KR20200101854A - A screening method for anti-cancer agents - Google Patents

Abstract

The present invention relates to a screening method of anti-cancer agents, the method comprising the steps of (a) measuring expression level of mRNA or protein thereof of one or more genes selected from a group consisting of EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, or ZCCHC18 in a biological sample; and (b) adding a candidate material to the biological sample in the step (a), and selecting the candidate material as an anti-cancer agent when there is a change in the expression level of the mRNA or protein thereof of said genes. The present invention further relates to a pharmaceutical composition for prevention or treatment of cancer, the composition comprising the component capable of regulating expression level of mRNA or protein thereof of said genes, as an effective component.

Description

Anticancer drug selection method {A SCREENING METHOD FOR ANTI-CANCER AGENTS}

The present invention relates to a method for screening an anticancer agent.

Cancer is a major disease that accounts for the number 1 cause of death in Korea, and although numerous studies have been conducted to conquer cancer, it is an incurable disease that has not been conquered. Treatments for diagnosed cancer generally include surgery, chemotherapy, and radiation therapy, but each method has many limitations. In addition, the possibility of recurrence is quite high even after cancer has been treated, and the sensitivity to anticancer drugs varies greatly depending on the individual, so it is essential to predict the prognosis and anticancer drug sensitivity of cancer patients in determining the treatment direction of cancer patients.

In particular, ovarian cancer has a very low survival rate after distant metastasis has progressed, and ovarian cancer has a very low cure rate because early diagnosis is difficult and peritoneal metastasis is severe. In addition, ovarian cancer is particularly difficult to find a suitable drug because the genetic diversity is very deep compared to other cancers. This is because recurrence is frequent due to the development of drug resistance. An illustrative example is according to a paper published in Nature in 2011 (Nature. 2011 Jun 29;474(7353):609-15), the copy number variation in ovarian cancer is compared to that of glioblastoma. Something extremely severe is described. Ovarian cancer is a very serious cancer with intertumoral heterogeneit or intratumoral heterogeneity. BRCA1/2 mutation was found in 33% of ovarian cancer patients, and 51% of ovarian cancer patients were found to have homologous recombination pathway alteration. olaparib) attracted attention as a targeted treatment for ovarian cancer. Looking at the results of the second stage of randomized clinical trials for olaparib in ovarian cancer patients published in Lancet oncology in 2015, the improvement of PFS was remarkable in BRCA mutant patients, but no statistically significant result was obtained in terms of survival rate increase in OS. (Lancet Oncol. 2015 Jan;16(1):87-97). However, among newly diagnosed advanced ovarian cancer patients published in NEJM journal in 2018, olaparib and placebo were administered daily for patients with complete or partial clinical response to platinum based chemotherapy in patients with mutations in the BRCA1 or BRCA2 gene. As a result of two treatments of 300mg each, the progression-free survival improved by 70%, and the survival rate was higher by 3 years. This is evaluated as a breakthrough result comparable to the existing platinum-based chemotherapy. However, there is no difference in the fact that treatment of ovarian cancer is still difficult as a result limited to patients with BRCA1/2 gene mutation. In addition to this, various clinical studies have been conducted, but they are very similar.

Cancer treatments can be broadly divided into surgical surgery, radiation therapy, and chemotherapy. For cancer, surgery can be performed, so surgical surgery is commonly used. However, even with surgical operation, the recurrence rate is very high if the cancer is advanced. Therefore, in order to prevent recurrence and improve the prognosis of cancer patients, a multidisciplinary treatment including chemotherapy or chemo-radiation therapy after surgical operation has been introduced. However, although these treatments improve general clinical outcomes in patients, the clinical pathologic heterogeneity of tumors and the different outcomes of patients at the same stage have limitations in predicting the mission of adjuvant chemotherapy, which is optimal for individual patients. There is a lack of access.

Despite recent advances, the challenges of cancer therapy remain to target specific treatment regimens for pathogenically distinct tumor types, and ultimately to personalize tumor treatment to maximize outcomes. Therefore, there is a need for tests that simultaneously provide predictive information about patient response to various treatment options.

According to the announcement at the 2006 Symposium on Anorexia and Nutritional Status in Cancer Patients, malnutrition was the direct cause of death in more than 20% of patients who die from cancer. An average of 63% of cancer patients suffer from malnutrition, and in the case of pancreatic cancer and gastric cancer, more than 83% of them suffer from malnutrition. The period when malnutrition becomes prominent in the cancer fighting process is usually in the late stages. In the previous stage, weight is also maintained relatively, and malnutrition is very rare. Chemotherapy is an exceptional situation, but during surgery, chemotherapy, and radiation therapy, the body weight decreases rapidly, and during this period, it is essential to maintain weight and physical strength by supplementing calories. The biggest problem is after the chemotherapy is over. After surgery or at the end of one month after chemotherapy, the appetite, digestive function, and systemic condition are improved, so weight begins to increase. In the case of patients, there are many cases where nutritional status is important in the process of fighting cancer, so there are many cases in which the weight is excessive by ingesting it regardless. If ovarian cancer patients maintain a high calorie diet even after surgery and chemotherapy are terminated during the cancer fighting process, and the resulting obesity and metabolic disorders are affected by ovarian cancer growth and metastasis, the prognosis is very likely to be poor. high.

In addition, according to a paper published in Nutrition and Cancer in 2016, in the case of ovarian cancer patients, the 5-year overall survival rate was 45.3% in case of an effect deficiency, and the prognosis was poor compared to 64% in case of no effect deficiency, and the risk rate was 5.8. It was doubled. In addition, progression free survival was significantly lower than those of patients who did not show effects deficiency at 15 months, compared to 28 months of patients without effects deficiency.

In other words, it is highly likely that the nutritional status of ovarian cancer patients and weight control through diet control were closely related to the prognosis of ovarian cancer patients. According to reports from various mata-analysis studies, an increase in body size obesity was found to be highly associated with ovarian cancer risk and survival rate. In particular, as reported in Cancer Research in 2015, it was found that obesity increases the success rate of ovarian cancer metastasis through lipogenesis. However, there have been no studies on the association between obesity or dietary control-related residual tumors, ovarian cancer growth, gene expression studies, and interactions between genes until the end of ovarian cancer treatment.

It is an object of the present invention to provide a biomarker for predicting anticancer agent susceptibility, comprising at least one selected from the group consisting of genes EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, or ZCCHC18.

Another object of the present invention is to measure the expression level of mRNA or protein of one or more genes selected from the group consisting of genes EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, or ZCCHC18. It is to provide a biomarker composition for prediction.

EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, or ZCCHC18, comprising a preparation for measuring the level of mRNA of one or more genes selected from the group consisting of or the expression level of a protein thereof, anticancer agent susceptibility prediction kit To provide.

Another object of the present invention is to provide a pharmaceutical composition for preventing or treating cancer comprising the gene expression inhibitor as an active ingredient.

Another object of the present invention is to provide a pharmaceutical composition for preventing or treating cancer comprising the gene activator as an active ingredient.

However, the technical problem to be achieved by the present invention is not limited to the problems mentioned above, and other problems that are not mentioned will be clearly understood by those of ordinary skill in the art from the following description.

In order to solve this need, the present inventors implanted ovarian cancer patient's derived tumor xenograft (PDTX) in immunodeficient nude mice to induce artificial dietary regulation in mice and then influence the growth of ovarian cancer. And RNA sequencing method to predict the prognosis through genetic change analysis in ovarian cancer patient-derived tumor tissues, thereby presenting a gene expression model capable of improving the prognosis of ovarian cancer patients, resulting in the completion of the present invention. .

Furthermore, by statistically analyzing gene expression patterns between normal tissues, benign tumor tissues, malignant tumor tissues, or metastatic cancer tissues, select genes with a change in expression level when treated with an anticancer composition or an anticancer agent, and observe the survival rate for the anticancer agent. A gene group capable of predicting susceptibility was selected and the effect of cancer treatment was confirmed.

Hereinafter, various embodiments described herein are described with reference to the drawings. In the following description, for a thorough understanding of the invention, various specific details, such as specific forms, compositions and processes, etc. are set forth. However, certain embodiments may be practiced without one or more of these specific details, or with other known methods and forms. In other instances, well-known processes and manufacturing techniques have not been described in specific details in order not to unnecessarily obscure the present invention. Reference throughout this specification to “one embodiment” or “embodiment” means that a particular feature, form, composition, or characteristic described in connection with the embodiment is included in one or more embodiments of the present invention. Thus, the context of “in one embodiment” or “embodiment” expressed in various places throughout this specification does not necessarily represent the same embodiment of the invention. Additionally, particular features, shapes, compositions, or properties may be combined in any suitable manner in one or more embodiments.

Unless otherwise defined in the present invention, all scientific and technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs.

In the present invention, the "marker for predicting anticancer agent sensitivity" refers to a substance capable of confirming the course of a disease, survival, or cure after cancer treatment by treating a subject with an anticancer composition or an anticancer agent. This includes organic biomolecules such as polypeptides or nucleic acids (eg, mRNA), lipids, glycolipids, glycoproteins or sugars (monosaccharides, disaccharides, oligosaccharides, etc.). For the purposes of the present invention, the biomarker for predicting anticancer agent sensitivity of the present invention is at least one gene selected from the group consisting of EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, or ZCCHC18 genes.

In the present invention, "sensitivity" means whether or not a specific drug is effective against cancer of an individual patient.

For example, the specific drugs are mainly anticancer drugs, and these anticancer drugs may or may not have an effect depending on the type of cancer. In addition, even in the case of the type of cancer recognized as effective, it is known that there are cases in which an effect is exhibited and in a case where the effect is not exhibited depending on individual patients. Whether or not an anticancer drug is effective against cancer of such individual patients is called anticancer drug sensitivity. Therefore, according to the present invention, chemotherapy with high efficacy and safety can be realized if the patient (responder) who can expect an effect before the start of treatment and the patient (non-responder) who cannot expect the effect can be predicted according to the present invention.

Anticancer agents of the present invention are alkylating agents, antimetabolites, folic acid analogs, pyrimidine analogs, purine analogs and related inhibitors, vinca alkaloids, epipodophyllotoxins, antibiotics, L-asparaginase, topoisomerase inhibitors, interferons, platinum coordination Complexes, taxane anthracendione substituted urea, methyl hydrazine derivatives, adrenal cortex inhibitors, adrenocorticosteroids, progestins, estrogens, antiestrogens, androgens, antiandrogens, gemcitabine and gonadotropin-releasing hormone analogs, oxariplatin, fluorouracil, Lebo poly-carbonate and the salts thereof, taxanes, paclitaxel, docetaxel, paclitaxel protein-bound particles (e.g., Havre Leshan (Abraxane ^®), gemcitabine, a platinum analogue, carboplatin, or a combination thereof, or sucrose It is selected from the group consisting of a composition consisting of carbohydrates, proteins, and fats including.

