Cancer patient customized cancer treatment method using digital PCR

Abstract

The present invention relates to a cancer patient customized cancer treatment method using digital PCR, which verifies that there is a difference in expression patterns of expression genes between cancer patients when quantitative analysis is performed on expression changes of 134 types of target genes according to the present invention using digital PCR. In addition, it has been demonstrated that the expression pattern can be analyzed more conveniently and accurately than qPCR. Therefore, the target gene expression pattern analysis method for a cancer patient according to the present invention provides information on which an existing cancer therapeutic agent or a cancer therapeutic agent to be developed can be selectively administered to a cancer patient, and thus can be applied to customized therapy per patient.

Description

Technical Field

[0001] The present invention relates to a customized cancer treatment method for cancer patients using digital PCR, and in particular, to a customized drug selection method for cancer patients using digital PCR and a kit used therefor. Background Art

[0002] Cancer is a disease that threatens human health and life, and cancer deaths account for about 13% of the total number of deaths. In 2007, 7.6 million people died of cancer worldwide. In the United States, 1.4 million new cancer reports have been made each year in the past few years, and cancer has become the second leading cause of death. According to the SEER report, the mortality rate of all types of cancer in the United States increased from 195.4 cases per 100,000 cases in 1950 to 204.4 cases in 1978, and then steadily decreased to 184.0 cases in 2005. This downward trend is due to the improvement of diagnostic technology, which enables cancer to be detected at an early stage. In all types of cancer, early detection and treatment play an important role in cancer prognosis and survival.

[0003] There are more than 300 cancer therapeutic agents that have been approved by the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) for clinical use. These cancer therapeutic agents are approved for at least one indication and have a specific target.

[0004] Conventional anticancer chemotherapy selects and administers an appropriate cancer therapeutic agent based on the type and severity of cancer, rather than the individual cancer patient. However, general clinical results show that the therapeutic effect of such anticancer chemotherapy varies greatly among patients, and various methods have been proposed to overcome this problem.

[0005] On the other hand, in recent years, the digital PCR method has attracted attention as a gene detection method that can perform absolute quantification even with a small amount of gene samples, and is in the stage of technical optimization for its application to molecular diagnostic technology. The digital PCR method can achieve absolute quantification even with a small amount of genes of the order of tens of pg or several ng, and this advantage is very suitable for confirming gene copy number. Therefore, for various disease-related genes, copy number analysis methods using digital PCR are continuously being developed (Korean Patent Publication No. 10-2017-0051256).

[0006] Therefore, the inventors have devoted themselves to developing a method that can conveniently and accurately select drugs suitable for individual cancer patients. Finally, they have confirmed that by using the digital PCR method to target cancer therapeutics approved by the US FDA to quantify and analyze the expression changes of 134 genes, it is possible to conveniently analyze (profiling) the expression pattern of each cancer patient with high accuracy, and select customized drugs for cancer patients based on this, thereby completing the present application. Summary of the invention

[0007] Technical issues

[0008] The object of the present invention is to provide a kit for selecting a customized drug for a cancer patient using a cancer therapeutic agent target and its use by further effectively implementing chemotherapy for a cancer patient.

[0009] Means of solving the problem

[0010] In order to achieve the purpose of the present invention, the present invention provides a kit for selecting customized drugs for cancer patients, comprising: primers or probes that specifically hybridize with target genes ADA and CD52; and primers or probes that specifically hybridize with each of at least 5 target genes selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​Ret, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ.

[0011] In addition, the present invention provides a method for selecting customized drugs for cancer patients, comprising:

[0012] 1) detecting the expression of at least five target genes selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​Ret, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβα, RXRβ and RXRγ in a biological sample isolated from a cancer patient; and

[0013] 2) Selecting a drug that acts on the target gene whose high expression is detected in step 1).

[0014] In addition, the present invention provides a method for screening customized drugs for cancer patients, comprising:

[0015] 1) Isolating cancer cells and normal cells from cancer tissues and normal tissues isolated from cancer patients and proliferating them;

[0016] 2) treating the cancer cells of step 1) with a candidate drug for cancer treatment;

[0017] 3) isolating total RNA from the cancer cells and normal cells in step 1) and the cancer cells treated with the candidate cancer therapeutic drug in step 2), and synthesizing cDNA using the total RNA as a template;

[0018] 4) using the cDNA synthesized in step 3) as a template, generating a plurality of droplets from a reaction solution, wherein the reaction solution comprises primers or probes that specifically hybridize with the target genes ADA and CD52, respectively, and a probe that specifically hybridizes with a target gene selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HD a primer or probe that specifically hybridizes to each of at least 5 target genes in the group consisting of AC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ, and RXRγ;

[0019] 5) amplifying the target nucleic acid sequence in the droplets generated in step 4); and

[0020] 6) Determine the amount of amplified target nucleic acid by counting the number of droplets having the target nucleic acid amplified by step 5), and then compare it with the amount of amplified target nucleic acid in normal cells, cancer cells, and cancer cells treated with candidate drugs.

[0021] Effects of the Invention

[0022] In the present invention, the expression changes of 134 cancer therapeutic target genes between normal tissues and cancer tissues of cancer patients were quantitatively analyzed conveniently and accurately by digital PCR, and the differences in target gene expression patterns between cancer patients were confirmed, so it is proposed that information can be provided for selecting customized drugs for cancer patients. Therefore, the present invention can be applied to customized treatment for each patient by selectively administering existing cancer therapeutic agents or cancer therapeutic agents to be developed to cancer patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figures 1A to 1C 3. The figure is a diagram of confirming the expression pattern of 134 target genes by performing qPCR on each of the normal tissue and cancer tissue samples taken from 3 renal cancer patients according to one embodiment of the present invention. The first N and T are the normal tissue (N) and cancer tissue (T) samples of renal cancer patient No. 1, the second N and T are the normal tissue (N) and cancer tissue (T) samples of renal cancer patient No. 2, and the third N and T are the normal tissue (N) and cancer tissue (T) samples of renal cancer patient No. 3.

[0024] Figure 2 3. The figure is a diagram of confirming the expression pattern of 134 target genes by performing ddPCR on each of the normal tissue and cancer tissue samples taken from 3 renal cancer patients according to one embodiment of the present invention. The first N and T are the normal tissue (N) and cancer tissue (T) samples of renal cancer patient No. 1, the second N and T are the normal tissue (N) and cancer tissue (T) samples of renal cancer patient No. 2, and the third N and T are the normal tissue (N) and cancer tissue (T) samples of renal cancer patient No. 3.

[0025] Figure 3 3 is a graph showing expression patterns of 134 target genes confirmed by performing ddPCR on each of normal tissue and cancer tissue samples taken from three renal cancer patients according to an embodiment of the present invention, where N is a normal tissue sample and T is a cancer tissue sample. DETAILED DESCRIPTION

[0026] Hereinafter, the present invention is described in detail.

[0027] The present invention provides a kit for selecting customized drugs for cancer patients, comprising: primers or probes that specifically hybridize with target genes ADA and CD52, respectively; and primers or probes that specifically hybridize with each of at least 5 target genes selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​Ret, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ.

