Biomarker for predicting responsiveness to substance for preventing or treating cancer and uses thereof

Abstract

According to the present invention, a specific biomarker is used to predict in advance the responsiveness to a substance for preventing or treating cancer, so that an optimal therapeutic agent can be selected for each patient, thereby preventing unnecessary drug administration and improving treatment success rates. In addition, by providing a pharmaceutical composition for enhancing sensitivity to a cancer therapeutic agent, the therapeutic effect can be increased even in cancers exhibiting resistance. Furthermore, the present invention enables efficient screening of sensitivity-enhancing substances, thereby improving the efficiency and industrial utilization of new drug development.

Description

Biomarkers for predicting responsiveness to cancer prevention or treatment substances and their uses

[0001] The present invention relates to a biomarker for predicting responsiveness to a substance for the prevention or treatment of cancer and the use thereof.

[0002]

[0003] Cancer is one of the leading causes of death worldwide, and various treatment methods, including surgery, radiation therapy, chemotherapy, targeted therapy, and immunotherapy, are utilized in clinical practice. However, even when the same anticancer substance is administered, treatment responses vary significantly among patients, and problems such as insufficient therapeutic effects or the development of resistance during treatment are continuously being reported in some patients.

[0004] Anticancer drug resistance can be induced by various molecular mechanisms, such as the regulation of drug uptake and efflux in cancer cells, alterations in target proteins, increased DNA repair capabilities, and evasion of apoptosis mechanisms; it is recognized as one of the major causes of cancer treatment failure. This resistance leads to problems such as unnecessary drug administration, increased side effects, treatment delays, and increased medical costs.

[0005] Recently, technologies for evaluating individual patients' drug responsiveness in vitro using patient-derived cancer cells and tumor organoids are being actively developed, and these technologies have the advantage of relatively accurately reflecting actual patients' treatment responses. In particular, cell and organoid-based drug response analysis is being utilized as a useful means to quantitatively evaluate responsiveness and tolerance characteristics to various cancer therapeutic agents.

[0006] Meanwhile, to interpret these cell and organoid-based analysis results more efficiently and utilize them rapidly in actual clinical practice, there is a need to develop technologies that predict patient treatment responses by analyzing molecular indicators closely associated with drug responsiveness. Accordingly, biomarker technology capable of predicting responsiveness to cancer therapeutic agents using molecular information obtained from biological samples is attracting attention as one of the core technologies for realizing precision medicine.

[0007]

[0008] As one aspect of the present invention, the purpose is to provide a method for providing information for predicting responsiveness to a substance for preventing or treating cancer, comprising the step of measuring the expression level of the FKBP10 (FKBP Prolyl Isomerase 10) gene from a biological sample obtained from an individual.

[0009] As one aspect of the present invention, the purpose is to provide a composition for predicting responsiveness to a cancer prevention or treatment substance, comprising a preparation for measuring the expression level of the FKBP10 gene.

[0010] As one aspect of the present invention, the purpose is to provide a kit for predicting responsiveness to a substance for preventing or treating cancer, comprising the above composition.

[0011] As one aspect of the present invention, the purpose is to provide a pharmaceutical composition for enhancing sensitivity to a substance for the prevention or treatment of cancer, comprising a preparation that inhibits the expression of the FKBP10 gene.

[0012] As one aspect of the present invention, the purpose is to provide a use of a preparation that inhibits the expression of the FKBP10 gene for the manufacture of a drug for enhancing sensitivity to a substance for the prevention or treatment of cancer.

[0013] As one aspect of the present invention, the purpose is to provide a method for enhancing sensitivity to a substance for the prevention or treatment of cancer, comprising the step of administering a pharmaceutically effective amount of a preparation that inhibits the expression of the FKBP10 gene to an individual in need thereof.

[0014] The technical problems that the present invention aims to solve are not limited to those mentioned above, and other unmentioned technical problems will be clearly understood by those skilled in the art from the description below.

[0015]

[0016] In one aspect of the present invention, a method for providing information for predicting responsiveness to a substance for preventing or treating cancer is provided, comprising the step of measuring the expression level of the FKBP10 (FKBP Prolyl Isomerase 10) gene from a biological sample obtained from an individual.

[0017] In the above method, the method may further include a step of determining that resistance to a cancer prevention or treatment substance is present if the expression level of the FKBP10 gene is higher than the expression level in a biological sample obtained from a normal control individual.

[0018] 상기 방법에 있어서, 보다 신뢰성 있는 정보를 제공하기 위하여, 상기 생땠선 시료로부터 MACROD2(Mono-ADP-Ribosylhydrolase 2), ABCA10(ATP Binding Cassette Subfamily A Member 10), ABCA13(ATP Binding Cassette Subfamily A Member 13), ARHGAP4(Rho GTPases Protein Activate 14), Numimic Protein A. Homolog 1), ATP6V1C2(ATPase H+ Transporting V1 Subunit C2), COL28A1(Collagen Type XXVIII Alpha 1 Chain), COL9A3(Collagen Type IX Alpha 3 Chain), CRYM(Crystallin Mu), ECM1(Extracellular Matrix Protein 1), Receptor(EDAR), Actoin F3(Coagulation Factor III), FAM167A(Family With Sequence Similarity 167 Member A), FGF11(Fibroblast Growth Factor 11), GOLGA7B(Golgin A7 Family Member B), HLA-B(Major Histocompatibility Complex, Class I, B), LOC 24152,2 MAPK8IP2(Mitogen-Activated Protein Kinase 8 Interacting Protein 2), NKD1(Naked Cuticle Homolog 1), PMAIP1(PMA Induced Protein 1), PMEPA1(Prostate Transmembrane Protein, Androgen Induced 1), PON3(Paraoxonase 3), RBP1(Retinol Binding Protein), RBP4(Retinol Binding Protein 4),The method may further include the step of measuring the expression level of at least one gene selected from the group consisting of SOX21 (SRY-Box Transcription Factor 21), SPATA17 (Spermatogenesis Associated 17), TGFB2 (Transforming Growth Factor Beta 2), THBS1 (Thrombospondin 1), and ZNF532 (Zinc Finger Protein 532).

[0019] In such cases, the method may further include a step of determining that resistance to a cancer preventive or therapeutic substance is present if the expression level of at least one gene selected from the group consisting of FKBP10, MACROD2, ABCA13, ATHL1, ECM1, EDAR, F3, FGF11, HLA-B, NKD1, PMAIP1, PMEPA1, RBP1, SOX21, TGFB2, THBS1, and ZNF532 is higher than the expression level in a biological sample obtained from a normal control individual, and / or if the expression level of at least one gene selected from the group consisting of ABCA10, ARHGAP4, ATP6V1C2, COL28A1, COL9A3, CRYM, FAM167A, GOLGA7B, LOC102724532, MAPK8IP2, PON3, RBP4, and SPATA17 is lower than the expression level in a biological sample obtained from a normal control individual, to the cancer preventive or therapeutic substance It may include an additional step of determining high sensitivity to it.

[0020] In the above method, the individual refers to an animal including humans, and specifically may refer to at least one selected from humans, dogs, cats, mice, etc., but is not particularly limited to any subject that is a potential subject for developing cancer. Specifically, it may be a human individual that is likely to develop cancer or has developed cancer, or has developed cancer. More specifically, it may be a human individual that is likely to develop cancer or has developed cancer, or has developed cancer, and is suspected of having resistance to a substance for preventing or treating cancer.

[0021] In the above method, the cancer may be at least one selected from the group consisting of pancreatic cancer, gastric cancer, lung cancer, hepatocellular carcinoma, colorectal cancer, breast cancer, prostate cancer, thyroid cancer, ovarian cancer, cervical cancer, renal cell carcinoma, bladder cancer, melanoma, leukemia, lymphoma, multiple myeloma, brain tumor, sarcoma, metastatic cancers thereof, and recurrent cancers thereof, but is not limited thereto.

[0022] In the above method, the substance for preventing or treating cancer may be at least one selected from the group consisting of gemcitabine, 5-fluorouracil, leucovorin, oxaliplatin, Nab-Paclitaxel, paclitaxel, cisplatin, capecitabine, S-1 (Tegafur / Gimeracil / Oteracil), erlotinib, olaparib, nivolumab, pembrolizumab, irinotecan, and SN-38, but is not limited thereto.

[0023] In the above method, the biological sample refers to any sample capable of detecting the expression level of a gene within an individual, and may be at least one selected from the group consisting of serum, blood, whole blood, plasma, urine, saliva, tissue, cell, organ, bone marrow, fine needle aspiration sample, core needle biopsy sample, and vacuum aspiration biopsy sample, but is not limited thereto, and may be prepared by processing by a method commonly used in the field of the art of the present invention.

[0024] In the above method, as a method for measuring the expression level, a method for measuring the concentration of mRNA, which is a transcription material of a gene, or the concentration of the protein in a sample may be chosen, but is not limited thereto, and may be performed by choosing a method commonly used in the technical field of the present invention.

[0025] In the above method, reverse transcriptase polymerase chain reaction (RT-PCR), competitive reverse transcriptase polymerase chain reaction (Competitive RT-PCR), real-time reverse transcriptase polymerase chain reaction (Real-time RT-PCR), RNase protection assay (RPA), Northern blotting, and DNA chips may be used as methods to measure the concentration of the mRNA in a sample, but are not limited thereto.

[0026] In the above method, the amount of protein can be determined by using an antibody that specifically binds to the protein as a method for measuring the concentration of the protein in a sample. As analytical methods for this purpose, immunoassay, ELISA (enzyme-linked immunosorbent assay), radioimmunoassay (RIA), radioimmunodiffusion, Ouchterlony immunodiffusion, rocket immunoelectrophoresis, immunohistochemistry, immunoprecipitation assay, complement fixation assay, FACS (fluorescence-activated cell sorting), and protein chip may be utilized, but are not limited thereto.