In the present invention, "sucrose" is a disaccharide in which α-glucose and β-fructose are 1,2-bonded. Sucrose has a molecular formula of C ₁₂ H ₂₂ O ₁₁ and is the main component of sugar in juices such as sugar cane, sugar beet, and sugar maple.

In the present invention, “predict” is used herein to refer to the likelihood that a subject patient will respond favorably or adversely to a drug or drug set. In one embodiment, the prediction relates to the degree of this response. For example, the prediction relates to whether and/or the probability that a patient will survive without cancer recurrence after treatment, for example after treatment with a particular therapeutic agent and/or surgical removal of the primary tumor and/or chemotherapy for a certain period of time. The predictions of the present invention can be used clinically to determine treatment by choosing the most appropriate treatment modality for cancer patients. The prediction of the present invention is whether the patient will respond favorably to a therapeutic treatment, such as a given therapeutic treatment, e.g., administration of a given treatment or combination, surgical intervention, chemotherapy, etc., or whether long-term survival of the patient is possible after therapeutic treatment. It is a useful tool for predicting whether or not.

In the present invention, cancer is glioma, thyroid cancer, lung cancer, liver cancer, pancreatic cancer, head and neck cancer, stomach cancer, colon cancer, urinary tract cancer, kidney cancer, prostate cancer, testicular cancer, breast cancer, cervical cancer, ovarian cancer, endometrial cancer, melanoma, It may be one or more selected from the group consisting of fallopian tube cancer, uterine cancer, blood cancer, bone cancer, skin cancer, brain cancer, vaginal cancer, endocrine cancer, parathyroid cancer, ureteral cancer, urethral cancer, bronchial cancer, bladder cancer, and bone marrow cancer, for example, ovarian cancer. However, it is not limited thereto.

In the present invention, "measurement of mRNA expression level" refers to the presence and expression of mRNA of at least one gene selected from the group consisting of EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, or ZCCHC18 in a biological sample to predict anticancer agent sensitivity. This is the process of confirming, by measuring the amount of mRNA. Analysis methods for this include, for example, reverse transcription polymerase reaction (RT-PCR), competitive reverse transcription polymerase reaction (Competitive RT-PCR), realtime reverse transcription polymerase reaction (Realtime RT-PCR), RNase protection assay (RPA; RNase protection assay), Northern blotting, DNA chip, and next generation sequencing (NGS), but are not limited thereto. The agent for measuring the mRNA level of a gene in the present invention is preferably an antisense oligonucleotide, a primer pair or a probe.

In the present invention, "antisense" refers to a sequence of a nucleotide base in which an antisense oligomer is hybridized with a target sequence in RNA by Watson-Crick base pairing, allowing the formation of typically mRNA and RNA: oligomer heterodimer within the target sequence. And an oligomer having a backbone between subunits. Oligomers may have exact sequence complementarity or approximate complementarity to the target sequence. These antisense oligomers can block or inhibit the translation of mRNA and alter the processing of mRNA to produce splice variants of the mRNA.

In the present invention, "primer" refers to a short nucleic acid sequence having a short free 3-terminal hydroxyl group, capable of forming a base pair with a complementary template, and serving as a starting point for template strand copying. The primers can initiate DNA synthesis in the presence of a reagent for polymerization (ie, DNA polymerase or reverse transcriptase) and four different nucleoside triphosphates at an appropriate buffer and temperature.

In the present invention, "probe" refers to a nucleic acid fragment such as RNA or DNA corresponding to a few bases to several hundred bases for a specific binding to an mRNA, and is labeled to determine the presence or absence of a specific mRNA. I can confirm. The probe may be manufactured in the form of an oligonucleotide probe, a single stranded DNA probe, a double stranded DNA probe, an RNA probe, or the like. Selection of suitable probes and conditions for hybridization can be modified based on those known in the art.

In the present invention, the term "protein expression level measurement" refers to the presence and expression of a protein expressed from a gene selected from the group consisting of EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, or ZCCHC18 in a biological sample to predict anticancer agent sensitivity. This is the process of checking the degree, and it is done by measuring the amount of protein. Analysis methods for this include Western blot, ELISA (enzyme linked immunosorbent assay), radioimmunoassay (RIA), radioimmunodiffusion, Ouchterlony immunodiffusion, and rocket immunoelectrophoresis. , Tissue immunostaining, Immunoprecipitation Assay, Complement Fixation Assay, Fluorescence Activated Cell Sorter (FACS), protein chip, mass spectrometer, etc. It is not limited. The agent for measuring the protein expression level in the present invention is preferably an antibody.

In the present invention, "antibody" refers to a specific protein molecule directed against an antigenic site. For the purposes of the present invention, an antibody refers to an antibody that specifically binds to a marker protein, and includes all of polyclonal antibodies, monoclonal antibodies and recombinant antibodies.

In order to achieve the above object, the present invention (a) the expression level of the mRNA or protein thereof of one or more genes selected from the group consisting of EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, or ZCCHC18 in a biological sample. Measuring; And (b) adding a candidate material to the biological sample in step (a), and selecting an anticancer agent when there is a change in the expression level of the mRNA or protein thereof of the genes. to provide.

In one embodiment of the present invention, the biological sample in step (a) is at least one sample selected from the group consisting of whole blood, serum, plasma, saliva, urine, sputum, lymph, tissues and cells isolated from the individual. To do. In another embodiment of the present invention, the method of measuring the mRNA expression level in step (b) is a reverse transcription polymerase reaction (RT-PCR), a competitive reverse transcription polymerase reaction (Competitive RT-PCR), and a real-time reverse transcription polymerase reaction ( Realtime RT-PCR), RNase protection assay (RPA), Northern blotting, and at least one method selected from the group consisting of DNA chips. In another embodiment of the present invention, the method for measuring the expression level of the protein in step (b) is Western blot, ELISA (enzyme linked immunosorbent assay), radioimmunoassay (RIA), radioimmunodiffusion method. ), Ouchterlony immunodiffusion method, rocket immunoelectrophoresis, tissue immunostaining, Immunoprecipitation Assay, Complement Fixation Assay, Fluorescence Activated Cell Sorter, FACS ) And a protein chip, and a mass spectrometer (Mass spectrometer).

In the present invention, the anticancer agent is glioma, thyroid cancer, lung cancer, liver cancer, pancreatic cancer, head and neck cancer, gastric cancer, colon cancer, urinary tract cancer, kidney cancer, prostate cancer, testicular cancer, breast cancer, cervical cancer, ovarian cancer, endometrial cancer, black It has anticancer action against one or more cancers selected from tumors, fallopian tube cancer, uterine cancer, blood cancer, bone cancer, skin cancer, brain cancer, vaginal cancer, endocrine cancer, parathyroid cancer, ureteral cancer, urethral cancer, bronchial cancer, bladder cancer, and bone marrow cancer. .

In another embodiment of the present invention, the anticancer agent is composed of a carbohydrate including sucrose, a protein, and a fat. In another embodiment of the present invention, the anticancer agent is composed of a carbohydrate, protein, and fat containing 60 to 80 kcal% of sucrose. In another embodiment of the present invention, the anticancer agent is composed of carbohydrates, proteins, and fats containing 70 kcal% of sucrose (70% of sucrose in Table 1).

In addition, in order to achieve the above object, the present invention measures the mRNA level of one or more genes selected from the group consisting of EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, or ZCCHC18 or the expression level of a protein thereof. It provides a kit for screening an anticancer agent comprising the following agents.

In the present invention, the agent for measuring the mRNA level of a gene may be an antisense oligonucleotide, a primer pair, or a probe.

In the present invention, the agent for measuring the level of protein may be an antibody.

In one embodiment of the present invention, the kit may be an RT-PCR kit, a competitive RT-PCR kit, a real-time RT-PCR kit, a quantitative RT-PCR kit, a DNA chip kit, or a protein chip kit.

In addition, in order to achieve the above object, the present invention provides a pharmaceutical composition for the prevention or treatment of cancer comprising an inhibitor of SPRN or UPB1 gene as an active ingredient.

In one embodiment of the present invention, the inhibitor of the SPRN or UPB1 gene is at least one selected from the group consisting of antisense nucleotides, siRNA (short interfering RNA) and shRNA (short hairpin RNA) that complement each mRNA. .

In another embodiment of the present invention, the inhibitor of the UPB1 gene may consist of a nucleotide sequence represented by SEQ ID NO: 1 or 2, and variously by a person skilled in the art with reference to the nucleotide sequence represented by SEQ ID NO: 5 or 6. Since it can be manufactured, it is not limited thereto.

In the present invention, the cancer is glioma, thyroid cancer, lung cancer, liver cancer, pancreatic cancer, head and neck cancer, gastric cancer, colon cancer, urinary tract cancer, kidney cancer, prostate cancer, testicular cancer, breast cancer, cervical cancer, ovarian cancer, endometrial cancer, black Tumor, fallopian tube cancer, uterine cancer, blood cancer, bone cancer, skin cancer, brain cancer, vaginal cancer, endocrine cancer, parathyroid cancer, ureter cancer, urethral cancer, bronchial cancer, bladder cancer, and may be one or more selected from bone marrow cancer, for example, ovarian cancer. However, it is not limited thereto.

In addition, in order to achieve the above object, the present invention provides a pharmaceutical composition for preventing or treating cancer comprising an activator of the MRGPRX3 gene as an active ingredient.

In the present invention, the activator of the MRGPRX3 gene may be included as long as it is capable of activating the MRGPRX3 gene, and may be, for example, a gene expression vector encoding the nucleotide sequence constituting the MRGPRX3 gene, but is not limited thereto.

In the present invention, the MRGPRX3 gene may consist of a nucleotide sequence represented by SEQ ID NO: 7 or 8, but is not limited thereto.

In the present invention, the "expression vector" is generally an expression vector useful in recombinant DNA techniques, often in the form of a plasmid. In the present specification, "plasmid" and "vector" may be used interchangeably since the plasmid is the most commonly used form among vectors.

Specific examples of the expression vector in the present invention include commercially widely used pCDNA vector, F, R1, RP1, Col, pBR322, ToL, Ti vector; Cosmid; Phages such as lambda, lambdoid, M13, Mu, p1 P22, Qμ, T-even, T2, T3, T7; It may be selected from the group consisting of plant viruses, but is not limited thereto, and all expression vectors known as expression vectors to those skilled in the art can be used in the present invention, and when selecting an expression vector, it depends on the properties of the target host cell. When the vector is introduced into the host cell, it may be performed by calcium phosphate transfection, viral infection, DEAE-dextran control transfection, lipofectamine transfection, or electroporation, but is not limited thereto, and those skilled in the art use. An introduction method suitable for an expression vector and a host cell can be selected and used.

