been reported to undergo changes in the expression pattern of various mRNAs. However, the diagnosis of DILI is still very difficult, and the precise mechanism of DILI is unknown.

 DILI can be classified into several types according to its clinical characteristics. According to the lesion of liver injury, DILI is classified into hepatocyte type (mainly alanine aminotransferase ALT elevation), bile type (mainly alkaline phosphatase ALP elevation) Or a mixture thereof. In DILI, in many cases, one type of the above type appears predominant, but there are many cases in which these types appear in combination. In the meantime, adverse reactions in the liver can be categorized into those that cause hepatic toxicity in essence and those that induce liver-specific toxicity. Essentially, in cases where liver toxicity is caused, the original compound itself or its metabolites , It is possible to find a correlation between the drug and the adverse reaction caused thereby, and it is possible to predict the hepatotoxicity through such a correlation without any species specificity, It is possible to restore liver toxicity. However, in the case of constitutionally specific liver toxicity, the correlation between the drug and the reaction caused by it is very rare, and an experimental animal model that can explain the mechanism has not yet been established. In addition, since the constitution-specific hepatotoxicity occurs in one out of 1,000 to 100,000 patients administered with the drug, it is not easy to predict liver toxicity in advance before marketing the drug. However, such hepatotoxicity sometimes causes very serious symptoms to the patient, but it may also threaten the life of the patient, so predicting constitution-specific liver toxicity is also considered to be one of the important challenges for clinicians and pharmaceutical companies.

DILI is generally not readily observed in clinical trials with thousands of participants, and since the drug is market approved and numerous drugs are administered to a large number of patients, rare toxic effects are often observed, There is a need to develop a method to detect and judge the possibility of rapid and sensitive liver toxicity at an early stage. The genetic predisposition to induce DILI may be due to differences in pharmacokinetics and pharmacodynamic pathways. If elevated ALT is observed in many patients receiving the drug, it is possible to predict that the drug is a drug that can cause DILI, but liver function tests are generally performed to diagnose rather than predict liver damage. Genomic biomarkers, on the other hand, can be used to predict liver damage in individuals, and recent federal genome-level studies have identified a human leukocyte antigen allele as a potent genetic factor that can predict liver damage when exposed to certain drugs There is one. However, although these federations provide a basis for understanding hepatic toxicity mechanisms, they have not yet developed them for use in hepatic toxicity testing.

Korean Patent Laid-Open No. 10-2009-7007160

Therefore, the present inventors have conducted a total of five treatments of a rat animal model in which pyrazinamide (PZA), ranitidine (RAN), enalapril (ENA), carbamazepine (CBZ) and chlorpromazine (CPZ) And identifying novel biomarkers capable of early diagnosis and prediction of drug liver toxicity by confirming changes in transcript and protein expression in rat liver tissue.

It is therefore an object of the present invention to provide a biomarker for predicting and diagnosing liver damage which can diagnose or predict hepatotoxicity due to exposure of a drug.

It is another object of the present invention to provide a method for predicting and diagnosing liver damage due to exposure of a drug using the biomarker according to the present invention.

In order to achieve the above object, the present invention provides a method for predicting and diagnosing liver damage caused by a drug comprising any one selected from the group consisting of 31 genes described in the following table, mRNA expressed from the gene, and protein expressed from the gene The present invention provides a biomarker composition.

In one embodiment of the present invention, the biomarker is a hepatocyte type in which the level of alanine aminotransferase (ALT) is increased; Bile type with increased levels of alkaline phosphatase (ALP); And a mixed type of liver damage type in which the levels of alanine aminotransferase (ALT) and alkaline phosphatase (ALP) are both increasing.

In one embodiment of the present invention, the hepatocellular liver injury may be induced by pyrazinamide (PZA).

In one embodiment of the present invention, the bile duct injury may be induced by chlorpromazine (CPZ).

In one embodiment of the present invention the mixed liver injury is induced by a drug selected from the group consisting of ranitidine (RAN), enalapril (ENA) and carbamazepine (CBZ) Lt; / RTI >

In one embodiment of the present invention, the biomarker may be for predicting or diagnosing liver damage through a change in the expression level of the gene described in the above table in liver tissue.

In one embodiment of the present invention, when the hepatocyte type is hepatocellular hepatocellular carcinoma, the genes listed in Table 1, 1 to 13, 16 to 21, 26 to 28, 30 and 31 MRNA or protein expression of genes No. 14, No. 15, No. 22, No. 25, and No. 29 may be increased compared to the normal control sample and mRNA or protein expression of genes No. 14, No. 15, No. 22, No. 25, and No. 29 may be decreased as compared with the normal control sample.

In one embodiment of the present invention, when the hepatocyte damage type is bile-type hepatocellular damage, one of the genes listed in the above Tables 1 to 13, 17, 19 to 21, 26, 27, 29 The expression of mRNA or protein of genes No. 14 to 16, 18, 22 to 25, 28 and 30 is increased compared to that of the normal control sample, Lt; / RTI >

In one embodiment of the present invention, when the liver damage type is mixed liver damage, mRNAs of genes 1 to 13, 17 to 21, 26 to 28 and 31 of the genes listed in the above table Or protein expression is increased compared to the normal control sample and mRNA or protein expression of genes 14 to 16, 22 to 25, 29 and 30 may be decreased compared to the normal control sample.

