KR102042332B1 - TCIRG1 biomarker for diagnosing recurrent and prognosis of liver cancer and use thereof - Google Patents

Abstract

The present invention relates to a TCIRG1 marker for predicting recurrence and prognosis of liver cancer and its use. Specifically, the present invention relates to a composition for diagnosing or predicting hepatic cancer, including an agent for measuring the expression level of mRNA or TCIRG1 protein of the TCIRG1 gene. Measuring the expression level of mRNA or TCIRG1 protein of TCIRG1 gene from a liver cancer diagnosis or prognostic kit comprising the composition as an active ingredient and a biological sample isolated from the patient; And it relates to a method for providing information for diagnosing liver cancer comprising comparing the measured expression level of TCIRG1 with the expression level of the gene of the control sample. The present invention also relates to a pharmaceutical composition for inhibiting metastasis and recurrence of liver cancer, comprising an inhibitor of TCIRG1 as an active ingredient.

Description

TCIRG1 marker for predicting recurrence and prognosis of liver cancer and its use {TCIRG1 biomarker for diagnosing recurrent and prognosis of liver cancer and use

The present invention relates to TCIRG1 markers and their use for predicting and diagnosing recurrence and postoperative prognosis of liver cancer.

Cancer is a major threat to human health and the single leading cause of death in industrialized countries. The cause of cancer is still unknown, but it is considered to be a combination of carcinogens that act as internal and hereditary factors and external factors as cancer-causing factors, continuous inflammation and damage, and cancer-causing viral infections. .

However, cancer is not desperate enough to be determined to be an incurable disease and can be cured by early diagnosis and active treatment. Therefore, early detection and early treatment are crucial for improving the effectiveness of cancer treatment, and even if advanced cancer is used with multiple and active methods, it can be cured or prolonged life and improve painful symptoms.

Among cancers, liver cancer is known as one of the most deadly cancers in the world, and more than half a million people die of liver cancer each year in Asia and sub-Saharan Africa. Liver cancer can be classified into primary liver cancer (hepatocellular carcinoma) originating from the liver cells itself and metastatic liver cancer in which cancers of other tissues have spread to the liver. More than 90% of liver cancers are primary liver cancers. Although most of the causes of liver cancer are reported to be acute or chronic infections caused by hepatitis B virus or hepatitis C virus, the molecular mechanisms within the cells regarding the development and progression of liver cancer are still unclear. . Conventional studies have shown that protooncogenes, such as various growth factor genes, are mutated to oncogenes for various reasons and are overexpressed or overactive, or tumors such as Rb protein or p53 protein. Tumor suppressor genes have been reported to cause the development and progression of various cancers, including liver cancer, when they are mutated for various reasons and underexpressed or lost function. In recent years, the onset and progression of most cancers, including liver cancer, is not caused by a few specific genes, but is caused by the complex interaction of various genes related to cell cycle, signaling, etc., and therefore, individual genes or proteins. Rather than focusing only on the expression and function of, the need for comprehensive research on various genes and proteins is emerging.

Prognosis of liver cancer refers to predicting various conditions of patients with liver cancer, such as the cure of liver cancer, the possibility of recurrence after treatment, and the patient's viability after the diagnosis of liver cancer. It depends on various conditions such as treatment progress. Liver cancer can be effectively treated only when various treatment methods are applied according to its prognosis. For example, patients with a good prognosis need to avoid risky treatments, such as aggressive chemotherapy, surgery, or radiation therapy, that can cause serious side effects, and should be relatively moderate and conservative. The safe treatment method should be chosen. Conversely, patients who are suspected of having poor prognosis should actively mobilize treatment methods such as chemotherapy, surgery, and radiation therapy to increase the duration or probability of survival. However, there is a lack of technology for accurately diagnosing and determining the prognosis of liver cancer, and studies to date indicate that liver cancer, which has already been advanced, is extremely poor in prognosis and dies within 6 months after diagnosis, and the average survival time is 4 months. Small liver cancers of less than 3cm in size have a good prognosis, with a 90% chance of surviving for one year without special treatment, and a five-year survival rate of 40-50%. have. However, accurately estimating the prognosis of liver cancer patients is very difficult with conventional techniques. For accurate estimation of the prognosis, an analysis method is needed to classify patients by risk group.To date, the prognosis is determined only by the pathological stage of diagnosis and primary surgical treatment without the means of accurately estimating the prognosis of liver cancer. I'm doing it. Unfortunately, the stage of liver cancer alone cannot accurately determine the prognosis for each liver cancer patient.

Therefore, it is necessary to develop a diagnostic marker that can determine the prognosis of liver cancer and further determine the possibility of recurrence after surgery.

Republic of Korea Patent No. 10-0964193

The present inventors have found that TCIRG1 can be used as a biomarker to accurately predict and diagnose the possibility and recurrence of liver cancer, and furthermore, through the analysis of quantitative expression of TCIRG1, the incidence of liver cancer and recurrence after surgery The present invention was completed by confirming the cutoff value of TCIRG1, which can predict the stage of liver cancer and the prognosis after surgery.

Accordingly, an object of the present invention is to provide a composition for diagnosing or predicting liver cancer, comprising an agent for measuring the expression level of mRNA or TCIRG1 protein of the TCIRG1 gene.

Another object of the present invention is to provide a kit for diagnosing or diagnosing liver cancer, comprising the composition according to the present invention.

Still another object of the present invention is to provide a method for providing information for diagnosing liver cancer.

Still another object of the present invention is to provide a pharmaceutical composition for inhibiting metastasis and recurrence of liver cancer, comprising an inhibitor of TCIRG1 as an active ingredient.

In order to achieve the above object, the present invention provides a composition for diagnosing or predicting liver cancer, comprising an agent for measuring the expression level of mRNA or TCIRG1 protein of the TCIRG1 gene.

In one embodiment of the present invention, the TCIRG1 gene is composed of the nucleotide sequence of SEQ ID NO: 1 and 2, TCIRG1 protein may be composed of the amino acid sequence of SEQ ID NO: 3.

In one embodiment of the invention, the agent may be a primer, probe, aptamer, antibody or substrate specific for TCIRG1.

In one embodiment of the present invention, the measurement is reverse transcription polymerase chain reaction, competitive polymerase chain reaction, real time polymerase chain reaction, Nuclease protection assay (RNase, S1 nuclease assay), in situ hybridization method, DNA microarray method Northern blot, Western blot, Enzyme Linked Immuno Sorbent Assay (ELISA), radioimmunoassay, immunodiffusion, immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, complement fixation assay, FACS, mass spectrometry and protein micro It may be performed by a method selected from the array method.

In one embodiment of the present invention, the liver cancer diagnosis or prognosis prediction may include evaluation of progression, recurrence, metastasis, and prognosis of liver cancer.

The present invention also provides a kit for diagnosing liver cancer or prognosis, comprising the composition according to the present invention.

In one embodiment of the present invention, the kit may be any one selected from a microarray, a gene amplification kit, an immunoassay kit, a luminex assay kit, a protein microarray kit, and an ELISA kit.

In addition, the present invention comprises the steps of measuring the expression level of mRNA or TCIRG1 protein of the TCIRG1 gene from a biological sample isolated from the patient; And comparing the measured expression level of TCIRG1 with the expression level of the corresponding gene of the control sample, providing an information providing method for diagnosing liver cancer.

In one embodiment of the invention, the sample may be tissue, whole blood, serum or plasma.

In one embodiment of the present invention, the information providing method, comparing the measured expression level of TCIRG1 with the expression level of the corresponding gene of the control sample may be performed by a standard or cut-off value. .

In one embodiment of the present invention, when the expression level of TCIRG1 is increased than the expression level in the control sample, it may be determined that the prognosis is not good because of the high probability of recurrence, tumor growth or metastasis of liver cancer.

In one embodiment of the present invention, the providing method may have a cutoff value of 11.0112 for determining the possibility of metastasis of liver cancer.

In one embodiment of the present invention, the providing method may have a cutoff value of 6.2821 for early liver cancer determination, a cutoff value of 6.4371 for mid-term liver cancer determination, and a cutoff value of 11.3794 for terminal liver cancer determination. have.

In one embodiment of the present invention, the information providing method may have a cutoff value of 2.5687 for determining the likelihood of recurrence of liver cancer.

Furthermore, the present invention provides a pharmaceutical composition for inhibiting metastasis and recurrence of liver cancer, comprising an inhibitor of TCIRG1 as an active ingredient.

In one embodiment of the invention, the inhibitor may be siRNA, shRNA, antisense oligonucleotide, aptamer or antibody specific for TCIRG.

The TCIRG1 biomarker provided by the present invention can improve the accuracy of cancer diagnosis of a patient by more accurately discriminating the onset, recurrence, and progression stage of liver cancer, and can improve the clinical outcome of the patient after the condition and treatment of the lesion. This can be useful for predicting treatment and for improving survival after liver cancer.