In the present invention, the cancer is glioma, thyroid cancer, lung cancer, liver cancer, pancreatic cancer, head and neck cancer, gastric cancer, colon cancer, urinary tract cancer, kidney cancer, prostate cancer, testicular cancer, breast cancer, cervical cancer, ovarian cancer, endometrial cancer, black Tumor, fallopian tube cancer, uterine cancer, blood cancer, bone cancer, skin cancer, brain cancer, vaginal cancer, endocrine cancer, parathyroid cancer, ureter cancer, urethral cancer, bronchial cancer, bladder cancer, and may be one or more selected from bone marrow cancer, for example, ovarian cancer. However, it is not limited thereto.

In addition, in order to achieve the above object, the present invention is any one of inhibitors of the SPRN or UPB1 gene; And it provides a pharmaceutical composition for the prevention or treatment of cancer comprising the activator of the MRGPRX3 gene as an active ingredient.

In the present invention, the inhibitors, activators, and cancers of the genes are the same as described above, and thus are omitted to avoid excessive complexity of the specification.

[Sequence List]

SEQ ID NO: 1: UPB1 siRNA

CAG AGU UUA GAC AUG ACU Att

SEQ ID NO: 2: UPB1 siRNA

CUG CAA UGU GUG GAG UCA Att

SEQ ID NO: 3: forward primer

GGA AGC ATG GAC TAT GCC CTT

SEQ ID NO: 4: reverse primer

TTC CAG GAT GGG AGA CAC CA

SEQ ID NO: 5: mRNA sequence of SPRN gene (NCBI Reference Sequence: NM_001012508)

1 ggcggaggcc tcgcgcaaaa cccaggcgcc gcggctccgc gctccggctg agggtccgcg

61 ccgccgcccg cccgctcctt cccgctcggc cgcggcctca gggacggata ctccagcgcg

121 cggttccaac cgaggcccgt ggtttagccc cacgaagatg aactgggcac ccgcaacgtg

181 ctgggctctg ctactggcgg ccgccttcct ctgcgacagc ggcgcagcca agggcggccg

241 cggaggtgcg cggggcagtg cccggggagg ggtccgcggg ggtgcgcgcg gggcctcgag

301 ggtgcgcgtg aggccggcgc agcgctacgg tgccccgggc tcctccctgc gcgtggctgc

361 cgccggggcg gcagccgggg cggcggcggg agcggccgcg ggcctggcgg cgggctcggg

421 ctggagaagg gccgcgggac ccggggaacg cggcctggag gacgaggagg acggggtgcc

481 cggaggcaac gggacaggcc ccggcatcta cagctaccgg gcgtggactt cgggcgctgg

541 acccacgcgc ggcccgcgtc tctgtctcgt gctgggcggc gccctcggag ccctggggct

601 gctgcggccc taggcctggc tgggctcggg gaccacatct ggcccccggc ccgcgccatc

661 ccccaggatc ctccggcctg ggctccccct tcctcccttg cccacggtct tggagcccca

721 ctgggtgcag gagctgctgg ctgtccctgt ggacccgcca tccaccgtcc tgcccacgcc

781 gcctcagcct gccacctccc acctagagga gaccatgggc cctgccccac ccactccagg

841 atgttagggt cccctcagcc aaaaaggcag ctgcctgtgg ctcctgtacc aaccgcccag

901 ccacgctcca tcgccgccca aagggaggtg ccaaggccag gaacccaagc caccccggct

961 cccctcgcct gcccaggggc cgtggtgact cacgggcagg gaggcgacat caggctggtt

1021 ctgccactga gcccctgagg aatctgaccc tccccaaaag aagcagtgaa atggaccaaa

1081 ggacttaaga atttgggggg aagtgaggga aaaacgttag gtgctaacca cctgcccaga

1141 agagtggatc tcacagccca ggaacattcc caagcaggaa aaccgtccgt ccgaggaacg

1201 tccatcctgg ctctctgcgg ctggtgggaa aacacaccct gccctgaggg gctgtccagg

1261 ccttctcccc cacaccctca ggccgagatc cgtgagagac ccactttgct ccaacaactt

1321 gaaacaagtc actttaccct ccttaggacc cattttgggg gggaaaaacc aacacattcc

1381 agagctttcc aagtcctttg aacttcaggt tcacattcag ggatcacaca gttctgcctg

1441 ttctcagggc acagcaactg ccaatcccgc tgaagaggcc tccctgggca cagcacaggc

1501 tgcacggtgc acgcatttcc ctgaaggcag ccccttcttc ggaagcagct gttccaggcc

1561 tcggaacagg gcctgggtat ccgcgtggtg ggctggcagc tgacggcctg ctcagtggag

1621 ccaggagcta actcagaccc caaagcaagc agggggccag tggcggggcc cagcgcccag

1681 caggacaccc atgcaagagg ctgagccccc caacatccaa ggacaggaga gacatggagt

1741 ggcgctggac agtcacgaca aggacttgcc tccagcactg gacacacctg tgttaagacc

1801 agccctctgc ttcccagtcc cgccagcctg gggcatcctc catgggctca gcactgagag

1861 gtcttgggtc tgccacgttc tctagctctc cagtcaccca ctcatccagg gtaggagggg

1921 ttctccctgc cccccgccgt ggccttggga tctcaccctc tccatgtcct ggggacagcc

1981 tcgccctcag ccggactgca tccctcctgg gcctgagcct cgggactcag tggacaccaa

2041 agtcaagacc agcacccacc acgggccctg ccagcctctg ccttccccag ctggcctggg

2101 ttctggcctg ggtgaggatc tggaagctgt tggcaggact caaccaagca ctgctctcta

2161 gctccagggc actaagccac aggaggcagc gccctgcagc ctcccgtcca cactgccagc

2221 aatgcccctg gcccagtgag cccagacgct cctccacccc ttccagacca agctcaacgc

2281 ctccaagacc agcaggccaa ggccaagccc tgccccagat cctcataggc agagaagccc

2341 ttctgacatt tcccccagga ggcagggggt ggtctgagtc tcctcacagc agagagaccc

2401 accggagccc cctcaacttt gcagatgccc acctggaaaa tgggctgagc tgcaccagac

2461 cctcacacac cacagcactg caagctgatg gaatgttcca gttatgatgg acacttcgtg

2521 atctgcaatg actgttgatt cagcacatta gcatctgaca cagccaacct gaatacttcc

2581 tgccccaggc ggtcagggtt atggcacgat gcaggtggca ctcaggggct aacttcaggc

2641 tgatgagtgt gtggggtatg gggcagcaga ggcagccagc cagcaaagag gggccactga

2701 gcaccagggc cctggtggag gctgctgtgg gacggtcagg ccaccaccgc aaagaggcag

2761 ccggagcttc tgcacaggat gtccctggcc ccaggtcctg cagcacctta gtccatacta

2821 ccagccccac ccaccttcct tcctcttccc tcttctagga cacaggctgt ggaccccttc

2881 aggtgcacta taatggggct ggaggggccc ccacatctct cagccccact aatgcagaat

2941 cccactaccc gtgagctaga aggtgctcag aggccagggg tctctactgc ccatgccggg

3001 cggccttcca gtcattgcac agcaaagcca tgtgcagggc gtccccctca accctgccct

3061 gaacatgccc cagggcactg aggggcgaag ccagtgcttg ggctctgctg ctgggagtct

3121 ctggtctgtg tctgtgtgtg cctgtaagtg tgaaataaac ctctctgatg gcaaaaaaaa

3181 aaaaaaaa

SEQ ID NO: 6: mRNA sequence of UPB1 gene (NCBI Reference Sequence: NM_016327)