[0027]

[0028] As one aspect of the present invention, a composition for predicting responsiveness to a substance for preventing or treating cancer is provided, comprising a preparation for measuring the expression level of the FKBP10 gene.

[0029] In the above composition, a preparation for measuring the expression level of the MACROD2 gene may be further included to predict reactivity more accurately.

[0030] In the above composition, for more accurate reactivity prediction, it may further include a preparation for measuring the expression level of at least one gene selected from the group consisting of ABCA10, ABCA13, ARHGAP4, ATHL1, ATP6V1C2, COL28A1, COL9A3, CRYM, ECM1, EDAR, F3, FAM167A, FGF11, GOLGA7B, HLA-B, LOC102724532, MAPK8IP2, NKD1, PMAIP1, PMEPA1, PON3, RBP1, RBP4, SOX21, SPATA17, TGFB2, THBS1, and ZNF532.

[0031] In the above composition, the agent for measuring the gene expression level may include, but is not limited to, a substance that specifically binds to the nucleotide sequence of the gene, a sequence complementary to the nucleotide sequence, a fragment of the nucleotide, or a protein encoded by the nucleotide sequence.

[0032] In the above composition, the substance that specifically binds to the protein may specifically be an antibody, and the antibody refers to a specific immunoglobulin directed to an antigenic site. The antibody refers to an antibody that specifically binds to the translation protein of the gene. The gene may be cloned into an expression vector to obtain its translation protein, and the antibody may be prepared from the obtained protein according to conventional methods in the art. The form of the antibody includes polyclonal antibodies or monoclonal antibodies, and all immunoglobulin antibodies are included. The antibody includes not only a complete form having two full-length light chains and two full-length heavy chains, but also a functional fragment of an antibody molecule that does not have the structure of a complete antibody having two light chains and two heavy chains, but possesses an antigen-binding function by having a specific antigen-binding site (binding domain) directed to an antigenic site. In a diagnosis using the above composition, the diagnosis can be made by performing hybridization using the translation protein of the gene and the antibody, and measuring the expression level of the gene through the degree of hybridization. The selection of an appropriate antibody and hybridization conditions can be appropriately selected according to techniques known in the art.

[0033] The nucleotide sequence, the sequence complementary to the nucleotide sequence, and the substance that specifically binds to the fragment of the nucleotide may specifically be a probe or a primer.

[0034] The above probe refers to a nucleotide fragment, such as RNA or DNA, ranging from a few bases to hundreds of bases, capable of specifically binding to nucleotides such as mRNA, and is labeled with a radioactive element, etc., to confirm the presence or absence and content (expression amount) of a specific mRNA. The above probe can be produced in the form of an oligonucleotide probe, a single-strand DNA probe, a double-strand DNA probe, an RNA probe, etc., and diagnosis can be made by performing hybridization using a probe complementary to the mRNA of the gene and measuring the expression amount of mRNA through the degree of hybridization. The selection of an appropriate probe and hybridization conditions can be appropriately selected according to techniques known in the relevant art field.

[0035] The above primer refers to a short nucleotide sequence having a short free 3' hydroxyl group, capable of forming base pairs with a complementary template, and acting as a starting point for template strand replication. The primer can initiate DNA synthesis in the presence of reagents for polymerization (i.e., DNA polymerase / polymerase or reverse transcriptase) and four different nucleoside triphosphates at an appropriate buffer solution and temperature, and can be diagnosed by measuring the expression level of a desired protein by performing PCR amplification using the primers of the mRNA of the gene. The PCR conditions and the length of the primer set can be appropriately selected according to techniques known in the art.

[0036] Since the nucleotide sequence of the gene, the sequence complementary to the nucleotide sequence, or the probe or primer that specifically binds to the fragment of the nucleotide is known, a person skilled in the art can design the primer or probe based on the sequence according to conventional methods in the art.

[0037] The above probe or primer can be chemically synthesized using a phosphoramidite solid support synthesis method or other widely known methods, and may have a length of 10 to 100 nucleotides (hereinafter referred to as 'nt'), 10 to 90 nt, 10 to 80 nt, 10 to 70 nt, 10 to 60 nt, 10 to 50 nt, 10 to 40 nt, 10 to 30 nt, 10 to 25 nt, 20 to 100 nt, 30 to 90 nt, 40 to 80 nt, 50 to 70 nt, 20 to 60 nt, 20 to 50 nt, 30 to 40 nt, 20 to 30 nt, or 20 to 25 nt.

[0038] In the above composition, technical details related throughout the specification, such as samples, cancer, and substances for the prevention or treatment of cancer, may be interpreted by referring to the above.

[0039]

[0040] As one aspect of the present invention, a kit for predicting reactivity to a substance for preventing or treating cancer is provided, comprising the above composition.

[0041] The above kit can diagnose the expression level of the said gene by measuring the expression level of the mRNA of the said gene or the translational protein thereof. The above kit may include a substance that specifically binds to the nucleotide sequence of the said gene, a sequence complementary to the said nucleotide sequence, a fragment of the said nucleotide, or a protein encoded by the said nucleotide sequence, as well as one or more other component compositions, solutions, or devices suitable for an analysis method for measuring the expression level of the said gene's translational protein used by the kit.

[0042] If the above kit is a kit for measuring the expression level of the mRNA of the said gene, it may be a kit containing essential elements necessary for performing RT-PCR. In addition to each primer pair specific to the mRNA of the said gene, the RT-PCR kit may include a test tube or other suitable container, reaction buffer, deoxyribonucleotides (dNTPs), enzymes such as Taq-polymerase and reverse transcriptase, DNase, RNase inhibitors, DEPC-water, sterile water, etc. Additionally, it may include a primer pair specific to the gene used as a quantitative control.

[0043] The above kit may include a substrate, a suitable buffer solution, a secondary antibody labeled with a chromogenic enzyme or a fluorescent substance, and a chromogenic substrate for the immunological detection of a substance that specifically binds to the nucleotide sequence of the gene, a sequence complementary to the nucleotide sequence, a fragment of the nucleotide, or a protein encoded by the nucleotide sequence. The substrate may be a nitrocellulose membrane, a 96-well plate synthesized from polyvinyl resin, a 96-well plate synthesized from polystyrene resin, and a glass slide glass; the chromogenic enzyme may be peroxidase or alkaline phosphatase; the fluorescent substance may be FITC, RITC, etc.; and the chromogenic substrate may be 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) or o-phenylenediamine (OPD), tetramethylbenzidine (TMB), etc.

[0044] As a specific example, the above kit may be a diagnostic microarray capable of measuring the expression level of the translation protein of the said gene or the mRNA of the gene encoding it. The said microarray can be easily manufactured by a person skilled in the art according to methods known in the art, and according to one embodiment, it may be a microarray in which a cDNA having a sequence corresponding to the mRNA of the said gene or a fragment thereof is attached to a substrate as a probe.

[0045] As a specific example, the above kit may be a diagnostic protein array or protein chip capable of measuring the expression level of the translation protein of the said gene. The said protein array or protein chip can be easily manufactured by a person skilled in the art according to methods known in the art, and according to one embodiment, a diagnosis can be made by extracting a patient's sample and confirming the reaction between the patient's sample and a substance capable of measuring the expression level of the said gene's translation protein, such as an antibody, receptor, nucleic acid, or carbohydrate, which can specifically bind to the said gene's translation protein immobilized in the kit.

[0046] In the above-mentioned kit, technical content related throughout the specification, such as the composition, sample, cancer, or substance for the prevention or treatment of cancer included in the kit, may be interpreted by referring to the above-mentioned provisions.

[0047]

[0048] As one aspect of the present invention, a method for screening substances that improve responsiveness to a substance for the prevention or treatment of cancer is provided, comprising the step of measuring the expression level of the FKBP10 gene from a biological sample obtained from an individual treated with a candidate substance.

[0049] In the above method, if the expression level of the FKBP10 gene is lower than the expression level in a biological sample obtained from an individual prior to treatment, the method may further include the step of selecting a substance that improves responsiveness to a substance for preventing or treating cancer.

[0050] In the above method, for more rigorous screening, the method may further include the step of measuring the expression level of at least one gene selected from the group consisting of MACROD2, ABCA10, ABCA13, ARHGAP4, ATHL1, ATP6V1C2, COL28A1, COL9A3, CRYM, ECM1, EDAR, F3, FAM167A, FGF11, GOLGA7B, HLA-B, LOC102724532, MAPK8IP2, NKD1, PMAIP1, PMEPA1, PON3, RBP1, RBP4, SOX21, SPATA17, TGFB2, THBS1, and ZNF532 from a biological sample obtained from an individual treated with a candidate substance.

[0051] In such cases, the method may further include the step of selecting a substance that improves responsiveness to a substance for preventing or treating cancer if the expression level of at least one gene selected from the group consisting of FKBP10, MACROD2, ABCA10, ABCA13, ARHGAP4, ATHL1, ATP6V1C2, COL28A1, COL9A3, CRYM, ECM1, EDAR, F3, FAM167A, FGF11, GOLGA7B, HLA-B, LOC102724532, MAPK8IP2, NKD1, PMAIP1, PMEPA1, PON3, RBP1, RBP4, SOX21, SPATA17, TGFB2, THBS1, and ZNF532 is lower than the expression level in a biological sample obtained from an individual prior to treatment.

[0052] In the above method, the candidate substance may include, without limitation, a newly synthesized or known compound that is expected to improve the responsiveness to a drug (substance) in the prevention or treatment of cancer, and may be, for example, at least one selected from the group consisting of nucleic acids, nucleotides, proteins, peptides, amino acids, sugars, lipids, and compounds, but is not particularly limited thereto.