Figure 1 shows the results of the identification and selection of genes associated with recurrence of hepatocellular carcinoma, 1a is a two-dimensional diagram showing the differential expression level of 7,550 genes in tissues derived from non-relapsed or relapsed HCC patients after liver resection Dendrograms are derived from the clustering of patients with total liver resection (TH) and partial liver resection (PH). 1b shows the results of the Benn diagram analysis of the gene characteristics between the TH and PH groups, 1c shows the differential characteristics of upregulated genes between non-relapsed and relapsed groups in patients with total liver resection, and 1d 953 genes commonly up-regulated between TH metastatic and GSE39791 metastatic characteristics, 1e shows a membrane chart for the top 10 gene sets from 953 distinct metastatic molecules analyzed with MSigDB, and 1f shows TH characteristics And GSEA analyzed with the LIAO_METASTASIS gene set, the bar code indicates the position of the gene and the y axis shows the content (degree of expression) of the gene.
FIG. 2 shows the results of overexpression of TCIRG1 and its clinically relevant analysis in hepatocellular carcinoma (HCC), wherein 2a shows the analysis of TCGA_LIHC data, with TCGA_LIHC data being the total set (n = 423, left result) and pair set (n = 100, median results), and significantly overexpressed in HCC and overexpressed at higher tumor grade (right results) (mean ± SD; * P <0.05; * ** P <0.001).
Figure 2b shows the TCIRG1 mRNA expression level in the Kaga-Meier survival curve in TCGA_LIHC for overall survival (left) and disease-free survival (right), P values were derived by log-rank test.
Figure 2c shows the results of TCIRG1 ROC curve analysis in TCGA_LIHC (left) and GSE39791 (right), statistically significant difference in AUC compared to the control (* P <0.05; *** P <0.001).
Figure 2d shows the results of confirming the mRNA expression level of TCIRG1 in the HCC tissue through qRT-PCR analysis.
FIG. 2E shows the results of immunochemical analysis of non-tumor tissue or tumor tissue (left) and expression rate of TCIRG1 (right) (*** P <0.001).
Figure 2f shows the results of Western blot confirming the expression level of TCIRG1 in HCC tissues (NT: adjacent non-tumor tissue, T: tumor tissue), glycerol aldehyde-3-phosphate dehydrogenase (GAPDH) is used as a loading control It was.
Figure 2g shows Kaplan-Meier survival curves according to positive or negative expression of TCIRG1 (left) and the intensity of tumor range by TCIRG1 expression in the non-transplanted cohort (right).
Figure 2h shows Kaplan-Meier survival curves according to positive or negative expression of TCIRG1 (left) and the intensity of tumor range by TCIRG1 expression in the implanted cohort (right).
Figure 2i shows the results of analyzing the TCIRG1 mRNA expression level using the Gene Expression Omnibus (GEO) database (accession number: GSE14520, GSE16757, GSE22058, GSE25097, GSE36376, GSE36411, GSE45436 and GSE89337) (mean ± SD; * * P <0.01; *** P <0.001).
2J graphically plots parallel coordinates for TCIRG1 expression in HCC published genomic data of NCBI GEO databases (accession numbers: GSE39791 and GSE77314; mean ± SD; ** P <0.01; *** P <0.001, paired ttest) will be.
Figure 2K shows TCIRG1 expression (left) (N: normal, eHCC: early liver cancer, ovHCC: overtHCC) and TCIRG1 expression (right) in hepatocellular carcinoma patients (accession number: GSE89337, mean ± D, ** P <0.01) It is shown.
Figure 3 shows the results of analyzing the anticancer effect targeting TCIRG1 in liver cancer cell line, 3a is two normal cell lines (THLE3 and MIHA) and 12 liver cancer cell lines (Hep3B, HepG2, Huh7, PLC / PRF / 5, TCIRG1 expression in SK-Hep1, SNU354, SNU368, SNU387, SNU398, SNU423, SNU449, and SNU475) was analyzed by qRT-PCR, and 3b was performed by Western blot for TCIRG1, which is expressed in cells. One result, GAPDH was used as a loading control, the number at the bottom of each band represents the expression level. 3c shows the result of analyzing colony forming ability in SNU475 and Huh7 cell lines, 3d shows the result of transfecting SNU475 and Huh7 cell lines with TCIRG1-specific siRNA and negative control siRNA and measuring the cell number through trypan blue staining. 3e shows the result of transfecting SNU475 and Huh7 cell lines with TCIRG1-specific siRNA and negative control siRNA and measuring the extent of cell growth by MTT assay, and 3f shows the BrdU (Bromodeoxyuridine) influx assay for SNU475 and Huh7 cell lines. The results are shown. 3g transfected cells with TCIRG1-specific siRNA and negative control siRNA and FACS analysis, where knockdown of TCIRG1 induced G1 / S arrest in SNU475 and Huh7 cell lines, with each percentage of the corresponding cell count The distribution is shown. 3h was transfected with TCIRG1-specific siRNA (siTCIRG1) and negative control siRNA (NC) and FACS analysis was performed with PI and Annexin V staining, bar graph showing percentage of Annexin V positive cells . 3i is the cells treated with 3-MA (5 mM) following transfection followed by FACS analysis, bar graph showing percentage of Annexin V negative and PI positive cell numbers.
Figure 4 is an analysis of the effect of inhibiting cancer metastasis targeting TCIRG1 in liver cancer cell line, showing the results of inhibition of migration (4a) and metastasis (b) in SNU475 and Huh7 cell lines by TCIRG1 knockdown. 4c is a wound healing assay, bar graph shows the degree of recovery by cell migration, 4d and 4e is the inhibition of cell migration by TCIRG1 knockdown (4d) in fibroblasts of ras-transformed NIH-3T3 mice ) And the degree of metastasis inhibition (4e) are shown. 4f shows Western blot expression levels of ECI-related factors TCIRG1, E-cadherin, N-cadherin, Fibronectin, Vimentin, Snail and Slug. 4g is the result of NCBI GEO database analysis, GEO data set of accession numbers GSE39791 and GSE77314 was used for expression analysis between TCIRG1 and CDH1, the left panel shows the expression of CDH1 in GSE39791 and GSE77314, the right panel is GSE39791 (Pearson correlation Negative relationship between TCIRG1 and CDH1 expression is shown in coefficient r = -0.21, ** P <0.01) and GSE77314 (Pearson correlation coefficient r = -0.36, *** P <0.001).
Figure 5 analyzes the effect of TCIRG1 in cancer metastasis, 5a shows the CT image of ras-transformed NIH-3T3 cells after suppressing the expression of TCIRG1 (left), each tumor volume measured graphically (Right side). 5b shows the results of analysis of cancer metastasis to the lung after injection of negative control siRNA (n = 5) and TCIRG1 siRNA (n = 5) in a mouse animal model implanted with ras-transformed NIH-3T3 cells (left) ). The number of pulmonary nodules in the mouse was shown as a bar graph (right).
Figure 6a shows the results of TCIRG1 cut-off analysis of non-tumor tissue (Non tumor, n = 50) and advanced hepatocellular carcinoma (G2, G3, G4, n = 301), 6b is a liver resection in GSE39791 The cut-off analysis of TCIRG1 expression levels in non-tumor tissues (Non tumor, n = 72) and recurrent hepatocellular carcinoma (Tumor, n = 72) of the same patient was received. G1, G2, G3, G4) Cut-off analysis of TCIRG1 expression level, 6d is cut-off analysis of TCIRG1 expression level according to normal-> early stage cancer (eHCC)-> severe liver cancer (avHCC) The results show that 6e is the result of analyzing the amount of TCIRG1 expression cutoff value in the relapsed tissue and the non-relapsed tissue after liver resection.

The present invention is characterized by identifying the possibility of using TCIRG1 as a biomarker that can predict and diagnose the onset, recurrence and prognosis of liver cancer.

Liver cancer is known to be the most fatal cancer in the world. Therefore, in order to prevent liver cancer and increase the treatment effect, it is necessary to accurately determine whether liver cancer develops, stage of progression, recurrence after surgery, and prognosis, and appropriate treatment method based on such judgment should be applied.

Therefore, the present inventors, while researching to find a biomarker for accurately diagnosing liver cancer, confirmed the possibility of using TCIRG1 (T-Cell Immune Regulator 1) as a diagnostic marker for liver cancer, and further recurrence and prognosis after liver cancer surgery. It was confirmed that it can be used for judging purposes.

In particular, TCIRG1, a diagnostic marker for liver cancer, which was discovered in the present invention, was a marker discovered for samples obtained from liver cancer patients, and it can be seen that practical use is secured at a clinical level.

First of all, the present inventors secured liver cancer tissues from patients who underwent liver resection to discover biomarkers that accurately predict and diagnose liver cancer. Clustering analysis was performed on the genes that are expressed. As a result, the TCIRG1 gene was specifically identified in the tissues of patients whose liver cancer recurred after liver resection.

In order to verify whether the TCIRG1 gene is specifically overexpressed in liver cancer, TCIRG1 expression levels were analyzed in non-tumor liver tissues and liver cancer tissues obtained from liver cancer patients. Significantly increased expression in tissues.

Therefore, it was found that TCIRG1 exhibited a specific overexpression during the onset of liver cancer, and that TCIRG1 can be used as a specific biomarker for diagnosing liver cancer.

In another embodiment of the present invention, the correlation between the expression level of TCIRG1 and the recurrence and prognosis of liver cancer was analyzed. The TCIRG1 expression-positive patient group showed lower disease-free survival rate than the TCIRG1 negative patient group, and the prognosis was poor. I could confirm it.

Therefore, TCIRG1 can be used not only for the development of liver cancer, but also for predicting the possibility of recurrence after liver cancer surgery and the prognosis of patients.If TCIRG1 is overexpressed compared to normal, liver cancer develops or after surgery It can be predicted that there has been a relapse, a possible metastasis, or a poor patient's prognosis.

Therefore, the present invention can provide a marker for diagnosing liver cancer comprising a TCIRG1 gene or a TCIRG1 protein encoded from the gene, and a composition for diagnosing or predicting liver cancer comprising a preparation for measuring the expression level of mRNA or TCIRG1 protein of the TCIRG1 gene. Can be provided.

In the present invention, the term "diagnosis" refers to confirming the pathological condition, and for the purpose of the present invention, the diagnosis means confirming the presence or absence of expression of a liver cancer diagnostic marker, and confirming the occurrence of liver cancer. , "Diagnosis" in the present invention includes determining whether liver cancer diagnostic markers are expressed and the degree of expression, and determining whether liver cancer is developed, developed, and reduced.

In the present invention, the "prognosis" refers to predicting various conditions of the patient according to the cancer, such as the possibility of cure of cancer, the possibility of recurrence after treatment, the survival of the patient after the cancer is diagnosed. The prognosis of cancer can be estimated from various points of view, but can typically be determined in terms of recurrence, viability, and disease-free survival. Prognosis for the purposes of the present invention may mean the prognosis of survival after diagnosis of liver cancer. By using the biomarkers provided in the present invention, it is possible to more easily predict the survival prognosis of liver cancer patients, which may be utilized to classify patients at high risk or to determine whether to use additional treatment methods. It can contribute to increase the survival rate later.

In addition, the "prediction" relates to whether and / or the likelihood that the patient will survive the treatment of the patient by preferentially or unfavorably responding to the therapy. The estimation method of the present invention can be used clinically to make treatment decisions by selecting the most appropriate treatment modality for patients with cancer. In addition, the predictive methods of the present invention determine whether a patient preferentially responds to a treatment regimen, such as, for example, a treatment regimen, including administration of a given therapeutic agent or combination, surgical intervention, chemotherapy, etc. It can be used to predict whether long term survival is possible.

In addition, the "diagnosis marker" refers to a substance capable of diagnosing cells or tissues of liver cancer by distinguishing them from normal cells or tissues, and a polypeptide showing an increase or decrease in cells of liver cancer compared to normal cells or Organic biomolecules such as nucleic acids (eg, mRNA, etc.), lipids, glycolipids, glycoproteins, sugars (monosaccharides, disaccharides, oligosaccharides, etc.) and the like. The marker for diagnosing liver cancer provided by the present invention may be a TCIRG1 gene or protein whose expression level is increased in cells (or tissues) of liver cancer compared to normal cells. Preferably, the TCIRG1 gene is a nucleotide sequence of SEQ ID NOs: 1 and 2 It may be to have. In addition, the TCIRG1 protein may be one having an amino acid sequence of SEQ ID NO: 3.

In the present invention, the level of the TCIRG1 gene, preferably means the mRNA level of the TCIRG1 gene is expressed, that is, the amount of mRNA, and the material capable of measuring the level, primers, probes, aptamers specific for the TCIRG1 gene , Antibodies or substrates.

In the present invention, the term “primer” refers to a single which can serve as an initiation point for template-directed DNA synthesis under suitable conditions (ie, four different nucleoside triphosphates and polymerases) in suitable buffers. -Refers to stranded oligonucleotides. Suitable lengths of primers can vary depending on various factors, such as temperature and the use of the primer. In addition, the sequence of the primer need not have a sequence that is completely complementary to some sequences of the template, it is sufficient to have sufficient complementarity within the range that can hybridize with the template to perform the primer-specific action. Therefore, the primer in the present invention does not need to have a sequence that is perfectly complementary to the nucleotide sequence of the TCIRG1 gene, which is a template, and it is sufficient to have sufficient complementarity within a range capable of hybridizing to the gene sequence to act as a primer.

The “amplification reaction” refers to a reaction for amplifying a nucleic acid molecule, and amplification reactions of such genes are well known in the art, for example, polymerase chain reaction (PCR), reverse transcriptase polymerase chain reaction (RT-PCR). , Ligase chain reaction (LCR), electron mediated amplification (TMA), nucleic acid sequence substrate amplification (NASBA), and the like.

In the present invention, the term “probe” refers to a linear oligomer of natural or modified monomers or linkages, and includes deoxyribonucleotides and ribonucleotides and can specifically hybridize to a target nucleotide sequence, which is a natural It exists or artificially synthesized. The probe according to the invention may be single chain, preferably oligodioxyribonucleotides.

Probes of the invention can include natural dNMPs (ie, dAMP, dGMP, dCMP and dTMP), nucleotide analogues or derivatives. In addition, the probes of the present invention may also comprise ribonucleotides. For example, the probes of the present invention can be used in the backbone modified nucleotides such as peptide nucleic acid (PNA) (M. Egholm et al., Nature, 365: 566-568 (1993)), phosphorothioate DNA, phosphorodithioate DNA, phosphoramidate DNA, amide-linked DNA, MMI-linked DNA, 2'-0-methyl RNA, alpha-DNA and methylphosphonate DNA, sugar modified nucleotides such as 2'-0-methyl RNA, 2'-fluoro RNA, 2'-amino RNA, 2'-0-alkyl DNA, 2'-0-allyl DNA, 2'-0-alkynyl DNA, hexose DNA, pyranosyl RNA and anhydrohex Tall DNA, and nucleotides with base modifications such as C-5 substituted pyrimidines (substituents are fluoro-, bromo-, chloro-, iodo-, methyl-, ethyl-, vinyl-, formyl-, Tityl-, propynyl-, alkynyl-, thiazolyl-, imidazoryl-, pyridyl-, 7-deazapurine with C-7 substituents (substituents are fluoro-, bromo-, chloro- , Iodo-, me -, ethyl-, vinyl-, formyl-, alkynyl -, alkenyl-, quinolyl and quinoxalyl thiazol-, quinolyl and quinoxalyl imidazolidin -, pyridyl-), inosine, and it may include a diamino purine.