[0028] In the present invention, the target may basically include ADA and CD52, and include a target selected from ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​Ret, RRM1, RRM2 , RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ, or all of them, but are not limited to.

[0029] In addition, the present invention provides a kit for selecting a customized drug for cancer patients, which further includes a target gene selected from ACPP, ADA, ALK, BCR-ABL-1, BTK, CD19, CD30, CD52, C-MET, CRBN, CTLA4, CYP17A1, DDR2, ERBB4, FCGR1A, FGF1, FGFR1, FGFR2, FGFR3, FRK, GNRH1, GNRHR, HDAC2, HDAC3, HPRT1, IFNAR1, IFNAR2, IL2RA, IL2RB, IL2RG, ITK, JAK1, JAK2, LDLR, LHCGR, LIMK1, MAP1A, MAP2, MAP2K1, MAP2K2, MAPK11, MET, NEK 11. Primers or probes that specifically hybridize to each of at least 10 target genes in the group consisting of NR3C1, NTRK1, PARP1, PARP2, PARP3, PDCD1, PGF, PIK3CD, PRLR, PSMB10, PSMB1, PSMB2, PSMB8, PSMB9, PSMD1, PSMD2, PTK6, RARA, RARB, RARG, RPL3, SH2B3, SIK1, SLC2A2, SMO, SSTR2, SSTR5, TEK, TLR8, TNFSF8, TNFSF11, TOP1MT, TOP2B, TUBA1A, TUBA4A, TUBB1, TUBB3, TUBB, TUBD1, TUBE1, TUBG1, VEGFA and VEGFB.

[0030] In the present invention, the target may include a protein selected from the group consisting of ACPP, ADA, ALK, BCR-ABL-1, BTK, CD19, CD30, CD52, C-MET, CRBN, CTLA4, CYP17A1, DDR2, ERBB4, FCGR1A, FGF1, FGFR1, FGFR2, FGFR3, FRK, GNRH1, GNRHR, HDAC2, HDAC3, HPRT1, IFNAR1, IFNAR2, IL2RA, IL2RB, IL2RG, ITK, JAK1, JAK 2. LDLR, LHCGR, LIMK1, MAP1A, MAP2, MAP2K1, MAP2K2, MAPK11, MET, NEK11, NR3C1, NTRK1, PARP1, PARP2, PARP3, PDCD1, PGF, P IK3CD, PRLR, PSMB10, PSMB1, PSMB2, PSMB8, PSMB9, PSMD1, PSMD2, PTK6, RARA, RARB, RARG, RPL3, SH2B3, SIK1, SLC2A2, SMO, S At least 10, 15, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39 of the group consisting of STR2, SSTR5, TEK, TLR8, TNFSF8, TNFSF11, TOP1MT, TOP2B, TUBA1A, TUBA4A, TUBB1, TUBB3, TUBB, TUBD1, TUBE1, TUBG1, VEGFA, and VEGFB. 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, or 85 targets, or all of them, but are not limited to the above targets.

[0031] In the present invention, the kit may be a kit for digital PCR, and specifically, may be a kit for droplet digital PCR.

[0032] The above-mentioned term "digital PCR (Digital polymerase chain reaction, Digital PCR)" is a new method for detecting and quantifying nucleic acids. Compared with the existing qPCR, it can achieve accurate quantitative analysis and high-sensitivity detection of target nucleic acid molecules. The existing qPCR result analysis method belongs to the analog method, while the result signal of the digital PCR method has a value of "0" or "1", so its analysis method belongs to the digital method. Its advantages are that it can analyze a large number of samples, detect multiple samples at a time, and perform multiple detection items at a time. Digital PCR technology is a technology that performs absolute quantification of DNA samples by applying a single molecule counting method that does not require a standard curve. Its advantage is that it can perform absolute quantification more accurately by reacting a droplet of PCR in each well.

[0033] The term "primer" refers to a nucleic acid sequence with a short free 3' terminal hydroxyl group, which can form a base pair with a complementary template and serve as a starting point for replicating the template chain. That is, a primer refers to a single-stranded oligonucleotide that can initiate template-directed DNA synthesis under appropriate buffer, appropriate conditions (e.g., 4 different nucleoside triphosphates and DNA, DNA polymerase and other polymerizing agents) and temperature.

[0034] Primers of the present invention can be chemically synthesized by solid phase phosphoramidite synthesis or other known methods. In addition, such primers can be modified (e.g., added, deleted, substituted) by many methods known in the art within the scope of not affecting the detection of the target gene, although it is not necessary to be completely complementary to the template, but it should be fully complementary to the extent that it can hybridize with the template. Non-limiting examples of such modifications include methylation, capping, substitution to one or more natural nucleotide homologues, and modifications between nucleotides, such as modification to non-charged connectors (e.g., methylphosphonates, phosphotriesters, aminophosphorylates, carbamates, etc.) or charged connectors (e.g., phosphorothioates, phosphorothioates, etc.). Nucleic acids can contain one or more additional covalently linked residues, such as proteins (e.g., nucleases, toxins, antibodies, signal peptides, poly-L-lysine, etc.), intercalators (e.g., acridine, proflavin, etc.), chelators (e.g., metals, radioactive metals, iron, oxidizing metals, etc.) and alkylating agents. Nucleotide sequences of the present invention can also be modified by labels that can directly or indirectly provide detectable signals. Examples of labels include radioisotopes, fluorescent molecules, biotin, and the like.

[0035] The term "probe" as mentioned above refers to a natural or modified monomer or linked linear oligomer, which may include deoxyribonucleotides and ribonucleotides and is capable of specifically hybridizing with a target nucleotide sequence, and may exist naturally or be artificially synthesized.

[0036] The nucleotide sequence targeted by the present invention that should be referred to when preparing the above-mentioned primers or probes can be confirmed in GenBank, and the primers or probes can be designed with reference to this sequence.

[0037] For example, the primer sets of Tables 1 and 2 below can be used as primer sets that specifically hybridize with each of the target genes of the present invention. Specifically, digital PCR can be used, and more specifically, droplet digital PCR can be used.