Also, the present invention provides a method for detecting a disease caused by drug-induced liver damage (DILI), comprising the steps of: (a) measuring the amount of mRNA or protein expression of 31 genes listed in the above table from a biological sample suspected of having liver damage (DILI) And (b) measuring the mRNA or protein expression level of the gene from the normal control sample and comparing the measured mRNA or protein expression level with the measurement result of the step (a), thereby providing information for predicting and diagnosing liver damage .

In one embodiment of the present invention, the biological sample may be an isolated liver tissue from a subject.

In one embodiment of the present invention, the measurement is performed using reverse transcriptase-polymerase chain reaction, real time-polymerase chain reaction, Western blot, northern blot, ELISA an immunosorbent assay, radioimmunoassay (RIA), radioimmunodiffusion, and immunoprecipitation assay.

The biomarker according to the present invention is a biomarker selected by transcription from a gene sensitive to liver damage caused by a drug. It is a marker specifically detected in liver tissue when liver damage is induced by exposure to a drug, Markers may be useful for predicting and diagnosing liver damage by drugs, and may be useful in analyzing the type of liver damage. In addition, the biomarker according to the present invention has an advantage of quickly and quickly diagnosing and predicting the toxicity caused by a drug, so that the side effect caused by the toxicity due to the drug can be prevented early.

Figure 1 shows an autonomous hierarchical cluster analysis of liver liver tissue following DILI-induced drug administration. The horizontal represents the liver tissue profile after drug administration and the vertical represents the probe measurement. (A) Three hepatotoxicity types can be distinguished through a secondary diagram of 7,725 genes that pass the minimum criteria on the second day of drug administration. (B) After 3 days of drug administration, 7,769 genes showing the difference between the drug-treated group and the control group are not distinguished by a specific hepatotoxicity type. (C) After 10 days of drug treatment, 7,161 genes whose expression is changed by the drug treatment group are not distinguished by a specific hepatotoxicity type.
FIG. 2 shows the results of 31 high-accuracy genotypes that can discriminate three types of hepatotoxicity in rat liver tissue two days after administration of DILI-induced drug using the Prototype Matching classification algorithm. (A) Dendritic clusters by DILI-inducing drugs show four different classes according to the expression pattern of 31 genes (B) As a result of Principal Component Analysis (PCA) of differentially expressed genes, Hepatocyte type is yellow, mixed type is blue, and bile type is red. (C) Accuracy was tested according to the LOOCV method, and all 106 samples were classified into four different classes. A total of 2311 genetic elements were predicted as a molecular classifier in the expression pattern changes. Of these, 31 genes were selected as the smallest molecular markers with 100% accuracy.
FIG. 3 shows the results of classifying genes whose expression levels vary according to the type of DILI (hepatocyte (A), mixed (B), and bile (C)) by function using DAVID. The bar graph represents the approximate p-value.
FIG. 4 is a result of analyzing the gene whose expression level was changed according to the type of DILI (hepatic cell type (A), mixed type (B) and bile type (C)) by GSEA and confirming that the gene set is a common reaction path in KEGG PATHWAY IN CANCER .
FIG. 5 is a GSEA result of analysis of molecular mechanisms involving genes whose expression levels vary according to the type of DILI. (A) In the hepatocyte type, the genes associated with REACTOME SLC-MEDIATED TRANSMEMBRANE TRANSPORT increased the most and the genes associated with the KEGG MAPK signaling pathway showed the most decreased expression. (B), the genes associated with REACTOME SIGNALING BY NGF were the most frequently expressed, and the genes related to REACTOME CLASS I MHC MEDIATED ANTIGEN PROCESSING PRESENTATION showed the greatest decrease in expression. (C) In the bile type, the genes associated with REACTOME CLASS I MHC MEDIATED ANTIGEN PROCESSING PRESENTATION showed the most decrease in expression.
Figure 6 is a molecular network analysis result characteristic of the type of DILI. The ConceptGen Network Graph for each DILI type indicates that there is a molecular network change associated with metabolism, inflammation, cell junction, actin cytoskeleton, MAPK signaling, and translation. (A) Hepatocyte type is associated with metabolism, inflammation, cell junction (B) Hybrid type metabolism, inflammation, actin cytoskeleton, MAPK signaling (C)
FIG. 7 is an integrated analysis of expression patterns of genes and proteins upon treatment of DILI-induced drugs in rat liver tissue. (A) 205 markers were selected that were up-regulated or down-regulated after 2 days of DILI-induced drug administration in rat liver tissue by proteomic analysis. The row shows the profile of the liver tissue after treatment with the indicated toxicant, the heat represents the probe measurement, and the saturation represents the difference in expression level. (B) Of the 205 outliers proteins, 135 proteins were consistent with the genetic component of the transcryptomic data set. In total count tests, 115 protein data sets and 100 gene expression data sets were able to distinguish three DILI types with high accuracy in each validation analysis. Of these, 84 genes and proteins were commonly down-regulated at both the protein and gene levels, as shown in the Venn diagram. (C) Protein data set validity analysis to evaluate the typing ability of these 84 markers showed 94.12% accuracy. (D) gene expression data set validity analysis showed an accuracy of 99.06%.

Hereinafter, the present invention will be described in detail.

The present invention is characterized by providing a biomarker capable of predicting and diagnosing liver damage induced by a drug in an early stage.