In addition, in the present invention, the level of the TCIRG1 protein, preferably means a TCIRG1 polypeptide produced through the translation process from the mRNA expressed TCIRG1 gene, as a substance capable of measuring the level of the TCIRG1 protein for the TCIRG1 protein "Antibodies" such as polyclonal antibodies, monoclonal antibodies and recombinant antibodies that can specifically bind.

In addition, in the present invention, since the TCIRG1 protein has been identified as a marker protein for diagnosing liver cancer as described above, a method for generating an antibody using the protein uses techniques known to those skilled in the art. It can be manufactured easily. For example, in the case of polyclonal antibodies, the TCIRG1 antigen can be produced by methods well known in the art for injecting animals into animals and collecting blood from the animals to obtain serum comprising the antibodies, which polyclonal antibodies are goats, rabbits, sheep. Can be produced from any animal species host such as, monkey, horse, pig, cow, dog, and the like. Monoclonal antibodies can be prepared using hybridoma methods well known in the art (Kohler et al., European Jounral of Immunology , 6, 511-519, 1976) or phage antibody libraries ( Clackson et al, Nature , 352, 624-628, 1991, Marks et al, J. Mol . Biol ., 222: 58, 1-597, 1991). In addition, the antibodies according to the invention may comprise functional fragments of antibody molecules, as well as complete forms having two full length light chains and two full length heavy chains. A functional fragment of an antibody molecule refers to a fragment having at least antigen binding function, and includes Fab, F (ab '), F (ab') 2 and Fv.

On the other hand, the present invention can provide a kit for diagnosing liver cancer or prognostic diagnosis comprising a composition containing a formulation capable of measuring the expression level of the TCIRG1 protein or a gene encoding the same.

 The liver cancer diagnosis or prognostic diagnostic composition included in the kit of the present invention may include a primer, a probe, an aptamer, an antibody, or a substrate capable of measuring the expression level of a TCIRG1 protein or a gene encoding the same, the definitions of which are described above. As it is.

 If the kit of the invention is subjected to a PCR amplification process, the kit of the invention may optionally contain reagents necessary for PCR amplification, such as buffers, DNA polymerases (eg, Thermus aquaticus (Taq), Thermus thermophilus (Tth), Thermus). filiformis, Thermis flavus, Thermococcus literalis or thermally stable DNA polymerase obtained from Pyrococcus furiosus (Pfu)), DNA polymerase cofactors and dNTPs, and when the liver cancer diagnostic kit is applied to an immunoassay, Kits of the invention may optionally comprise a secondary antibody and a substrate of the label. Furthermore, the kits according to the invention can be produced in a number of separate packaging or compartments comprising the reagent components described above.

On the other hand, the present invention provides a liver cancer diagnostic microarray comprising a composition for diagnosing liver cancer capable of measuring the expression level of the TCIRG1 protein or a gene encoding the same.

In the microarray of the present invention, primers, probes or antibodies capable of measuring the expression level of a TCIRG1 protein or gene encoding it are used as a hybridizable array element and immobilized on a substrate. Preferred substrates may include suitable rigid or semi-rigid supports, such as membranes, filters, chips, slides, wafers, fibers, magnetic beads or nonmagnetic beads, gels, tubing, plates, polymers, microparticles and capillaries. have. The hybridization array element is arranged and immobilized on the substrate, and such immobilization can be performed by a chemical bonding method or a covalent binding method such as UV. For example, the hybridization array element can be bonded to a glass surface modified to include an epoxy compound or an aldehyde group, and can also be bonded by UV at the polylysine coating surface. In addition, the hybridization array element can be coupled to the substrate via a linker (eg, 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 can be labeled (labeled), it can be hybridized with the array element on the microarray. Hybridization conditions may vary, and detection and analysis of the degree of hybridization may vary depending on the labeling substance.

On the other hand, the present invention comprises the steps of measuring the expression level of mRNA or TCIRG1 protein of the TCIRG1 gene from a biological sample isolated from the patient; And comparing the measured expression level of TCIRG1 with the expression level of the corresponding gene of the control sample, providing an information providing method for diagnosing liver cancer.

The method of measuring the expression level or TCIRG1 protein level of the TCIRG1 gene in the above may be carried out including a known process for detecting or separating the mRNA or protein from a biological sample using a known technique.

In the present invention, the "biological sample" refers to a sample collected from a living body, in which the expression level of the TCIRG1 gene or the protein level is different from the normal control group according to the incidence or progression of liver cancer. But not limited to, tissue, cells, blood, serum, plasma, saliva, urine, and the like.

Determination of the expression level of the TCIRG1 gene is preferably to measure the level of mRNA, the method for measuring the level of mRNA reverse transcription polymerase chain reaction (RT-PCR), real-time reverse transcription polymerase chain reaction, RNase protection assay, Northern blots and DNA chips, but are not limited thereto.

The measurement of the TCIRG1 protein level may use an antibody, in which case the TCIRG1 marker protein in the biological sample and the antibody specific thereto form a conjugate, i.e., an antigen-antibody complex, and the amount of antigen-antibody complex formation is detected. Quantitative measurements can be made through the magnitude of the signal on the label. Such a detection label may be selected from the group consisting of enzymes, fluorescent materials, ligands, luminescent materials, microparticles, redox molecules and radioisotopes, but is not limited thereto.

Analytical methods for measuring protein levels include, but are not limited to, Western blot, ELISA, radioimmunoassay, radioimmunoassay, oukteroni immunodiffusion, rocket immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, Complement fixation assays, FACS, protein chips, and the like.

Therefore, the present invention can determine the amount of TCIRG1 mRNA expression or protein in the control group and the amount of TCIRG1 mRNA expression or protein in liver cancer patients or suspected liver cancer patients through the above-described detection methods, the degree of expression That is, by comparing with a sample of a normal person, it is possible to predict and diagnose the onset, progression or prognosis of liver cancer.

According to one embodiment of the present invention, the tissue lysates are obtained from liver cancer tissues and normal liver tissues obtained from liver cancer patients, and then subjected to Western blotting using an antibody against TCIRG1. After the measurement, the measurement was performed through a process of comparative analysis with the normal control.

In another aspect, the present invention provides a cut off value for the amount of TCIRG1 expression for predicting the diagnosis, specifically, recurrence, progression, or prognosis of liver cancer.

The cut off value is a cut off value for TCIRG1 in a sample according to the present invention, for example, tissue, serum, plasma, and the like.

In the liver cancer diagnosis or prognosis estimation method according to the present invention, cancer may be diagnosed or the prognosis may be estimated by comparing the gene expression level measurement result with that of the control group. Alternatively, the cancer may be diagnosed or the prognosis may be estimated against a predetermined cut-off value. As a negative control, a normal sample or a sample from a patient treated after cancer, such as a non-tumor sample, can be used, and a positive control can be a sample from a patient determined as liver cancer. In one example, a sample derived from a normal person, a normal tissue sample taken from a cancer determination patient, and a sample derived from a patient treated after determination as cancer may be used as a control and used for comparison of the obtained profile.

Various methods known in the art can be used to compare marker profiles between control groups and test groups using samples. For example, reference may be made to digital image comparison of expression profiles and comparison using DB for expression data. Profiles obtained through marker detection according to the present application can be processed using known data analysis methods. For example, the nearest neighbor classifier, partial-least squares, SVM, AdaBoost, and clustering-based classification methods can be used. In addition, various statistical processing methods may be used to confirm the significance of the method for diagnosing and predicting liver cancer according to the present invention. As a statistical method, in one embodiment, a logistic regression method may be used. In addition, statistical processing can determine the level of confidence in the significant difference between the test substance and the control to diagnose cancer. The data used for statistical processing are the values analyzed in duplicate, triple or multiple for each marker. This statistical method is very useful for making clinically meaningful judgments through statistical processing of biomarkers as well as clinical and genetic data.

Therefore, the present inventors analyzed the TCIRG1 cutoff value for diagnosing liver cancer. In one embodiment of the present invention, the amount of TCIRG1 expression was quantitatively measured in the liver tissue of a non-hepatic cancer patient and the liver tissue of a liver cancer patient. After quantitatively measuring the amount of TCIRG1 expression in non-tumor tissues and advanced hepatocellular carcinoma tissues, a cutoff value was derived based on the amount of non-hepatic cancer tissues expressed in liver cancer patient tissues, and expressed in hepatocellular carcinoma tissues. The cutoff value was derived based on the expression amount in the non-tumor tissue, and the cutoff value was 11.0112.

Therefore, when the cutoff value of TCIRG1 of a sample is 11.0112 or more, it can be predicted that liver cancer has developed, and can also be predicted as advanced liver cancer which has the possibility of metastasis of onset liver cancer.

In another embodiment of the present invention, a TCIRG1 cutoff value analysis of non-tumor tissue and recurrent hepatocellular carcinoma tissue of a patient who had undergone liver resection showed a cutoff value of 2.5687.

Therefore, if the cutoff value of TCIRG1 is 2.5687 or more in the patient's sample after surgery, it may be predicted that liver cancer may recur after surgical treatment.

In another embodiment, the amount of TCIRG1 expression is quantified in cancer tissues of stage 1 (G1), stage 2 (G2), stage 3 (G3) and stage 4 (G4) liver cancer, and TCIRG1 cutoff values are analyzed. The cutoff values of normal and early cancer (eHCC) were 6.2821, and the cutoff values of eHCC and intermediate cancer (avHCC) were 6.4371, and G3 (stage 3 liver cancer) and G4 ( In stage 4 liver cancer), the cutoff value was 11.3794.

Therefore, if the TCIRG1 cutoff value is 6.2821, it can be determined as early liver cancer, if it is 6.4371, it can be regarded as medium-term cancer, and if it is 11.3794, it can be determined as terminal liver cancer.

Furthermore, the present inventors analyzed the growth and proliferation of hepatocellular carcinoma after knocking down TCIRG1 with siRNA against TCIRG1 in order to determine whether it was possible to suppress liver cancer when inhibiting TCIRG1, and thus inhibiting TCIRG1 expression or activity. It was found that the growth and proliferation of the cells were inhibited, cell cycle abnormality was induced, and cell death was induced to ultimately prevent and treat liver cancer.

Therefore, a substance capable of inhibiting the activity and expression of TCIRG1 can be used as a therapeutic agent for liver cancer.

Therefore, the present invention provides a pharmaceutical composition for inhibiting metastasis and recurrence of liver cancer, comprising an inhibitor of TCIRG1 as an active ingredient.

The pharmaceutical composition according to the present invention may include any material capable of inhibiting the expression of TCIRG1, and preferably may include chemicals, nucleotides, antisenses, siRNA oligonucleotides or natural extracts as active ingredients, and more. Preferably, an antisense or siRNA (small interference RNA) oligonucleotide having a sequence complementary to the nucleotide sequence of the TCIRG1 gene of the present invention may be included as an active ingredient, and more preferably, siRNA for TCIRG1 may be used.

In the present invention, the term "antisense oligonucleotide" refers to DNA or RNA or a derivative thereof containing a nucleic acid sequence complementary to a sequence of a specific mRNA, and binds to a complementary sequence in the mRNA to translate TCIRG1 into a protein. The antisense sequence of the present invention refers to a DNA or RNA sequence complementary to TCIRG1 mRNA and capable of binding to TCIRG1 mRNA, which translates into TCIRG1 mRNA, translocation into the cytoplasm, and maturation. Or inhibit the essential activity for all other global biological functions.