1 gggcacctcc tcccactgcg ggcaaagggc aggcagttcg tgcgcggaca caagcactgg

61 cggaccgtgg ccatggcggg cgctgagtgg aagtcgctgg aggaatgctt ggagaagcac

121 ctgccgctcc ccgacttgca ggaagtgaag cgcgttctct atggcaagga actcaggaag

181 cttgatctgc ccagggaagc tttcgaagct gcctccagag aagactttga actgcaggga

241 tatgcctttg aagcagcgga ggagcagctg agacgacccc gcattgtgca cgtggggctg

301 gttcagaaca gaatccccct ccccgcaaat gcccctgtgg cagaacaggt ctctgccctt

361 catagacgca taaaggctat cgtagaggtg gctgcaatgt gtggagtcaa catcatctgt

421 ttccaggaag catggactat gccctttgcc ttctgtacga gagagaagct tccttggaca

481 gaatttgctg agtcagcaga ggatgggccc accaccagat tctgtcagaa gctggcgaag

541 aaccatgaca tggtggtggt gtctcccatc ctggaacgag acagcgagca tggggatgtt

601 ttgtggaata cagccgtggt gatctccaat tccggagcag tcctgggaaa gaccaggaaa

661 aaccacatcc ccagagtggg tgatttcaac gagtcaactt actacatgga gggaaacctg

721 ggccaccccg tgttccagac gcagttcgga aggatcgcgg tgaacatttg ctacgggcgg

781 caccaccccc tcaactggct tatgtacagc atcaacgggg ctgagatcat cttcaacccc

841 tcggccacga taggagcact cagcgagtcc ctgtggccca tcgaggccag aaacgcagcc

901 attgccaatc actgcttcac ctgcgccatc aatcgagtgg gcaccgagca cttcccgaac

961 gagtttacct cgggagatgg aaagaaagct caccaggact ttggctactt ttatggctcg

1021 agctatgtgg cagcccctga cagcagccgg actcctgggc tgtcccgtag ccgggatgga

1081 ctgctagttg ctaagctcga cctaaacctc tgccagcagg tgaatgatgt ctggaacttc

1141 aagatgacgg gcaggtatga gatgtacgca cgggagctcg ccgaagctgt caagtccaac

1201 tacagcccca ccatcgtgaa agagtagccg gcttcagtgc ctgccttggg gtgaggaaga

1261 cacctctgcc ccagtggatt agcaagtgtg gcaggcttaa catgtccagg ttctccccaa

1321 taacattgtc caggttggtt ttaaaattcc caggcagggg gagagtggca tggggagtga

1381 cttcttaatg ggtaaggggc tgcttacttc tggggtattg gaaatgtttg gggactaggt

1441 agaggtgaat gtactaaatg ccactgaatt tgtatacttc agaatgtttg ttatgtaaat

1501 tttacctcaa ctaaaaaaaa aaatgcccag gtactgcttg tgcaggtgga tttgaggtta

1561 ggcagatgat gctgtccatc ccgtacacca gtgggaagag ggtgagggct gatccagaga

1621 ccctgagcct acagcaaggc tgtggtgggt cggatggtct ttggatgtgt cagcttagct

1681 aggccacagt caccagtaat tcaatcagac actaatctag gtatttctgt gaaggtattt

1741 tgtagatgtg acagaagtcc attcccaatt gactaagtaa gtgagattat ctcagataat

1801 ctgggtcagc ctgacctgat tagtcagaag gcctaaagaa cagagctaag ggtttccctg

1861 aggaagaaat tctgcctgag gacagcagcc cagtgcttgg cgagagttcc tgacagtctg

1921 cccttctgat agcctgcctc acagagttta gacatgacta gccagctcct acaatcactg

1981 aagtcaattc cttgcaataa atctcaatat atcccctact ggttctgctt ctctagttga

2041 atctgactga tacagatttt ggtgccaaaa gtggttctag aaaaatagaa tcttaaagat

2101 gagttttctg cattggttct ggattttttt agaattcttc cctagtttga ttgaacttaa

2161 aggcatcaat gactctattt ccatagagtc agggtaaaga gggtagttgg tagtccatgg

2221 catggtgcag caatagttat ttatgtgcga gactagccat cagccatcag tttgtgccca

2281 gagttccagc ctgccctttc tgatggcttg tcctgtggat atcagacttg cctgaccaga

2341 ttccatcatc atagaaggta atttgttgca ctaaatcctt ttatatctct atccatcacc

2401 tactaattct gctagttctg ctaatgtggt tgagctccat tttacacatc agattactca

2461 cttctctaca ccttggtttt tacatctgta aaatgggact gggccaggtg tggtggggtg

2521 gcttatgcct gtgatcccag cactttggga agccaaggca ggtggatcac ttgaggtcag

2581 gagttcaaga ccagcctggc caacacggcg aaaccccgtc tctactaaaa atacaaaaat

2641 tagctgggca tggtggcgca tgcctataat cccagctact cagcaggctg aggtatgaga

2701 attgcttgaa tctgggaggc aaaggctgca gtgagctgag atcacgccac tgtgctccag

2761 cctggacaac agagtgagag cctatctcca aaaaaaaaaa ggggtgggga ccatattcct

2821 gctttatgtc aagacactgg taagagacag actagatggg ccagggagcc ccttggcagt

2881 tatcagtgca gcgcctattt agccctgtcc ctgaacaaca cggcaagagc ccaacctgcc

2941 aagtctcaaa tagcagttaa ccagagtatc gggttggagg tggggttgag attctgtaat

3001 tccccgctta ttgttcccaa tcagagaagg cagccagaga aggcagcttc atcccttcac

3061 tggcccagca gctgaactat atggaaacct ccatgtcagg gctagggtac tcctggacag

3121 ccaccaagga tgagaaaccc tgatggagct gcctggccac agctctgcgg taacttcctt

3181 gaactctctg tgctgcaggt tttcacttta cctaatggcc cttcttgcac ctttaaaaaa

3241 aaaaaaaaaa aattccagtc ctacagacac agtgagcttt tttgcctgtt cctttagctt

3301 tcaaaattta gtgtcagcca aggcgggcag atcacaaggt caagagatgg aaaccatcct

3361 ggccaacatg gtgaaacccc atctctacta aaaatacaaa aattagctgg gtatggtggc

3421 gcacgcctgt agtcccaggt actcagcagg ctgagggagg agaatcactt gaacccggga

3481 ggcggaggtt gcagtgagcc gagatcacac cactgcactc cagcttggcg acagagtgag

3541 actccgtctc aaaaaacaaa acaaaacaaa acaccttagt gtttttggtt tctagagggt

3601 gtaatcaacc taatacagaa gccagcttag gtgacaaatt ggtacatttg tgaaacaggc

3661 atgaataaat ggaccacaac tctttgatta tctgcaactc tcattgcctg gaaacagaac

3721 agtcaggccc atcttagagt atgcaggccc tgtacagcca aggtcatttc aaggtttaac

3781 tcatccctgg aacatgcaga tgctcagtaa acatttgaat gaa

SEQ ID NO: 7: MRGPRX3 gene mRNA sequence variant 1 (NCBI Reference Sequence: NM_054031)

1 gcccagtctg gaaagtgagg agcgtctttg cccggccgcc atcccatcta ggaagtgagg

61 agcgcctctt cccggccgcc atcccatcta ggaagtgagg agcgtctctg cccggccgcc

121 catcgtctga gatgtgggga gtgcctttgc cccgccgccc cgtctgggat gtgaggagcg

181 cctctgcccg gtcgcgaccc cgtctgggag ctcctgtagg catctcctga attaagcaac

241 acagaaaagt cctctgaagt cactgaatcc cataaaggct ctctaccttt agcacaaggg

301 aggtcttcac cactggacaa agaaggaacg ataaggggtc atcagactgg ggtttctgag

361 catggattca accatcccag tcttgggtac agaactgaca ccaatcaacg gacgtgagga

421 gactccttgc tacaagcaga ccctgagctt cacggggctg acgtgcatcg tttcccttgt

481 cgcgctgaca ggaaacgcgg ttgtgctctg gctcctgggc tgccgcatgc gcaggaacgc

541 tgtctccatc tacatcctca acctggtcgc ggccgacttc ctcttcctta gcggccacat

601 tatatgttcg ccgttacgcc tcatcaatat ccgccatccc atctccaaaa tcctcagtcc

661 tgtgatgacc tttccctact ttataggcct aagcatgctg agcgccatca gcaccgagcg

721 ctgcctgtcc atcctgtggc ccatctggta ccactgccgc cgccccagat acctgtcatc

781 agtcatgtgt gtcctgctct gggccctgtc cctgctgcgg agtatcctgg agtggatgtt

841 ctgtgacttc ctgtttagtg gtgctaattc tgtttggtgt gaaacgtcag atttcattac

901 aatcgcgtgg ctggtttttt tatgtgtggt tctctgtggg tccagcctgg tcctgctggt

961 caggattctc tgtggatccc ggaagatgcc gctgaccagg ctgtacgtga ccatcctcct

1021 cacagtgctg gtcttcctcc tctgtggcct gccctttggc attcagtggg ccctgttttc

1081 caggatccac ctggattgga aagtcttatt ttgtcatgtg catctagttt ccattttcct

1141 gtccgctctt aacagcagtg ccaaccccat catttacttc ttcgtgggct cctttaggca

1201 gcgtcaaaat aggcagaacc tgaagctggt tctccagagg gctctgcagg acacgcctga

1261 ggtggatgaa ggtggagggt ggcttcctca ggaaaccctg gagctgtcgg gaagcagatt

1321 ggagcagtga ggaagaacct ctgccctgtc agacaggact ttgagagcaa tgctgccctg

1381 ccacccttga caattatatg catttttctt agccttctgc ctcagaaatg tctcagtggt

1441 ccctcaaggt cttcgaatag atgtttatct aacctgacag ttgcagtttt cacccatgga

1501 aagcattagt ctgacagtac aatgtttgga ttctccttga tattaccaat acattttccc

1561 tgttatcttg cactgaatct ttcctactga acactttttc tgcacttttc attgtaataa

1621 aaggagttgc tgtccacaaa aaaaaaaaaa aaaaaaaaaa

SEQ ID NO: 8: MRGPRX3 gene mRNA sequence variant 2 (NCBI Reference Sequence: NM_001370464)

1 agcatcttcg taagcctgga ttgctcacca gctttcattt cagctcctgt aggcatctcc

61 tgaattaagc aacacagaaa agtcctctga agtcactgaa tcccataaag gctctctacc

121 tttagcacaa gggaggtctt caccactgga caaagaagga acgataaggg gtcatcagac

181 tggggtttct gagcatggat tcaaccatcc cagtcttggg tacagaactg acaccaatca

241 acggacgtga ggagactcct tgctacaagc agaccctgag cttcacgggg ctgacgtgca

301 tcgtttccct tgtcgcgctg acaggaaacg cggttgtgct ctggctcctg ggctgccgca

361 tgcgcaggaa cgctgtctcc atctacatcc tcaacctggt cgcggccgac ttcctcttcc

421 ttagcggcca cattatatgt tcgccgttac gcctcatcaa tatccgccat cccatctcca

481 aaatcctcag tcctgtgatg acctttccct actttatagg cctaagcatg ctgagcgcca

541 tcagcaccga gcgctgcctg tccatcctgt ggcccatctg gtaccactgc cgccgcccca

601 gatacctgtc atcagtcatg tgtgtcctgc tctgggccct gtccctgctg cggagtatcc

661 tggagtggat gttctgtgac ttcctgttta gtggtgctaa ttctgtttgg tgtgaaacgt

721 cagatttcat tacaatcgcg tggctggttt ttttatgtgt ggttctctgt gggtccagcc

781 tggtcctgct ggtcaggatt ctctgtggat cccggaagat gccgctgacc aggctgtacg

841 tgaccatcct cctcacagtg ctggtcttcc tcctctgtgg cctgcccttt ggcattcagt

901 gggccctgtt ttccaggatc cacctggatt ggaaagtctt attttgtcat gtgcatctag

961 tttccatttt cctgtccgct cttaacagca gtgccaaccc catcatttac ttcttcgtgg

1021 gctcctttag gcagcgtcaa aataggcaga acctgaagct ggttctccag agggctctgc

1081 aggacacgcc tgaggtggat gaaggtggag ggtggcttcc tcaggaaacc ctggagctgt

1141 cgggaagcag attggagcag tgaggaagaa cctctgccct gtcagacagg actttgagag

1201 caatgctgcc ctgccaccct tgacaattat atgcattttt cttagccttc tgcctcagaa

1261 atgtctcagt ggtccctcaa ggtcttcgaa tagatgttta tctaacctga cagttgcagt

1321 tttcacccat ggaaagcatt agtctgacag tacaatgttt ggattctcct tgatattacc

1381 aatacatttt ccctgttatc ttgcactgaa tctttcctac tgaacacttt ttctgcactt

1441 ttcattgtaa taaaaggagt tgctgtccac aaccctaaaa

The therapeutic response to the anticancer agent and anticancer composition provided by the present invention and the method for predicting the prognosis of the patient are the genes EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, or ZCCHC18 by detecting and measuring the expression of one or more combinations, and , It can be usefully used to increase the survival rate of cancer patients through one or more combinations of inhibitors and activators capable of controlling the expression of each gene. Furthermore, when suppressing or activating the expression level of the gene, cancer can be very effectively prevented or treated.