[0053] In the above method, regarding technical content related throughout the specification, such as individuals, samples, cancer, substances for preventing or treating cancer, expression levels, etc., it may be interpreted by referring to the above.

[0054]

[0055] As one aspect of the present invention, a pharmaceutical composition for enhancing sensitivity to a substance for the prevention or treatment of cancer is provided, comprising a preparation that inhibits the expression of the FKBP10 gene.

[0056] In the above composition, to achieve a higher sensitivity enhancement effect, a preparation that inhibits the expression of the MACROD2 gene may be further included.

[0057] In order to achieve a higher sensitivity enhancement effect, the above composition may further include an agent that inhibits the expression of at least one gene selected from the group consisting of ABCA10, ABCA13, ARHGAP4, ATHL1, ATP6V1C2, COL28A1, COL9A3, CRYM, ECM1, EDAR, F3, FAM167A, FGF11, GOLGA7B, HLA-B, LOC102724532, MAPK8IP2, NKD1, PMAIP1, PMEPA1, PON3, RBP1, RBP4, SOX21, SPATA17, TGFB2, THBS1, and ZNF532.

[0058] In the above composition, the cancer may exhibit resistance to at least one anticancer agent selected from the group consisting of gemcitabine, 5-fluorouracil, leucovorin, oxaliplatin, nab-paclitaxel, paclitaxel, cisplatin, capecitabine, S-1, erlotinib, olaparib, nivolumab, pembrolizumab, irinotecan, and SN-38, but is not limited thereto.

[0059] In the above composition, the term "agent that inhibits gene expression" refers to a substance that directly or indirectly inhibits the transcription, translation, or protein stability of a specific gene to significantly reduce the mRNA expression level or protein expression level of the said gene, and the agent may include a transcription inhibitor, a signaling pathway inhibitor, an epigenetic regulator (histone deacetylation inducer, DNA methylation inducer, etc.), microRNA, siRNA, shRNA, antisense oligonucleotide, a CRISPR-based gene inhibition means, or a combination thereof, and the reduction in expression may be confirmed through qRT-PCR, RNA-seq, Western blot, immunohistochemical staining (IHC), or ELISA analysis.

[0060] The above composition may further include a pharmaceutically acceptable carrier and may be formulated together with the carrier. In the present invention, the term "pharmaceutically acceptable carrier" refers to a carrier or diluent that does not irritate living organisms and does not impair the biological activity and properties of the administered compound. Acceptable pharmaceutical carriers for compositions formulated as liquid solutions are those that are sterile and biocompatible, and may include saline solution, sterile water, Ringer's solution, buffered saline solution, albumin injection solution, dextrose solution, maltodextrin solution, glycerol, ethanol, and mixtures of one or more of these components; additionally, other conventional additives such as antioxidants, buffers, and bacteriostatic agents may be added as needed. Furthermore, diluents, dispersants, surfactants, binders, and lubricants may be additionally added to formulate the composition into injectable formulations such as aqueous solutions, suspensions, and emulsions, as well as pills, capsules, granules, or tablets.

[0061] The above composition may be applied to any formulation containing the above composition as an active ingredient, and may be prepared as an oral or parenteral formulation. The pharmaceutical formulations of the present invention include forms suitable for oral, rectal, nasal, topical (including the cheek and under the tongue), subcutaneous, vaginal, or parenteral (including intramuscular, subcutaneous, and intravenous) administration, or forms suitable for administration by inhalation or insufflation.

[0062] In the above composition, the composition is administered in a pharmaceutically effective amount. The effective dose level may be determined based on factors including the type and severity of the patient's disease, drug activity, sensitivity to the drug, time of administration, route of administration and elimination rate, duration of treatment, concurrently used drugs, and other factors well known in the medical field. The pharmaceutical composition of the present invention may be administered as an individual therapeutic agent or in combination with other therapeutic agents, may be administered sequentially or simultaneously with conventional therapeutic agents, and may be administered as a single or multiple doses. It is important to administer an amount that obtains maximum effect with a minimum amount without side effects by taking all of the above factors into consideration, and this can be easily determined by a person skilled in the art.

[0063] In the above composition, the dosage of the composition varies widely depending on the patient's body weight, age, gender, health status, diet, time of administration, method of administration, excretion rate, and severity of the disease, and the appropriate dosage may vary, for example, depending on the amount of drug accumulated in the patient's body and / or the specific efficacy of the composition used. Generally, it can be calculated based on the EC50 measured as effective in in vivo animal models and in vitro, for example, 0.01 μg to 1 g per kg of body weight, and may be administered in divided doses of one to several times per unit period on a daily, weekly, monthly, or yearly basis, or may be administered continuously over a long period using an infusion pump. The number of repeated administrations is determined by considering the time the drug remains in the body and the drug concentration in the body. Depending on the course of disease treatment, the composition may be administered for recurrence even after treatment has been achieved.

[0064] In the above composition, the composition may additionally contain one or more active ingredients that exhibit the same or similar functions in relation to the prevention or treatment of cancer, or a compound that maintains / increases the solubility and / or absorption of the active ingredients. Additionally, optionally, it may additionally include chemotherapy agents, anti-inflammatory agents, antiviral agents and / or immunomodulators, etc.

[0065] In the above composition, the composition may be formulated using methods known in the art to provide rapid, sustained, or delayed release of the active ingredient after administration to a mammal. The formulation may be in the form of powder, granules, tablets, emulsions, syrups, aerosols, soft or hard gelatin capsules, sterile injectable solutions, or sterile powders.

[0066] In the above composition, technical details related throughout the specification, such as cancer, cancer prevention or treatment substances, may be interpreted by referring to the above.

[0067]

[0068] As one aspect of the present invention, a pharmaceutical composition for the prevention or treatment of cancer is provided, comprising a preparation that inhibits the expression of the FKBP10 gene and an anticancer agent.

[0069] In the above composition, to maximize the synergistic effect, a preparation that inhibits the expression of the MACROD2 gene may be further included.

[0070] In the above composition, to maximize the synergistic effect, it may further include an agent that inhibits the expression of at least one gene selected from the group consisting of ABCA10, ABCA13, ARHGAP4, ATHL1, ATP6V1C2, COL28A1, COL9A3, CRYM, ECM1, EDAR, F3, FAM167A, FGF11, GOLGA7B, HLA-B, LOC102724532, MAPK8IP2, NKD1, PMAIP1, PMEPA1, PON3, RBP1, RBP4, SOX21, SPATA17, TGFB2, THBS1, and ZNF532.

[0071] In the above composition, the cancer may exhibit resistance to at least one anticancer agent selected from the group consisting of gemcitabine, 5-fluorouracil, leucovorin, oxaliplatin, nab-paclitaxel, paclitaxel, cisplatin, capecitabine, S-1, erlotinib, olaparib, nivolumab, pembrolizumab, irinotecan, and SN-38, but is not limited thereto.

[0072] The above anticancer agent may be at least one selected from the group consisting of gemcitabine, 5-fluorouracil, leucovorin, oxaliplatin, nab-paclitaxel, paclitaxel, cisplatin, capecitabine, S-1, erlotinib, olaparib, nivolumab, pembrolizumab, irinotecan, and SN-38, but is not limited thereto.

[0073] Regarding the above composition, technical content related throughout the specification, such as cancer, substances for preventing or treating cancer, pharmaceutical compositions, and agents for inhibiting expression, may be interpreted by referring to the above.

[0074]

[0075] According to the present invention, by predicting the responsiveness to cancer prevention or treatment substances in advance using specific biomarkers, the optimal therapeutic agent can be selected for each patient, thereby preventing unnecessary drug administration and improving the treatment success rate. Furthermore, by providing a pharmaceutical composition that enhances sensitivity to cancer treatment substances, the therapeutic effect can be enhanced even against cancers exhibiting resistance. Moreover, since sensitivity-enhancing substances can be efficiently selected, the efficiency of new drug development and industrial applicability are improved.

[0076] However, it should be understood that the effects are not limited to those mentioned above and include all effects that can be inferred from the composition of the invention described in the detailed description or claims.

[0077]

[0078] Figures 1a to 1e: (a) Gene plot showing susceptibility to 5-FU, Nab-paclitaxel, and SN-38, respectively, according to the expression level of the ABCA10 gene, and (d,e) Graphs showing the Kaplan-Meier analysis results of overall survival (OS) and recurrence-free survival (RFS) according to the expression level of the ABCA10 gene.

[0079] Figures 2a to 2d: (a,b) Gene plots showing susceptibility to Nab-paclitaxel and SN-38, respectively, according to the expression level of the ABCA13 gene, and (c,d) Graphs showing the Kaplan-Meier analysis results of overall survival (OS) and recurrence-free survival (RFS) according to the expression level of the ABCA13 gene.

[0080] Figures 3a to 3d: (a,b) Gene plots showing susceptibility to 5-FU and SN-38, respectively, according to the expression level of the ARHGAP4 gene, and (c,d) Graphs showing the Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to the expression level of the ARHGAP4 gene.

[0081] Figures 4a to 4d: (a,b) Gene plots showing susceptibility to 5-FU and SN-38, respectively, according to the expression levels of the ATHL1(PGGHG) gene, and (c,d) Graphs showing the Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to the expression levels of the ATHL1(PGGHG) gene.

[0082] Figs. 5a to 5e: (a) Gene plot showing susceptibility to Gemcitabine, Oxaliplatin, and SN-38, respectively, according to the expression level of the ATP6V1C2 gene; (d,e) Graphs showing the Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to the expression level of the ATP6V1C2 gene.