[0038] Specifically, the primers that specifically hybridize with the target genes ADA and CD52, respectively, can be selected from the group consisting of primers shown in SEQ ID NOs: 99, 100, 111 and 112 in Table 2 below; the primers that specifically hybridize with each of the target genes ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ can be selected from the group consisting of SEQ ID NOs: The primers specifically hybridizing with the target genes ADA and CD52 may each be a primer set consisting of the base sequences of SEQ ID NOs: 99 and 100; and a primer set consisting of the base sequences of SEQ ID NOs: 1 to 96. More specifically, the primers specifically hybridizing with the target genes ADA and CD52 may each be a primer set consisting of the base sequences of SEQ ID NOs: 99 and 100; The primer set consisting of the base sequences of SEQ ID NOs: 111 and 112, and the primers that specifically hybridize to the target genes ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​Ret, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ, and RXRγ can each be a primer set consisting of the base sequences of SEQ ID NOs: 1 and 2, a primer set consisting of the base sequences of SEQ ID NOs: 3 and 4, or a primer set consisting of the base sequences of SEQ ID NOs: 5 and 6. a primer set consisting of the base sequence of SEQ ID NOs: 5 and 6, a primer set consisting of the base sequence of SEQ ID NOs: 7 and 8, a primer set consisting of the base sequence of SEQ ID NOs: 9 and 10, a primer set consisting of the base sequence of SEQ ID NOs: 11 and 12, a primer set consisting of the base sequence of SEQ ID NOs: 13 and 14, a primer set consisting of the base sequence of SEQ ID NOs: 15 and 16, a primer set consisting of the base sequence of SEQ ID NOs: 17 and 18, a primer set consisting of the base sequence of SEQ ID NOs: 19 and 20, a primer set consisting of the base sequence of SEQ ID NOs: 21 and 22, a primer set consisting of the base sequence of SEQ ID NOs: 23 and 24, a primer set consisting of the base sequence of SEQ ID NOs: 25 and 26, a primer set consisting of the base sequence of SEQ ID NOs: 27 and 28, a primer set consisting of the base sequence of SEQ ID NOs: 29 and 30, a primer set consisting of the base sequence of SEQ ID NOs: 31 and 32a primer set consisting of the base sequence of SEQ ID NOs: 21 and 22, a primer set consisting of the base sequence of SEQ ID NOs: 23 and 24, a primer set consisting of the base sequence of SEQ ID NOs: 25 and 26, a primer set consisting of the base sequence of SEQ ID NOs: 27 and 28, a primer set consisting of the base sequence of SEQ ID NOs: 29 and 30, a primer set consisting of the base sequence of SEQ ID NOs: 31 and 32, a primer set consisting of the base sequence of SEQ ID NOs: 33 and 34, a primer set consisting of the base sequence of SEQ ID NOs: 35 and 36, a primer set consisting of the base sequence of SEQ ID NOs: 37 and 38, a primer set consisting of the base sequence of SEQ ID NOs: 39 and 40, a primer set consisting of the base sequence of SEQ ID NOs: 41 and 42, a primer set consisting of the base sequence of SEQ ID NOs: 43 and 44, a primer set consisting of the base sequence of SEQ ID NOs: 45 and 46, a primer set consisting of the base sequence of SEQ ID NOs: 47 and 48. a primer set consisting of a base sequence of SEQ ID NOs: 47 and 48, a primer set consisting of a base sequence of SEQ ID NOs: 49 and 50, a primer set consisting of a base sequence of SEQ ID NOs: 51 and 52, a primer set consisting of a base sequence of SEQ ID NOs: 53 and 54, a primer set consisting of a base sequence of SEQ ID NOs: 55 and 56, a primer set consisting of a base sequence of SEQ ID NOs: 57 and 58, a primer set consisting of a base sequence of SEQ ID NOs: 59 and 60, a primer set consisting of a base sequence of SEQ ID NOs: 61 and 62, a primer set consisting of a base sequence of SEQ ID NOs: 63 and 64, a primer set consisting of a base sequence of SEQ ID NOs: 65 and 66, a primer set consisting of a base sequence of SEQ ID NOs: 67 and 68, a primer set consisting of a base sequence of SEQ ID NOs: 69 and 70, a primer set consisting of a base sequence of SEQ ID NOs: 71 and 72, and a primer set consisting of a base sequence of SEQ ID NOs: a primer set consisting of the base sequence of SEQ ID NOs: 73 and 74, a primer set consisting of the base sequence of SEQ ID NOs: 75 and 76, a primer set consisting of the base sequence of SEQ ID NOs: 77 and 78, a primer set consisting of the base sequence of SEQ ID NOs: 79 and 80, a primer set consisting of the base sequence of SEQ ID NOs: 81 and 82, a primer set consisting of the base sequence of SEQ ID NOs: 83 and 84, a primer set consisting of the base sequence of SEQ ID NOs: 85 and 86, a primer set consisting of the base sequence of SEQ ID NOs: 87 and 88, a primer set consisting of the base sequence of SEQ ID NOs: 89 and 90, a primer set consisting of the base sequence of SEQ ID NOs: 91 and 92, a primer set consisting of the base sequence of SEQ ID NOs: 93 and 94, and a primer set consisting of the base sequence of SEQ ID NOs: 94 and 95.A primer set consisting of the base sequences of NO:95 and 96.