In addition, the antisense nucleic acid can be modified at the position of one or more bases, sugars or backbones to enhance efficacy (De Mesmaeker et al., Curr Opin Struct Biol ., 5, 3, 343-55, 1995). The nucleic acid backbone can be modified with phosphorothioate, phosphoroester, methyl phosphonate, short chain alkyl, cycloalkyl, short chain heteroatomic, heterocyclic intersaccharide linkages and the like. In addition, antisense nucleic acids may comprise one or more substituted sugar moieties. Antisense nucleic acids can include modified bases. Modified bases include hypoxanthine, 6-methyladenine, 5-methylpyrimidine (particularly 5-methylcytosine), 5-hydroxymethylcytosine (HMC), glycosyl HMC, gentobiosil HMC, 2-aminoadenine, 2 Thiouracil, 2-thiothymine, 5-bromouracil, 5-hydroxymethyluracil, 8-azaguanine, 7-deazaguanine, N6 (6-aminohexyl) adenine, 2,6-diaminopurine, etc. There is this. In addition, the antisense nucleic acids of the present invention may be chemically bound to one or more moieties or conjugates that enhance the activity and cellular adsorption of the antisense nucleic acids. Cholesterol moieties, cholesteryl moieties, cholic acid, thioethers, thiocholesterols, fatty chains, phospholipids, polyamines, polyethylene glycol chains, adamantane acetic acid, palmityl moieties, octadecylamine, hexylamino-carbonyl-oxy Fat-soluble moieties such as a cholesterol ester moiety, and the like. Oligonucleotides comprising fat-soluble moieties and methods of preparation are already well known in the art (US Pat. Nos. 5,138,045, 5,218,105 and 5,459,255). The modified nucleic acid can increase stability to nucleases and increase the binding affinity of the antisense nucleic acid with the target mRNA.

Antisense oligonucleotides can be synthesized in vitro in conventional manner to be administered in vivo or to allow antisense oligonucleotides to be synthesized in vivo. One example of synthesizing antisense oligonucleotides in vitro is to use RNA polymerase I. One example of allowing antisense RNA to be synthesized in vivo is to allow the antisense RNA to be transcribed using a vector whose origin is in the opposite direction of the recognition site (MCS). Such antisense RNA is desirable to ensure that there is a translation stop codon in the sequence so that it is not translated into the peptide sequence.

As used herein, the term "siRNA" refers to a nucleic acid molecule capable of mediating RNA interference or gene silencing (International Patent Nos. 00/44895, 01/36646, 99/32619, 01/29058, 99/07409 and 00 SiRNA is provided as an efficient gene knock-down method or gene therapy method because it can inhibit the expression of a target gene.

The siRNA molecule of the present invention may have a structure in which a sense strand (a sequence corresponding to a TCIRG1 mRNA sequence) and an antisense strand (a sequence complementary to a TCIRG1 mRNA sequence) are positioned opposite to each other to form a double-stranded structure. The siRNA molecule of can have a single chain structure with self-complementary sense and antisense strands. Furthermore, siRNAs are not limited to completely paired double-stranded RNA moieties paired with RNA, but can be paired by mismatches (the corresponding bases are not complementary), bulges (there are no bases corresponding to one chain), and the like. Parts that do not achieve may be included. In addition, the siRNA terminal structure can be either blunt or cohesive ends as long as the expression of the TCIRG1 gene can be suppressed by the RNAi effect, and the adhesive end structures are 3'-terminal protrusion structures and 5'-terminal structures. Both protruding structures are possible.

In addition, the siRNA molecules of the present invention may have a form in which a short nucleotide sequence is inserted between self-complementary sense and antisense strands, in which case the siRNA molecule formed by expression of the nucleotide sequence is subjected to intramolecular hybridization. As a result, a hairpin structure is formed, and as a whole, a stem-and-loop structure is formed. This stem-and-loop structure is processed in vitro or in vivo to produce an active siRNA molecule capable of mediating RNAi.

The method for preparing siRNA is to directly synthesize siRNA in vitro and then introduce it into the cell through a transformation process, and to siRNA expression vector or PCR-derived siRNA expression cassette prepared to express siRNA in the cell. There is a method of conversion or infection.

In addition, the compositions of the present invention comprising gene specific siRNAs may include agents that promote intracellular influx of siRNAs. Agents that promote the influx of siRNA into the cell generally can be used agents that promote the influx of nucleic acids. Examples of these include the use of liposomes or the lipophilic of one of many sterols, including cholesterol, cholate and deoxycholic acid. It can be combined with a carrier. Also, poly-L-lysine, spermine, polysilazane, polyethylenimine, polydihydroimidazolenium, polyallylamine Cationic polymers such as chitosan), succinylated PLL, succinylated PEI, polyglutamic acid, and polyaspartic acid. anionic polymers such as polyaspartic acid, polyacrylic acid, polymethacylic acid, dextran sulfate, heparin, and hyaluronic acid. It is available.

In addition, when an antibody specific for the TCIRG1 protein is used as a substance for reducing the expression and activity of the TCIRG1 protein, the antibody may be directly coupled (eg, covalently) to an existing therapeutic agent or indirectly through a linker or the like. Can be. Therapeutic agents that can be bound to the antibody include, but are not limited to, radionuclide such as 131I, 90Y, 105Rh, 47Sc, 67Cu, 212Bi, 211At, 67Ga, 125I, 186Re, 188Re, 177Lu, 153Sm, 123I, 111In, etc. ); Biological response variants or drugs such as methotrexate, adriamycin, and lympokine such as interferon; Toxins such as lysine, abrin, diphtheria and the like; Heterofunctional antibodies, ie antibodies that bind to other antibodies so that the complex binds to both cancer cells and agonist cells (eg, K cells such as T cells); and -May be associated with associated or non-complexed antibodies.

In addition, in the present invention, the pharmaceutical composition of the present invention may further include a pharmaceutically acceptable carrier. As used herein, "pharmaceutically acceptable" refers to a composition that is physiologically acceptable and that, when administered to a human, typically does not cause allergic or similar reactions, such as gastrointestinal disorders, dizziness, and the like. Pharmaceutically acceptable carriers include, for example, carriers for oral administration such as lactose, starch, cellulose derivatives, magnesium stearate, stearic acid and the like, and parenteral administration such as water, suitable oils, saline, aqueous glucose and glycols, and the like. And the like may further comprise stabilizers and preservatives. Suitable stabilizers include antioxidants such as sodium hydrogen sulfite, sodium sulfite or ascorbic acid. Suitable preservatives include benzalkonium chloride, methyl- or propyl-paraben and chlorobutanol. Other pharmaceutically acceptable carriers may be referred to those described in the following documents (Remington's Pharmaceutical Sciences, 19th ed., Mack Publishing Company, Easton, PA, 1995).

The pharmaceutical composition according to the present invention may be formulated in a suitable form according to methods known in the art together with the pharmaceutically acceptable carrier as described above. That is, the pharmaceutical composition of the present invention can be prepared in various parenteral or oral dosage forms according to known methods, and isotonic aqueous solution or suspension is preferable as an injectable formulation as a typical parenteral dosage form. Injectable formulations may be prepared according to techniques known in the art using suitable dispersing or wetting agents and suspending agents. For example, each component may be formulated for injection by dissolving in saline or buffer. In addition, formulations for oral administration include, but are not limited to, powders, granules, tablets, pills and capsules.

Pharmaceutical compositions formulated in such a manner may be administered in an effective amount via a variety of routes including oral, transdermal, subcutaneous, intravenous or intramuscular. The term “administration” introduces certain substances into a patient in any suitable manner. The route of administration of the substance may be administered via any general route as long as it can reach the target tissue.

In addition, the above "effective amount" refers to an amount that exhibits a prophylactic or therapeutic effect when administered to a patient. The dosage of the pharmaceutical composition according to the present invention may vary depending on various factors such as the disease type and severity of the patient, age, sex, weight, sensitivity to the drug, type of current treatment, administration method, target cell, and the like. It can be easily determined by experts. In addition, the pharmaceutical composition of the present invention may be administered in combination with a conventional therapeutic agent, may be administered sequentially or simultaneously with a conventional therapeutic agent, and may be administered in a single or multiple doses. Preferably all of the above factors can be administered in an amount that can achieve the maximum effect in a minimum amount without side effects, more preferably 1 to 10000 ㎍ / weight kg / day, even more preferably 10 to 1000 mg It may be administered repeatedly several times a day at an effective dose of / kg body weight / day.

The present invention further comprises the steps of (a) contacting a sample to be analyzed with a cell comprising a TCIRG1 gene or a TCIRG1 protein; (b) measuring the expression amount of the TCIRG1 gene, the amount of TCIRG1 protein or the activity of TCIRG1 protein; And (c) determining that the sample is a substance for preventing or treating liver cancer when the amount of expression of the TCIRG1 gene, the amount of the TCIRG1 protein, or the activity of the TCIRG1 protein is reduced as a result of the measurement in step (b). In addition, the present invention may provide a method for screening a substance for preventing or treating liver cancer.

According to the method of the present invention, a sample to be analyzed may be first contacted with a cell containing or expressing a TCIRG1 gene or a TCIRG1 protein. Here, the "sample" refers to an unknown substance used in screening to test whether the amount of expression of TCIRG1 gene, the amount of TCIRG1 protein or the activity of TCIRG1 protein is affected. The sample may include, but is not limited to, chemicals, nucleotides, antisense-RNAs, small interference RNAs (siRNAs), and natural extracts. Thereafter, the expression level of the TCIRG1 gene, the amount of TCIRG1 protein, or the activity of the TCIRG1 protein can be measured in the cells treated with the sample. The sample may be determined to be a substance capable of treating or preventing liver cancer.

The method of measuring the activity of TCIRG1 in the above may be carried out through various methods known in the art, for example, but not limited to reverse transcriptase-polymerase chain reaction, real-time polymerization Real time-polymerase chain reaction, Western blot, Northern blot, enzyme linked immunosorbent assay (ELISA), radioimmunoassay (RIA), radioimmunodiffusion and immunoprecipitation assay It can be performed using.

Hereinafter, the present invention will be described in detail by way of examples. However, these examples are intended to illustrate the present invention in more detail, and the scope of the present invention is not limited to these examples.

<Preparation Example>

Organization Preparation

Liver cancer tissues were collected from HCC patients at Seoul National University Hospital from January 1995 to May 2006. Liver cancer tissues were immediately frozen and stored in liquid nitrogen. In addition, informed consent was obtained from patients enrolled in this experiment. Written consent was obtained from each subject in accordance with the Declaration of Helsinki, and the liver cancer tissue was used in the following experiments with the approval of the Institutional Review Board of the Catholic University Medical College (IRB Approval Number: MC12SNMI0184).

Experimental Method

① Molecular Pathway  Molecular pathway mining and gene set enrichment analysis

Gene sets were downloaded from MSigDB (http://software.broadinstitute.org/gsea/msigdb) of the Broad Institute Gene Set Enrichment Analysis (GSEA) (http: // www. broadinstitute.org/gsea). GSEA was performed to access the LIAO_METASTASIS gene set and the presence of obvious metastatic gene signals. Given the data sets whose genes are ranked by correlation of expression levels by the phenotype of interest, the basic GSEA test quantifies the extent to which a given set of genes is enriched at the top (positive correlation) or the bottom (negative correlation). Indicates a score. Proximity of the gene set was measured using the Kolmogorov-Smirnoff (KS) score, with higher scores indicating higher proximity. The analyzed KS scores were compared with the distribution of 1000 substituted KS scores for all gene sets to assess significance.

② On TCIRG1  About Tissue microarray

The hematoxylene and eosin (H & E) slides were reconfirmed and a formalin-fixed and paraffin-embedded (FFPE) recording block was selected for each case for a time. Core tissue biopsies (diameter 2 mm) were taken from individual FFPE blocks (donor blocks) and placed into recipient paraffin blocks (tissue array blocks) using trepin. Eight array blocks containing 302 HCC cancer tissues were prepared (Superbiochips Laboratories, Seoul, Korea).