[0083] Figures 6a to 6e: (a) Gene plot showing susceptibility to 5-FU, Nab-paclitaxel, and SN-38, respectively, according to the expression level of the COL28A1 gene; (d,e) Graphs showing the Kaplan-Meier analysis results of overall survival (OS) and recurrence-free survival (RFS) according to the expression level of the COL28A1 gene.

[0084] Figs. 7a to 7d: (a,b) Gene plots showing susceptibility to 5-FU and SN-38, respectively, according to COL9A3 gene expression levels, and (c,d) Graphs showing Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to COL9A3 gene expression levels.

[0085] Figures 8a to 8d: (a,b) Gene plots showing sensitivity to Gemcitabine and Oxaliplatin, respectively, according to CRYM gene expression levels, and (c,d) Graphs showing Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to CRYM gene expression levels.

[0086] Figs. 9a to 9d: (a,b) gene plots showing susceptibility to Oxaliplatin and SN-38, respectively, according to the expression level of the ECM1 gene, and (c,d) graphs showing the Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to the expression level of the ECM1 gene.

[0087] Figs. 10a to 10d: (a,b) gene plots showing susceptibility to 5-FU and SN-38, respectively, according to EDAR gene expression levels, and (c,d) graphs showing Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to EDAR gene expression levels.

[0088] Figs. 11a to 11d: (a,b) Gene plots showing susceptibility to Gemcitabine and SN-38, respectively, according to F3 gene expression levels, and (c,d) Graphs showing Kaplan-Meier analysis results of overall survival (OS) and recurrence-free survival (RFS) according to F3 gene expression levels.

[0089] Figs. 12a to 12f: (ad) Gene plot showing susceptibility to 5-FU, Gemcitabine, Oxaliplatin, and SN-38, respectively, according to FAM167A gene expression levels, (e,f) Graphs showing Kaplan-Meier analysis results of overall survival (OS) and progression-free survival (PFS) according to FAM167A gene expression levels.

[0090] Figs. 13a to 13d: (a,b) gene plots showing susceptibility to 5-FU and Oxaliplatin, respectively, according to FGF11 gene expression levels, and (c,d) graphs showing Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to FGF11 gene expression levels.

[0091] Figs. 14a to 14d: (a,b) Gene plots showing susceptibility to 5-FU and Gemcitabine, respectively, according to FKBP10 gene expression levels, and (c,d) Graphs showing Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to FKBP10 gene expression levels.

[0092] Figs. 15a to 15d: (a,b) gene plot showing susceptibility to 5-FU and Nab-paclitaxel, respectively, according to the expression level of the GOLGA7B gene, and (c,d) graphs showing the Kaplan-Meier analysis results of overall survival (OS) and recurrence-free survival (RFS) according to the expression level of the GOLGA7B gene.

[0093] Figs. 16a to 16d: (a,b) Gene plots showing susceptibility to 5-FU and SN-38, respectively, according to HLA-B gene expression levels, and (c,d) Graphs showing Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to HLA-B gene expression levels.

[0094] FIGS. 17a to 17d: (a,b) Gene plot showing susceptibility to 5-FU and SN-38, respectively, according to the expression level of the LOC102724532 gene, and (c,d) Graphs showing the Kaplan-Meier analysis results of overall survival (OS) and recurrence-free survival (RFS) according to the expression level of the LOC102724532 gene.

[0095] Figs. 18a to 18d: (a,b) gene plots showing susceptibility to Nab-paclitaxel and Oxaliplatin, respectively, according to the expression level of the MACROD2 gene, and (c,d) graphs showing the Kaplan-Meier analysis results of overall survival (OS) and progression-free survival (PFS) according to the expression level of the MACROD2 gene.

[0096] Figures 19a to 19e: (a) Gene plot showing susceptibility to 5-FU, Nab-paclitaxel, and SN-38, respectively, according to the expression level of the MAPK8IP2 gene; (d,e) Graphs showing the Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to the expression level of the MAPK8IP2 gene.

[0097] FIGS. 20a to 20e: (a) gene plot showing susceptibility to 5-FU, Gemcitabine, and Oxaliplatin, respectively, according to NKD1 gene expression levels, (d,e) graphs showing Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to NKD1 gene expression levels.

[0098] FIGS. 21a to 21d: (a,b) gene plots showing susceptibility to 5-FU and SN-38, respectively, according to the expression level of the PMAIP1 gene, and (c,d) graphs showing the Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to the expression level of the PMAIP1 gene.

[0099] FIGS. 22a to 22d: (a,b) Gene plots showing susceptibility to Oxaliplatin and SN-38, respectively, according to PMEPA1 gene expression levels, and (c,d) Graphs showing Kaplan-Meier analysis results of overall survival (OS) and recurrence-free survival (RFS) according to PMEPA1 gene expression levels.

[0100] FIGS. 23a to 23e: (a) Gene plot showing susceptibility to 5-FU, Gemcitabine, and SN-38, respectively, according to PON3 gene expression levels, (d,e) Graphs showing Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to PON3 gene expression levels.

[0101] FIGS. 24a to 24e: (a) gene plot showing susceptibility to 5-FU, Gemcitabine, and Oxaliplatin, respectively, according to the expression level of the RBP1 gene, and (d,e) graphs showing the Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to the expression level of the RBP1 gene.

[0102] FIGS. 25a to 25d: (a,b) gene plots showing susceptibility to Gemcitabine and SN-38, respectively, according to the expression level of the RBP4 gene, and (c,d) graphs showing the Kaplan-Meier analysis results of overall survival (OS) and recurrence-free survival (RFS) according to the expression level of the RBP4 gene.

[0103] Figs. 26a to 26d: (a,b) Gene plots showing susceptibility to Gemcitabine and SN-38, respectively, according to SOX21 gene expression levels, and (c,d) Graphs showing Kaplan-Meier analysis results of overall survival (OS) and recurrence-free survival (RFS) according to SOX21 gene expression levels.

[0104] FIGS. 27a to 27d: (a,b) Gene plots showing susceptibility to 5-FU and Gemcitabine, respectively, according to SPATA17 gene expression levels, and (c,d) Graphs showing Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to SPATA17 gene expression levels.

[0105] FIGS. 28a to 28d: (a,b) gene plots showing susceptibility to 5-FU and Gemcitabine, respectively, according to TGFB2 gene expression levels, and (c,d) graphs showing Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to TGFB2 gene expression levels.

[0106] FIGS. 29a to 29e: (a) Gene plot showing susceptibility to 5-FU, Gemcitabine, and Oxaliplatin, respectively, according to THBS1 gene expression levels, (d,e) Graphs showing Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to THBS1 gene expression levels.

[0107] Figs. 30a to 30d: (a,b) Gene plots showing susceptibility to 5-FU and SN-38, respectively, according to the expression level of the ZNF532 gene, and (c,d) Graphs showing the Kaplan-Meier analysis results of overall survival (OS) and relapse-free survival (RFS) according to the expression level of the ZNF532 gene.

[0108] Fig. 31: FKBP10 mRNA expression levels were measured by qRT-PCR 48 hours after transfection with siControl or siFKBP10 (20 nM). Data were normalized to β-actin, and relative expression levels were expressed with siControl set to 1. A decrease in expression of approximately 70% was observed in AsPC-1 and approximately 80% in MIA PaCa-2. (Data are expressed as mean ± SD. ***p < 0.001 vs siControl (Student's t-test))

[0109] Fig. 32: MACROD2 mRNA expression levels were measured by qRT-PCR 48 hours after transfection with siControl or siMACROD2 (20 nM). Data were normalized to β-actin, with siControl set to 1 to represent relative expression levels. A decrease in expression of more than 90% was confirmed. (Data are expressed as mean ± SD. ***p < 0.001 vs siControl (Student's t-test))

[0110] Fig. 33: AsPC-1 cells treated with siControl (blue; circle) or siFKBP10 (pink; triangle) were cultured in a 3D U-bottom plate (top) and a 2D plate (bottom). Cell viability was measured by the CellTiter-Glo assay 72 hours after treatment with each anticancer agent at different concentrations. The X-axis represents drug concentration (nM, log scale), and the Y-axis represents cell viability (%) relative to the vehicle. For 5-FU and GEM, the curves for the siFKBP10 treatment group shifted significantly to the left, indicating increased sensitivity. Sensitization effects were also observed with OXA and SN-38. (Data are mean ± SEM (n=3))

[0111] Fig. 34: AsPC-1 cells treated with siControl (top) or siFKBP10 (bottom) were cultured in a 3D U-bottom plate and observed under an optical microscope 72 hours after treatment with each drug at the indicated concentrations (μM). (Scale bar = 100 μm)

[0112] Fig. 35: MIA PaCa-2 cells treated with siControl (blue; circle) or siFKBP10 (pink; triangle) were cultured in a 3D U-bottom plate (top) and a 2D plate (bottom). Cell viability was measured by the CellTiter-Glo assay 72 hours after treatment with each anticancer agent at different concentrations. The X-axis represents drug concentration (nM, log scale), and the Y-axis represents cell viability (%) relative to the vehicle. Under 3D culture conditions (top), a leftward shift in the curves of the siFKBP10-treated group was observed for OXA, 5-FU, and GEM, whereas under 2D conditions (bottom), there was no significant difference between the two groups. (Data are mean ± SEM (n=3)).

[0113] Fig. 36: BxPC-3 cells treated with siControl (blue; circle) or siMACROD2 (pink; triangle) were cultured in a 3D U-bottom plate (top) and a 2D plate (bottom). Cell viability was measured by the CellTiter-Glo assay 72 hours after treatment with each anticancer agent at different concentrations. The X-axis represents drug concentration (nM, log scale), and the Y-axis represents cell viability (%) relative to the vehicle. Under the 2D condition (bottom), the curves of the siMACROD2-treated group shifted significantly to the left for OXA, 5-FU, and SN-38. Under the 3D condition (top), a distinct sensitization effect was observed in GEM. (Data are mean ± SEM (n=3)).