In the present invention, the present inventors evaluated a specific gene expression associated with DILI (drug-induced liver injury) using a rat model. To do this, rats were administered a representative drug known to induce DILI in humans, and transcript changes in rat liver tissue were analyzed. In the present invention, pyrazinamide (PZA, 150 to 1500 mg / kg), ranitidine (RAN, 209.5 to 2095 mg / kg) is the representative drug for inducing DILI in three types (hepatocyte, kg), enalapril (ENA, 148.65 to 1486.5 mg / kg), carbamazepine (CBZ, 97.85 to 978.5 mg / kg) and chlorpromazine kg) were used. Of these drugs, pyrazinamide, which is used for the treatment and treatment of tuberculosis patients, has been used to induce hepatocyte DILI. On the other hand, ranitidine, which is used for the treatment of peptic ulcer disease and gastroesophageal reflux disease by inhibiting gastric acid production with histamine H2-receptor antagonist, was used to induce mixed DILI. In addition, carbamazepine, an angiotensin converting enzyme (ACE) inhibitor used in the treatment of hypertension and chronic heart failure, enalapril, epilepsy and bipolar disorder, was also used to induce mixed DILI. On the other hand, the treatment of hiccups and vomiting and the treatment of schizophrenia were used to induce bile-type DILI.

The changes in overall genome expression in rat liver tissues administered with the above drugs were confirmed by microarray transcript analysis and as a result, it was confirmed that the expression patterns of the molecules in liver tissues were different according to DILI type . Thus, by observing these large-scale gene expression changes, it was confirmed that the type of DILI can be distinguished sensitively at the initial stage of exposure to the drug.

The present inventors have identified molecular markers capable of distinguishing three different types of DILI from multiple analyzes based on gene expression patterns in DILI, and these markers have been identified in early stages of drug exposure in rat liver tissue It was confirmed that the three types of DILI can be distinguished by 100% accuracy at the stage (two days later).

number Probe ID Gene name Accession number One 4010736 Cap1 NM_022383.2 2 1400040 LOC683474 XM_001061932.1 3 610021 RGD1563702 XR_008437.1 4 670711 Crp NM_017096.2 5 1570497 Canx NM_172008.1 6 6520142 Larp1 XM_220446.4 7 6290347 Mtpn NM_024374.3 8 3780400 Xylb NM_001033704.1 9 5670390 Abi1 NM_024397.1 10 4050619 Iraq1 XM_001057078.1 11 6130152 Tln1 XM_001069865.1 12 5050494 Ociad1 NM_001013874.1 13 6860035 Acox3 NM_053339.1 14 1980576 Mst1 NM_024352.1 15 5570397 Bri3 XM_001071637.1 16 4150400 LOC501637 XM_577034.1 17 460551 Shc1 NM_053517.1 18 2570195 LOC313340 XM_233139.3 19 2640687 Eif4ebp2 NM_001033069.1 20 1770025 Nr2f2 NM_080778.1 21 4120671 Vegfa NM_031836.1 22 4760040 RGD1563705 XM_576474.2 23 3940593 Rasa1 NM_013135.1 24 2370390 RGD1566244 XR_007720.1 25 5130041 Polr2g NM_053948.2 26 6770156 Brd4 XM_001077931.1 27 4590133 Pum1 XM_342928.3 28 3390484 Pnrc1 NM_173322.1 29 630736 Gtl3 NM_001037978.1 30 7000563 LOC501548 XM_576950.1 31 2480402 Pdlim5 NM_053326.1

Accordingly, the present invention can provide a biomarker for predicting and diagnosing liver damage comprising one or more genes selected from the 31 genes listed in the above table or proteins expressed from the genes.

The increase or decrease in the biomarker gene expression amount in the biological sample can be detected by confirming the amount of the mRNA, and the increase or decrease in the expression amount of the protein expressed from the biomarker gene can be detected by confirming the amount of the protein. The process of separating the mRNA or protein from the biological sample can be performed using known processes, and the amount can be measured by various methods known to those skilled in the art.

In the present invention, the "biological sample" refers to a sample obtained from a living body different from the normal control group by the expression level or protein level of the gene by a drug, and preferably includes liver tissue.

The term "biomarker" as used herein refers to a polypeptide or nucleic acid (eg, mRNA), lipid, glycolipid, glycoprotein, sugar (monosaccharide, disaccharide, oligosaccharide, etc.) ), And the like. The biomarker provided by the present invention may be the above-mentioned 31 genes or the proteins in which the expression levels of the genes are decreased or increased in the liver tissue of the subject administered with the drug as compared to normal liver tissues.

In the present invention, the biomarker can predict and diagnose liver damage caused by a drug by means of drugs including, but not limited to, pyrazinamide (PZA), ranitidine (RAN), enalapril , ENA), carbamazepine (CBZ), and chlorpromazine (CPZ).

Meanwhile, the present invention can provide a composition for predicting and diagnosing liver damage (DILI) by a drug comprising a substance that measures the expression level of a marker gene or the level of a protein expressed from the gene according to the present invention.

In the present invention, the expression level of the gene refers to the level of the mRNA at which the gene is expressed, that is, the amount of the mRNA. As the substance capable of measuring the level, a primer or a probe specific for the gene . In the present invention, a primer or a probe specific to the gene may be a primer or a probe capable of specifically amplifying the entirety of the 31 genes or a specific region of the gene, and the primer or probe may be prepared by a method known in the art You can design through.

