WO2019168103A1 - Method for screening activated kinase as target of therapy - Google Patents

Method for screening activated kinase as target of therapy Download PDF

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WO2019168103A1
WO2019168103A1 PCT/JP2019/007839 JP2019007839W WO2019168103A1 WO 2019168103 A1 WO2019168103 A1 WO 2019168103A1 JP 2019007839 W JP2019007839 W JP 2019007839W WO 2019168103 A1 WO2019168103 A1 WO 2019168103A1
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kinase
phosphorylation
cancer
phosphorylated
responsible
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毅 朝長
阿部　雄一
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国立研究開発法人医薬基盤・健康・栄養研究所
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    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
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    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
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    • A61P1/00—Drugs for disorders of the alimentary tract or the digestive system
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    • C12N9/99—Enzyme inactivation by chemical treatment

Definitions

  • the present invention relates to a series of inventions based on a screening method for an activated kinase that can be a target. Specifically, the present invention relates to a method for screening a responsible kinase that can be a therapeutic target or a drug efficacy prediction target selected by phosphorylation proteomics, in particular, a disease, malignancy, for which the therapeutic target or drug efficacy prediction target has no effective therapeutic drug.
  • the present invention relates to a screening method for a responsible kinase that is a cause of a disease selected from among cancers with high advanced cancer and cancers having characteristic cancer characteristics.
  • Non-patent Document 2 Personalized medicine is expected to improve clinical effects by selecting optimal drugs that target cancer characteristics, and is attracting attention as a next-generation strategy in cancer treatment.
  • Molecular markers for identifying therapeutic targets according to the cancer characteristics of each patient are an important element in realizing precision medicine.
  • comprehensive measurements of molecular profiling from clinical cancer tissues have been carried out in various projects using genomics (Non-patent Document 3).
  • genomics has identified new subtypes in various cancers, subtype-based treatment strategies have still been limited by the large gap that exists between each patient's oncological phenotype and genotype ( Non-patent document 7).
  • Non-patent Document 8 Phosphorylation modification is an important regulator of protein function and is deeply involved in the control of carcinogenesis / malignancy. Therefore, in cancer biology, analysis has been advanced with a focus on fluctuations in phosphorylation signal pathways in cancer cells (Non-patent Document 8).
  • Protein kinases control various cell functions including cell cycle and cell movement through phosphorylation modification reaction to proteins.
  • EGFR epimal growth factor receptor
  • Non-patent Document 1 EGFR (epidermal growth factor receptor) signaling pathway has been studied as an important phosphorylation signaling pathway (Non-patent Document 1). Therefore, dysregulation of kinase is closely related to carcinogenesis (Non-patent Document 2).
  • 518 kinases encoded in the human genome are defined as “kinome” (Non-patent Document 1), and it is expected that essential knowledge in cancer biology will be obtained by kinome analysis. So far, genome analysis has revealed kinase mutations and resistance mechanisms against anticancer agents as some cancer drivers (Non-Patent Documents 3 and 4).
  • chimeric kinases such as EML4-ALK resulting from genomic instability reconstruct the cellular phosphorylation state and develop subtypes characteristic of cancer (Non-Patent Document 5).
  • Genome analysis has contributed greatly in cancer biology, including identification of driver genes including many kinases, but genome analysis alone cannot fully explain the resistance mechanisms of anticancer drugs. For example, changes in intracellular localization such as abnormal phosphorylation signals by the bypass pathway and nuclear localization of EGFR have been reported as causes of drug resistance (Non-Patent Documents 6 and 7).
  • genome analysis has been widely applied in previous studies on drug susceptibility of colorectal cancer, such as cetuximab, one of the molecular targeted therapeutics used as an anticancer drug, and many markers including cetuximab marker Has been revealed.
  • Proteomics that is, proteomic analysis, is intended for highly sensitive measurement of protein quantification and post-translational modification data that are direct targets of drugs.
  • large-scale phosphorylation modification data of intracellular proteins is an index indicating the state of a phosphorylation signal transduction pathway important for carcinogenesis and the activation state of a kinase that is a phosphorylation signal regulator. Therefore, it can be said that the integration of drug sensitivity data and cancer proteome data provides a lot of useful information in predicting the sensitivity of molecular target drugs targeting kinases.
  • Proteomics methods are used, in particular immobilized metal affinity chromatography (IMAC) (Non-patent document 9), metal oxide affinity chromatography (Non-patent document 10), and hydroxy acid-modified metal oxide affinity chromatography (Non-patent document 11).
  • IMAC immobilized metal affinity chromatography
  • Non-patent document 10 metal oxide affinity chromatography
  • Non-patent document 11 hydroxy acid-modified metal oxide affinity chromatography
  • Phosphorylated proteomics has been widely applied to analyze highly sensitive phosphorylation states controlled by kinomes. It has been reported that phosphorylation of serine, threonine and tyrosine residues in proteins, particularly phosphorylated tyrosine (pY) residues, play an important role in tumor development (Non-patent Document 12).