[0039] In addition, the target genes ACPP, ADA, ALK, BCR-ABL-1, BTK, CD19, CD30, CD52, C-MET, CRBN, CTLA4, CYP17A1, DDR2, ERBB4, FCGR1A, FGF1, FGFR1, FGFR2, FGFR3, FRK, GNRH1, GNRHR, HDAC2, HDAC3, HPRT1, IFNAR1, IFNAR2, IL2RA, IL2RB, IL2RG, ITK, JAK1, JAK2, LDLR, LHCGR, LIMK1, MAP1A, MAP2, MAP2K1, MAP2K2, MAPK11, MET, NEK11, NR3C1, NTRK1 , PARP1, PARP2, PARP3, PDCD1, PGF, PIK3CD, PRLR, PSMB10, PSMB1, PSMB2, PSMB8, PSMB9, PSMD1, PSMD2, PTK6, RARA, RARB, RARG, RPL3, SH2B3, SIK1, SLC2A2, SMO, SSTR2, SSTR5, TEK, TLR8, TNFSF8, TNFSF11, TOP1MT, TOP2B, TUBA1A, TUBA4A, TUBB1, TUBB3, TUBB, TUBD1, TUBE1, TUBG1, VEGFA and VEGFB can be selected from the following SEQ IDThe group consisting of primers shown in NOs: 97, 98, 101 to 110, 113 to 268, more specifically, target genes ACPP, ADA, ALK, BCR-ABL-1, BTK, CD19, CD30, CD52, C-MET, CRBN, CTLA4, CYP17A1, DDR2, ERBB4, FCGR1A, FGF1, FGFR1, FGFR2, FGFR3, FRK, GNRH1, GNRHR, HDAC2, HDAC3, HPRT1, IFNAR1, IFNAR2, IL2RA, IL2RB, IL2RG, ITK, JAK1, JAK2, LDLR, LHCGR, LIMK1, MAP1A, MAP2, MAP2K1, MAP2K2, MAPK11, and MAPK2. Each of the primers specifically hybridizing with ET, NEK11, NR3C1, NTRK1, PARP1, PARP2, PARP3, PDCD1, PGF, PIK3CD, PRLR, PSMB10, PSMB1, PSMB2, PSMB8, PSMB9, PSMD1, PSMD2, PTK6, RARA, RARB, RARG, RPL3, SH2B3, SIK1, SLC2A2, SMO, SSTR2, SSTR5, TEK, TLR8, TNFSF8, TNFSF11, TOP1MT, TOP2B, TUBA1A, TUBA4A, TUBB1, TUBB3, TUBB, TUBD1, TUBE1, TUBG1, VEGFA, and VEGFB can be SEQ ID NO: 1. a primer set consisting of the base sequences of SEQ ID NOs: 97 and 98, a primer set consisting of the base sequences of SEQ ID NOs: 101 and 102, a primer set consisting of the base sequences of SEQ ID NOs: 103 and 104, a primer set consisting of the base sequences of SEQ ID NOs: 105 and 106, a primer set consisting of the base sequences of SEQ ID NOs: 107 and 108, a primer set consisting of the base sequences of SEQ ID NOs: 109 and 110, a primer set consisting of the base sequences of SEQ ID NOs: 113 and 114, a primer set consisting of the base sequences of SEQ ID NOs: 115 and 116, a primer set consisting of the base sequences of SEQ ID NOs: 117 and 118, a primer set consisting of the base sequences of SEQ ID NOs: 119 and 120, a primer set consisting of the base sequences of SEQ ID NOs: 121 and 122, a primer set consisting of the base sequences of SEQ ID NOs: 123 and 124, A primer set consisting of the base sequences of SEQ ID NOs: 123 and 124, a primer set consisting of the base sequences of SEQ ID NOs: 125 and 126, a primer set consisting of the base sequences of SEQ ID NOs: 127 and 128, a primer set consisting of the base sequences of SEQ ID NOs: 129 and 130,a primer set consisting of the base sequences of SEQ ID NOs: 129 and 130, a primer set consisting of the base sequences of SEQ ID NOs: 131 and 132, a primer set consisting of the base sequences of SEQ ID NOs: 133 and 134, a primer set consisting of the base sequences of SEQ ID NOs: 135 and 136, a primer set consisting of the base sequences of SEQ ID NOs: 137 and 138, a primer set consisting of the base sequences of SEQ ID NOs: 139 and 140, a primer set consisting of the base sequences of SEQ ID NOs: 141 and 142, a primer set consisting of the base sequences of SEQ ID NOs: 143 and 144, a primer set consisting of the base sequences of SEQ ID NOs: 145 and 146, a primer set consisting of the base sequences of SEQ ID NOs: 147 and 148, a primer set consisting of the base sequences of SEQ ID NOs: 149 and 150, a primer set consisting of the base sequences of SEQ ID NOs: 151 and 152 a primer set consisting of the base sequences of SEQ ID NOs: 151 and 152, a primer set consisting of the base sequences of SEQ ID NOs: 153 and 154, a primer set consisting of the base sequences of SEQ ID NOs: 155 and 156, a primer set consisting of the base sequences of SEQ ID NOs: 157 and 158, a primer set consisting of the base sequences of SEQ ID NOs: 159 and 160, a primer set consisting of the base sequences of SEQ ID NOs: 161 and 162, a primer set consisting of the base sequences of SEQ ID NOs: 163 and 164, a primer set consisting of the base sequences of SEQ ID NOs: 165 and 166, a primer set consisting of the base sequences of SEQ ID NOs: 167 and 168, a primer set consisting of the base sequences of SEQ ID NOs: 169 and 170, a primer set consisting of the base sequences of SEQ ID NOs: 171 and 172, a primer set consisting of the base sequences of SEQ ID NOs: a primer set consisting of the base sequence of SEQ ID NOs: 173 and 174, a primer set consisting of the base sequence of SEQ ID NOs: 175 and 176, a primer set consisting of the base sequence of SEQ ID NOs: 177 and 178, a primer set consisting of the base sequence of SEQ ID NOs: 179 and 180, a primer set consisting of the base sequence of SEQ ID NOs: 181 and 182, a primer set consisting of the base sequence of SEQ ID NOs: 183 and 184, a primer set consisting of the base sequence of SEQ ID NOs: 185 and 186, a primer set consisting of the base sequence of SEQ ID NOs: 187 and 188, a primer set consisting of the base sequence of SEQ ID NOs: 189 and 190, a primer set consisting of the base sequence of SEQ ID NOs: 191 and 192, a primer set consisting of the base sequence of SEQ ID NOs: 193 and 194, a primer set consisting of the base sequence of SEQ ID NOs: 195 and 196a primer set consisting of the base sequence of SEQ ID NOs: 195 and 196, a primer set consisting of the base sequence of SEQ ID NOs: 197 and 198, a primer set consisting of the base sequence of SEQ ID NOs: 199 and 200, a primer set consisting of the base sequence of SEQ ID NOs: 201 and 202, a primer set consisting of the base sequence of SEQ ID NOs: 203 and 204, a primer set consisting of the base sequence of SEQ ID NOs: 205 and 206, a primer set consisting of the base sequence of SEQ ID NOs: 207 and 208, a primer set consisting of the base sequence of SEQ ID NOs: 209 and 210, a primer set consisting of the base sequence of SEQ ID NOs: 211 and 212, a primer set consisting of the base sequence of SEQ ID NOs: 213 and 214, a primer set consisting of the base sequence of SEQ ID NOs: 215 and 216, a primer set consisting of the base sequence of SEQ ID NOs: 217 and 218 A primer set consisting of the base sequences of NO: 217 and 218.

[0040] In the present invention, the cancer can be renal cancer, gastric cancer, lung cancer, breast cancer, ovarian cancer, liver cancer, bronchial cancer, nasopharyngeal cancer, laryngeal cancer, pancreatic cancer, bladder cancer, colorectal cancer, colon cancer, cervical cancer, brain cancer, prostate cancer, bone cancer, head and neck cancer, skin cancer, thyroid cancer, parathyroid cancer, ureteral cancer or blood cancer, specifically, it can be renal cancer, but not limited to this.

[0041] Furthermore, regardless of the cancer type, the cancer patient may have symptoms of a terminal cancer patient, such as ascites or pleural effusion (BAL fluid), but is not limited thereto.

[0042] In the present invention, the kit may include DNA polymerase, dNTPs, buffer, etc. to perform PCR amplification reaction. The kit may also include a user guide that records the optimal reaction execution conditions. The guide is a printed material that explains the method of using the kit, for example, the preparation method of reverse transcription buffer and PCR buffer, the proposed reaction conditions, etc. The guide includes a guide booklet in the form of a brochure or leaflet, a label affixed to the kit, and instructions on the surface of the packaging box containing the kit. In addition, the guide includes information disclosed or provided through electronic media (e.g., the Internet).

[0043] In the present invention, the expression changes of 134 cancer therapeutic agent target genes between normal tissues and cancer tissues of cancer patients were quantified by digital PCR, confirming that there were differences in the target gene expression patterns of each cancer patient. In addition, it was also confirmed that digital PCR can achieve more accurate analysis than qPCR. Therefore, the expression analysis of the 134 cancer therapeutic agent target genes by digital PCR according to the present invention can be applied to the selection of customized cancer therapeutic agents for cancer patients.

[0044] In addition, the present invention provides a method for selecting customized drugs for cancer patients, comprising:

[0045] 1) detecting the expression of at least five target genes selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ in a biological sample isolated from a cancer patient; and

[0046] 2) Selecting a drug that acts on the target gene whose high expression is detected in step 1).

[0047] In the method of the present invention, the biological sample of step 1) includes various biological samples, specifically blood, serum, plasma, tissue, cells, lymph, bone marrow fluid, saliva, urine, feces, eye fluid, semen, brain extract, cerebrospinal fluid, joint fluid, thymus fluid, ascites or amniotic fluid, more specifically tissue or cell, further specifically cancer tissue or cancer cell.

[0048] In the method of the present invention, the step 1) may basically include ADA and CD52 as target genes, and may include a gene selected from ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM 1, at least 10, 15, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44 or 45 target genes in the group consisting of RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ, or all of them include the targets, but are not limited to them.