③ Cell culture and transfection

Hep3B, HepG2, Huh7, PLC / PRF / 5, SK-Hep1, SNU354, SNU368, SNU387, SNU398, SNU423, SNU449 and SNU475 liver cancer cell lines were obtained from Korean Cell Line Bank (KCLB, Seoul, South Korea) . THLE3 normal liver cell lines were obtained from the American-Type Culture Collection (ATCC, Manassas, VA, USA). Roy-Chowdhury (Albert Einstein College of Medicine, NY, USA) was used. All these cell lines were RPMI1640, DMEM (GenDEPOT, Barker, TX, USA) or supplemented with 10% FBS (GenDEPOT, Barker, TX, USA) and 100 units / ml penicillin-streptomycin (GenDEPOT, Barker, TX, USA) or Culture was performed using EMEM (ATCC, Manassas, VA, USA) medium. All cell lines were incubated at 37 ° C. and 5% carbon dioxide conditions. SiRNA and negative regulatory RNA duplexes for transfection were used synthesized by Bioneer (Daejeon, Korea). RNA duplexes were transfected into cell lines at a concentration of 100 nM, and all transfections were performed using Lipofectamine RNAiMAX reagent (Invitrogen, Carlsbad, Calif., USA) and were performed according to the manufacturer's instructions (TCIRG1 siRNA sequence SEQ ID NO: 4, control). siRNA sequences are shown in SEQ ID NO: 5).

④ TCGA  And GEO  Data analysis

Data was collected from the Cancer Genome Atlas Hepatocellular Carcinoma (TCGA_LIHC) project and the NCBIGEO database (Accession No. GSE14520, GSE16757, GSE22058, GSE25097, GSE36376, GSE36411, GSE45436, GSE77314, and GSE89337) to reconstruct the expression level of TCIRG1 mRNA in HCC. . TCGA mRNA expression data was also accessed using cBioPortal on the Cancer Genomics website (http://www.cbioportal.org/public-portal/). For each gene, a provisional RNASeq V2 RSEM z-score was used. The z score represents the normalized relative expression level and was used as a substitute for mRNA level.

⑤ RNA isolation and qRT - PCR  analysis

Total RNA was isolated from frozen liver cancer tissues and liver cancer cell lines using TRIzol reagent. mRNA specific cDNA synthesis was performed using a Tetro cDNA synthesis kit (Bioline). qRT-PCR was performed using the SensiFAST ™ SYBR® NoROX Kit (Bioline). Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as an endogenous control to normalize the difference in the total amount of cDNA added to each reaction.

⑥ Weston Blot  analysis

Tissue proteins and whole cell lysates were prepared using RIPA butter containing PMSF (phenylmethane-sulfonylfluoride) and 1X protease inhibitor cocktail tablets (Roche, Indianapolis, IN, USA). Total protein was electrophoresed on SDS-PAGE, electrophoresed with PVDF membrane, followed by blocking reaction with blocking buffer (5% skimmed milk in Tris-buffered saline, 0.1% Tween-20), followed by anti-TCIRG1, anti-Snail (both from Abcam, Cambridge, MA, USA), anti-GAPDH, anti-fibronectin (both from Santa Cruz Biotechnology, Santa Cruz, CA, USA), anti-E-cadherin, anti-N-cadherin (both from BD Transduction, San Jose, Calif., USA), anti-Vimentin and anti-Slug (both from Cell Signaling Technology, Danvers, MA, USA). Subsequently, the chemiluminescence signal was detected using Immobilon ^TM horseradish peroxidase substrate (Millipore, Billerica, MA, USA), and visualized using aLAS-4000 image analyzer (FujiPhoto Film Co., Tokyo, Japan).

⑦ Colony formation  analysis( Clonogenic  assay)

Cells were transfected by treatment with TCIRG1 siRNA in cells cultured in 60 mm ² cell culture plates. After transfection, 12 hours later, the cells were dispensed into 6 well plates again with 1 × 10 ³ and 2 × 10 ³ cell numbers and further incubated for 2 weeks. Cells were then washed with PBS buffer and fixed at room temperature for 1% paraformaldehyde for 30 minutes. Fixed cells were stained for 1 hour at room temperature with 0.5% crystal violet, and the number of colonies formed was analyzed using the clone counter program.

⑧ Cell viability

Cells were aliquoted into 6-well plates, transfected with negative control siRNA or TCIRG1 siRNA, incubated for 72 hours, and then cells were collected by trypsin treatment. Thereafter, the cells were stained with trypan blue solution, and counted by observing the stained cells using a hematocytometer (Marienfeld Superior, Lauda Konigshofen, Germany).

⑨ Cell proliferation analysis

Cells were aliquoted into 12-well plates for transfection. After transfection, the cells were reacted with 5 mg / ml of MTT [3- (4,5-dimethylthiazol-2-yl) -2,5-diphenyltetrazolium bromide] reagent for 1 hour. Dark blue formazan product formed by living cells was dissolved in dimethyl sulfoxide (DMSO; Sigma-Aldrich) and assayed for cell proliferation by measuring absorbance using a VICTOR3 ™ Multilabel plate reader (PerkinElmer, Boston, MA, USA). It was.

⑩ FACS  Fluorescence-activated cell sorting

For analysis of cell distribution, cells were divided into 60 mm ² cell culture plates, transfected with negative control siRNA and TCIRG1 siRNA, respectively, cultured for 72 hours, and then cells were collected via trypsin treatment. The collected cells were fixed with 70% ethanol and washed with PBS buffer, then 1 mg / mL RNase (Sigma-Aldrich), 0.05% Triton X-100 and 50 ug / mL propidium iodide (BD Biosciences, San Jose, CA, USA) and suspended in 200 ul PBS buffer. The suspended cells were incubated for 1 hour at 37 ° C. in the absence of carbon dioxide, and then analyzed by FACS Caliburflow cytometer (BD Biosciences) equipped with FLOWJO software (Tree Star, Ashland, OR, USA).

In addition, the degree of programmed cell death was analyzed using Annexin V-fluorescein isothiocynate (FITC) Apoptosis Detection Kit I (BD Biosciences, San Diego, Calif., USA). To this end, the cells were transfected with negative control siRNA and TCIRG1 siRNA, respectively, as described above, cells were collected with trypsin, washed with PBS, and then suspended with 1 × binding buffer (1 × 10 6 cells / mL). 100 uL containing 1 × 10 ⁵ cell numbers were transferred to 5 mL cell culture tubes. Then, 5 ul of Annexin V-FITC and 5 ul of propidium iodide (PI) solution were added to the cell culture tube and incubated under dark conditions for 15 minutes at room temperature. After incubation, 400 ul of 1 × binding buffer was placed in each tube, and the fraction causing cell death was identified using a FACSCanto flow cytometer (BD Biosciences).

이동 cell migration and infiltration assays Motilityand  invasion assay

Cell migration and infiltration assays were performed in vitro, cell migration was performed by a modified Boyden chamber assay (BD Bioscience), and infiltration analysis was performed using Matrigel (BD Biosciences). Matrigel was diluted with coating buffer to a concentration of 0.3 mg / ml for infiltration analysis. The diluted Matrigel solution dispensed with 100ul was then covered with a portion of the transwell cell culture insert, incubated at 37 ° C. for 2 hours, and then the insert (insert) was prepared for seeding. When insert preparation was thus completed, cells were applied to the top surface of the transwell insert and the cell-applied inserts were placed in a 24-well plate. The lower cells were used by adding 2% FBS as a chemical attractant. Cells were incubated overnight and then stained using Diff-Quik stain kit (Sysmex, Chuo-ku, Cobe, Japan). Cell images were observed using an Axiovert 200 inverted microscope (Zeiss, Oberkochen, Germany) at 200 × magnification and counted cell numbers in three random image fields.

⑫ lung metastasis mouse model

To prepare a lung metastasis mouse model, 3ul of ras-transformed NIH-3T3 cells transfected with negative control siRNA and TCIRG1 siRNA, respectively, were mixed with 0.1 ml of PBS and intravenously injected into the tail of a 5 week-old male thymus-free male nude mouse. The mice were examined daily after injection and 12 days after intravenous injection, mice were anesthetized for micro-computed tomography (Micro-CT) imaging. Mice were placed on scanner beds and micro CT images were acquired using Triumph II PET / CT System equipment (Trifoil Imaging, Chatsworth, CA, USA). Images were reconstructed and quantified total lung tumor volume per mouse using MicroView analysis software (GE Healthcare, Pittsburgh, PA, USA). Mice were sacrificed to obtain lung images after CT imaging and the number of nodules on the lung surface was calculated.

⑬ Statistical analysis

All experiments were performed at least three times and all samples analyzed in triplicate. Results are expressed as mean ± standard deviation (SD). Statistical differences between groups were evaluated by unpaired bilateral Student's t-test using Graphpad ™ 5.0 (GraphPad software Inc., San Diego, Calif., USA). P values less than 0.05 were considered statistically significant and Receiver operating characteristic curve (ROC) analysis was performed with MedCalc version 12.1.4.0 (MedCalc Software, Mariakerke, Belgium). Continuous variables were judged as mean ± SE and interquartile range, and categorical variables as numbers and percentages. Categorical variables were judged by number and percentage, and epilepsy and multivariate regression analysis were performed to identify independent predictors of hepatocellular carcinoma patients. All preoperative predictors identified as significant at the 2-tail nominal probability value <0.05 in univariate regression were entered into the multivariate logistic regression model.

< Example  1>

Hepatocellular carcinoma  Large Gene Identification Associated with Relapse

Liver transplantation is the most ideal treatment for HCC (hepatocellular carcinoma), but the fatal problem of recurrence and metastasis remains the most common after liver transplantation. Therefore, it is necessary to develop molecular markers to determine the possibility of HCC metastasis and recurrence in primary tumors. To this end, we secured 56 HCC tissues from patients who had partial or total liver resection and performed transcriptomic analysis to identify gene expression patterns associated with relapse after liver resection. A total of 56 hepatocellular carcinoma tissues included 9 recurrent cancer tissues from 36 total liver resection patients and 15 cancer tissues from patients with relapsed cancer among 20 partial hepatic resections. (See Table 1 below).

Table 1 Number of Recurrent Patients with Liver Resection

For analysis, hierarchical clustering analysis of 7,550 gene elements was performed, and statistical analysis was performed between the non-recurring group (FIG. 1A, green notation group) and the relapse group (FIG. 1A, yellow notation group) (first-order ANOVA test). , p <0.05), and as a result, were grouped into two distinct subcluster groups within the dendrogram, the non-cancer recurrence group and the cancer relapse group. Reanalysis using both hepatic resection groups showed distinct clusters showing recurrence-related molecular markers in both relapse groups in dendrograms (see FIG. 1A, top right and bottom). These analyzes identified the differentially expressed genes (DEGs) in each patient in the Welch's t test for total liver resection (6,682 gene elements) and partial liver resection (2,036). Subsequently, gene expression patterns were analyzed by Venn diagram analysis of tissues obtained from whole liver resection and partial liver resection. As a result, 422 gene elements were identified as molecules with common expression patterns in all of these groups ( 1b). In addition, these 422 gene elements were excluded from 6,682 gene elements because recurrence may occur after partial liver resection in cancerous cells of degenerative nodules of precancerous lesions. In addition, volcanic plot analysis (p <0.05 and 1.3-fold up-regulated) of total hepatocellular carcinoma tissues revealed that over 2,760 genes were overexpressed in the relapsed cancer group compared to the non-recurred liver cell cancer group. It was confirmed that the presence (see Fig. 1c). Finally, to identify genetic elements specific for recurrence of liver cancer, a comparative analysis was performed with the GSE39791 data set to identify genetic predictors of recurrence patterns of liver cancer in the NCBI GEO database. As a result, 953 gene elements were identified as the validated recurrence associated molecules (see FIG. 1D).