1 is an image showing a correlation analysis according to gene expression patterns in ovarian cancer PDTX tissue obtained from each feed group. Samples from the 70% sucrose group and the control diet group (see Table 1) that effectively inhibited the growth of ovarian cancer PDTX were classified into subgroups with high similarity according to the Pearson correlation coefficient.
Figure 2 is a schematic diagram of finding differentially expressed genes for subgroups B1/B2/B3 of each 70% sucrose group (see Table 1) based on subgroups A1/A2 of the control diet. When the A1 subgroup of FIG. 2 (a) was used as a control, four genes that changed in common were found in B1/B2/B3 samples. When the A2 subgroup of FIG. 2 was used as a control group, 5 genes that change in common were found in B1/B2/B3 samples. In Fig. 2(c), one gene whose expression is changed in common again was found in each common gene. (Signal threshold >= 0.001, 1.5 fold, p <0.05)
3 is a graph showing the level of gene expression by RNA sequencing. EXOC3L2, KCNK6, SPRN, and MRGPRX3 are genes that are increased or decreased in the B1/B2/B3 subgroup when the A1 subgroup is used as a control. In addition, MRGPRX3, CERS3, LCAT, UPB1, ZCCHC18 are genes that are increased or decreased in the B1/B2/B3 subgroup when the A2 subgroup is used as a control.
4 to 6 show the survival curves of cancer patients based on expression levels for various carcinomas for each gene in the ovarian cancer dataset of The Cancer Genome Atlas (TCGA) as shown in Table 1. Figure 4 shows the survival curve for MRGPRX3 for head and neck cancer, lung cancer, and cervical cancer patients (p> 0.05). 5 shows survival curves for patients with renal cancer, urinary tract cancer and pancreatic cancer for SPRN. 6 shows survival curves for liver cancer and kidney cancer patients for UPB1.
7 is a low malignant potential tissue (LMP) and ovarian cancer tissue (cancer) in the GSE9899 set microarrayed in the tissues of ovarian cancer patients among The Gene Expression Omnibus (GEO) datasets as shown in Table 1. It is a graph confirming the expression level of MRGPRX3, SPRN, and UPB1. In the case of MRGPRX3, it was confirmed that the amount of expression was statistically significantly increased in ovarian cancer compared to LMP.
8 is the expression level of UPB1 in normal tissues (Normal) and ovarian cancer tissues (cancer) in the GSE26712 set subjected to microarray in ovarian cancer patient tissues among The Gene Expression Omnibus (GEO) datasets as shown in Table 1. It is a graph confirming. In the ovarian cancer GSE26712 set, only UPB1 was present in the dataset, and it was confirmed that the expression of UPB1 was statistically significantly increased in ovarian cancer.
9 is a cut-off value (UPB1 expression) using the expression level of UPB1 and the survival period of the ovarian cancer patient in the GSE14764 set subjected to microarray in the tissue of ovarian cancer patients among The Gene Expression Omnibus (GEO) dataset as shown in Table 1. Level, 4.593), patients with higher expression than the cutoff value were marked as "High", and patients with low expression were marked as "Low", and this is a graph confirming the difference in UPB1 expression between High and Low patients (Fig. 9 (a)). And it is a graph showing the survival curve of each UPB1 high or low patients (Fig. 9 (b)). When the expression of UPB1 was high, the risk was increased by 2.35 times (p = 0.045).
10 is the expression level of each gene for MRGPRX3, SPRN, UPB1 and survival of ovarian cancer patients in the GSE19829-GPL570 dataset, microarrayed from the tissues of ovarian cancer patients among The Gene Expression Omnibus (GEO) dataset, as shown in Table 1. The cutoff value (MRGPRX3 = 5.298, UPB1 = 8.184, SPRN = 8.063) is calculated using the period, and based on each cutoff value, if the gene expression is high, it is "High or positive", and the patient showing low expression is "Low or negative". It was marked with ". And, it is a graph confirming the difference in MRGPRX3, UPB1 and SPRN gene expression between High and Low patients.
11 is a graph showing the survival time of ovarian cancer patients according to each gene expression based on the gene expression cutoff values set in FIG. 10 for MRGPRX3, SPRN, and UPB1 in the GSE19829-GPL570 dataset as shown in Table 1.
12 is a graph showing survival rates by classifying patients by a combination of differences in gene expression for SPRN and UPB1 in GSE19829-GPL570 as shown in Table 1. FIG.
13 is a graph showing survival rates by classifying patients by a combination of differences in gene expression for MRGPRX3, SPRN, and UPB1 in GSE19829-GPL570 as shown in Table 1.
14 shows the results of confirming the mRNA expression level of UPB1 in the OVCAR3 cell line through real-time polymerase chain reaction after transforming siRNA that specifically binds to UPB1.
15 shows the results of confirming the mRNA expression level of UPB1 in the SKOV3 cell line through real-time polymerase chain reaction after transforming siRNA that specifically binds to UPB1.
FIG. 16 shows the results of confirming the viability of the OVCAR3 cell line through crystal violet staining analysis after transforming siRNA that specifically binds to UPB1.
FIG. 17 shows the results of confirming the viability of the SKOV3 cell line through crystal violet staining analysis after transforming siRNA that specifically binds to UPB1.

Hereinafter, the present invention will be described in more detail through examples. These examples are only for describing the present invention in more detail, and it will be apparent to those of ordinary skill in the art that the scope of the present invention is not limited by these examples according to the gist of the present invention. .

[ Preparation example One] Patient consent and PDTX produce

Cancer tissues of patients diagnosed with ovarian cancer at Gangnam Severance Hospital were collected at the Korea Gynecological Cancer Bank. PDTX was made by dividing the ovarian cancer tissue of a patient donated from the Korea Gynecological Cancer Bank into approximately 3 mm ³ sections and transplanting them into BALB/c nude mice. Prior to the start of this study, research approval was obtained from IRB of Gangnam Severance Hospital (IRB approval No.3-2014-0184), and research consent was received from patients who donated cancer tissues.

[ Example One] Animal experiment

Each specially formulated feed was supplied to 5-week-old BALB/c nude mice (female) and drinking water was provided for 2 months (see Table 1). Thereafter, the tissues of PDTX-126 and PDTX-98 were divided into ³ mm ³ sections, and mice were anesthetized using a combination of zoletil, rompun, and saline (1:1:7). . Thereafter, PDTX tissue was transplanted into the subcutaneous tissue at two locations per mouse. At weekly intervals, the intake amount of the feed and the intake calories of the feed amount eaten by the mouse corresponding to the prepared feed (see Table 1) were calculated, and the weight of the mouse was measured. In addition, the volume of the tumor was measured using a digital caliper (Tumor volume (mm ³ ) = long length x short length ² x 0.5) (see Tables 2 to 4, Table 4 is from PDTX-126 and PDTX-98). This is the result of integrating the results of). PDTX-126 recorded mouse and PDTX information for a total of 187 days and PDTX-98 for a total of 134 days, and then sacrificed. In the sacrificed mice, white adipose tissues of the liver and peritoneum were excised, weighed, and blood was collected from the inferior vena cava. PDTX tumor tissue was excised, the final volume and weight were measured, and pictures of the mouse and cancer tissue were recorded. All animal experiments were approved by Yonsei University's Animal Ethics Committee (IACUC Approval No. 2017-0157)

As shown in Tables 2 to 4, it was confirmed that tumor growth was the lowest in a 70% sucrose diet (70% Sucrose). In the case of the 60% fat diet (60% Fat) and the 70% fat diet (70% Fat), the tumor growth was low, but at the same time, the tumor growth was very rapid, so it is not suitable for chemotherapy. It was confirmed that the diet was not (Final volume (mm ³ ) criteria: Vary slow 0-250, Slow 250-500, Medium 500-1000, Fast 1000-1500, Vary fast> 1500).

[ Example 2] RNA sequencing

Ion AmpliSeq ^TM Transcript Library manufacturing

After a certain period of time after feeding the feed shown in Table 1, using the PDTX tissue obtained from BALB/c nude mice, total RNA was extracted with TRIzol ^® reagent (Ambion, Carlsbad, CA) according to the manufacturer's protocol, and Qubit ^® RNA HS Assay Kit (Life Technologies, Carlsbad, CA) quantified, and the percentage of RNA fragments greater than 200 nt was calculated using smear analysis of an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA). Using a ^{Qubit ® dsDNA HS Assay Kit (Life} Technologies) was quantified the DNA sample. The Ion AmpliSeq ^TM transcript library was prepared with Ion Transcriptome Human Gene Expression Kit (Life Technologies) according to the manufacturer's protocol. 10 ng of total RNA was reverse transcribed to create cDNA by random priming. cDNA product was Ion AmpliSeq ^TM The Library Kit Plus, which together Ion AmpliSeq ^TM It is a target gene amplified using the Human Gene Expression Core Panel. After primer digestion, the adapter and the molecular barcode were ligated to the amplification product, followed by purification with magnetic beads. This library was amplified and purified for a total of 5 cycles. The amplification product size and DNA concentration were measured according to the manufacturer's recommendations using the Agilent High Sensitivity DNA Kit (Agilent Technologies).

Sample emulsion PCR, emulsion break and concentration were performed using Ion PI ^™ Template OT2 200 Kit v3 (Life Technologies, Part #4488318 Rev. B.0) according to the manufacturer's instructions. Several barcoded libraries were combined in the same molar ratio for one Ion PI ^TM v2 chip. Two pooled Ion AmpliSeq ^™ Exome libraries were loaded onto a single Ion PI ^™ v2 chip. Five pooled AmpliSeq ^™ transcript libraries were loaded onto a single Ion PI ^™ v2 chip. Subsequent emulsion PCR and concentration of sequencing beads of the pooled library were performed within about 7 hours using the Ion OneTouch ^™ system (Life Technologies) according to the manufacturer's protocol. Finally, 520 Flows sequencing was performed on an Ion PI ^TM v2 chip using Ion PI ^TM Sequencing 200 Kit v3 (Life Technologies, Part #4488315 Rev. B.0) on an Ion Proton ^TM sequencer (Life Technologies).

[ Example 3] RNA sequencing readout and gene expression analysis

RNA sequencing read mapping was performed using DNASTAR Lasegene 15 software and human genome19 (hg19) reference. Each of the samples was subjected to linear correlation (R ² value) analysis. Also, clustering was performed according to the Euclidean distance method. According to the grouping results, as shown in Table 1, the control diet group was classified into two subgroups (A1 and A2 in Fig. 1), and the 70% sucrose group was divided into three subgroups (B1, B2, and B3 in Fig. 1). Was performed (see FIG. 2). Differentially expressed genes (DEGs) were obtained between each group (Fig. 3). The gene list is listed in Tables 5 and 6 below.

As shown in Tables 5 and 6 and 3, as shown in Table 1, the genes EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, and ZCCHC18 after treatment with an anticancer composition containing 70% sucrose as an active ingredient By measuring the level of, it was possible to predict the sensitivity to anticancer drugs. Preferably, by measuring the level of the genes EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, and ZCCHC18, sensitivity to the anticancer composition according to the present invention consisting of carbohydrates, fats, and proteins containing 70% sucrose Was predictable.