In the present invention, the term " primer " refers to a single-stranded DNA strand that can act as a starting point for template-directed DNA synthesis under suitable conditions (i.e., four different nucleoside triphosphates and polymerase enzymes) Means an oligonucleotide. The appropriate length of the primer may vary depending on various factors, such as temperature and use of the primer. In addition, the sequence of the primer does not need to have a sequence completely complementary to a partial sequence of the template, and it is sufficient that the primer has sufficient complementarity within a range capable of hybridizing with the template and acting as a primer. Therefore, the primer of the present invention does not need to have a perfectly complementary sequence to the nucleotide sequence of the gene that is the template, and it is sufficient that the primer has sufficient complementarity within the range capable of hybridizing with the gene sequence to perform the primer action. In addition, it is preferable that the primer according to the present invention can be used for gene amplification reaction.

The amplification reaction refers to a reaction for amplifying a nucleic acid molecule. The amplification reactions of these genes are well known in the art, and examples thereof include polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR) (LCR), electron mediated amplification (TMA), nucleic acid sequencing substrate amplification (NASBA), and the like.

In the present invention, the term " probe " means a linear oligomer of natural or modified monomers or linkages, including deoxyribonucleotides and ribonucleotides, capable of specifically hybridizing to a target nucleotide sequence, Or artificially synthesized. The probes according to the present invention may be single-stranded, preferably oligodeoxyribonucleotides. Probes of the invention can include natural dNMPs (i.e., dAMP, dGMP, dCMP and dTMP), nucleotide analogs or derivatives. In addition, the probe of the present invention may also include a ribonucleotide.

In the present invention, the " measurement of the level of the protein " is a process of confirming the expression level of the biomarker protein whose expression is increased or decreased by the drug exposure in the biological sample. Preferably, The amount of protein is determined using an antibody.

The term " antibody " refers to a specific protein molecule directed against an antigenic site. For purposes of the present invention, an antibody is an antibody capable of specifically binding to the proteins expressed from the 31 marker genes of the present invention , And includes all antibodies such as polyclonal antibodies, monoclonal antibodies and recombinant antibodies. Such an antibody can be used as long as it is produced by a person having ordinary skill in the art using known techniques.

The present invention also provides a kit for predicting and diagnosing liver damage by a drug comprising a biomarker for predicting and diagnosing liver damage by the drug or a composition for predicting and diagnosing liver damage caused by the drug.

The kit for predicting and diagnosing liver damage by the drug of the present invention may include a primer, a probe or an antibody capable of measuring the level of expression of the marker gene or the amount of the protein, and the definitions thereof are as described above.

If the kit for predicting and diagnosing liver damage by the drug of the present invention is applied to a PCR amplification process, the kit of the present invention may optionally include a reagent necessary for PCR amplification, such as a buffer, a DNA polymerase (for example, Thermus aquaticus ), Thermus thermophilus (Tth), Thermus filiformis, Thermis flavus, Thermococcus literalis or Pyrococcus furiosus (Pfu)), DNA polymerase joins and dNTPs, and the kit of the invention may be immunized When applied to the assay, the kit of the present invention may optionally comprise a secondary antibody and a labeling substrate. Further, the kit according to the present invention may be manufactured from a number of separate packaging or compartments containing the reagent components described above.

The present invention also provides a microarray for predicting and diagnosing liver damage caused by a drug comprising the biomarker. In the microarray of the present invention, a primer, a probe or an antibody capable of measuring the expression level of the marker protein or the gene encoding the marker protein is used as a hybridizable array element and immobilized on a substrate . Preferred substrates may include, for example, membranes, filters, chips, slides, wafers, fibers, magnetic beads or nonmagnetic beads, gels, tubing, plates, polymers, microparticles and capillaries, as suitable rigid or semi-rigid supports have. The hybridization array elements are arranged and immobilized on the substrate, and such immobilization can be performed by chemical bonding methods or covalent bonding methods such as UV. For example, the hybridization array element may be bonded to a glass surface modified to include an epoxy compound or an aldehyde group, and may also be bound by UV on a polylysine coating surface. In addition, the hybridization array element can be coupled to the substrate via a linker (e.g., ethylene glycol oligomer and diamine).

On the other hand, when the sample to be applied to the microarray of the present invention is a nucleic acid, it may be labeled and hybridized with an array element on a microarray. Hybridization conditions may vary, and detection and analysis of hybridization degree may be variously performed depending on the labeled substance.

In addition, the present invention can provide a method for predicting and diagnosing liver damage caused by a drug through a method of measuring the expression level of the marker gene or the expression protein level thereof, preferably the method comprising: (a) Measuring the amount of mRNA or protein expression of the 31 genes from biological specimens suspected of having liver injury (DILI); And (b) measuring the mRNA or protein expression level of the gene from the normal control sample and comparing the mRNA or protein expression level with the measurement result of step (a).