[0114] Fig. 37: BxPC-3 cells treated with siControl (top) or siMACROD2 (bottom) were cultured in a 3D U-bottom plate and observed under an optical microscope 72 hours after treatment with each drug at the indicated concentrations (μM). (Scale bar = 100 μm)

[0115]

[0116] Hereinafter, to explain more specifically, examples and experimental examples will be described in detail. However, the following examples and experimental examples are illustrative and the scope of the invention is not limited thereto.

[0117]

[0118] Example 1. Discovery of drug resistance gene biomarkers through organoid screening

[0119]

[0120] 1. Experimental Method

[0121]

[0122] (1) Establishment and culture of patient-derived pancreatic cancer organoids

[0123]

[0124] 1) Ethical Approval and Organizational Collection

[0125] Clinical data and tissue collection from pancreatic cancer patients were performed in accordance with relevant guidelines under the approval of the Institutional Review Board of Seoul National University Hospital.

[0126]

[0127] 2) Establishment of organoids

[0128] Patient-derived pancreatic cancer organoids (PDPCOs) were established from tumor tissue obtained via endoscopic ultrasound-guided fine needle biopsy (EUS-FNB). A total of 42 PDPCO lines were used in the experiments of the present invention, and all established organoids were included in the analysis, with no samples excluded.

[0129]

[0130] 3) Organoid culture

[0131] The established organoids were cultured in a medium dedicated to pancreatic cancer organoids based on Wnt3a / R-spondin1 / Noggin conditioned medium (50% vol / vol). The medium was prepared by adding 1× B27 supplement (Life Technologies, Carlsbad, CA, USA), 0.5 mM N-acetyl-L-cysteine ​​(Sigma-Aldrich), 10 mM nicotinamide (Sigma-Aldrich), 50 ng / mL human epidermal growth factor (EGF; PeproTech Inc., Cranbury, NJ, USA), 500 nM A83-01, 100 ng / mL human fibroblast growth factor 10 (FGF10; PeproTech), and 10 nM gastrin (R&D Systems, Inc., Minneapolis, MN, USA) to Advanced DMEM / F12 (Life Technologies) as the base medium.

[0132]

[0133] 4) Organoid subculture

[0134] For subculture, organoids were collected and washed, and then fragmented by mechanical shearing or enzymatic degradation using TrypLE Express (Life Technologies). The fragmented organoids were re-embedded in fresh Matrigel (Corning, NY, USA) to maintain culture.

[0135]

[0136] (2) Organoid-based rapid drug responsiveness screening

[0137]

[0138] 1) Screening Platform Configuration

[0139] A high-speed screening system using a 384-well plate was constructed. After coating each well with 10 μL of Matrigel, 20 μL of a suspension containing approximately 1,000 organoid cells was dispensed for seeding. After organoid attachment and stabilization, 5 μL of a drug solution prepared at a 5× concentration was added to achieve a final concentration of 1×.

[0140]

[0141] 2) Drug treatment conditions

[0142] In this study, drug sensitivity was evaluated for five anticancer drugs clinically used in the treatment of pancreatic cancer. The maximum treatment concentration, serial dilution conditions, and analysis time points for each drug are shown in Table 1 below.

[0143] Drug Name Max Concentration Dilution Ratio Analysis Time Oxaliplatin 500 μM 1 / 4 serial dilution Day 5 Gemcitabine 200 μM 1 / 5 serial dilution Day 5 5-Fluorouracil (5-FU) 500 μM 1 / 4 serial dilution Day 5 SN-38 20 μM 1 / 5 serial dilution Day 3 Nab-paclitaxel 100 μM 1 / 10 serial dilution Day 3

[0144]

[0145] 3) Measurement of cell viability

[0146] CellTiter-Glo at the specified time point (3 or 5 days) after drug treatment ® Cell viability was measured using the 3D Cell Viability Assay (Promega). CellTiter-Glo ® After adding and mixing the 3D reagent with the culture medium at a 1:1 (vol / vol) ratio, the luminescence signal was measured to quantify the cell viability based on ATP content.

[0147]

[0148] 4) Drug responsiveness analysis

[0149] The dose-response curves for each organoid line were analyzed using GraphPad Prism software. Area Under the Curve (AUC) values ​​were calculated from the dose-response curves, and based on these values, the sensitive and resistant groups for each drug were defined.

[0150]

[0151] (3) Transcriptome sequencing and analysis

[0152]

[0153] 1) RNA Sequencing Data Processing

[0154] RNA sequencing (RNA-seq) data were processed using the nf-core / rnaseq pipeline (v3.14.0) in accordance with RNA-seq best practices guidelines (Docker environment). Raw sequencing reads were trimmed using fastp to remove adapter sequences and low-quality nucleotides. The preprocessed reads were aligned to the human reference genome GRCh38 using STAR aligner.

[0155]

[0156] 2) Quantification of gene expression

[0157] Gene expression quantification was performed using Salmon in alignment-based mode to generate a gene expression count matrix.

[0158]

[0159] 3) Batch effect correction and normalization

[0160] To minimize technical variations that may occur in multiple sequencing batches, batch correction was performed on the gene expression matrix using pyComBat. Subsequently, library size normalization was performed by applying the built-in size factor method of the DESeq2 package.

[0161]

[0162] (4) Discovery of biomarkers associated with drug responsiveness

[0163]

[0164] 1) Classification of susceptible and resistant groups

[0165] Each organoid was classified into a sensitive group and a resistant group based on the AUC values ​​derived from the drug response analysis.

[0166]

[0167] 2) Analysis of differentially expressed genes

[0168] Differentially Expressed Genes (DEGs) analysis between the susceptible and resistant groups was performed using the DESeq2 package. Genes satisfying p-value < 0.05 and |log₂(fold change)| ≥ 1.0 were determined to be statistically significant differentially expressed genes.

[0169]

[0170] 3) Functional Association Analysis

[0171] To explore the biological associations of differentially expressed genes, functional enrichment analysis was performed using the GSEApy Python package.

[0172]

[0173] 4) Verification of association with clinical prognosis

[0174] Among the DEGs derived from organoid-based drug sensitivity analysis, genes showing a significant prognostic association in survival analysis using public databases were selected as final biomarker candidates. Specifically, using the TCGA Pancreatic Adenocarcinoma cohort (cBioPortal) and the Kaplan-Meier Plotter RNA-seq dataset, Kaplan-Meier survival analysis and log-rank tests were performed on overall survival (OS) and progression-free survival (PFS) or recurrence-free survival (RFS) to evaluate statistical significance.

[0175]

[0176] 2. Experimental Results

[0177]

[0178] The experimental results according to the above experimental method are shown in Tables 2 to 4 below. The explanation regarding each field and its notation is as follows.

[0179] - 유전자 목록: ABCA10(ATP Binding Cassette Subfamily A Member 10), ABCA13(ATP Binding Cassette Subfamily A Member 13), ARHGAP4(Rho GTPase Activating Protein 4), ATHL1(Athymic Nude Homolog 1; PGGHG(Putative Gamma-Glutamyl Hydrolase-Related Protein)), ATP6V1C2(ATPase H+ Transporting V1 Subunit C2), COL28A1(Collagen Type XXVIII Alpha 1 Chain), COL9A3(Collagen Type IX Alpha 3 Chain), CRYM(Crystallin Mu), ECM1(Extracellular Matrix Protein 1), EDAR(Ectodysplasin A Receptor), F3(Coagulation Factor III, Tissue Factor), FAM167A(Family With Sequence Similarity 167 Member A), FGF11(Fibroblast Growth Factor 11), FKBP10(FKBP Prolyl Isomerase 10), GOLGA7B(Golgin A7 Family Member B), HLA-B(Major Histocompatibility Complex, Class I, B), LOC102724532, MACROD2(Mono-ADP-Ribosylhydrolase 2), MAPK8IP2(Mitogen-Activated Protein Kinase 8 Interacting Protein 2), NKD1(Naked Cuticle Homolog 1), PMAIP1(PMA Induced Protein 1, NOXA), PMEPA1(Prostate Transmembrane Protein, Androgen Induced 1), PON3(Paraoxonase 3),Retinol Binding Protein 1 (RBP1), Retinol Binding Protein 4 (RBP4), SRY-Box Transcription Factor 21 (SOX21), Spermatogenesis Associated 17 (SPATA17), Transforming Growth Factor Beta 2 (TGFB2), Thrombospondin 1 (THBS1), and Zinc Finger Protein 532 (ZNF532);

[0180] - Drug list: 5-FU (5-Fluorouracil), Nab-paclitaxel, SN-38 (7-Ethyl-10-hydroxycamptothecin), Gemcitabine, Oxaliplatin

[0181] - Reactivity: R (Resistant) if indicating resistance to the drug, S (Sensitive) if indicating sensitivity to the drug

[0182] - Rate of change, log2(rate of change): The multiple change in the expression of the corresponding gene in the experimental group compared to the control group, and the log2 value thereof

[0183] - p-value: indicator of statistical significance

[0184] - Source: Public databases from which survival analysis data was derived, using KM plotter (RNA-seq based) or C bio portal (http: / cbioportal.org).

[0185] - Overall survival: If the expression level of the corresponding gene acts to extend overall survival, it is P (Prolonged); if it acts to shorten it, it is S (Shortened).

[0186] - Hazard Ratio (HR): The rate of increase or decrease in the risk of death due to the expression of the corresponding gene (HR < 1 indicates a favorable prognosis, HR > 1 indicates a poor prognosis)

[0187] - PFS or RFS: As prognostic factors related to cancer progression or recurrence, PFS (Progression-Free Survival) is used as the standard when based on C-bio portal data, and RFS (Recurrence-Free Survival) is used when based on KM plotter data; if it acts to extend survival, it is P (Prolonged), and if it acts to shorten it, it is S (Shortened).