[Example 4] Survival analysis

Download GSE 19829-GPL570 set from The Gene Expression Omnibus (GEO) dataset, SPRN (affymetrix probe no. 238333_s_at), MRGPRX3 (affymetrix probe no. 1553293_at), and UPB1 (affymetrix probe no. 228219_s_at) genes corresponding to the genes. Microarray expression values were used. Then, the cutoff value of each gene was obtained based on the survival period (PLoS One. 2012;7(12):e51862.). Based on the cutoff value, high expression was classified into "High" (positive) and low expression was classified into "Low" (negative). For each combination of genes, a survival curve was drawn using the Kaplan-Meier method, and statistical significance was calculated by a log-rank test. All statistical analyzes were performed using Graphpad Prism 7 software.

Based on The Cancer Genome Atlas (TCGA) dataset, for various carcinomas for each gene, survival curves of cancer patients were obtained based on the expression level (FIGS. 4 to 6 ). When the expression of MRGPRX3 was increased, the survival rate for head and neck cancer patients increased, and when the expression of MRGPRX3 was decreased, the survival rate for lung and cervical cancer patients was decreased (FIG. 4 ). In addition, when the expression of SPRN was increased, the survival rate for urinary tract cancer and pancreatic cancer patients increased, and when the expression of SPRN was decreased, the survival rate for kidney cancer patients increased (FIG. 5). When the expression of UPB1 was increased, it was confirmed that the survival rate for liver cancer and kidney cancer patients increased (FIG. 6).

In addition, using the results of the GEO dataset (GSE9899, GSE26712, GSE14764), the expression levels of MRGPRX3, SPRN, and UPB1 for normal, low malignant potential tissue (LMP), and malignant tumors (Cancer) were evaluated. It was calculated (see Figs. 7 and 8). In the case of MRGPRX3, it was confirmed that the expression level was statistically significantly increased in ovarian cancer (malignant tumor) compared to LMP. In the ovarian cancer GSE26712 set, only UPB1 was present in the dataset, and the expression of UPB1 was statistically significantly increased in ovarian cancer. 9 is a graph showing the difference in the expression level for UPB1 in the ovarian cancer GSE14764 set among the GEO datasets (FIG. 9(a)) and a graph showing the survival curves of patients (FIG. 9(b)). In the GSE14764 set, only UPB1 was present in the dataset, and the cutoff value (4.593) was calculated using the survival time of the ovarian cancer patient for the expression level of UPB1. Patients showing higher expression than the cutoff value were "High" and low expression. The visible patient was marked as "Low". Figure 9 (a) is a graph representing the difference between High and Low values, and Figure 9 (b) shows the survival curves for high and low patients. When the expression was high, the risk was increased by 2.35 times (p=0.045).

In the GSE19829-GPL570 dataset, cutoff values were calculated using the expression levels of each gene for MRGPRX3, SPRN, and UPB1 (FIG. 10) and survival time of ovarian cancer patients (FIG. 11) (Receiver operation characteristic analysis). Each cutoff value was MRGPRX3=5.298, UPB1=8.184, and SPRN=8.063. Based on each cutoff value, a high value was indicated as "High" (positive), and a patient with low expression was indicated as "Low" (negative). 10 is a graph showing the difference between High and Low values. 11 shows the survival rate of the patient according to the large or small amount of gene expression and the survival rate according to the combination of each gene was calculated. Survival rate was analyzed using three candidate genes (MRGPRX3 (NM_054031), SPRN (NM_001012508), UPB1 (NM_016327)) of the above 8 genes. In the case of MRGPRX3, it was confirmed that low-expression had a low survival rate (red line) (p=0.15), and SPRN and UPB1 had a low survival rate of overexpression (blue line) (p=0.16, p=0.012). However, only the survival rate of UPB1 was statistically significant (p<0.05).

In addition, as shown in FIG. 12, in GSE19829-GPL570, both genes for SPRN and UPB1 were divided into overexpression patients (double positive) with a cutoff value or more or underexpression patients (double negative) with both genes below the cutoff value, and the survival curve was Confirmed (Log rank p=0.0474). "Single positive" indicates a case in which one of the two genes is overexpressed in a patient with a cutoff value or more. It was confirmed that the "double negative" patient had a higher survival rate compared to the two cases that did not.

In GSE19829-GPL570, patients were classified by gene expression combinations for MRGPRX3, SPRN, and UPB1 to confirm the survival curve (FIG. 13). In GSE19829-GPL570, the gene expression levels for MRGPRX3, SPRN, and UPB1 were able to confirm overexpression of MRGPRX3, underexpression of SPRN, and UPB1 ("+/-/-"), thus, ovarian cancer identical to the present expression pattern. In the case of the patient, it was confirmed that the survival rate was statistically significantly higher than that of the patient showing the opposite expression ("-/+/+") (Log-rank p=0.005).

Through this study, after treatment of cancer patients with anticancer compositions or anticancer agents, as genes that can predict the patient's susceptibility to anticancer compositions or anticancer agents, EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, and ZCCHC18 Was confirmed.

[Example 5] Confirmation of growth inhibition effect by suppression of gene expression

Confirmation of gene expression suppression effect

After transforming the siRNA shown in Table 7 below, which is specific for UPB1, a gene capable of predicting the sensitivity of the patient identified in Example 4, to the ovarian cancer cell lines OVCAR3 and SKOV3 cell lines, the mRNA of UPB1 shown in Table 8 The expression level was confirmed through real-time polymerase chain reaction using specific primers, and the results are shown in FIGS. 14 and 15. Here, as a control, siRNA (siLuc) represented by SEQ ID NO: 3 shown in Table 7 below was used.

Sequence number Target gene Base sequence SEQ ID NO: 1 UPB1 (UPB1 #1) 5'-CAG AGU UUA GAC AUG ACU A=tt-3'(antisense) SEQ ID NO: 2 UPB1 (UPB1 #2) 5'-CUG CAA UGU GUG GAG UCA A=tt-3' (antisense)

Sequence number Characteristic Base sequence SEQ ID NO: 3 Forward direction 5'-GGA AGC ATG GAC TAT GCC CTT-3' SEQ ID NO: 4 Reverse 5'-TTC CAG GAT GGG AGA CAC CA-3'

As shown in FIGS. 14 and 15, the siRNAs shown in Table 7 below suppressed the expression level of the UPB1 gene by about 60 to 80% compared to the control (siLuc).

Confirmation of the effect of inhibiting the growth of cancer cell lines by suppressing gene expression

The OVCAR3 and SKOV3 cell lines were transformed with the siRNA shown in Table 7 below, which is specific for UPB1, a gene that can predict patient sensitivity identified in Example 4, and then sufficiently cultured for 24 hours. Then, a crystal violet staining solution (0.5% crystal violet with 20% MeOH) was added to the well plate containing each of the cell lines and stained. Then, after removing the crystal violet staining solution from the well plate, the excess crystal violet staining solution was removed using tertiary distilled water, and a 2% sodium dodecyl sulfate (SDS) solution was added thereto. The dyed crystal violet staining solution was dissolved, and absorbance was measured at 595 nm, and the results are shown in FIGS. 16 and 17. Here, as a control, siRNA (siLuc) represented by SEQ ID NO: 3 described in Table 7 was used.

As shown in Figs. 16 and 17, the OVCAR3 and SKOV3 cell lines transformed with siRNA specific to UPB1 inhibited the growth of cells by 20 to 40% compared to the control (siLuc).

Through the above results, when the expression level of the gene that can predict the sensitivity according to the present invention is suppressed, the growth of the cancer cell line can be very remarkably suppressed. Therefore, the composition for suppressing the expression level of such a gene is It can be used very effectively for prevention or treatment.

As described above, specific parts of the present invention have been described in detail, and it is obvious that these specific techniques are only preferred embodiments, and the scope of the present invention is not limited thereto for those of ordinary skill in the art. Accordingly, it will be said that the substantial scope of the present invention is defined by the appended claims and their equivalents.