  • Non-patent Document 13 the existing tyrosine phosphorylated proteomics by the phosphopeptide enrichment method has a limit in completeness
  • Non-patent Documents 14 and 15 Quantitative proteomics combined with liquid chromatography-tandem mass spectrometry (LC-MS / MS) has been used for analysis of cetuximab-resistant colorectal cancer.
  • LC-MS / MS liquid chromatography-tandem mass spectrometry
  • protein expression information is not necessarily consistent with the phosphorylation modifying activity of kinases as promising drug targets. Therefore, reverse phase protein array (RPPA) is applied for the purpose of kinome activity profiling, and the activation state of phosphorylation signal transduction pathway related to drug sensitivity has been clarified (Non-patent Document 16).
  • RPPA reverse phase protein array
  • RPPA can be used to measure established signal transduction pathways, it is difficult to obtain a highly sensitive phosphorylation state including unknown pathways due to antibody limitations.
  • the present inventors specifically aimed to identify an unknown kinase target by creating a profile of kinome activity using a combination of tyrosine phosphorylated proteomics and existing phosphorylated proteomics.
  • a kinome activity profile is created, aiming to identify phosphorylation signals that are activated compared to normal sites. It was.
  • the present inventors first conducted high-sensitivity phosphorylated proteomic analysis of cetuximab-sensitive and resistant colon cancer cell lines to search for novel drug targets in cetuximab-resistant cancer.
  • Highly sensitive phosphorylated proteomics data using existing phosphorylated proteomics (IMAC enrichment of phosphorylated serine, phosphorylated threonine and phosphorylated tyrosine (pSTY) peptide) and tyrosine phosphorylated proteomics by immunoprecipitation of phosphorylated tyrosine peptide Got.
  • active kinase candidates and responsible kinases can be obtained by using activity-regulated phosphorylation information on kinases and kinase-substrate enrichment analysis (KSEA) information based on Kinase-Substrate Relationships (KSR)
  • KSEA kinase-substrate enrichment analysis
  • KSR Kinase-Substrate Relationships
  • phosphorylated proteomics analysis was performed on endoscopic specimens in cancer sites and normal sites collected from stomach cancer patients, and an attempt was made to search for cancer site-specific activated phosphorylation signals.
  • known phosphorylated signal pathways activated at the cancer site and kinases on the signal were selected from the phosphorylated proteomic analysis results.
  • the present invention includes the following aspects. ⁇ Method of screening for responsible kinase> [1] Based on the data obtained from phosphorylation proteomics, the phosphorylation site where phosphorylation modification activity is significantly increased is identified, the actual value of the kinase activity control phosphorylation site in the protein function information database, and / or the kinase substrate A method for screening a responsible kinase that can be a therapeutic target or a drug efficacy prediction target, by selecting a kinase having a significantly increased phosphorylation-modifying activity based on a predicted kinase activity obtained by a computational scientific method using related information; [2] The method according to [1], wherein phosphorylation proteomics is performed on a control sample including a control and a target sample including a target, or a target sample including a target; [3] The method according to [2], wherein the target sample is a biopsy; [4] The method according to [3], wherein the target sample is a
  • the statistical method in step 2) is a method for extracting phosphorylation sites showing significant variation in group 2 or phosphorylation sites showing significance in multiple groups, [5] or [6 ]
  • the method according to [8] The method according to any one of [5] to [7], wherein the concentration of phosphorylated tyrosine in step 1) is performed by concentration of phosphorylated peptide using metal affinity chromatography and then immunoprecipitation using an anti-phosphotyrosine antibody. ;
  • [9] The method according to any one of [5] to [8], wherein phosphorylated serine, phosphorylated threonine, and phosphorylated tyrosine using metal affinity chromatography are comprehensively analyzed to obtain highly sensitive phosphorylated proteomics data;
  • the therapeutic target is a responsible kinase responsible for the disease selected from among diseases for which there is no effective therapeutic agent, advanced malignant cancer, and cancer with characteristic cancer characteristics, and controls
  • the method according to any one of [1] to [9], wherein the sample is a normal cell and the target sample is the disease cell; [11] The method according to [10], wherein the disease for which there is no effective therapeutic agent is a drug resistant disease or an intractable disease involving responsible kinase; [12] The method according to [11], wherein the drug resistant disease is a disease in a patient who has an effective molecular targeted therapeutic agent but has become resistant to the therapeutic agent; [13] [12] The method according to [12], wherein the molecular targeted therapeutic agent is a kinase inhibitor.