[0049] In addition, the step 1) may further include as target genes ACPP, ADA, ALK, BCR-ABL-1, BTK, CD19, CD30, CD52, C-MET, CRBN, CTLA4, CYP17A1, DDR2, ERBB4, FCGR1A, FGF1, FGFR1, FGFR2, FGFR3, FRK, GNRH1, GNRHR, HDAC2, HDAC3, HPRT1, IFNAR1, IFNAR2, IL2RA, IL2RB, IL2RG, ITK, JAK1, J AK2, LDLR, LHCGR, LIMK1, MAP1A, MAP2, MAP2K1, MAP2K2, MAPK11, MET, NEK11, NR3C1, NTRK1, PARP1, PARP2, PARP3, PDCD1, PGF, PI K3CD, PRLR, PSMB10, PSMB1, PSMB2, PSMB8, PSMB9, PSMD1, PSMD2, PTK6, RARA, RARB, RARG, RPL3, SH2B3, SIK1, SLC2A2, SMO, SSTR2 , SSTR5, TEK, TLR8, TNFSF8, TNFSF11, TOP1MT, TOP2B, TUBA1A, TUBA4A, TUBB1, TUBB3, TUBB, TUBD1, TUBE1, TUBG1, VEGFA and VEGFB, specifically, at least 10, 15, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, or 85 targets, or all include the target gene, but are not limited to it.

[0050] In the method of the present invention, the detection of gene expression in step 1) can be performed according to the digital PCR method, specifically, can be performed according to the droplet digital PCR method.

[0051] In the method of the present invention, the drug acting on the target gene in step 2) may be a cancer therapeutic agent approved by the US FDA or the European EMA for clinical use, but is not limited thereto. For example, cancer therapeutic agents approved by the US FDA for clinical use are shown in The Author(s) BMC Systems Biology 2017, 11(Suppl 5):87.

[0052] More specifically, the method for selecting customized drugs for cancer patients using droplet digital PCR can be performed by the following steps:

[0053] a) separating cancer tissue and normal tissue from cancer patients;

[0054] b) isolating total RNA from the separated cancer tissue and normal tissue, and synthesizing cDNA using the total RNA as a template;

[0055] c) using the synthesized cDNA as a template, generating a plurality of droplets from a reaction solution, wherein the reaction solution comprises primers or probes that specifically hybridize with target genes ADA and CD52, respectively, and primers or probes that specifically hybridize with each of at least 5 target genes selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ;

[0056] d) amplifying target nucleic acid sequences from the generated droplets;

[0057] e) determining the amount of amplified target nucleic acid by counting the number of droplets having the amplified target nucleic acid, and then comparing the amount of amplified target nucleic acid with that in normal tissue and cancer cells, thereby selecting target genes that are highly expressed in cancer tissues compared to normal tissues; and

[0058] f) selecting the selected drug acting on the target gene.

[0059] In the present invention, the expression changes of 134 cancer therapeutic agent target genes between normal tissues and cancer tissues of cancer patients are quantified by digital PCR, confirming that there are differences in the target gene expression patterns of each cancer patient. In addition, it is also confirmed that digital PCR can achieve more accurate analysis than qPCR. Therefore, according to the present invention, by detecting the expression patterns of the 134 cancer therapeutic agent target genes by digital PCR, drugs suitable for cancer patients can be selected, and can be applied to customized treatment of cancer patients.

[0060] In addition, the present invention provides a method for screening customized drugs for cancer patients, comprising:

[0061] 1) Isolating cancer cells and normal cells from cancer tissues and normal tissues isolated from cancer patients and proliferating them;

[0062] 2) treating the cancer cells of step 1) with a candidate drug for cancer treatment;

[0063] 3) isolating total RNA from the cancer cells and normal cells in step 1) and the cancer cells treated with the candidate cancer therapeutic drug in step 2), and synthesizing cDNA using the total RNA as a template;

[0064] 4) using the cDNA synthesized in step 3) as a template, generating a plurality of droplets from a reaction solution, wherein the reaction solution comprises primers or probes that specifically hybridize with the target genes ADA and CD52, respectively, and a probe that specifically hybridizes with a target gene selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HD a primer or probe that specifically hybridizes to each of at least 5 target genes in the group consisting of AC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ, and RXRγ;

[0065] 5) amplifying the target nucleic acid sequence in the droplets generated in step 4); and

[0066] 6) Determine the amount of amplified target nucleic acid by counting the number of droplets having the target nucleic acid amplified by step 5), and then compare it with the amount of amplified target nucleic acid in normal cells, cancer cells, and cancer cells treated with candidate drugs.

[0067] In the method of the present invention, the method for separating cancer cells and normal cells from cancer tissues and normal tissues isolated from cancer patients in step 1) can use any method known in the art, for example, using tissue decomposition enzymes or mechanical methods to decompose cancer tissues or normal tissues, and separating cancer cells from the decomposed tissues according to cell size, density or surface characteristics by density gradient separation, separation using a cell sorter, magnetic separation, etc.

[0068] In the method of the present invention, the cancer treatment candidate drug in step 2) includes any substance, molecule, element, compound, entity or combination thereof. For example, it includes but is not limited to proteins, polypeptides, small organic molecules, polysaccharides, polynucleotides, etc. In addition, it can also be a natural product, a synthetic compound or a chemical compound, or a combination of two or more substances. Specific examples are polypeptides, beta-turn mimetics, polysaccharides, phospholipids, hormones, prostaglandins, steroids, aromatic compounds, heterocyclic compounds (), benzodiazepines, oligomeric N-substituted glycines, oligocarbamates, sugars, fatty acids, purines, pyrimidines or their derivatives, structural analogs or combinations thereof, which can be synthetic substances, and other candidate drugs can be natural substances.

[0069] In the method of the present invention, the method for isolating total RNA in step 3) can utilize any method known in the art, for example, phenol extraction method can be used.

[0070] In the method of the present invention, the step 4) may substantially include ADA and CD52, and may include a protein selected from ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RR At least 10, 15, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44 or 45 target genes in the group consisting of M2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ, or all of them include the target genes, but are not limited to them.

[0071] In addition, the step 4) may include a member selected from the group consisting of ACPP, ADA, ALK, BCR-ABL-1, BTK, CD19, CD30, CD52, C-MET, CRBN, CTLA4, CYP17A1, DDR2, ERBB4, FCGR1A, FGF1, FGFR1, FGFR2, FGFR3, FRK, GNRH1, GNRHR, HDAC2, HDAC3, HPRT1, IFNAR1, IFNAR2, IL2RA, IL2RB, IL2RG, ITK, JAK1, and JAK2 , LDLR, LHCGR, LIMK1, MAP1A, MAP2, MAP2K1, MAP2K2, MAPK11, MET, NEK11, NR3C1, NTRK1, PARP1, PARP2, PARP3, PDCD1, PGF, PI K3CD, PRLR, PSMB10, PSMB1, PSMB2, PSMB8, PSMB9, PSMD1, PSMD2, PTK6, RARA, RARB, RARG, RPL3, SH2B3, SIK1, SLC2A2, SMO, SS at least 10, 15, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, or more of the group consisting of TR2, SSTR5, TEK, TLR8, TNFSF8, TNFSF11, TOP1MT, TOP2B, TUBA1A, TUBA4A, TUBB1, TUBB3, TUBB, TUBD1, TUBE1, TUBG1, VEGFA, and VEGFB. 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84 or 85 target genes, or all include the target genes, but are not limited thereto.