<110> Industry-Academic Cooperation Foundation, Yonsei University <120> A SCREENING METHOD FOR ANTI-CANCER AGENTS <130> PDPB187364k01 <150> KR 10-2019-0019777 <151> 2019-02-20 <160> 8 <170> KoPatentIn 3.0 <210> 1 <211> 21 <212> RNA <213> Artificial Sequence <220> <223> UPB1 siRNA <400> 1 cagaguuuag acaugacuat t 21 <210> 2 <211> 21 <212> RNA <213> Artificial Sequence <220> <223> UPB1 siRNA <400> 2 cugcaaugug uggagucaat t 21 <210> 3 <211> 21 <212> DNA <213> Artificial Sequence <220> <223> forward primer <400> 3 ggaagcatgg actatgccct t 21 <210> 4 <211> 20 <212> DNA <213> Artificial Sequence <220> <223> reverse primer <400> 4 ttccaggatg ggagacacca 20 <210> 5 <211> 3188 <212> RNA <213> Homo sapiens <400> 5 ggcggaggcc tcgcgcaaaa cccaggcgcc gcggctccgc gctccggctg agggtccgcg 60 ccgccgcccg cccgctcctt cccgctcggc cgcggcctca gggacggata ctccagcgcg 120 cggttccaac cgaggcccgt ggtttagccc cacgaagatg aactgggcac ccgcaacgtg 180 ctgggctctg ctactggcgg ccgccttcct ctgcgacagc ggcgcagcca agggcggccg 240 cggaggtgcg cggggcagtg cccggggagg ggtccgcggg ggtgcgcgcg gggcctcgag 300 ggtgcgcgtg aggccggcgc agcgctacgg tgccccgggc tcctccctgc gcgtggctgc 360 cgccggggcg gcagccgggg cggcggcggg agcggccgcg ggcctggcgg cgggctcggg 420 ctggagaagg gccgcgggac ccggggaacg cggcctggag gacgaggagg acggggtgcc 480 cggaggcaac gggacaggcc ccggcatcta cagctaccgg gcgtggactt cgggcgctgg 540 acccacgcgc ggcccgcgtc tctgtctcgt gctgggcggc gccctcggag ccctggggct 600 gctgcggccc taggcctggc tgggctcggg gaccacatct ggcccccggc ccgcgccatc 660 ccccaggatc ctccggcctg ggctccccct tcctcccttg cccacggtct tggagcccca 720 ctgggtgcag gagctgctgg ctgtccctgt ggacccgcca tccaccgtcc tgcccacgcc 780 gcctcagcct gccacctccc acctagagga gaccatgggc cctgccccac ccactccagg 840 atgttagggt cccctcagcc aaaaaggcag ctgcctgtgg ctcctgtacc aaccgcccag 900 ccacgctcca tcgccgccca aagggaggtg ccaaggccag gaacccaagc caccccggct 960 cccctcgcct gcccaggggc cgtggtgact cacgggcagg gaggcgacat caggctggtt 1020 ctgccactga gcccctgagg aatctgaccc tccccaaaag aagcagtgaa atggaccaaa 1080 ggacttaaga atttgggggg aagtgaggga aaaacgttag gtgctaacca cctgcccaga 1140 agagtggatc tcacagccca ggaacattcc caagcaggaa aaccgtccgt ccgaggaacg 1200 tccatcctgg ctctctgcgg ctggtgggaa aacacaccct gccctgaggg gctgtccagg 1260 ccttctcccc cacaccctca ggccgagatc cgtgagagac ccactttgct ccaacaactt 1320 gaaacaagtc actttaccct ccttaggacc cattttgggg gggaaaaacc aacacattcc 1380 agagctttcc aagtcctttg aacttcaggt tcacattcag ggatcacaca gttctgcctg 1440 ttctcagggc acagcaactg ccaatcccgc tgaagaggcc tccctgggca cagcacaggc 1500 tgcacggtgc acgcatttcc ctgaaggcag ccccttcttc ggaagcagct gttccaggcc 1560 tcggaacagg gcctgggtat ccgcgtggtg ggctggcagc tgacggcctg ctcagtggag 1620 ccaggagcta actcagaccc caaagcaagc agggggccag tggcggggcc cagcgcccag 1680 caggacaccc atgcaagagg ctgagccccc caacatccaa ggacaggaga gacatggagt 1740 ggcgctggac agtcacgaca aggacttgcc tccagcactg gacacacctg tgttaagacc 1800 agccctctgc ttcccagtcc cgccagcctg gggcatcctc catgggctca gcactgagag 1860 gtcttgggtc tgccacgttc tctagctctc cagtcaccca ctcatccagg gtaggagggg 1920 ttctccctgc cccccgccgt ggccttggga tctcaccctc tccatgtcct ggggacagcc 1980 tcgccctcag ccggactgca tccctcctgg gcctgagcct cgggactcag tggacaccaa 2040 agtcaagacc agcacccacc acgggccctg ccagcctctg ccttccccag ctggcctggg 2100 ttctggcctg ggtgaggatc tggaagctgt tggcaggact caaccaagca ctgctctcta 2160 gctccagggc actaagccac aggaggcagc gccctgcagc ctcccgtcca cactgccagc 2220 aatgcccctg gcccagtgag cccagacgct cctccacccc ttccagacca agctcaacgc 2280 ctccaagacc agcaggccaa ggccaagccc tgccccagat cctcataggc agagaagccc 2340 ttctgacatt tcccccagga ggcagggggt ggtctgagtc tcctcacagc agagagaccc 2400 accggagccc cctcaacttt gcagatgccc acctggaaaa tgggctgagc tgcaccagac 2460 cctcacacac cacagcactg caagctgatg gaatgttcca gttatgatgg acacttcgtg 2520 atctgcaatg actgttgatt cagcacatta gcatctgaca cagccaacct gaatacttcc 2580 tgccccaggc ggtcagggtt atggcacgat gcaggtggca ctcaggggct aacttcaggc 2640 tgatgagtgt gtggggtatg gggcagcaga ggcagccagc cagcaaagag gggccactga 2700 gcaccagggc cctggtggag gctgctgtgg gacggtcagg ccaccaccgc aaagaggcag 2760 ccggagcttc tgcacaggat gtccctggcc ccaggtcctg cagcacctta gtccatacta 2820 ccagccccac ccaccttcct tcctcttccc tcttctagga cacaggctgt ggaccccttc 2880 aggtgcacta taatggggct ggaggggccc ccacatctct cagccccact aatgcagaat 2940 cccactaccc gtgagctaga aggtgctcag aggccagggg tctctactgc ccatgccggg 3000 cggccttcca gtcattgcac agcaaagcca tgtgcagggc gtccccctca accctgccct 3060 gaacatgccc cagggcactg aggggcgaag ccagtgcttg ggctctgctg ctgggagtct 3120 ctggtctgtg tctgtgtgtg cctgtaagtg tgaaataaac ctctctgatg gcaaaaaaaa 3180 aaaaaaaa 3188 <210> 6 <211> 3823 <212> RNA <213> Homo sapiens <400> 6 gggcacctcc tcccactgcg ggcaaagggc aggcagttcg tgcgcggaca caagcactgg 60 cggaccgtgg ccatggcggg cgctgagtgg aagtcgctgg aggaatgctt ggagaagcac 120 ctgccgctcc ccgacttgca ggaagtgaag cgcgttctct atggcaagga actcaggaag 180 cttgatctgc ccagggaagc tttcgaagct gcctccagag aagactttga actgcaggga 240 tatgcctttg aagcagcgga ggagcagctg agacgacccc gcattgtgca cgtggggctg 300 gttcagaaca gaatccccct ccccgcaaat gcccctgtgg cagaacaggt ctctgccctt 360 catagacgca taaaggctat cgtagaggtg gctgcaatgt gtggagtcaa catcatctgt 420 ttccaggaag catggactat gccctttgcc ttctgtacga gagagaagct tccttggaca 480 gaatttgctg agtcagcaga ggatgggccc accaccagat tctgtcagaa gctggcgaag 540 aaccatgaca tggtggtggt gtctcccatc ctggaacgag acagcgagca tggggatgtt 600 ttgtggaata cagccgtggt gatctccaat tccggagcag tcctgggaaa gaccaggaaa 660 aaccacatcc ccagagtggg tgatttcaac gagtcaactt actacatgga gggaaacctg 720 ggccaccccg tgttccagac gcagttcgga aggatcgcgg tgaacatttg ctacgggcgg 780 caccaccccc tcaactggct tatgtacagc atcaacgggg ctgagatcat cttcaacccc 840 tcggccacga taggagcact cagcgagtcc ctgtggccca tcgaggccag aaacgcagcc 900 attgccaatc actgcttcac ctgcgccatc aatcgagtgg gcaccgagca cttcccgaac 960 gagtttacct cgggagatgg aaagaaagct caccaggact ttggctactt ttatggctcg 1020 agctatgtgg cagcccctga cagcagccgg actcctgggc tgtcccgtag ccgggatgga 1080 ctgctagttg ctaagctcga cctaaacctc tgccagcagg tgaatgatgt ctggaacttc 1140 aagatgacgg gcaggtatga gatgtacgca cgggagctcg ccgaagctgt caagtccaac 1200 tacagcccca ccatcgtgaa agagtagccg gcttcagtgc ctgccttggg gtgaggaaga 1260 cacctctgcc ccagtggatt agcaagtgtg gcaggcttaa catgtccagg ttctccccaa 1320 taacattgtc caggttggtt ttaaaattcc caggcagggg gagagtggca tggggagtga 1380 cttcttaatg ggtaaggggc tgcttacttc tggggtattg gaaatgtttg gggactaggt 1440 agaggtgaat gtactaaatg ccactgaatt tgtatacttc agaatgtttg ttatgtaaat 1500 tttacctcaa ctaaaaaaaa aaatgcccag gtactgcttg tgcaggtgga tttgaggtta 1560 ggcagatgat gctgtccatc ccgtacacca gtgggaagag ggtgagggct gatccagaga 1620 ccctgagcct acagcaaggc tgtggtgggt cggatggtct ttggatgtgt cagcttagct 1680 aggccacagt caccagtaat tcaatcagac actaatctag gtatttctgt gaaggtattt 1740 tgtagatgtg acagaagtcc attcccaatt gactaagtaa gtgagattat ctcagataat 1800 ctgggtcagc ctgacctgat tagtcagaag gcctaaagaa cagagctaag ggtttccctg 1860 aggaagaaat tctgcctgag gacagcagcc cagtgcttgg cgagagttcc tgacagtctg 1920 cccttctgat agcctgcctc acagagttta gacatgacta gccagctcct acaatcactg 1980 aagtcaattc cttgcaataa atctcaatat atcccctact ggttctgctt ctctagttga 2040 atctgactga tacagatttt ggtgccaaaa gtggttctag aaaaatagaa tcttaaagat 2100 gagttttctg cattggttct ggattttttt agaattcttc cctagtttga ttgaacttaa 2160 aggcatcaat gactctattt ccatagagtc agggtaaaga gggtagttgg tagtccatgg 2220 catggtgcag caatagttat ttatgtgcga gactagccat cagccatcag tttgtgccca 2280 gagttccagc ctgccctttc tgatggcttg tcctgtggat atcagacttg cctgaccaga 2340 ttccatcatc atagaaggta atttgttgca ctaaatcctt ttatatctct atccatcacc 2400 tactaattct gctagttctg ctaatgtggt tgagctccat tttacacatc agattactca 2460 cttctctaca ccttggtttt tacatctgta aaatgggact gggccaggtg tggtggggtg 2520 gcttatgcct gtgatcccag cactttggga agccaaggca ggtggatcac ttgaggtcag 2580 gagttcaaga ccagcctggc caacacggcg aaaccccgtc tctactaaaa atacaaaaat 2640 tagctgggca tggtggcgca tgcctataat cccagctact cagcaggctg aggtatgaga 2700 attgcttgaa tctgggaggc aaaggctgca gtgagctgag atcacgccac tgtgctccag 2760 cctggacaac agagtgagag cctatctcca aaaaaaaaaa ggggtgggga ccatattcct 2820 gctttatgtc aagacactgg taagagacag actagatggg ccagggagcc ccttggcagt 2880 tatcagtgca gcgcctattt agccctgtcc ctgaacaaca cggcaagagc ccaacctgcc 2940 aagtctcaaa tagcagttaa ccagagtatc gggttggagg tggggttgag attctgtaat 3000 tccccgctta ttgttcccaa tcagagaagg cagccagaga aggcagcttc atcccttcac 3060 tggcccagca gctgaactat atggaaacct ccatgtcagg gctagggtac tcctggacag 3120 ccaccaagga tgagaaaccc tgatggagct gcctggccac agctctgcgg taacttcctt 3180 gaactctctg tgctgcaggt tttcacttta cctaatggcc cttcttgcac ctttaaaaaa 3240 aaaaaaaaaa aattccagtc ctacagacac agtgagcttt tttgcctgtt cctttagctt 3300 tcaaaattta gtgtcagcca aggcgggcag atcacaaggt caagagatgg aaaccatcct 3360 ggccaacatg gtgaaacccc atctctacta aaaatacaaa aattagctgg gtatggtggc 3420 gcacgcctgt agtcccaggt actcagcagg ctgagggagg agaatcactt gaacccggga 3480 ggcggaggtt gcagtgagcc gagatcacac cactgcactc cagcttggcg acagagtgag 3540 actccgtctc aaaaaacaaa acaaaacaaa acaccttagt gtttttggtt tctagagggt 3600 gtaatcaacc taatacagaa gccagcttag gtgacaaatt ggtacatttg tgaaacaggc 3660 atgaataaat ggaccacaac tctttgatta tctgcaactc tcattgcctg gaaacagaac 3720 agtcaggccc atcttagagt atgcaggccc tgtacagcca aggtcatttc aaggtttaac 3780 tcatccctgg aacatgcaga tgctcagtaa acatttgaat gaa 3823 <210> 7 <211> 1660 <212> RNA <213> Homo sapiens <400> 7 gcccagtctg gaaagtgagg agcgtctttg cccggccgcc atcccatcta ggaagtgagg 60 agcgcctctt cccggccgcc atcccatcta ggaagtgagg agcgtctctg cccggccgcc 120 catcgtctga gatgtgggga gtgcctttgc cccgccgccc cgtctgggat gtgaggagcg 180 cctctgcccg gtcgcgaccc cgtctgggag ctcctgtagg catctcctga attaagcaac 240 acagaaaagt cctctgaagt cactgaatcc cataaaggct ctctaccttt agcacaaggg 300 aggtcttcac cactggacaa agaaggaacg ataaggggtc atcagactgg ggtttctgag 360 catggattca accatcccag tcttgggtac agaactgaca ccaatcaacg gacgtgagga 420 gactccttgc tacaagcaga ccctgagctt cacggggctg acgtgcatcg tttcccttgt 480 cgcgctgaca ggaaacgcgg ttgtgctctg gctcctgggc tgccgcatgc gcaggaacgc 540 tgtctccatc tacatcctca acctggtcgc ggccgacttc ctcttcctta gcggccacat 600 tatatgttcg ccgttacgcc tcatcaatat ccgccatccc atctccaaaa tcctcagtcc 660 tgtgatgacc tttccctact ttataggcct aagcatgctg agcgccatca gcaccgagcg 720 ctgcctgtcc atcctgtggc ccatctggta ccactgccgc cgccccagat acctgtcatc 780 agtcatgtgt gtcctgctct gggccctgtc cctgctgcgg agtatcctgg agtggatgtt 840 ctgtgacttc ctgtttagtg gtgctaattc tgtttggtgt gaaacgtcag atttcattac 900 aatcgcgtgg ctggtttttt tatgtgtggt tctctgtggg tccagcctgg tcctgctggt 960 caggattctc tgtggatccc ggaagatgcc gctgaccagg ctgtacgtga ccatcctcct 1020 cacagtgctg gtcttcctcc tctgtggcct gccctttggc attcagtggg ccctgttttc 1080 caggatccac ctggattgga aagtcttatt ttgtcatgtg catctagttt ccattttcct 1140 gtccgctctt aacagcagtg ccaaccccat catttacttc ttcgtgggct cctttaggca 1200 gcgtcaaaat aggcagaacc tgaagctggt tctccagagg gctctgcagg acacgcctga 1260 ggtggatgaa ggtggagggt ggcttcctca ggaaaccctg gagctgtcgg gaagcagatt 1320 ggagcagtga ggaagaacct ctgccctgtc agacaggact ttgagagcaa tgctgccctg 1380 ccacccttga caattatatg catttttctt agccttctgc ctcagaaatg tctcagtggt 1440 ccctcaaggt cttcgaatag atgtttatct aacctgacag ttgcagtttt cacccatgga 1500 aagcattagt ctgacagtac aatgtttgga ttctccttga tattaccaat acattttccc 1560 tgttatcttg cactgaatct ttcctactga acactttttc tgcacttttc attgtaataa 1620 aaggagttgc tgtccacaaa aaaaaaaaaa aaaaaaaaaa 1660 <210> 8 <211> 1480 <212> RNA <213> Homo sapiens <400> 8 agcatcttcg taagcctgga ttgctcacca gctttcattt cagctcctgt aggcatctcc 60 tgaattaagc aacacagaaa agtcctctga agtcactgaa tcccataaag gctctctacc 120 tttagcacaa gggaggtctt caccactgga caaagaagga acgataaggg gtcatcagac 180 tggggtttct gagcatggat tcaaccatcc cagtcttggg tacagaactg acaccaatca 240 acggacgtga ggagactcct tgctacaagc agaccctgag cttcacgggg ctgacgtgca 300 tcgtttccct tgtcgcgctg acaggaaacg cggttgtgct ctggctcctg ggctgccgca 360 tgcgcaggaa cgctgtctcc atctacatcc tcaacctggt cgcggccgac ttcctcttcc 420 ttagcggcca cattatatgt tcgccgttac gcctcatcaa tatccgccat cccatctcca 480 aaatcctcag tcctgtgatg acctttccct actttatagg cctaagcatg ctgagcgcca 540 tcagcaccga gcgctgcctg tccatcctgt ggcccatctg gtaccactgc cgccgcccca 600 gatacctgtc atcagtcatg tgtgtcctgc tctgggccct gtccctgctg cggagtatcc 660 tggagtggat gttctgtgac ttcctgttta gtggtgctaa ttctgtttgg tgtgaaacgt 720 cagatttcat tacaatcgcg tggctggttt ttttatgtgt ggttctctgt gggtccagcc 780 tggtcctgct ggtcaggatt ctctgtggat cccggaagat gccgctgacc aggctgtacg 840 tgaccatcct cctcacagtg ctggtcttcc tcctctgtgg cctgcccttt ggcattcagt 900 gggccctgtt ttccaggatc cacctggatt ggaaagtctt attttgtcat gtgcatctag 960 tttccatttt cctgtccgct cttaacagca gtgccaaccc catcatttac ttcttcgtgg 1020 gctcctttag gcagcgtcaa aataggcaga acctgaagct ggttctccag agggctctgc 1080 aggacacgcc tgaggtggat gaaggtggag ggtggcttcc tcaggaaacc ctggagctgt 1140 cgggaagcag attggagcag tgaggaagaa cctctgccct gtcagacagg actttgagag 1200 caatgctgcc ctgccaccct tgacaattat atgcattttt cttagccttc tgcctcagaa 1260 atgtctcagt ggtccctcaa ggtcttcgaa tagatgttta tctaacctga cagttgcagt 1320 tttcacccat ggaaagcatt agtctgacag tacaatgttt ggattctcct tgatattacc 1380 aatacatttt ccctgttatc ttgcactgaa tctttcctac tgaacacttt ttctgcactt 1440 ttcattgtaa taaaaggagt tgctgtccac aaccctaaaa 1480