Next, GSEA (gene set enrichment analysis) analysis was performed on 953 gene elements in order to investigate the biological relevance of the cancer recurrence-related genes identified by the above analysis. This analysis was able to identify intracellular signal transduction pathways of the 953 gene associated with recurrence of HCC, and LIAO_METASTASIS was identified as a very important gene as a recurrent molecular marker (see FIGS. 1E and 1F).

< Example  2>

Hepatocellular Carcinoma after Tissue Resection TCIRG1  Expression Analysis

Of the 953 hepatocellular carcinoma-associated molecular markers, the TCIRG1 gene was shown to be significantly overexpressed in the TCGA_LIHC data. This database contains a gene expression (mRNA) data set of 50 non-tumor liver tissues and 373 HCC tissues, and includes 50 pairs of matched sets (50 HCCs correspond to uncultured tissues). The matched sets also showed significant differences between the non-cancer and HCC groups. Interestingly, the expression of the TCIRG1 gene in a subset of hepatocellular carcinoma, defined by Edmondson grades I-II (G1-G2, n = 225) and III-VI (G3-G4, n = 132), was expressed in G1-G2. It was shown to be significantly overexpressed in G3-G4 as compared to (see FIG. 2A). Overexpression of TCIRG1 in HCC compared the expression levels of TCIRG1 genes in various GEO datasets (accession numbers GSE14520, GSE16757, GSE22058, GSE25097, GSE36376, GSE36411, GSE45436, and GSE89337), and the data were expressed as scatter polts (see FIG. 2I). ). Since TCIRG1 expression was upregulated (overexpressed) in patients with TCGA_LIHC tumors, we analyzed the prognostic relevance of TCIRG1 expression in HCC patients using TCGA_LIHC data in cBioPortal (www.cbioportal.org). % Showed overexpression of the TCIRG1 gene. The Kaplan-Meier survival curves of HCC patients showed that the 5-year disease free survival (DFS) of patients with increased TCIRG1 expression was significantly lower than that of HCC patients without TCIRG1 expression change (see FIG. 2B).

Furthermore, the present inventors compared and analyzed the ROC curve to verify whether TCIRG1 can be used as a prognostic predictor biomarker for HCC after liver resection (see FIG. 2C). As a result, the area under curve (AUC) was 0.74 in the TCGA_LIHC group and 0.74 in the GSE39791 group. This suggests the possibility of use as a potential biomarker for the diagnosis of HCC. In addition, TCIRG1 expression in matching sets (GSE39791 and GSE77314) providing gene expression information in two HCC patient cohorts was found to be significantly overexpressed in hepatocellular carcinoma tissue (HCC) compared to non-tumor tissue (FIG. 2J). Reference). TCIRG1 gene expression was significantly overexpressed in high grade HCC patient groups (G3-G4, see FIG. 2A). Consistently, TCIRG1 expression was significantly overexpressed in HCC patient group (ovHCC, n = 26), which was more apparent than normal liver tissue (normal, n = 13) or early HCC (eHCC, n = 25) tissue (see FIG. 2K). In addition, differential gene expression analysis according to non-recurrence or recurrence in the same patient group (GSE89337) showed that TCIRG1 was significantly overexpressed in patients with recurrent hepatocellular carcinoma after total liver resection (Fig. 1k, right).

To confirm overexpression of TCIRG1 in HCC patients, expression levels of TCIRG1 were analyzed by qRT-PCR in 35 randomly selected hepatocellular carcinomas paired with adjacent noncancerous liver tissue. As a result, 24 out of 35 HCC tissues (68.6%) showed overexpression of TCIRG1 (see FIG. 2D).

Next, in order to confirm the overexpression of TCIRG1 protein in HCC tissue, immunostaining was performed using a TCIRG1-specific antibody. As a result, the antibody positive rate for TCIRG1 in HCC tissue was 24.4% (133/546), and the positive rate for TCIRG1 in non-tumor group was 1.0% (1/100) (see FIG. 2E). The expression of TCIRG1 protein was reconfirmed by Western blot analysis in 14 randomly selected human and non-cancerous liver tissues. 2f).

In addition, multivariate logistic regression analysis of various clinical variables related to liver metastases, including TCIRG1, showed that overexpression of TCIRG1 was the strongest link among six other metastatic features (Odds ratio 1.768, p <0.001) (Table 2). Reference).

TABLE 2

Logistic Regression

In addition, the DFS rate of TCIRG1 positive patients was significantly lower in patients with negative expression for TCIRG1 in the cohort of 546 HCC patients and 285 HCC patients. (See FIGS. 2G and 2H). In other words, the cancer progression was significantly higher in the TCIRG1-positive patients in both cohorts (see Table 3 below). These results suggest that TCIRG1 is a significant marker for predicting recurrence of hepatocellular carcinoma after liver resection. do.

TABLE 3

Clinical Pathologic Features of Two Cohorts of Hepatocellular Carcinoma Patients Performing Liver Transplantation

< Example  3>

In liver cancer cell lines TCIRG1  Analysis of Tumor Suppression Effects According to Defects

Furthermore, the inventors conducted experiments on cell viability, cell proliferation, BrdU staining and colony formation in the state of knocking down TCIRG1 through RNA interference in order to further confirm the function of TCIRG1 in liver tumor formation. The expression level of TCIRG1 inherent in cells was analyzed in 14 different liver cell lines through qRT-PCR and Western blot for selection of liver cancer cell lines overexpressing TCIRG1. Cell lines were also included.

As a result, TCIRG1 expression was overexpressed in human liver cancer cell lines Hep3B, HepG2, Huh7, PLC / PRF / 5, SK-Hep1, SNU354, SNU368, SNU387, SNU398, SNU423, SNU449, and SNU475. (See FIGS. 3A and 3B).

On the other hand, in the SNU475 and Huh7 liver cancer cell lines knocked down TCIRG1 via RNA interference, both cell growth and proliferation were inhibited (see FIGS. 3C to 3F). Growth inhibition of liver cancer cells may be caused in part by disruption of cell growth regulation such as cell cycle arrest, cell aging or apoptosis following TCIRG1 targeting, and the present inventors first analyze the cell cycle effects of TCIRG1 knockdown The cell lines were transfected with TCIRG1 target siRNA (siTCIRG1) for analysis of cell death, followed by analysis with Annexin V-FITC and PI.

As a result, TCIRG1 knocked-down SNU475 and Huh7 hepatocellular carcinoma cell lines showed a decrease in the number of S and G2 / M cells and a significant increase in the number of G1 cells (see FIG. 3G). FACS analysis showed that the TCIRG1 siRNA was transfected. Infected SNU475 cells were shown to significantly induce cell death compared to cells transfected with negative control siRNA (NC) (see FIG. 3H). It has also been shown that cell death by autophagy (plots indicated by dots in the upper left section) is induced in Huh7 cells transfected with TCIRG1 siRNA. In addition, treatment with 3-methyl adenine, a specific inhibitor of autophagy, was shown to inhibit cell death due to autophagic (see FIG. 3I). These results indicate that overexpression of TCIRG1 is associated with the development of liver cancer by promoting the suppression of apoptosis by autophagy during liver cancer development.

In addition, GSEA with a molecular signal associated with relapse shows that the LIAO_METASTASIS gene contains significantly more relapse signals (see FIG. 1G). To investigate the effect of TCIRG1 on malignant tumors of liver cancer cells, cell mobility and invasion assays were performed in vitro.

As a result of the analysis, the modified Boyden chamber analysis showed that both TCIRG1 knocked down SNU475 and Huh7 cell lines significantly inhibited cell migration and invasion by chemoattractant (2% FBS) (see FIGS. 4A and 4B). In addition, the results of scratch healing analysis showed that the TCIRG1 knocked down cell population decreased the wound healing effect of hepatic cancer cells by chemoattractants compared to the control group (see FIG. 4C). Boyden chamber assay assays were performed using ras transformed NIH-3T3 cells to confirm the translocation potential of TCIRG1. As a result, TCIRG1 knockdown was found to significantly inhibit cell migration and invasion due to chemoattractants of ras transformed NIH-3T3 cells (see FIGS. 4D and 4E).

Furthermore, the present inventors confirmed the expression of EMT regulatory proteins in liver cancer cells by Western blot to confirm the regulatory effect of TCIRG1 on EMT. As a result, E-cadherin was found to be markedly increased in TNURG1 knocked down SNU475 and Huh7 cell lines, whereas N-cadherin, Fibronectin, Vimentin, Snail and Slug were decreased in the same cells (see Figure 4f).

In addition, analysis of TCIRG1 expression in two large HCC patient cohorts showed matched gene expression patterns (GSE39791 and GSE77314), and expression of E-cadherin (CDH1) was significantly reduced in hepatocellular carcinoma compared to non-tumor tissues. , TCIRG1 and E-cadherin were shown to be inverse in the same data set (see Figure 4g).

Finally, in vitro experimental metastasis analysis revealed that both TCIRG1 knockdown slows or reduces the metastasis potential of ras-transformed NIH-3T3 cells by both micro-CT imaging analysis and pulmonary tuberculosis count analysis (FIG. 5A and FIG. 5A). 5b).

Through the above experimental results, the present inventors confirmed the possibility of using TCIRG1 as a biomarker for predicting the prognosis of hepatocellular carcinoma, and furthermore, it can be used as a marker for predicting the recurrence or metastasis of hepatocellular carcinoma after surgery. In the TCIRG1 overexpressed group, the disease-free survival rate was significantly lower after surgery, indicating that the inhibitor of TCIRG1 could be used as a therapeutic agent to prevent or inhibit recurrence and metastasis of hepatocellular carcinoma.

< Example  4>

Predictable onset, progression and recurrence of liver cancer TCIRG1 Present cutoff value for expression level

Furthermore, the present inventors have confirmed that TCIRG1 expression is increased by confirming that the expression level of TCIRG1 is increased at the onset of hepatocellular carcinoma and that TCIRG1 expression is increased in the tissues of patients with recurrent liver cancer after liver resection. It was found that it can be used as a marker for, and further it can be used as a marker for predicting the progression, prognosis and the likelihood of recurrence of liver cancer. The expression level of TCIRG1 was quantified to derive a cutoff value that can provide status information on liver cancer.

<4-1> Predictable Liver Cancer Of TCIRG1  Cutoff value

In the cohort of two large liver cancer patients performed in the previous experiment, the results of ROC analysis for the hepatocellular carcinoma patient group and the non-hepatic cancer patient group were confirmed (see FIG. 2C). In TCGA_LIHC, the AUC was analyzed to be 0.74 when the patient's non-tumor tissue (Non tumor, n = 50) and advanced hepatocellular carcinoma (G2, G3, G4, n = 301) were evaluated. Therefore, the present inventors derived the TCIRG1 cut-off values for advanced liver cancer based on these derived values. More specifically, to evaluate the efficacy as a biomarker, receiver operator characteristic (ROC) curves and scatter plots were analyzed. ROC expresses the relationship between sensitivity and specificity on the two-dimensional plane. The higher the AUC (Area Uder Curve) value corresponding to the area under the ROC, the better the diagnostic method. All statistical analyzes and all scatter plots and ROCs generated were Medcalc (MedCalc, Mariakerke, Belgium, version 12.2.1).

As a result of the analysis, as shown in Figure 6a, the TCIRG1 cut-off value for advanced liver cancer was 11.0112 (cutoff value: 11.0112, log2 RSEM). Therefore, if the cutoff value is 11.0112 through quantitative analysis of the expression level of TCIRG1, it may be determined as advanced liver cancer, and it may be determined that liver cancer is more likely to metastasize.