[0072] In addition, the primer or probe in step 4) can be a primer or probe for digital PCR, specifically, a primer or probe for droplet digital PCR. The droplet digital PCR is a system that divides the PCR reaction solution into about 15,000 to 20,000 droplets and then amplifies and counts the target nucleic acid. Depending on whether the target nucleic acid in the droplet is amplified or not, the positive droplets (1) and negative droplets (0) are regarded as digital signals for counting, and the copy number of the target nucleic acid is calculated by Poisson distribution, so that the result value can be finally confirmed by the copy number of each sample volume (μl).

[0073] In addition, by inoculating the oil of the reaction solution containing probes such as FAM, HEX or VIC or EvaGreen fluorescent dye into the cartridge and settling it in the droplet generator, about 20,000 droplets can be generated.

[0074] In the method of the present invention, the amplification of the target nucleic acid sequence in step 5) can be performed by multiplex PCR. Multiplex PCR refers to a method of performing PCR amplification in one reaction tube using multiple primer sets at the same time. For example, by performing multiplex PCR using the primer set for the target gene in one reaction tube, the gene expression level can be confirmed at the same time.

[0075] In the method of the present invention, the PCR plate after the PCR in step 6) is mounted on a digital PCR droplet reader, and the EvaGreen fluorescence value of the droplets is confirmed and counted by QuantaSoft, thereby finally analyzing the copy number of the amplified target nucleic acid, but the invention is not limited thereto.

[0076] Ideally, the label is a fluorescent label, and the fluorescent labeling substance can be FAM (5- or 6-carboxyfluorescein), VIC, NED, fluorescein, FITC, IRD-700 / 800, CY3, CY5, CY3.5, CY5.5, HEX, TET, TAMRA, JOE, ROX, BODIPY TMR, Oregon Green, Rhodamine Green, Rhodamine Red, Texas Red, Yakima Yellow, Alexa Fluor PET, Biosearch BlueTM, Marina Blue, Bothell Blue, 350FAMTM, SYBR Green 1, fluorescein, EvaGreenTM, Alexa Fluor 488JOETM, VICTM, HEXT, TETTM, Cal Fluor Gold 540, Yakima Yellow, ROXTM, Cal Fluor Red 610, Cy3.5TM, Texas Red, 568Cy5TM, QuasarTM 670, LightCyclerRed640, Alexa Fluor 633, QuasarTM 705, LightCycler Red705, Alexa Fluor680, Cytation 9, LC Green or LC Green Plus+, specifically, it can be FAM, HEX, SYBR Green or EvaGreen, but not limited to this.

[0077] The excitation wavelength and emission wavelength of the fluorescent marker vary according to the type, and the method of use is also different. Considering this, the fluorescent marker used in a PCR reaction needs to be judged whether it can be used selectively after a separate detection, and different colors can be used. The specific content and selection of the fluorescent marker are obvious to those skilled in the art.

[0078] In the method of the present invention, the candidate drug for which the amount of the target nucleic acid amplified in step 6) is increased in cancer cells compared to normal cells and decreased in cancer cells treated with the cancer treatment candidate drug compared to cancer cells can be selected as a customized drug for cancer patients.

[0079] In the present invention, the expression changes of 134 cancer therapeutic agent target genes between normal tissues and cancer tissues of cancer patients are quantified by digital PCR, confirming that there are differences in the target gene expression patterns of each cancer patient. In addition, it is also confirmed that digital PCR can achieve more accurate analysis than qPCR. Therefore, according to the present invention, the expression patterns of the 134 cancer therapeutic agent target genes are detected by digital PCR, and drugs suitable for cancer patients can be screened, and can be applied to drug screening for customized treatment of cancer patients.

[0080] Hereinafter, the present invention is described in detail by way of examples.

[0081] However, the following embodiments are merely for illustrating the present invention, and the contents of the present invention are not limited to the following embodiments.

[0082] <Example 1> Sample preparation

[0083] Normal and cancer tissue samples from three patients with renal cancer were obtained from the specimen bank of the pathology classroom of Wonju Severance Christian Hospital, South Korea. Three pairs of normal and cancer tissue samples were placed in cryovials and stored frozen at -70°C before RNA extraction. Total RNA extraction was performed using a commercially available kit, RNeasy Midi Kit (Qiagen, Chatsworth, CA, USA) according to the manufacturer's procedure. The quantity and quality of the extracted total RNA were evaluated by UV spectrophotometry (DU 530, Beck-mann, USA).

[0084] 2 μg of extracted total RNA was subjected to reverse transcription reaction in a volume of 20 μl under the condition of unit DNAse I (4.2 μM MgCl2). The composition of the reaction solution is as follows: 2 μg of total RNA, 3.68 μl of 50 mM MgCl2, 0.96 μl of DNAse I, and DEPC water were used to adjust the reaction solution volume to 20 μl.

[0085] For samples previously treated with DNAse I, reverse transcription was performed using Superscript II Reverse transcription Kit (Invitrogen cat#18064-071) under the following conditions: 20 μl of 5X first strand buffer. 10 μl of 100 mM DTT, 20 μl of 10 mM dNTPs, 5 μl of pdN6 (1.6 μg / μl), 0.5 μl of RTase (200 U / μl), 20 μl of RNA, and 24.5 μl of DEPC water. The total reaction solution volume was 100 μl.

[0086] The reverse transcription reaction was performed under the following temperature conditions: 25°C for 10 min, 42°C for 50 min, 72°C for 10 min, and hold at 4°C.

[0087] After the reverse transcription reaction was terminated, the cDNA was adjusted to 5 ng / μl using DEPC water.

[0088] <Example 2> Digital PCR analysis for selecting customized drugs for cancer patients

[0089] In order to select customized drugs for cancer patients, the cDNA obtained in Example 1 was used as a template and the primers for 48 target genes in Table 1 were used to complete the mRNA expression profiles of 48 targets by droplet digital PCR (ddPCR).

[0090] In addition, mRNA expression profiles of 134 targets were completed by ddPCR using primers for 86 target genes in Table 2 below.

[0091] Specifically, 48 and 86 molecular biological targets suitable for the present invention were selected from therapeutic targets for renal cancer therapeutics (e.g., about 300 cancer therapeutics approved by the U.S. FDA or the European EMA, such as everolimus as an mTOR inhibitor), and ddPCR primers for the targets were designed as shown in Tables 1 and 2 below.

[0092] Table 1

[0093]

[0094]

[0095]

[0096] Table 2

[0097]

[0098]

[0099]

[0100]

[0101]

[0102] A ddPCR reaction solution was prepared using the primers according to the composition in Table 3. 12 μl of the ddPCR reaction solution was inoculated into the wells of the nanoplate, and ddPCR was performed using the QIAcuity One ddPCR device under the conditions in Table 4. The gene quantity was quantified using the QuantaSoft program.