The above method of measuring the expression level of the gene or the amount of the protein can be carried out using a known technique including a known process of separating mRNA or protein from a biological sample. The measurement of the expression level of the gene is preferably to measure the level of mRNA, and the method of measuring the level of mRNA can be performed through various methods known in the art, for example, a reverse transcription polymerase chain reaction but are not limited to, reversetranscriptase-polymerase chain reaction, real time-polymerase chain reaction, northern blot, RNase protection assay, DNA chip and the like. In this case, the marker protein and the specific antibody in the biological sample form a conjugate, that is, an antigen-antibody complex, and the amount of the antigen-antibody complex formed is measured using a detection label can be quantitatively measured through the magnitude of the signal of the detection label. Such detection labels can be selected from the group consisting of enzymes, minerals, ligands, emitters, microparticles, redox molecules and radioisotopes, but is not limited thereto. As an assay method for measuring the protein level, for example, Western blot, enzyme linked immunosorbent assay (ELISA), radioimmunoassay (RIA), radioimmunodiffusion, immunoprecipitation assay, But are not limited to, Ouchteroni immunodiffusion, rocket immunoelectrophoresis, tissue immuno staining, complement fixation assay, FACS, protein chip, and the like.

Therefore, the present invention can confirm the amount of mRNA expression or the amount of protein in the control group, the amount of mRNA expression or the amount of protein when exposed to the drug, and compare the degree of expression with the control group, Can predict and diagnose liver damage.

Hereinafter, the present invention will be described in more detail by way of examples. It will be apparent to those skilled in the art that these embodiments are merely illustrative of the present invention and that the scope of the present invention is not limited to these embodiments.

≪ Example 1 >

Animal Models and Drug Disposal

(RAN, CAS number, 66357-35-5; Sigma R101, Sigma R101, Sigma P7136), pyrazinamide (PZA, CAS number, 98-96-4; Sigma P7136), and ranitidine ), Enalapril (ENA, CAS number, 75847-73-3; Sigma E6888), carbamazepine (CBZ, CAS number, 298-46-4; Sigma C4024), and chlorpromazine These drugs were purchased from Sigma-Aldrich (St. Louis, Mo., USA) and prepared according to the manufacturer's instructions.

Seven-week-old Sprague-Dawley male rats purchased from Orient (Korea, Seoul) were used as experimental animals. Twelve hours / night for 12 hours / night at 23 ℃ and 60 ± 10% And water and feed were freely accessible. During the study period, all animals were observed at least once a day for signs of obvious toxicity or clinical symptoms. Animal experiments were conducted in compliance with the guidelines of the IACIC (Institutional Animal Care and Use Committee), and animals were randomly divided into treatment groups and control groups.

The dosage of each drug was determined by administering 5% (small amount), 10% (weight), and 50% (overdose) thereof, with reference to the published LD ₅₀ of each drug. In each of the three animals, (150, 300, 1500 mg / kg), RAN (209.5, 419, 2095 mg / kg), ENA (148.65, 297.3, 1486.5 mg / kg), CBZ (97.85, 195.7, 978.5 mg / kg) dissolved in corn oil / kg), CPZ (7.1, 14.2, 71 mg / kg) was orally administered once. Rats were sacrificed on days 2, 3, and 10 after administration, liver tissue and serum samples were collected, and RNA and protein were extracted therefrom and further experiments were conducted.

< Example  2>

General Toxicity Evaluation of Animal Models by Drug Administration

<2-1> Observation of weight and organ weight changes

The present inventors examined whether weight change in the body weight and the liver, which are indexes of general toxicity judgment, in the animal model of Example 1 exposed to the drug was observed.

As a result, as shown in Table 2 below, weight change and weight change of the organ (liver) were not detected in the animal models 2, 3, and 10 days after administration of the drug as compared with the normal control group.

<2-2> Biochemical analysis of blood

On the other hand, whole blood of rats was collected 2, 3, and 10 days after drug administration in order to analyze the blood of the animal model exposed to the drug clinically and biochemically. Serum levels of drug-induced AST, ALT, total bilirubin (TBIL) and ALB were measured using standard blood biochemical techniques.

As a result, as shown in Table 3 below, the amount of albumin tended to decrease slightly on the second day, but it was found that there was no significant difference from the control group in general.

These results indicate that it is not easy to diagnose and predict DILI early through a general toxicity assessment. The present inventors have found that, by detecting a sensitive change in intracellular level by a drug, We decided to study the molecular diagnostic method.

&Lt; Example 3 >

Identification of molecular markers through microarrays

The present inventors performed microarray analysis to identify molecular markers showing specific expression pattern that can diagnose and predict DILI early using a rat model.

<3-1> Total RNA Extraction

Two days after administration of the drug, total RNA was isolated from rat liver tissue samples using TRI reagent (Molecular Research Center, Cincinnati, OH) according to the manufacturer's protocol. To briefly describe this process, tissue was homogenized with 1 ml of TRI reagent after freezing it with liquid nitrogen. The mixture was incubated at room temperature for 5 minutes, mixed with 200 μl of chloroform, vigorously mixed, and further incubated at room temperature for 3 hours. The sample was then centrifuged at 14,000 rpm for 20 minutes, the aqueous layer transferred to a new tube, the same volume of isopropanol added, and then left on ice for 30 minutes. Then, the sample was centrifuged at 14,000 rpm for 15 minutes, and the RNA precipitate was washed with 75% ethanol and dissolved in RNA-free distilled water. The quality of the extracted RNA was determined by using an Experion bioanalyzer (Bio-Rad Laboratories, Hercules, Calif.) Using RNA StdSens Chips and the RNA concentration was determined by ND-1000 ™ spectrophotometer (Thermo Scientific, Wilmington, DE, USA) . Only samples with at least 28S / 18S ratio of> 1.6 were selected and used for further experiments.