Claims (13)

(a) measuring the expression level of the mRNA or protein thereof of one or more genes selected from the group consisting of EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, or ZCCHC18 in the biological sample; And
(b) adding a candidate material to the biological sample in step (a), and selecting an anticancer agent when there is a change in the expression level of the mRNA or protein thereof of the genes. The method of claim 1,
In the step (a), the biological sample is one or more samples selected from the group consisting of whole blood, serum, plasma, saliva, urine, sputum, lymph fluid, tissues and cells isolated from the individual. The method of claim 1,
The method of measuring the mRNA expression level in step (b) is reverse transcription polymerase reaction (RT-PCR), competitive reverse transcription polymerase reaction (Competitive RT-PCR), realtime reverse transcription polymerase reaction (Realtime RT-PCR), RNase protection. Assay (RPA; RNase protection assay), Northern blotting (Northern blotting), characterized in that at least one method selected from the group consisting of DNA chips. The method of claim 1,
Methods for measuring the expression level of the protein in step (b) include Western blot, ELISA (enzyme linked immunosorbent assay), radioimmunoassay (RIA), radioimmunodiffusion, and Ouchterlony. Immuno-diffusion method, rocket immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay (Immunoprecipitation Assay), complement fixation assay (Complement Fixation Assay), flow cytometry (Fluorescence Activated Cell Sorter, FACS) and protein chip, Mass spectrometer (Mass spectrometer), characterized in that at least one method selected from the group consisting of, the method. The method of claim 1,
The anticancer agent is glioma, thyroid cancer, lung cancer, liver cancer, pancreatic cancer, head and neck cancer, stomach cancer, colon cancer, urinary tract cancer, kidney cancer, prostate cancer, testicular cancer, breast cancer, cervical cancer, ovarian cancer, endometrial cancer, melanoma, fallopian tube cancer , Uterine cancer, blood cancer, bone cancer, skin cancer, brain cancer, vaginal cancer, endocrine cancer, parathyroid cancer, ureteral cancer, urethral cancer, bronchial cancer, bladder cancer, and bone marrow cancer. The method of claim 1,
The anticancer agent is a method consisting of carbohydrates, proteins, and fats including sucrose. EXOC3L2, KCNK6, SPRN, MRGPRX3, CERS3, LCAT, UPB1, or ZCCHC18, comprising an agent for measuring the level of mRNA of one or more genes selected from the group consisting of or the expression level of a protein thereof, anticancer agent selection kit. The method of claim 7,
The kit is an RT-PCR kit, a competitive RT-PCR kit, a real-time RT-PCR kit, a quantitative RT-PCR kit, a DNA chip kit or a protein chip kit. A pharmaceutical composition for the prevention or treatment of cancer comprising an inhibitor of the mRNA of the SPRN or UPB1 gene as an active ingredient. The method of claim 9,
The inhibitor of the mRNA is at least one selected from the group consisting of antisense nucleotides complementary to each mRNA, siRNA (short interfering RNA) and shRNA (short hairpin RNA), pharmaceutical composition. The method of claim 9,
The cancer is glioma, thyroid cancer, lung cancer, liver cancer, pancreatic cancer, head and neck cancer, stomach cancer, colon cancer, urinary tract cancer, kidney cancer, prostate cancer, testicular cancer, breast cancer, cervical cancer, ovarian cancer, endometrial cancer, melanoma, fallopian tube cancer , Uterine cancer, blood cancer, bone cancer, skin cancer, brain cancer, vaginal cancer, endocrine cancer, parathyroid cancer, ureteral cancer, urethral cancer, bronchial cancer, bladder cancer, and one or more selected from the group consisting of bone marrow cancer, a pharmaceutical composition. A pharmaceutical composition for preventing or treating cancer comprising an activator of the MRGPRX3 gene as an active ingredient. The method of claim 12,
The cancer is glioma, thyroid cancer, lung cancer, liver cancer, pancreatic cancer, head and neck cancer, stomach cancer, colon cancer, urinary tract cancer, kidney cancer, prostate cancer, testicular cancer, breast cancer, cervical cancer, ovarian cancer, endometrial cancer, melanoma, fallopian tube cancer , Uterine cancer, blood cancer, bone cancer, skin cancer, brain cancer, vaginal cancer, endocrine cancer, parathyroid cancer, ureteral cancer, urethral cancer, bronchial cancer, bladder cancer, and one or more selected from the group consisting of bone marrow cancer.

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