[0103] Table 3

[0104] Single layer 1X (μl) 3X EG PCR Master Mix (FAM) 4 10X Primer Mix 0.96 RNase-free water 6.04 template 1

[0105] Table 4

[0106]

[0107] <Comparative Example 1> Real-time quantitative PCR analysis

[0108] Real-time quantitative PCR (qPCR) analysis was performed using the cDNA obtained in Example 1 as a template and the primers in Tables 1 and 2 above.

[0109] Specifically, a qPCR reaction solution was prepared according to the composition of Table 5. 10 μl of the qPCR reaction solution was inoculated into 384 wells, and qPCR was performed using an ABI 7900HT device under the conditions of Table 6. The gene quantity was quantified using the SDS2.4software program.

[0110] Table 5

[0111] Reaction solution 1X (μl) 2X SYBR 5 0.25 μM primer mix 1.2 RNase-free water 2.8 template 1

[0112] Table 6

[0113]

[0114]

[0115] <Experimental Example 1> Target gene expression profile analyzed by digital PCR

[0116] Using normal tissue and cancer tissue samples from three renal cancer patients, ddPCR was performed using the method described in Example 2 to complete the expression profile of 48 target genes ( Figure 2 ).

[0117] In addition, using a pair of normal tissue and cancer tissue samples from three renal cancer patients ( Figures 1A to 1C , Figure 2 The expression profiles of 134 target genes were completed by performing ddPCR using the method described in Example 2 above. Figure 3 ).

[0118] In addition, using normal tissue and cancer tissue samples taken from 3 renal cancer patients, qPCR was performed by the method described in Comparative Example 1 to complete the expression profiles of 134 target genes ( Figures 1A to 1C ).

[0119] Results, such as Figures 1A to 1C , Figure 2 as well as Figure 3 As shown in Figure 2, differences in the expression patterns of 134 target genes were confirmed between normal tissues and cancer tissues of renal cancer patients ( Figures 1A to 1C In particular, when ddPCR and qPCR were performed on 48 target genes, a more obvious expression pattern of the target genes was shown when ddPCR was performed compared with when qPCR was performed, for example, a more obvious expression pattern was shown in PSMB5, ​​PDFGRβ, POlB, etc. ( Figure 1A and Figure 2 ).

[0120] In addition, it was confirmed that expression profiles of 134 target genes for normal tissues and cancer tissues of renal cancer patients could be obtained by performing ddPCR, and 23 target genes, such as ADA, B-RAF, CD52, DNMT1, HPRT1, PolA, PSMB1, PSMB5, ​​RRM1, RRM2, SRC, TOP2A, TYMS, AR, PARP1, PARP2, CRBN, DDR2, FGFR1, GNRH1, MAP2K2, VEGFB, and TUBB, were significantly overexpressed in cancer tissues compared with normal tissues, showing a difference of 5 times or more. In particular, it was difficult to confirm the expression pattern when performing qPCR on ADA and CD52 as target genes, whereas their expression patterns were clearly confirmed by performing ddPCR ( Figures 1A to 1C , Figure 3 ).

[0121] The above results indicate that even for the same type of renal cancer, the expression of target genes for cancer therapeutic agents differs from patient to patient, and thus grasping the individual expression pattern of each patient can achieve effective treatment.

[0122] Therefore, after analyzing the expression patterns of 134 cancer therapeutic agent expression genes between normal tissues and cancer tissues of cancer patients, the present invention can be applied to customized treatment for each patient by selectively administering existing cancer therapeutic agents or cancer therapeutic agents to be developed to cancer patients based on such expression patterns.

[0123] Industrial Applicability

[0124] In the present invention, the expression changes of 134 cancer therapeutic target genes between normal tissues and cancer tissues of cancer patients are quantitatively, conveniently and accurately analyzed by digital PCR, thereby confirming that there are differences in the expression patterns of target genes between cancer patients. Therefore, if existing cancer therapeutic agents or cancer therapeutic agents to be developed are selectively administered to cancer patients, the kit containing 134 cancer therapeutic target gene-specific primers or probes can be suitable for customized treatment for each patient.

Claims

1. A kit for selecting a customized drug for a cancer patient, comprising: Primers or probes that specifically hybridize to target genes ADA and CD52, respectively; as well as A primer or probe that specifically hybridizes to each of at least 5 target genes selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT 4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ.

2. The kit for selecting a customized drug for cancer patients according to claim 1, wherein: The targets basically include ADA and CD52, and include at least 10 targets selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ.

3. The kit for selecting a customized drug for cancer patients according to claim 2, wherein: The targets essentially include ADA and CD52, and include at least 20 targets selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ.

4. The kit for selecting a customized drug for cancer patients according to claim 3, wherein: The targets essentially include ADA and CD52, and include at least 25 targets selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ.

5. A kit for selecting customized drugs for cancer patients according to claim 4, wherein: The targets essentially include ADA and CD52, and include at least 35 targets selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ.

6. A kit for selecting customized drugs for cancer patients according to claim 5, wherein: The targets essentially include ADA and CD52, and include at least 45 targets selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ.

7. The kit for selecting a customized drug for cancer patients according to claim 1, wherein: The primers that specifically hybridize to each of the target genes are selected from the group consisting of primers shown in SEQ ID NOs: 1 to 96, 99, 100, 111 and 112.

8. The kit for selecting a customized drug for a cancer patient according to claim 1, further comprising: ACPP, ADA, ALK, BCR-ABL-1, BTK, CD19, CD30, CD52, C-MET, CRBN, CTLA4, CYP17A1, DDR2, ERBB4, FCGR1A, FGF1, FGFR1, FGFR2, FGFR3, FRK, GNRH1, GNRHR, HDAC2, HDAC3, HPRT1, IFNAR1, IFNAR2, IL2RA, IL2RB, IL2RG, ITK, JAK1, JAK2, LDLR, LHCGR, LIMK1, MAP1A, MAP2, MAP2K1, MAP2K2, MAPK11, MET, NEK11, NR3C1, NTRK1, PA Primers or probes that specifically hybridize to each of at least 10 target genes in the group consisting of RP1, PARP2, PARP3, PDCD1, PGF, PIK3CD, PRLR, PSMB10, PSMB1, PSMB2, PSMB8, PSMB9, PSMD1, PSMD2, PTK6, RARA, RARB, RARG, RPL3, SH2B3, SIK1, SLC2A2, SMO, SSTR2, SSTR5, TEK, TLR8, TNFSF8, TNFSF11, TOP1MT, TOP2B, TUBA1A, TUBA4A, TUBB1, TUBB3, TUBB, TUBD1, TUBE1, TUBG1, VEGFA and VEGFB.