<4-2> Predictable Liver Cancer Recurrence Of TCIRG1  Cutoff value

In this experiment, in GSE39791, the expression of TCIRG1 in most patients was evaluated in the non-tumor tissue (Non tumor, n = 72) and recurrent hepatocellular carcinoma (Tumor, n = 72) of the same patient who underwent liver resection. Hepatocellular carcinoma tissues were higher than non-cultured tissues, and ROC analysis showed a value of AUC = 0.64. As a result, the cut-off value was derived based on the above value. As shown in FIG. 6B, the cut-off value of TCIRG1 was found to be 8.25 (8.25, log2 expression).

Therefore, if the cutoff value for the TCIRG1 expression level is 8.25, it may be determined that hepatocellular carcinoma may recur after liver resection.

<4-3> Stages of Hepatocellular Carcinoma Of TCIRG1  Cutoff value

Cancer tissues of patients with stages of hepatocellular carcinoma (G1, G2, G3, G4) were obtained, quantitatively analyzed for TCIRG1 expression levels and cutoff values were derived.

For reference, the above experiments confirmed that the expression of TCIRG1 was high as the stage of liver cancer was high in the TCGA_LIHC cohort. As a result of analyzing cutoff values for TCIRG1 according to the progression of each hepatocellular carcinoma, the cut-off value of TCIRG1 expression in G3 (stage 3 liver cancer) and G4 (stage 4 liver cancer) was 11.3794 (log2 RSEM) (FIG. 6C). Reference).

Therefore, if the cutoff value of 11.3794 for the amount of TCIRG1 expression in advanced liver cancer, it may be determined that the terminal liver cancer, that is, stage 4 liver cancer.

In addition, the cut-off values of normal-to-intermediate cancer (eHCC)-> medium-term cancer (avHCC) for the stage of hepatocellular carcinoma showed that the cut-off value of normal and early cancer (eHCC) was 6.2821. The cut-off value was 6.4371 in early cancer (eHCC) and intermediate cancer (avHCC) (see FIG. 6D).

Therefore, through these results, the cutoff value for the amount of TCIRG1 expression can be determined as early liver cancer when the 6.2821, it can be determined as a medium-term cancer in the case of 6.4371.

<4-4> Prognosis after Liver Resection Of TCIRG1  Cutoff value

Finally, the expression level of TCIRG1 was measured to determine the prognosis for patients after liver resection, and the expression level of TCIRG1 was measured in tumor tissues with recurrence of hepatocellular carcinoma and non-recurring tissue after liver resection. The value was derived.

As a result, as shown in FIG. 6E, it was confirmed that TCIRG1 expression levels in liver tissue recurred after liver resection were significantly increased compared to those in which liver cancer did not recur. The TCIRG1 expression amount cutoff value of was 2.5687.

Therefore, if the cutoff value of TCIRG1 for the tissue obtained from the patient is 2.5687 after liver resection, it may be determined that the probability of recurrence of liver cancer is high and the prognosis is poor.

So far I looked at the center of the preferred embodiment for the present invention. Those skilled in the art will appreciate that the present invention can be implemented in a modified form without departing from the essential features of the present invention. Therefore, the disclosed embodiments should be considered in descriptive sense only and not for purposes of limitation. The scope of the present invention is shown in the claims rather than the foregoing description, and all differences within the scope will be construed as being included in the present invention.

<110> THE CATHOLIC UNIVERSITY OF KOREA INDUSTRY-ACADEMIC COOPERATION FOUNDATION <120> TCIRG1 biomarker for diagnosing recurrent and prognosis of liver          cancer and use <130> PN1706-208 <160> 5 <170> KoPatentIn 3.0 <210> 1 <211> 2727 <212> DNA <213> Artificial Sequence <220> <223> TCIRG1 cDNA sequence <400> 1 cgcctgcccg gaaaggagtg agcggcgcct agtcccgggc tggcgggagt gcagttctga 60 gtcccgcccg gcgtgcgcgg agcggggcag ccagcagcgg aggcgcggcg cgcagcacac 120 ccggggacca tgggctccat gttccggagc gaggaggtgg ccctggtcca gctctttctg 180 cccacagcgg ctgcctacac ctgcgtgagt cggctgggcg agctgggcct cgtggagttc 240 agagacctca acgcctcggt gagcgccttc cagagacgct ttgtggttga tgttcggcgc 300 tgtgaggagc tggagaagac cttcaccttc ctgcaggagg aggtgcggcg ggctgggctg 360 gtcctgcccc cgccaaaggg gaggctgccg gcacccccac cccgggacct gctgcgcatc 420 caggaggaga cggagcgcct ggcccaggag ctgcgggatg tgcggggcaa ccagcaggcc 480 ctgcgggccc agctgcacca gctgcagctc cacgccgccg tgctacgcca gggccatgaa 540 cctcagctgg cagccgccca cacagatggg gcctcagaga ggacgcccct gctccaggcc 600 cccggggggc cgcaccagga cctgagggtc aactttgtgg caggtgccgt ggagccccac 660 aaggcccctg ccctagagcg cctgctctgg agggcctgcc gcggcttcct cattgccagc 720 ttcagggagc tggagcagcc gctggagcac cccgtgacgg gcgagccagc cacgtggatg 780 accttcctca tctcctactg gggtgagcag atcggacaga agatccgcaa gatcacggac 840 tgcttccact gccacgtctt cccgtttctg cagcaggagg aggcccgcct cggggccctg 900 cagcagctgc aacagcagag ccaggagctg caggaggtcc tcggggagac agagcggttc 960 ctgagccagg tgctaggccg ggtgctgcag ctgctgccgc cagggcaggt gcaggtccac 1020 aagatgaagg ccgtgtacct ggccctgaac cagtgcagcg tgagcaccac gcacaagtgc 1080 ctcattgccg aggcctggtg ctctgtgcga gacctgcccg ccctgcagga ggccctgcgg 1140 gacagctcga tggaggaggg agtgagtgcc gtggctcacc gcatcccctg ccgggacatg 1200 ccccccacac tcatccgcac caaccgcttc acggccagct tccagggcat cgtggatgcc 1260 tacggcgtgg gccgctacca ggaggtcaac cccgctccct acaccatcat caccttcccc 1320 ttcctgtttg ctgtgatgtt cggggatgtg ggccacgggc tgctcatgtt cctcttcgcc 1380 ctggccatgg tccttgcgga gaaccgaccg gctgtgaagg ccgcgcagaa cgagatctgg 1440 cagactttct tcaggggccg ctacctgctc ctgcttatgg gcctgttctc catctacacc 1500 ggcttcatct acaacgagtg cttcagtcgc gccaccagca tcttcccctc gggctggagt 1560 gtggccgcca tggccaacca gtctggctgg agtgatgcat tcctggccca gcacacgatg 1620 cttaccctgg atcccaacgt caccggtgtc ttcctgggac cctacccctt tggcatcgat 1680 cctatttgga gcctggctgc caaccacttg agcttcctca actccttcaa gatgaagatg 1740 tccgtcatcc tgggcgtcgt gcacatggcc tttggggtgg tcctcggagt cttcaaccac 1800 gtgcactttg gccagaggca ccggctgctg ctggagacgc tgccggagct caccttcctg 1860 ctgggactct tcggttacct cgtgttccta gtcatctaca agtggctgtg tgtctgggct 1920 gccagggccg cctcggcccc cagcatcctc atccacttca tcaacatgtt cctcttctcc 1980 cacagcccca gcaacaggct gctctacccc cggcaggagg tggtccaggc cacgctggtg 2040 gtcctggcct tggccatggt gcccatcctg ctgcttggca cacccctgca cctgctgcac 2100 cgccaccgcc gccgcctgcg gaggaggccc gctgaccgac aggaggaaaa caaggccggg 2160 ttgctggacc tgcctgacgc atctgtgaat ggctggagct ccgatgagga aaaggcaggg 2220 ggcctggatg atgaagagga ggccgagctc gtcccctccg aggtgctcat gcaccaggcc 2280 atccacacca tcgagttctg cctgggctgc gtctccaaca ccgcctccta cctgcgcctg 2340 tgggccctga gcctggccca cgcccagctg tccgaggttc tgtgggccat ggtgatgcgc 2400 ataggcctgg gcctgggccg ggaggtgggc gtggcggctg tggtgctggt ccccatcttt 2460 gccgcctttg ccgtgatgac cgtggctatc ctgctggtga tggagggact ctcagccttc 2520 ctgcacgccc tgcggctgca ctgggtggaa ttccagaaca agttctactc aggcacgggc 2580 tacaagctga gtcccttcac cttcgctgcc acagatgact agggcccact gcaggtcctg 2640 ccagacctcc ttcctgacct ctgaggcagg agaggaataa agacggtccg ccctggcagt 2700 gaaaaaaaaa aaaaaaaaaa aaaaaaa 2727 <210> 2 <211> 2486 <212> DNA <213> Artificial Sequence <220> <223> TCIRG1 cDNA sequence <400> 2 ggacgcccct gctccaggcc cccggggggc cgcaccagga cctgagggtc aagtgagtga 60 gggatgacct catgcccttt ctggccagcc cagaacccct ggccagtcgc tgggctgggc 120 caggctgagc tccgactcct tgtccagtgc tctccccagg ctggccccgc ctcctccttc 180 aggcccggaa cttcccacag tcccaagccc tagccctagg gggttctcct cttctggtcc 240 tgcccgggag gcctcctgcc ttcccctgtg ggcagggcca gtgtgcccaa ttgcccgatt 300 gcccgtgctg ggcagggtcc tgcccggggg gcctggtggg ggaggcaggg caggaggttg 360 gagcagccct gcccagcccc gtggccgcca gctttgtggc aggtgccgtg gagccccaca 420 aggcccctgc cctagagcgc ctgctctgga gggcctgccg cggcttcctc attgccagct 480 tcagggagct ggagcagccg ctggagcacc ccgtgacggg cgagccagcc acgtggatga 540 ccttcctcat ctcctactgg ggtgagcaga tcggacagaa gatccgcaag atcacggact 600 gcttccactg ccacgtcttc ccgtttctgc agcaggagga ggcccgcctc ggggccctgc 660 agcagctgca acagcagagc caggagctgc aggaggtcct cggggagaca gagcggttcc 720 tgagccaggt gctaggccgg gtgctgcagc tgctgccgcc agggcaggtg caggtccaca 780 agatgaaggc cgtgtacctg gccctgaacc agtgcagcgt gagcaccacg cacaagtgcc 840 tcattgccga ggcctggtgc tctgtgcgag acctgcccgc cctgcaggag gccctgcggg 900 acagctcgat ggaggaggga gtgagtgccg tggctcaccg catcccctgc cgggacatgc 960 cccccacact catccgcacc aaccgcttca cggccagctt ccagggcatc gtggatgcct 1020 acggcgtggg ccgctaccag gaggtcaacc ccgctcccta caccatcatc accttcccct 1080 tcctgtttgc tgtgatgttc ggggatgtgg gccacgggct gctcatgttc ctcttcgccc 1140 tggccatggt ccttgcggag aaccgaccgg ctgtgaaggc cgcgcagaac gagatctggc 1200 agactttctt caggggccgc tacctgctcc tgcttatggg cctgttctcc atctacaccg 1260 gcttcatcta caacgagtgc ttcagtcgcg ccaccagcat cttcccctcg ggctggagtg 1320 tggccgccat ggccaaccag tctggctgga gtgatgcatt cctggcccag cacacgatgc 1380 ttaccctgga tcccaacgtc accggtgtct tcctgggacc ctaccccttt ggcatcgatc 1440 ctatttggag cctggctgcc aaccacttga gcttcctcaa ctccttcaag atgaagatgt 1500 ccgtcatcct gggcgtcgtg cacatggcct ttggggtggt cctcggagtc ttcaaccacg 1560 tgcactttgg ccagaggcac cggctgctgc tggagacgct gccggagctc accttcctgc 1620 tgggactctt cggttacctc gtgttcctag tcatctacaa gtggctgtgt gtctgggctg 1680 ccagggccgc ctcggccccc agcatcctca tccacttcat caacatgttc ctcttctccc 1740 acagccccag caacaggctg ctctaccccc ggcaggaggt ggtccaggcc acgctggtgg 1800 tcctggcctt ggccatggtg cccatcctgc tgcttggcac acccctgcac ctgctgcacc 1860 gccaccgccg ccgcctgcgg aggaggcccg ctgaccgaca ggaggaaaac aaggccgggt 1920 tgctggacct gcctgacgca tctgtgaatg gctggagctc cgatgaggaa aaggcagggg 1980 gcctggatga tgaagaggag gccgagctcg tcccctccga ggtgctcatg caccaggcca 2040 tccacaccat cgagttctgc ctgggctgcg tctccaacac cgcctcctac ctgcgcctgt 2100 gggccctgag cctggcccac gcccagctgt ccgaggttct gtgggccatg gtgatgcgca 2160 taggcctggg cctgggccgg gaggtgggcg tggcggctgt ggtgctggtc cccatctttg 2220 ccgcctttgc cgtgatgacc gtggctatcc tgctggtgat ggagggactc tcagccttcc 2280 tgcacgccct gcggctgcac tgggtggaat tccagaacaa gttctactca ggcacgggct 2340 acaagctgag tcccttcacc ttcgctgcca cagatgacta gggcccactg caggtcctgc 2400 cagacctcct tcctgacctc tgaggcagga gaggaataaa gacggtccgc cctggcagtg 2460 aaaaaaaaaa aaaaaaaaaa aaaaaa 2486 <210> 3 <211> 830 <212> PRT <213> Artificial Sequence <220> <223> TCIRG1 amino acid <400> 3 Met Gly Ser Met Phe Arg Ser Glu Glu Val Ala Leu Val Gln Leu Phe   1 5 10 15 Leu Pro Thr Ala Ala Ala Tyr Thr Cys Val Ser Arg Leu Gly Glu Leu              20 25 30 Gly Leu Val Glu Phe Arg Asp Leu Asn Ala Ser Val Ser Ala Phe Gln          35 40 45 Arg Arg Phe Val Val Asp Val Arg Arg Cys Glu Glu Leu Glu Lys Thr      50 55 60 Phe Thr Phe Leu Gln Glu Glu Val Arg Arg Ala Gly Leu Val Leu Pro  65 70 75 80 Pro Pro Lys Gly Arg Leu Pro Ala Pro Pro Pro Arg Asp Leu Leu Arg                  85 90 95 Ile Gln Glu Glu Thr Glu Arg Leu Ala Gln Glu Leu Arg Asp Val Arg             100 105 110 Gly Asn Gln Gln Ala Leu Arg Ala Gln Leu His Gln Leu Gln Leu His         115 120 125 Ala Ala Val Leu Arg Gln Gly His Glu Pro Gln Leu Ala Ala Ala His     130 135 140 Thr Asp Gly Ala Ser Glu Arg Thr Pro Leu Leu Gln Ala Pro Gly Gly 145 150 155 160 Pro His Gln Asp Leu Arg Val Asn Phe Val Ala Gly Ala Val Glu Pro                 165 170 175 His Lys Ala Pro Ala Leu Glu Arg Leu Leu Trp Arg Ala Cys Arg Gly             180 185 190 Phe Leu Ile Ala Ser Phe Arg Glu Leu Glu Gln Pro Leu Glu His Pro         195 200 205 Val Thr Gly Glu Pro Ala Thr Trp Met Thr Phe Leu Ile Ser Tyr Trp     210 215 220 Gly Glu Gln Ile Gly Gln Lys Ile Arg Lys Ile Thr Asp Cys Phe His 225 230 235 240 Cys His Val Phe Pro Phe Leu Gln Gln Glu Glu Ala Arg Leu Gly Ala                 245 250 255 Leu Gln Gln Leu Gln Gln Gln Ser Gln Glu Leu Gln Glu Val Leu Gly             260 265 270 Glu Thr Glu Arg Phe Leu Ser Gln Val Leu Gly Arg Val Leu Gln Leu         275 280 285 Leu Pro Pro Gly Gln Val Gln Val His Lys Met Lys Ala Val Tyr Leu     290 295 300 Ala Leu Asn Gln Cys Ser Val Ser Thr Thr His Lys Cys Leu Ile Ala 305 310 315 320 Glu Ala Trp Cys Ser Val Arg Asp Leu Pro Ala Leu Gln Glu Ala Leu                 325 330 335 Arg Asp Ser Ser Met Glu Glu Gly Val Ser Ala Val Ala His Arg Ile             340 345 350 Pro Cys Arg Asp Met Pro Pro Thr Leu Ile Arg Thr Asn Arg Phe Thr         355 360 365 Ala Ser Phe Gln Gly Ile Val Asp Ala Tyr Gly Val Gly Arg Tyr Gln     370 375 380 Glu Val Asn Pro Ala Pro Tyr Thr Ile Ile Thr Phe Pro Phe Leu Phe 385 390 395 400 Ala Val Met Phe Gly Asp Val Gly His Gly Leu Leu Met Phe Leu Phe                 405 410 415 Ala Leu Ala Met Val Leu Ala Glu Asn Arg Pro Ala Val Lys Ala Ala             420 425 430 Gln Asn Glu Ile Trp Gln Thr Phe Phe Arg Gly Arg Tyr Leu Leu Leu         435 440 445 Leu Met Gly Leu Phe Ser Ile Tyr Thr Gly Phe Ile Tyr Asn Glu Cys     450 455 460 Phe Ser Arg Ala Thr Ser Ile Phe Pro Ser Gly Trp Ser Val Ala Ala 465 470 475 480 Met Ala Asn Gln Ser Gly Trp Ser Asp Ala Phe Leu Ala Gln His Thr                 485 490 495 Met Leu Thr Leu Asp Pro Asn Val Thr Gly Val Phe Leu Gly Pro Tyr             500 505 510 Pro Phe Gly Ile Asp Pro Ile Trp Ser Leu Ala Ala Asn His Leu Ser         515 520 525 Phe Leu Asn Ser Phe Lys Met Lys Met Ser Val Ile Leu Gly Val Val     530 535 540 His Met Ala Phe Gly Val Val Leu Gly Val Phe Asn His Val His Phe 545 550 555 560 Gly Gln Arg His Arg Leu Leu Leu Glu Thr Leu Pro Glu Leu Thr Phe                 565 570 575 Leu Leu Gly Leu Phe Gly Tyr Leu Val Phe Leu Val Ile Tyr Lys Trp             580 585 590 Leu Cys Val Trp Ala Ala Arg Ala Ala Ser Ala Pro Ser Ile Leu Ile         595 600 605 His Phe Ile Asn Met Phe Leu Phe Ser His Ser Pro Ser Asn Arg Leu     610 615 620 Leu Tyr Pro Arg Gln Glu Val Val Gln Ala Thr Leu Val Val Leu Ala 625 630 635 640 Leu Ala Met Val Pro Ile Leu Leu Leu Gly Thr Pro Leu His Leu Leu                 645 650 655 His Arg His Arg Arg Arg Leu Arg Arg Arg Pro Ala Asp Arg Gln Glu             660 665 670 Glu Asn Lys Ala Gly Leu Leu Asp Leu Pro Asp Ala Ser Val Asn Gly         675 680 685 Trp Ser Ser Asp Glu Glu Lys Ala Gly Gly Leu Asp Asp Glu Glu Glu     690 695 700 Ala Glu Leu Val Pro Ser Glu Val Leu Met His Gln Ala Ile His Thr 705 710 715 720 Ile Glu Phe Cys Leu Gly Cys Val Ser Asn Thr Ala Ser Tyr Leu Arg                 725 730 735 Leu Trp Ala Leu Ser Leu Ala His Ala Gln Leu Ser Glu Val Leu Trp             740 745 750 Ala Met Val Met Arg Ile Gly Leu Gly Leu Gly Arg Glu Val Gly Val         755 760 765 Ala Ala Val Val Leu Val Pro Ile Phe Ala Ala Phe Ala Val Met Thr     770 775 780 Val Ala Ile Leu Leu Val Met Glu Gly Leu Ser Ala Phe Leu His Ala 785 790 795 800 Leu Arg Leu His Trp Val Glu Phe Gln Asn Lys Phe Tyr Ser Gly Thr                 805 810 815 Gly Tyr Lys Leu Ser Pro Phe Thr Phe Ala Ala Thr Asp Asp             820 825 830 <210> 4 <211> 19 <212> RNA <213> Artificial Sequence <220> <223> TCIRG1 siRNA <400> 4 caccuucgcu gccacagau 19 <210> 5 <211> 19 <212> RNA <213> Artificial Sequence <220> <223> control siRNA <400> 5 ccuacgccac caauuucgu 19