[0188] - Hazard ratio of PFS or RFS: The rate of increase or decrease in the risk of cancer progression or recurrence due to the expression of the corresponding gene (HR < 1 indicates a favorable prognosis, HR > 1 indicates a poor prognosis)

[0189] 유전자약물반응성log2(변화율)변화율p값ABCA105-FUS-1.880.2716837160.00145Nab-paclitaxelS-1.40.3789291420.0093SN-38S-1.290.4089510290.0296ABCA13Nab-paclitaxelR1.252.378414230.0044SN-38R1.282.4283897690.00714ARHGAP45-FUS-1.460.3634931290.0316SN-38S-1.70.3077861030.00967ATHL1(PGGHG)5-FUR1.462.7510836360.000553SN-38R1.082.1140360810.0124ATP6V1C2GemcitabineS-1.10.4665164960.00638OxaliplatinS-1.270.4146597730.0048SN-38S-1.720.3035487210.0000569COL28A15-FUS-1.470.3609822990.0158Nab-paclitaxelS-1.680.3120826370.00118SN-38S-2.260.208771980.0000681COL9A35-FUS-1.360.389582290.0383SN-38S-1.340.3950206560.0362CRYMGemcitabineS-1.370.3868912480.00566OxaliplatinS-1.220.4292827180.0254ECM1OxaliplatinR1.392.6207868080.0369SN-38R1.63.0314331330.0129EDAR5-FUR1.482.7894873330.0135SN-38R1.282.4283897690.0305F3GemcitabineR1.192.2815274320.0216SN-38R1.382.6026837110.0106FAM167A5-FUS-1.30.4061261980.0243GemcitabineS-1.120.4600938250.0318OxaliplatinS-1.410.3763116870.0122SN-38S-1.310.403320880.0197FGF115-FUR1.132.1885874030.0159OxaliplatinR1.673.1821459350.000192FKBP105-FUR1.593.0104934950.0222GemcitabineR1.542.9079450350.0156GOLGA7B5-FUS-1.040.4863274740.0251Nab-paclitaxelS-1.010.4965462480.0149HLA-B5-FUR1.152.2191389440.00156SN-38R1.042.0562276530.00379LOC1027245325-FUS-1.010.4965462480.000055SN-38S-10.50.0000277MACROD2Nab-paclitaxelR1.152.2191389440.00304OxaliplatinR1.142.2038102320.00948MAPK8IP25-FUS-1.060.479632060.018Nab-paclitaxelS-10.50.0116SN-38S-1.060.479632060.0148NKD15-FUR2.887.3615012050.0000974GemcitabineR2.927.5684611740.0000183OxaliplatinR2.425.3517102190.00196PMAIP15-FUR1.482.7894873330.000000147SN-38R1.082.1140360810.0005PMEPA1OxaliplatinR1.372.5847056610.0105SN-38R1.062.0849315220.044PON35-FUS-1.510.3511112190.00949GemcitabineS-1.120.4600938250.0358SN-38S-1.680.3120826370.00253RBP15-FUR1.462.7510836360.0329GemcitabineR1.292.4452805550.0395OxaliplatinR1.372.5847056610.0466RBP4GemcitabineS-1.030.4897101490.0383SN-38S-1.030.4897101490.0211SOX21GemcitabineR1.753.3635856610.00114SN-38R1.522.8679104960.00983SPATA175-FUS-1.370.3868912480.00988GemcitabineS-1.280.4117955090.00707TGFB25-FUR1.312.47941540.0198GemcitabineR1.322.4966610980.01THBS15-FUR1.182.2657677710.0259GemcitabineR1.162.2345742760.0132OxaliplatinR1.112.1584564730.0338ZNF5325-FUR1.773.4105395670.000000148SN-38R1.422.675855110.0000788.

[0190] 유전자출처전체 생존율전체 생존율의 위험비(HR)p값(Log rank test)ABCA10K-M plotterRNA seq.P0.550.0045ABCA13K-M plotterRNA seq.S2.070.006ARHGAP4K-M plotterRNA seq.P0.580.0078ATHL1(PGGHG)K-M plotterRNA seq.S1.580.03ATP6V1C2K-M plotterRNA seq.P0.650.068COL28A1K-M plotterRNA seq.P0.450.0039COL9A3K-M plotterRNA seq.P0.750.19CRYMK-M plotterRNA seq.P0.670.06ECM1K-M plotterRNA seq.S2.590.00073EDARK-M plotterRNA seq.S1.30.25F3K-M plotterRNA seq.S2.330.00008FAM167AC Bio PortalPancreatic Adenocarcinoma (TCGA, PanCancer Atlas)(184 total samples, 168 complete samples) mRNA expression z-score relative to diploid sample threshold + / - 2.0P0.5180.107FGF11K-M plotterRNA seq.S1.450.094FKBP10K-M plotterRNA seq.S1.410.17GOLGA7BK-M plotterRNA seq.P0.730.19HLA-BK-M plotterRNA seq.S1.580.079LOC102724532K-M plotterRNA seq.P0.630.036MACROD2C Bio PortalPancreatic Adenocarcinoma (TCGA, PanCancer Atlas)(184 total samples, 168 complete samples) mRNA expression z-score relative to diploid sample threshold + / - 2.0S3.0690.0002199MAPK8IP2K-M plotterRNA seq.P0.490.0079NKD1K-M plotterRNA seq.S1.640.058PMAIP1K-M plotterRNA seq.S1.960.011PMEPA1K-M plotterRNA seq.S1.810.024PON3K-M plotterRNA seq.S1.430.12RBP1K-M plotterRNA seq.S1.620.027RBP4K-M plotterRNA seq.P0.80.33SOX21K-M plotterRNA seq.S1.60.033SPATA17K-M plotterRNA seq.P0.450.0011TGFB2K-M plotterRNA seq.S1.740.013THBS1K-M plotterRNA seq.S1.510.064ZNF532K-M plotterRNA seq.S1.910.0021.

[0191] The hazard ratio (HR) p-value (Log rank) of genetic PFS, RFSPFS, or RFS test)ABCA10P0.390.031ABCA13S553879424.70.000077ARHGAP4P0.330.0054ATH L1(PGGHG)S1.60.26ATP6V1C2P0.110.00091COL28A1P0.290.032COL9A3P0.420.0 32CRYMP0.120.0000099ECM1S12.610.0019EDARS8.680.00073F3S471627299.70. 000047FAM167AP0.2920.008669FGF11S6.850.00062FKBP10S5.070.015GOLGA7BP0 .430.048HLA-BS5.030.019LOC102724532P0.210.0071MACROD2S2.3770.00695MA PK8IP2P0.230.0043NKD1S13.250.0017PMAIP1S2.650.019PMEPA1S4.470.00017PO N3P0.240.015RBP1S5.970.0074RBP4P0.420.042SOX21S5.410.000011SPATA17P0 .350.024TGFB2S11.640.000074THBS1S15.180.0005ZNF532S406874631.60.00042

[0192]

[0193] Example 2. Confirmation of the functionality of drug resistance gene biomarkers in human-derived cell lines

[0194]

[0195] 1. Experimental Method

[0196]

[0197] (1) Cell line and culture

[0198]

[0199] For experiments related to the FKBP10 gene, AsPC-1 and MIA PaCa-2 cell lines with high gene expression were used, and for experiments related to the MACROD2 gene, BxPC-3 cell lines were used. All cells were cultured in DMEM + 10% FBS + 1% penicillin / streptomycin medium at 37°C and 5% CO₂.

[0200]

[0201] (2) siRNA transduction

[0202]

[0203] siRNA for each target gene (siFKBP10 or siMACROD2) was transfected using Lipofectamine RNAiMAX (Thermo Fisher) at a final concentration of 20 nM. Non-targeting siRNA (siControl) was treated at the same concentration as a negative control. 48 hours after transfection, knockdown efficiency was confirmed by qRT-PCR and normalized to β-actin.

[0204]

[0205] (3) Drug responsiveness test

[0206]

[0207] 1) Cell seeding

[0208] After siRNA transduction, cells were seeded into 384-well plates. For 3D culture, 500 cells / well and 45 μL / well were seeded into 384-well U-bottom ultra-low attachment plates (Corning #4516), and for 2D culture, 1,000 cells / well and 45 μL / well were seeded into 384-well tissue culture plates (Corning #3764).

[0209]

[0210] 2) Drug treatment

[0211] 24 hours after cell seeding (Day 1), the following five anticancer agents were administered: Oxaliplatin (OXA): peak concentration 300 μM, 5-Fluorouracil (5-FU): peak concentration 300 μM, SN-38: peak concentration 20 μM, Gemcitabine (GEM): peak concentration 100 μM, Nab-paclitaxel (NAB-P): peak concentration 100 μM.

[0212] Each drug was serially diluted by 1 / 3 from the peak concentration to create 8 concentration points, and experiments were conducted under a total of 9 conditions, including a vehicle control (DMSO). The drugs were prepared at 10x concentration and added at 5 μL / well (45 μL cells + 5 μL drug = final 50 μL). All conditions were performed in triplicate.

[0213]

[0214] 3) Measurement of cell viability

[0215] Cell viability was measured 72 hours after drug treatment using the CellTiter-Glo assay (Promega). The CellTiter-Glo 3D Cell Viability Assay (Promega #G9681) was used for 3D cultures, and the CellTiter-Glo Luminescent Cell Viability Assay (Promega #G7570) was used for 2D cultures. CellTiter-Glo reagents quantify the number of viable cells based on the principle of lysing cells and generating a luminescence signal proportional to ATP content. The reagents were added in an equal volume (50 μL / well) to the culture medium. For 2D cultures, fluorescence was measured after mixing in a plate shaker for 2 minutes and incubating at room temperature for 10 minutes following the addition of the reagents. For 3D cultures, the plates were mixed in a shaker for 5 minutes to lyse the spheroids and incubated at room temperature for 25 minutes. Fluorescence was measured using a GloMax Explorer Microplate Reader (Promega).