9. The kit for selecting customized drugs for cancer patients according to claim 8, further comprising: Select from ACPP, ADA, ALK, BCR-ABL-1, BTK, CD19, CD30, CD52, C-MET, CRBN, CTLA4, CYP17A1, DDR2, ERBB4, FCGR1A, FGF1, FGFR1, FGFR2, FGFR3, FRK, GNRH1, GNRHR, HD AC2, HDAC3, HPRT1, IFNAR1, IFNAR2, IL2RA, IL2RB, IL2RG, ITK, JAK1, JAK2, LDLR, LHCGR, LIMK1, MAP1A, MAP2, MAP2K1, MAP2K2, MAPK11, MET, NEK11, NR3C1, NT At least 20 targets from the group consisting of RK1, PARP1, PARP2, PARP3, PDCD1, PGF, PIK3CD, PRLR, PSMB10, PSMB1, PSMB2, PSMB8, PSMB9, PSMD1, PSMD2, PTK6, RARA, RARB, RARG, RPL3, SH2B3, SIK1, SLC2A2, SMO, SSTR2, SSTR5, TEK, TLR8, TNFSF8, TNFSF11, TOP1MT, TOP2B, TUBA1A, TUBA4A, TUBB1, TUBB3, TUBB, TUBD1, TUBE1, TUBG1, VEGFA and VEGFB.

10. The kit for selecting customized drugs for cancer patients according to claim 9, further comprising: Select from ACPP, ADA, ALK, BCR-ABL-1, BTK, CD19, CD30, CD52, C-MET, CRBN, CTLA4, CYP17A1, DDR2, ERBB4, FCGR1A, FGF1, FGFR1, FGFR2, FGFR3, FRK, GNRH1, GNRHR, HD AC2, HDAC3, HPRT1, IFNAR1, IFNAR2, IL2RA, IL2RB, IL2RG, ITK, JAK1, JAK2, LDLR, LHCGR, LIMK1, MAP1A, MAP2, MAP2K1, MAP2K2, MAPK11, MET, NEK11, NR3C1, NT At least 40 targets from the group consisting of RK1, PARP1, PARP2, PARP3, PDCD1, PGF, PIK3CD, PRLR, PSMB10, PSMB1, PSMB2, PSMB8, PSMB9, PSMD1, PSMD2, PTK6, RARA, RARB, RARG, RPL3, SH2B3, SIK1, SLC2A2, SMO, SSTR2, SSTR5, TEK, TLR8, TNFSF8, TNFSF11, TOP1MT, TOP2B, TUBA1A, TUBA4A, TUBB1, TUBB3, TUBB, TUBD1, TUBE1, TUBG1, VEGFA and VEGFB.

11. The kit for selecting customized drugs for cancer patients according to claim 10, further comprising: Select from ACPP, ADA, ALK, BCR-ABL-1, BTK, CD19, CD30, CD52, C-MET, CRBN, CTLA4, CYP17A1, DDR2, ERBB4, FCGR1A, FGF1, FGFR1, FGFR2, FGFR3, FRK, GNRH1, GNRHR, HD AC2, HDAC3, HPRT1, IFNAR1, IFNAR2, IL2RA, IL2RB, IL2RG, ITK, JAK1, JAK2, LDLR, LHCGR, LIMK1, MAP1A, MAP2, MAP2K1, MAP2K2, MAPK11, MET, NEK11, NR3C1, NT At least 60 targets from the group consisting of RK1, PARP1, PARP2, PARP3, PDCD1, PGF, PIK3CD, PRLR, PSMB10, PSMB1, PSMB2, PSMB8, PSMB9, PSMD1, PSMD2, PTK6, RARA, RARB, RARG, RPL3, SH2B3, SIK1, SLC2A2, SMO, SSTR2, SSTR5, TEK, TLR8, TNFSF8, TNFSF11, TOP1MT, TOP2B, TUBA1A, TUBA4A, TUBB1, TUBB3, TUBB, TUBD1, TUBE1, TUBG1, VEGFA and VEGFB.

12. The kit for selecting customized drugs for cancer patients according to claim 8, wherein: The primers that specifically hybridize to each of the target genes are selected from the group consisting of primers shown in SEQ ID NOs: 97, 98, 101 to 110, and 113 to 268.

13. The kit for selecting customized drugs for cancer patients according to claim 1, wherein: The kit is a kit for digital PCR.

14. The kit for selecting customized drugs for cancer patients according to claim 1, wherein: The kit is a kit for droplet digital PCR.

15. The kit for selecting customized drugs for cancer patients according to claim 1, wherein: The cancer is selected from the group consisting of kidney cancer, stomach cancer, lung cancer, breast cancer, ovarian cancer, liver cancer, bronchial cancer, nasopharyngeal cancer, laryngeal cancer, pancreatic cancer, bladder cancer, large intestine cancer, colon cancer, cervical cancer, brain cancer, prostate cancer, bone cancer, head and neck cancer, skin cancer, thyroid cancer, parathyroid cancer, ureteral cancer and blood cancer.

16. A method for selecting customized drugs for cancer patients, comprising: 1) detecting the expression of at least five target genes selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, HDAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ and RXRγ in a biological sample isolated from a cancer patient; and 2) Selecting a drug that acts on the target gene whose high expression is detected in step 1).

17. The method for selecting customized drugs for cancer patients according to claim 16, wherein: The expression detection of the gene was performed by digital PCR method.

18. The method for selecting customized drugs for cancer patients according to claim 17, wherein: The expression detection of the gene was performed by droplet digital PCR method.

19. A method for customized drug screening for cancer patients, comprising: 1) Isolating cancer cells and normal cells from cancer tissues and normal tissues isolated from cancer patients and proliferating them; 2) treating the cancer cells of step 1) with a candidate drug for cancer treatment; 3) isolating total RNA from the cancer cells and normal cells in step 1) and the cancer cells treated with the candidate cancer therapeutic drug in step 2), and synthesizing cDNA using the total RNA as a template; 4) using the cDNA synthesized in step 3) as a template, generating a plurality of droplets from a reaction solution, wherein the reaction solution comprises primers or probes that specifically hybridize with the target genes ADA and CD52, respectively, and a primer or probe that specifically hybridizes with a target gene selected from the group consisting of ABL1, ABL2, ALAD, EGFR, B-RAF, CD20, CD33, CHD1, C-RAF, CSF1R, DHFR, DNMT1, EPHA2, FLT1, FLT3, FLT4, FYN, GARFT, HDAC1, H a primer or probe that specifically hybridizes to each of at least 5 target genes in the group consisting of DAC6, HER2, KDR, Kit, Lck, mTOR, NK1R, PDGFRα, PDGFRβ, PolA, PolB, PSMB5, ​​RET, RRM1, RRM2, RRM2B, SRC, TLR7, TOP1, TOP2A, TYMS, YES, CYP19A1, AR, ERα, ERβ, RXRα, RXRβ, and RXRγ; 5) amplifying the target nucleic acid sequence in the droplets generated in step 4); as well as 6) Determine the amount of amplified target nucleic acid by counting the number of droplets having the target nucleic acid amplified by step 5), and then compare it with the amount of amplified target nucleic acid in normal cells, cancer cells, and cancer cells treated with candidate drugs.

20. The method for screening customized drugs for cancer patients according to claim 19, wherein: The primers or probes are primers or probes for digital PCR.

21. The method for screening customized drugs for cancer patients according to claim 20, wherein: The primers or probes are primers or probes for droplet digital PCR.

22. The method for screening customized drugs for cancer patients according to claim 19, wherein: The candidate drug is selected for which the amount of the target nucleic acid amplified in step 6) is increased in cancer cells compared to normal cells and is decreased in cancer cells treated with the cancer therapeutic candidate drug compared to cancer cells.

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