Claims (16)

TCIRG1 (T-Cell Immune Regulator 1) gene comprising a preparation for measuring the expression level of mRNA or TCIRG1 protein, liver cancer diagnostic or prognostic composition. The method of claim 1,
The TCIRG1 gene is composed of the nucleotide sequence of SEQ ID NO: 1 or 2, TCIRG1 protein, characterized in that consisting of the amino acid sequence of SEQ ID NO: 3, liver cancer diagnosis or prognostic composition. The method of claim 1,
Said agent is a primer, probe, aptamer or antibody specific for TCIRG1, liver cancer diagnosis or prognostic composition. The method of claim 1,
The measurement was performed by reverse transcription polymerase chain reaction, competitive polymerase chain reaction, real time polymerase chain reaction, Nuclease protection assay (RNase, S1 nuclease assay), in situ hybridization, DNA microarray method, Northern blot, Western blot, ELISA ( Enzyme Linked Immuno Sorbent Assay), radioimmunoassay, immunodiffusion, immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, complement fixation assay, FACS, mass spectrometry and protein microarray use. Characterized in that for liver cancer diagnosis or prognosis prediction composition. The method of claim 1,
The liver cancer diagnosis or prognosis prediction is characterized in that the progress, recurrence, metastasis and prognostic evaluation of liver cancer, liver cancer diagnosis or prognostic composition. Claim 1, comprising a composition according to claim, liver cancer diagnosis or prognosis diagnostic kit. The method of claim 6,
The kit is any one or more selected from a microarray, a gene amplification kit, an immunoassay kit, a luminex assay kit, a protein microarray kit, and an ELISA kit, liver cancer diagnosis or prognostic kit. Measuring the expression level of mRNA or TCIRG1 protein of the T-Cell Immune Regulator 1 (TCIRG1) gene from a biological sample isolated from the patient; And
Comparing the measured expression level of TCIRG1 with the expression level of the gene of the control sample, Information providing method for diagnosing liver cancer. The method of claim 8,
The sample is tissue, whole blood, serum or plasma, characterized in that, providing information for diagnosing liver cancer. The method of claim 8,
Comparing the measured expression level of the TCIRG1 with the expression level of the gene of the control sample, characterized in that performed by the standard or cut-off (cut-off) value, information providing method for diagnosing liver cancer. The method of claim 8,
The information providing method is characterized in that, when the expression level of TCIRG1 is increased than the expression level in the control sample, it is determined that the prognosis is not good because of a high probability of recurrence, tumor growth or metastasis of liver cancer, method for providing information for diagnosing liver cancer . The method of claim 8,
The providing method is characterized in that the cutoff value for determining the possibility of metastasis of liver cancer is 11.0112, information providing method for diagnosing liver cancer. The method of claim 8,
The providing method is characterized in that the cutoff value for the early liver cancer determination is 6.2821, the cutoff value for the intermediate liver cancer determination is 6.4371, the cutoff value for the terminal liver cancer determination is 11.3794, providing information for diagnosing liver cancer Way. The method of claim 8,
The information providing method, characterized in that the cut-off value for determining the recurrence of liver cancer is 2.5687, information providing method for diagnosing liver cancer. TCIRG1 (T-Cell Immune Regulator 1) comprising a siRNA consisting of the nucleotide sequence of SEQ ID NO: 4 complementary to the gene as an active ingredient, pharmaceutical composition for inhibiting metastasis and recurrence of liver cancer.
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