[0216]

[0217] 4) Data Analysis

[0218] The relative survival rate (%) compared to vehicle control was calculated. IC 50 and the 95% confidence interval (CI) were calculated using GraphPad Prism 10 (GraphPad Software, USA). For the non-linear regression analysis, the log(inhibitor) vs. normalized response -- Variable slope (four parameters) model was applied.

[0219]

[0220] 2. Experimental Results

[0221]

[0222] 1) Verification of siRNA knockdown efficiency

[0223] The efficiency of target gene expression inhibition after siRNA transduction was confirmed by qRT-PCR. For FKBP10, expression decreased by approximately 70% in AsPC-1 cells compared to siControl, and by approximately 80% in MIA PaCa-2 cells (both p < 0.001). For MACROD2, a decrease in expression of more than 99% was confirmed in BxPC-3 cells (p < 0.001). Such high knockdown efficiency is sufficient for subsequent drug responsiveness experiments.

[0224]

[0225] 2) Drug sensitivity and spheroid morphology changes caused by FKBP10 knockdown

[0226] After knocking down FKBP10 in AsPC-1 cells, dose-response curves for five anticancer drugs were analyzed under 3D and 2D culture conditions. Previous organoid screening data have confirmed that high expression of FKBP10 is associated with resistance to 5-FU and gemcitabine. In this experiment, we functionally verified this and additionally analyzed the effects of other drugs. The results are shown in Table 5, Figure 33, and Figure 34 below.

[0227] In the case of 5-FU, IC in 3D 50 It was confirmed that FKBP10 contributes to 5-FU resistance, as the IC50 decreased approximately 3.2-fold from 980.7 to 310.3 μM in the siControl and approximately 13.5-fold from 7,400 to 546.4 μM in the 2D. In the case of gemcitabine, the IC50 was [missing] even at the highest concentration (100 μM) in the siControl. 50 Although it did not reach [the target] and showed very high resistance, in siFKBP10 it became measurable at 1.5 μM in 3D and 15.5 μM in 2D. This strongly suggests that FKBP10 is a key regulator of gemcitabine resistance.

[0228] While no direct association between FKBP10, OXA, and SN-38 was confirmed in previous organoid screenings, this experiment observed sensitization effects of 3D 1.7-fold (44.1 → 25.8 μM) and 2D 1.8-fold (90.0 → 50.0 μM) for OXA. Sensitization effects of 3D 1.7-fold (2.5 → 1.5 μM) and 2D 3.4-fold (3.4 → 1.0 μM) were also confirmed for SN-38. These results suggest that FKBP10 may be involved in a broader range of drug resistance mechanisms than expected and imply that inhibition of FKBP10 can enhance the efficacy of combination therapies such as FOLFIRINOX.

[0229] Regarding Nab-paclitaxel, IC in 3D 50 It actually increased from 62.6 to 183.6 nM, while in 2D it decreased from 180.7 to 100.9 nM. These conflicting results between culture conditions indicate that the relationship between FKBP10 and taxane-class drugs is not simple, and further verification is required.

[0230] In morphological analysis, invasive morphology, in which cells protrude outward from the edges of spheroids, was distinctly observed in siControl-treated AsPC-1 spheroids even under vehicle conditions. This protruding structure reflects the invasive phenotype of cancer cells. Upon drug treatment, this invasive morphology was maintained or only partially reduced in the siControl group. In contrast, in the siFKBP10-treated group, the spheroids changed into a more rounded and compact form starting from vehicle conditions, and outward cell protrusion was significantly reduced. Upon drug treatment, the reduction in spheroid size and morphological collapse were more pronounced compared to the siControl group. These results suggest that FKBP10 may be involved not only in drug resistance but also in cell invasiveness and migration, indicating that FKBP10 may be associated with the metastatic potential of pancreatic cancer.

[0231] ModelAsPC-1OXA (μM)5FU (μM)SN38 (μM)GEM (μM)NAB-P (nM)IC5095% CIIC5095% CIIC5095% CIIC5095% CIIC5095% CI3DsiControl44.132.8 - 60.2980.7359..1 - 6334.22.52.0 - 3.1>100ND62.621.1 - 155.3siFKBP1025.817.2 - 39.0310.3152.9 - 902.81.51.2 - 2.01.50.7 - 3.4183.665.9 - 452.32DsiControl90.071.6 - 115.074002030.1 - 61141.33.42.8 - 4.3>100ND180.744.1 - 587.9siFKBP1050.036.3 - 70.4546.4311.8 - 1110.91.00.8 - 1.315.57.6 - 38.2100.926.7 - 298.3

[0232] To determine whether the role of FKBP10 varies depending on the cell line, the same experiment was performed on another pancreatic cancer cell line, MIA PaCa-2. The results are shown in Table 6 and Figure 35 below.

[0233] In 3D culture, OXA decreased from 5.6 to 2.9 μM (approx. 1.9-fold), 5-FU from 187 to 87.7 μM (approx. 2.1-fold), and GEM from 1.0 to 0.6 μM (approx. 1.7-fold), confirming the sensitization effect caused by FKBP10 inhibition. Although the fold change was lower compared to AsPC-1, a consistent trend was observed across all three drugs.

[0234] Interestingly, no significant difference was observed between siControl and siFKBP10 in 2D culture. Rather, IC50s for some drugs (5-FU, GEM) 50 It increased slightly in siFKBP10. These results suggest that the drug resistance modulating function of FKBP10 plays a more significant role in a 3D environment. 3D spheroid culture better reflects the in vivo tumor microenvironment—including cell-cell contact, cell-extracellular matrix interactions, internal hypoxic environments and nutrient gradients, and drug penetration barriers—compared to 2D monolayer culture. In fact, drugs effective in 2D often fail in clinical practice because 2D models fail to reflect these tumor microenvironmental factors. The fact that the FKBP10 knockdown effect was observed only in 3D in this experiment suggests the possibility that FKBP10 contributes to drug resistance through functions related to extracellular matrix remodeling or cell-cell interactions.

[0235] ModelMIA PaCa-2OXA (μM)5FU (μM)SN38 (nM)GEM (μM)NAB-P (nM)IC5095% CIIC5095% CIIC5095% CIIC5095% CIIC5095% CI3DsiControl5.63.0 - 10.4187134.5 - 294.152.241.0 - 66.21.00.7 - 1.725.89.5 - 59.7siFKBP102.91.7 - 4.887.769.0 - 113.742.735.5 - 51.20.60.5 - 0.816.67.6 - 33.52DsiControl20.516.9 - 24.9144.3128.8 - 162.780.463.9 - 100.75.73.9 - 8.438.548.5 - 120.5siFKBP1022.418.9 - 26.6157.7143.0 - 175.065.454.5 - 78.56.44.6 - 9.233.415.4 - 120. 0

[0236]

[0237] 3) Drug sensitivity and spheroid morphology changes due to MACROD2 knockdown

[0238] Previous organoid screening data has confirmed that high MACROD2 expression is associated with resistance to oxaliplatin and nab-paclitaxel. To functionally verify this, drug responsiveness after knockdown was analyzed in BxPC-3 cells with high MACROD2 expression. The results are shown in Table 7, Figure 36, and Figure 37 below.

[0239] Organoid screening confirmed that high expression of MACROD2 is associated with oxaliplatin resistance, and in this experiment as well, OXA IC in 2D culture 50 This was functionally verified as it decreased from 26.4 to 15.5 μM (about 1.7 times). However, in 3D culture, the effect was negligible from 88.4 to 79.9 μM, indicating that there was a difference depending on the culture conditions.

[0240] In previous screenings, no direct association was confirmed between MACROD2, 5-FU, and SN-38; however, in this experiment, a potent sensitization effect of approximately 5-fold (13.5 → 2.7 μM) was observed for 5-FU in 2D. A sensitization effect of approximately 2.6-fold (69.9 → 27.2 nM) was also confirmed for SN-38 in 2D. This suggests the possibility that MACROD2 may also affect pyrimidine metabolism or topoisomerase-related pathways.

[0241] For GEM, a sensitization effect of approximately 4.4-fold (93,365 → 21,196 nM) was observed in 3D culture, whereas the effect was negligible in 2D (43.5 → 29.4 nM). Interestingly, the 3D IC under siControl conditions. 50 Since the 2D level (93.4 μM) is about 2,000 times higher than the 2D level (43.5 nM), it can be seen that BxPC-3 exhibits very high resistance to gemcitabine in a 3D environment. This suggests that MACROD2 inhibition is effective in overcoming this 3D-specific high resistance.

[0242] Although high MACROD2 expression was confirmed to be associated with nab-paclitaxel resistance in organoid screening, in this experiment, IC in 2D 50 There was almost no change from 13.5 to 13.7 μM. In 3D, it decreased from 39.9 to 13.6 μM, but caution is required in statistical interpretation due to the wide 95% CI. This discrepancy may be attributed to cell line-specific differences or differences between organoids and cell line models, and further verification is required.

[0243] In terms of morphological analysis, unlike AsPC-1, BxPC-3 is characterized by forming naturally relatively round and compact spheroids during 3D culture, making it relatively difficult to observe morphological changes. Nevertheless, in the siMACROD2-treated group, a tendency for the overall size of spheroids to decrease compared to the siControl group was observed even under Vehicle conditions. Upon drug treatment, the reduction in spheroid size and cell density was more pronounced in the siMACROD2 group, and partial collapse of the spheroid structure was observed under some conditions. This suggests that MACROD2 inhibition may affect cell proliferation or survival itself, in addition to drug sensitization effects.