<3-2> Labeled  all cRNA  Manufacturing Hybridization

Biotin-labeled cRNA was prepared using 1.5 쨉 g of the total RNA extracted in the above Example <3-1>. Double-stranded cDNA was synthesized using Illumina® TotalPrep RNA Amplification Kit (Ambion). Biotin-UTP-labeled antisense RNA was transferred in vitro using Ambion's Kit. All labeling procedures were carried out using Ambion standard methods. Size and quantification of the products before and after cRNA purification were verified with the Experion ^™ StdSens RNA Analysis Kit (Bio-Rad, Hercules, CA). After purification, the product was diluted with a hybridization buffer to a concentration of 240 ng / mu l and hybridized at 58 DEG C for 18 hours. Illumina Sentrix RatRef-12 24K Expression Array BeadChip (Illumina, San Diego, Calif.) Was used for liver transcript profile of rats. Experiments to hybridize, wash and scan labeled cRNA to BeadChip were presented in Illumina BeadStation 500 × manual . The array signal was developed by reacting with streptavidin-Cy3 for 10 minutes, and the BeadChip was washed and centrifuged at 275 x g for 4 minutes. The array was scanned using Illumina BeadArray reader, a confocal type imaging system with 532 (Cy3) nm laser illumination. Data from each sample was extracted with Genome Studio software (Illumina) using default parameters.

<3-3> Analysis of data

Illumina Sentrix RatRef-12 24K Expression Array Bead Chip Expression data were analyzed using GenPlex software 3.0 (Istech Inc., Korea). Spots representing P-call (Detection P value <0.1) were removed for initial data filtering and only filtered data was used for further analysis. Quntile normalization was used for data standardization and hierarchical clusters on log ratio were analyzed using Cluster TreeView 2.3 (Stanford Univ, USA).

Among the 22,517 genetic elements, the genetic component that passed the minimum filtering criterion (Detection P value <0.1) was the entire transfer between the rats. On the other hand, as can be seen from FIG. 1, the hierarchical cluster analysis showed different expression patterns over time. On the second day of administration, 7,725 gene elements selected from the minimum filtering criteria were analyzed by hierarchical cluster analysis (Control group, PZA (hepatocyte type), CPZ (bile type), CBZ, RAN, ENA (mixed type)). However, since the characteristic clusters could not be distinguished through hierarchical cluster analysis on the 3rd and 10th days of administration, the present inventors determined that it is appropriate to predict and diagnose liver toxicity through the gene expression pattern by the administration of the drug on the second day of administration .

< Example  4>

Identification of molecular markers that characterize expression patterns by drugs

On the second day of drug administration through autonomous hierarchical clusters, the most definite molecular characteristics that can distinguish hepatocyte, hybrid, and bile were found, and at this time, the present inventors found that these hepatocellular, mixed, I wanted to check the set. One Way ANOVA (P <0.0001) was used as a multi-classification algorithm combined with the Bonferroni multiple test calibration method to search for as many genes as possible to distinguish these types. As a result, 2,311 outlier genes classified into four groups, representing three different DILI types, were selected according to the expression profile. To determine the minimum number of genes that can accurately distinguish these DILI types with 100% accuracy, a total computation test (genetic sorting algorithm, BSS / WSS (the ratio of between group to within- group sums of squares and Prototype Matching classification algorithm], and confirmed the minimum Aurus lia gene using Leave-One-Out Cross Validation (LOOCV). Thirty-one genes were selected as the minimum genes that can distinguish DILI from other types of DILI-induced genes.

The 31 genes are as shown in Table 4 below, and the hierarchical clusters of these 31 gene expressions were identified by their expression profiles to correctly distinguish three DILI types on the dendrogram (Fig. 2A). In addition, principal component analysis (PCA), another technique for analyzing datasets, has shown that four classes are clearly distinguished on spatial arrangements (see FIG. 2B). These 31 outliers genes were further validated by predictive reliability analysis and were classified into 100 random splits by LOOCV. As a result of summarizing the frequency of each classification using the high accuracy classification, each classification showed 100% prediction (see FIG. 2C).

On the other hand, outlier genes having the above-described accuracy could not be selected in the experimental group on the 3rd and 10th day of administration (data not shown).

< Example  5>

Indicating a characteristic expression pattern by the drug Molecular pathway  analysis

In order to investigate the biological relevance of distinctive molecular characteristics according to the type of DILI, the present inventors used a combination of Welch's T-test (P <0.05) and 1.5-fold change cut-off, . We have uploaded a characteristic expression pattern according to the invention in the DAVID web-based bioinformatics platform (http://david.abcc.ncifcrf.gov/) to search for molecular pathways associated with the expression pattern according to the DILI type . Database for Annotation, Visualization and Integrated Discovery (DAVID) 6.7 Bioinformatics Resources is a database of various molecular mechanisms, such as the KEGG and Biocarta pathway databases. The database can be used to determine the classes of functionally related genes and determine genes involved in the same mechanism. That is, in the present invention, DAVID can identify the pathway of genes differentially expressed according to drug treatment. Therefore, the present inventors used the DAVID Functional Annotation Chart and Functional Annotation clustering tools to study the biological mechanisms associated with genes differentially expressed in rats exposed to three types of hepatotoxic inducing drugs, fild enrichment, p- value, and bonferroni corrected p-value. Using the combination of Welch's T-test (P <0.05) and a 1.5-fold change cut-off, the present inventors examined characteristic expression patterns according to DILI types. As a result, 1,145 out- The lyer gene was found to be associated with 11 major pathways when observed at a threshold of gene count = 10 and ease score = 0.1. The major signaling pathways were Tight junction, PPAR signaling pathway, Leukocyte transendothelial migration, Arrhythmogenic right ventricular cardiomyopathy (ARVC), Adherence junction, MAPK signaling pathway, Neurotrophin signaling pathway, Colon cancer, Focal adhesion, Toll-like receptor signaling pathway, associated with lysosomes (see Figure 3A). In addition, 1,439 outliers with altered expression pattern in the mixed type have been shown to be involved in drug metabolism, steroid hormone deficiency, foreign body metabolism by cytochrome P450, retinol metabolism, PPAR signaling pathway, spliceosome, ), Tight junction, Ribosome, Leukocyte transendothelial migration, Endocytosis, Adipocytokine signaling pathway, MAPK signaling pathway, Neurotrophin signaling pathway, Lysosome, Cancer-related pathway , Prostate cancer, pancreatic cancer, arachidonic acid metabolism, colon cancer, non-small cell lung cancer, and chronic myelogenous leukemia (see FIG. 3B). On the other hand, 1,130 outlier genes whose expression patterns were changed in the bile form were found to be related to six pathways of ribosome, spliceosome, drug metabolism, small cell lung cancer, cancer-related pathways, and endocytosis (see FIG.

The present inventors then conducted Gene Set Enrichment Analysis (GSEA) for specific gene sets down-regulated by DILI associated with other types of DILI in MsigDB (The Molecular Signatures Database) to investigate the mechanism by which each type of DILI works. Respectively. In addition, we conducted network analysis using ConceptGen (http://conceptgen.ncibi.org) to confirm the interactions of these molecular mechanisms.

As a result, the following four pathways as shown in Table 5 were confirmed, and it was found that there was a particularly particularly high correlation with paths related to KEGG PATHWAYS IN CANCER (see FIG. 4). On the other hand, in the pathway related to KEGG PATHWAYS IN CANCER, the down-regulated genes were different according to each DILI type, and distinct molecular changes according to each type appeared.

In addition, the present inventors examined the signal transmission pathways involved in up-regulated or down-regulated genes according to the type of each DILI through MsigDB. As a result, results as shown in Table 6 and FIG. 5 were obtained.

To further observe the molecular mechanism associated with DILI, the present inventors used a ConceptGen mapping tool to study the correlation of various molecular pathways with the characteristic molecular profile of each DILI-inducing drug.

As a result, as shown in FIG. 6, the ConceptGenNetwork Graph according to each DILI type showed metabolic, inflammation, cell junction, actin cytoskeleton, MAPK signal transduction and translation process as a characteristic molecular mechanism by DILI.

Among them, drugs (PZA) that cause hepatocyte-type damage are metabolism, inflammation, cell junction pathway (see FIG. 6A), drugs that cause mixed damage (CBZ, RAN, ENA) The signaling pathway (see FIG. 6B) and the bile duct damaging drug (CPZ) were closely associated with metabolic inflammation and translation pathways (see FIG. 6C). This network analysis is consistent with the results of the above GSEA analysis, and it was confirmed that the signal transduction pathway related to metabolism and inflammation is a mechanism that is commonly involved with DILI-related molecular mechanisms.

< Example  6>

Transcryptomics and  Biology with proteomics Marker  Sympathy

<6-1> Rat  Protein extraction from liver tissue

Rat liver tissues were treated with 7 M urea, 2 M thiourea containing 4% (w / v) 3- [(3-cholamidopropyl) dimethylammonio] -1-propanesulfonate (CHAPS), 1% (w / v) dithiothreitol (v / v) pharmalyte and 1 mM benzamidine and homogenized using a motor-driven homogenizer (PowerGen 125, Fisher Scientific). Proteins were extracted by vortexing at room temperature for 1 hour. After centrifugation at 15,000 x g for 1 hour at 15 &lt; 0 &gt; C, the insoluble material was removed and only the soluble portion was used for 2D gel electrophoresis. Protein loading was normalized by Bradford assay.

<6-2> Through 2D gel electrophoresis Expression level  Identified Protein Changes

For the proteomic analysis, the present inventors collected 6 extracted proteins. IPG dried membranes were equilibrated for 12-16 hours using 2M thiourea containing 7M urea and 2% 3 - [(3-cholamidopropyl) dimethylammonio] -1-propanesulfonate (CHAPS), 1% dithiothreitol (DTT), 1% pharmalyte And 200 μg of sample was loaded. Isoelectric focusing (IEF) was performed at 20 ° C using a Multiphor II electrophoresis unit and an EPS 3500 XL power supply (Amersham Biosciences, UK) according to the manufacturer's protocol. Prior to 2Dization, the membranes were first incubated with 1% DTT in 2.5% iodoacetamide in an equilibration buffer (50 mM Tris-Cl, pH 6.8 containing 6 M urea, 2% SDS and 30% glycerol) . The membranes were then placed in SDS OAGE gels (20 x 24 cm, 10-16%) and subjected to SDS-PAGE according to the manufacturer's protocol using the Hoefer DALT 2D system (Amersham Biosciences, UK). The 2D gel was electrophoresed at 1,700 Vh at 20 ° C and then silver stained. However, the sensitization step using fixed and glutaraldehyde was omitted. Quantitative analysis of digital images was performed using PDQuest version 7.0 software (Bio-Rad, Hercules, Calif.) According to the manufacturer's method. The amount of each spot was normalized to the intensity of the total effective spot. Protein spots were selected to show significant changes in expression when the expression level was more than 2 times that of the control sample. Then, we analyzed by hierarchical clustering and multi - classification test for further integrated analysis.