[0244] ModelBxPC-3OXA (uM)5FU (uM)SN38 (nM)GEM (nM)NAB-P (uM)IC5095% CIIC5095% CIIC5095% CIIC5095% CIIC5095% CI3DsiControl88.465.8 - 113.7>300ND6063ND*9336553620 - 21594839915NDsiMACROD279.969.4 - 91.3>300ND3633ND*2119613504 - 36418135530.7 - 29.82DsiControl26.417.1 - 40.813.55.9 - 34.969.951.3 - 94.743.514.9 - 105.113.5NDsiMACROD215.510.2 - 23.52.71.1 - 6.727.218.0 - 40.529.410.5 - 68.913.7ND

[0245]

[0246] The scope of the present invention is defined by the claims set forth below, and all modifications or variations derived from the meaning and scope of the claims and equivalent concepts thereof should be interpreted as being included within the scope of the present invention.

Claims

1. A step comprising measuring the expression level of the FKBP10 (FKBP Prolyl Isomerase 10) gene from a biological sample obtained from an individual, A method for providing information to predict responsiveness to a substance for the prevention or treatment of cancer.

2. The method of claim 1, further comprising the step of determining that resistance to a cancer prevention or treatment substance is present if the expression level of the FKBP10 gene is higher than the expression level in a biological sample obtained from a normal control individual. A method for providing information to predict responsiveness to a substance for the prevention or treatment of cancer. 3.청구항 1에 있어서, 상기 생물학적 시료로부터 MACROD2(Mono-ADP-Ribosylhydrolase 2), ABCA10(ATP Binding Cassette Subfamily A Member 10), ABCA13(ATP Binding Cassette Subfamily A Member 13), ARHGAP4(Rho GTPase Activating Protein 4), ATHL1(Athymic Nude Homolog 1), ATP6V1C2(ATPase H+ Transporting V1 Subunit C2), COL28A1(Collagen Type XXVIII Alpha 1 Chain), COL9A3(Collagen Type IX Alpha 3 Chain), CRYM(Crystallin Mu), ECM1(Extracellular Matrix Protein 1), EDAR(Ectodysplasin A Receptor), F3(Coagulation Factor III), FAM167A(Family With Sequence Similarity 167 Member A), FGF11(Fibroblast Growth Factor 11), GOLGA7B(Golgin A7 Family Member B), HLA-B(Major Histocompatibility Complex, Class I, B), LOC102724532, MAPK8IP2(Mitogen-Activated Protein Kinase 8 Interacting Protein 2), NKD1(Naked Cuticle Homolog 1), PMAIP1(PMA Induced Protein 1), PMEPA1(Prostate Transmembrane Protein, Androgen Induced 1), PON3(Paraoxonase 3), RBP1(Retinol Binding Protein 1), RBP4(Retinol Binding Protein 4),A method further comprising the step of measuring the expression level of at least one gene selected from the group consisting of SOX21 (SRY-Box Transcription Factor 21), SPATA17 (Spermatogenesis Associated 17), TGFB2 (Transforming Growth Factor Beta 2), THBS1 (Thrombospondin 1), and ZNF532 (Zinc Finger Protein 532), A method for providing information to predict responsiveness to a substance for the prevention or treatment of cancer.

4. The method of claim 3 further comprises the step of determining that resistance to a cancer prevention or treatment substance is present if the expression level of at least one gene selected from the group consisting of FKBP10, MACROD2, ABCA13, ATHL1, ECM1, EDAR, F3, FGF11, HLA-B, NKD1, PMAIP1, PMEPA1, RBP1, SOX21, TGFB2, THBS1, and ZNF532 is higher than the expression level in a biological sample obtained from a normal control individual. A method for providing information to predict responsiveness to a substance for the prevention or treatment of cancer.

5. The method of claim 3 further comprises the step of determining that sensitivity to a cancer prevention or treatment substance is high if the expression level of at least one gene selected from the group consisting of ABCA10, ARHGAP4, ATP6V1C2, COL28A1, COL9A3, CRYM, FAM167A, GOLGA7B, LOC102724532, MAPK8IP2, PON3, RBP4, and SPATA17 is lower than the expression level in a biological sample obtained from a normal control individual. A method for providing information to predict responsiveness to a substance for the prevention or treatment of cancer.

6. The invention of Claim 1, wherein the cancer is at least one selected from the group consisting of pancreatic cancer, gastric cancer, lung cancer, hepatocellular carcinoma, colorectal cancer, breast cancer, prostate cancer, thyroid cancer, ovarian cancer, cervical cancer, renal cell carcinoma, bladder cancer, melanoma, leukemia, lymphoma, multiple myeloma, brain tumor, sarcoma, metastatic cancers thereof, and recurrent cancers thereof. A method for providing information to predict responsiveness to a substance for the prevention or treatment of cancer.

7. The substance for preventing or treating cancer according to Claim 1, wherein the substance is at least one selected from the group consisting of gemcitabine, 5-fluorouracil, leucovorin, oxaliplatin, Nab-Paclitaxel, paclitaxel, cisplatin, capecitabine, S-1 (Tegafur / Gimeracil / Oteracil), erlotinib, olaparib, nivolumab, pembrolizumab, irinotecan, and SN-38. A method for providing information to predict responsiveness to a substance for the prevention or treatment of cancer.

8. A preparation comprising a method for measuring the expression level of the FKBP10 gene, A composition for predicting responsiveness to a substance for the prevention or treatment of cancer.

9. The formulation of Claim 8, further comprising a preparation for measuring the expression level of the MACROD2 gene, A composition for predicting responsiveness to a substance for the prevention or treatment of cancer.

10. The formulation of claim 8, further comprising a preparation for measuring the expression level of at least one gene selected from the group consisting of ABCA10, ABCA13, ARHGAP4, ATHL1, ATP6V1C2, COL28A1, COL9A3, CRYM, ECM1, EDAR, F3, FAM167A, FGF11, GOLGA7B, HLA-B, LOC102724532, MAPK8IP2, NKD1, PMAIP1, PMEPA1, PON3, RBP1, RBP4, SOX21, SPATA17, TGFB2, THBS1, and ZNF532. A composition for predicting responsiveness to a substance for the prevention or treatment of cancer.

11. In claim 8, the cancer is at least one selected from the group consisting of pancreatic cancer, gastric cancer, lung cancer, liver cancer, colorectal cancer, breast cancer, prostate cancer, thyroid cancer, ovarian cancer, cervical cancer, kidney cancer, bladder cancer, melanoma, leukemia, lymphoma, multiple myeloma, brain tumor, sarcoma, metastatic cancers thereof, and recurrent cancers thereof. A composition for predicting responsiveness to a substance for the prevention or treatment of cancer.

12. In claim 8, the substance for preventing or treating cancer is at least one selected from the group consisting of gemcitabine, 5-fluorouracil, leucovorin, oxaliplatin, nab-paclitaxel, paclitaxel, cisplatin, capecitabine, S-1, erlotinib, olaparib, nivolumab, pembrolizumab, irinotecan, and SN-38. A composition for predicting responsiveness to a substance for the prevention or treatment of cancer.

13. A composition comprising any one of claims 8 to 12, A kit for predicting responsiveness to a substance for the prevention or treatment of cancer.

14. A step comprising measuring the expression level of the FKBP10 gene from a biological sample obtained from an individual treated with a candidate substance, A method for screening substances that improve responsiveness to substances for the prevention or treatment of cancer.

15. The method of claim 14, further comprising the step of selecting a substance that improves responsiveness to a substance for preventing or treating cancer when the expression level of the FKBP10 gene is lower than the expression level in a biological sample obtained from an individual prior to treatment. A method for screening substances that improve responsiveness to substances for the prevention or treatment of cancer.

16. A preparation containing a substance that inhibits the expression of the FKBP10 gene, A pharmaceutical composition for enhancing sensitivity to a substance for the prevention or treatment of cancer.

17. The present invention of claim 16, further comprising an agent that inhibits the expression of the MACROD2 gene, A pharmaceutical composition for enhancing sensitivity to a substance for the prevention or treatment of cancer.

18. The agent of claim 16 further comprising an agent that inhibits the expression of at least one gene selected from the group consisting of ABCA10, ABCA13, ARHGAP4, ATHL1, ATP6V1C2, COL28A1, COL9A3, CRYM, ECM1, EDAR, F3, FAM167A, FGF11, GOLGA7B, HLA-B, LOC102724532, MAPK8IP2, NKD1, PMAIP1, PMEPA1, PON3, RBP1, RBP4, SOX21, SPATA17, TGFB2, THBS1, and ZNF532. A pharmaceutical composition for enhancing sensitivity to a substance for the prevention or treatment of cancer.

19. In claim 16, the cancer is at least one selected from the group consisting of pancreatic cancer, gastric cancer, lung cancer, liver cancer, colorectal cancer, breast cancer, prostate cancer, thyroid cancer, ovarian cancer, cervical cancer, kidney cancer, bladder cancer, melanoma, leukemia, lymphoma, multiple myeloma, brain tumor, sarcoma, metastatic cancers thereof, and recurrent cancers thereof. A pharmaceutical composition for enhancing sensitivity to a substance for the prevention or treatment of cancer.

20. In claim 16, the cancer exhibits resistance to at least one selected from the group consisting of gemcitabine, 5-fluorouracil, leucovorin, oxaliplatin, nab-paclitaxel, paclitaxel, cisplatin, capecitabine, S-1, erlotinib, olaparib, nivolumab, pembrolizumab, irinotecan, and SN-38. A pharmaceutical composition for enhancing sensitivity to a substance for the prevention or treatment of cancer.

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