<6-3> Transcryptomics and  Integrated analysis of proteomics

The PANTHER (Protein ANalysis THrough Evolutionary Relationships) Classification System was used to identify the molecular functions and biological pathways common to transcriptomics and proteomics observed in the above example.

Through the integrated analysis of transcryptom and proteome, the present inventors were able to identify gene and protein characteristics capable of distinguishing the three DILI types. First, the inventors of the present invention, after 2 days from the treatment of the DILI-induced drug, We identified 205 proteins whose protein expression was greatly changed. The autonomic hierarchical clusters of these altered expression patterns showed a consistent pattern (see FIG. 7A), a genetic component of a total of 135 protein elements that matched the transcriptomic data set, We identified 115 protein elements capable of differentiating each DILI type by proteome expression pattern. In addition, the present inventors confirmed that 100 gene elements among 135 liver DILI proteomes can distinguish DILI types with an accuracy of 99.07% (data not shown). On the other hand, the present inventors identified 84 genes and protein elements in which expression levels were commonly changed in both transcriptomics and proteomics. These 84 genes and protein elements can distinguish DILI types with very high accuracy and we have identified the final 60 genes and protein elements after dispensing redundant elements, as shown in Table 7 below. The analysis of the molecular functions, biological processes and cellular components of these 60 elements using PANTHER, a pathway discovery tool, was found to be closely related to catalytic activity, metabolism and intracellular pathways.

DILI: Drug induced liver injury.

Claims (12)

A biomarker composition for predicting and diagnosing liver damage by a drug comprising any one selected from the group consisting of 31 genes listed in the following table, mRNA expressed from the gene, and proteins expressed from the gene.

The method according to claim 1,
The biomarker may be a hepatocyte type in which the level of alanine aminotransferase (ALT) is increased; Bile type with increased levels of alkaline phosphatase (ALP); And a mixed type liver damage type in which the levels of alanine aminotransferase (ALT) and alkaline phosphatase (ALP) are both increased. 3. The method of claim 2,
Wherein the hepatocellular liver damage is induced by pyrazinamide (PZA). The biomarker composition for predicting and diagnosing liver damage by a drug. 3. The method of claim 2,
Wherein the bile duct injury is induced by chlorpromazine (CPZ). The biomarker composition for predicting and diagnosing liver damage by a drug. 3. The method of claim 2,
Wherein the mixed liver injury is induced by a drug selected from the group consisting of ranitidine (RAN), enalapril (ENA) and carbamazepine (CBZ). A biomarker composition for predicting and diagnosing cancer. The method according to claim 1,
The biomarker is a biomarker composition for predicting and diagnosing liver damage caused by a drug, characterized in that liver damage is predicted or diagnosed through a change in the expression level of the gene listed in the table 1 in liver tissue. 3. The method of claim 2,
MRNA or protein expression of genes 1 to 13, 16 to 21, 26 to 28, 30 and 31 of the genes listed in the table of claim 1 when the liver damage type is hepatocellular liver damage And the expression of mRNA or protein of genes 14, 15, 22 to 25 and 29 is decreased as compared with the normal control sample. . 3. The method of claim 2,
When the liver damage type is biliary type liver damage, mRNAs of genes 1 to 13, 17, 19 to 21, 26, 27, 29 and 31 of the genes listed in the table of claim 1 Or protein expression is increased as compared to the normal control sample and the expression of the mRNA or protein of the genes 14 to 16, 18, 22 to 25, 28 and 30 is decreased as compared with the normal control sample A biomarker composition for predicting and diagnosing liver damage caused by a drug that is a drug of interest. 3. The method of claim 2,
MRNA or protein expression of the genes 1 to 13, 17 to 21, 26 to 28 and 31 of the genes listed in the table of the first claim when the type of liver damage is mixed liver damage, And the expression of mRNA or protein of genes 14 to 16, 22 to 25, 29 and 30 is decreased as compared to a normal control sample. (a) measuring the amount of mRNA or protein expression of the 31 genes listed in the table of claim 1 from a biological sample suspected of causing liver damage by drug (DILI); And
(b) measuring the mRNA or protein expression level of the gene from a normal control sample and comparing the mRNA or protein expression level with the measurement result of step (a). 11. The method of claim 10,
Wherein the biological sample is a liver tissue isolated from a subject. 11. The method of claim 10,
The measurement may be performed using a reverse transcriptase-polymerase chain reaction, real time-polymerase chain reaction, Western blot, northern blot, enzyme linked immunosorbent assay (ELISA) wherein the method is performed by a method selected from the group consisting of radioimmunoassay, radioimmunodiffusion, and immunoprecipitation assay.

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