  • the target sample is tissue from the subject, blood circulation
  • the method according to any one of [1] to [9], which is selected from cells and extracellular vesicles; [15] The method according to [14], wherein the disease for which there is no effective therapeutic agent is a drug resistant disease or an intractable disease involving responsible kinase; [16] The method according to [15], wherein the drug resistant disease is a disease in a patient who has an effective molecular targeted therapeutic agent but has become resistant to the therapeutic agent; [17] The method according to [16], wherein the molecular targeted therapeutic agent is a kinase inhibitor; [18] When the control sample is a cell sensitive to a therapeutic agent,
  • a method of stratifying subjects by determining whether a therapeutic is effective or not 1) Screening a responsible kinase which is a drug efficacy prediction target by the method according to any one of [13] to [19], 2) If the responsible kinase used to predict the effectiveness of a therapeutic agent to treat or prevent the disease in the subject is absent, the subject is assigned to the group for which the therapeutic agent is effective, and the responsible kinase If the subject is present, the subject is assigned to a group where the therapeutic agent is not effective, and the subject is stratified.
  • TKIs tyrosine kinase inhibitors
  • genome analysis has been used in studies on TKI sensitivity, but some TKI resistance cannot be predicted from genomic data. Therefore, the highly sensitive phosphorylated proteomic analysis of the present invention, in particular, tyrosine phosphorylation (pY) proteomic analysis, can contribute to predicting TKI sensitivity and overcoming resistance.
  • pY tyrosine phosphorylation
  • the highly sensitive phosphorylated proteomic analysis method of the present invention revealed an unknown phosphorylated tyrosine signaling network and overcame difficulties in analyzing phosphorylated tyrosine signaling.
  • the combination of IMAC-based phosphorylation proteomics and sensitive tyrosine phosphorylation proteomics can contribute to the elucidation of new targets that lead to new drugs that cannot be identified using genomic data.
  • the high-sensitivity phosphorylated proteomic analysis method of the present invention has not only drug-resistant cancer but also diseases with no effective therapeutic drug, advanced cancer with high malignancy, and cancer characteristics characteristic of individuals. It can be applied to responsible kinase, which is the cause of diseases selected from cancer.
  • the responsible kinase in cancer can be predicted in real time from the phosphorylated proteomics data using the screening method of the present invention. be able to. It is therefore expected to allow the determination of the most appropriate treatment strategy for an individual patient, for example the selection of the most appropriate kinase inhibitor.
  • real-time prediction means prediction of the kinase activity state at a certain point in the anticancer drug treatment period.
  • the present invention can contribute to precision medicine, and can provide a drug that is highly effective and has few side effects, particularly a molecular target drug used in cancer treatment. By avoiding treatments that are not expected to be effective, it brings economic benefits not only to patients themselves, but also to healthcare professionals, regulatory authorities, and health authorities, which is also beneficial from the perspective of public health care costs. is there.
  • FIG. 1a shows a quantitative proteomic analysis workflow comparing two cetuximab sensitive and two cetuximab resistant cell lines.
  • FIG. 1c shows the results of Western blotting comparing the activation states of kinases in the EGFR signaling pathway between cetuximab-treated or untreated colon cell lines. The levels of phosphorylated ERK1 / 2 and MEK1 / 2 and the protein expression level were analyzed, respectively. GAPDH was used as an internal standard.
  • FIG. 1a shows a quantitative proteomic analysis workflow comparing two cetuximab sensitive and two cetuximab resistant cell lines.
  • FIG. 1c shows the results of Western blotting comparing
  • FIG. 1d is a Venn diagram showing the results of identification of phosphorylation sites by phosphorylation proteomics and tyrosine phosphorylation proteomics. Each proteomic analysis was performed three times.
  • FIG. 1e is a Venn diagram showing the results of identification of class 1 phosphorylated tyrosine sites by phosphorylated proteomics and tyrosine phosphorylated proteomics. Phosphorylated tyrosine sites identified from pSTY phosphorylated proteomics are shown as small circles, and phosphorylated tyrosine sites identified from tyrosine phosphorylated proteomics are shown as large circles. Phosphotyrosine sites plotted in the Venn diagram were identified in all three experiments.
  • Figure 5 shows a volcano plot of phosphorylated proteomics data in cetuximab treated or untreated HCT116 (a) and HT29 (b) cell lines by using pSTY proteomics data and tyrosine phosphorylated proteomics data.
  • FIG. 3 shows identification of active kinase candidates as potential drug targets from phosphorylated proteomics data.
  • FIG. 3a shows the procedure for the reconstruction of the kinase network.
  • FIG. 3b shows cetuximab-treated or untreated HCT116 cells obtained from two different approaches based on activity-regulated phosphorylation information on the kinase and kinase substrate enrichment analysis (KSEA) information based on the kinase-substrate relationship (KSR) And is a bar graph showing the number of active kinase candidates in HT29 cells.
  • FIG. 3c is a bar graph showing the number of activated kinase candidates obtained from pSTY proteomics data and tyrosine phosphorylated proteomics data, respectively.
  • FIG. 3d is the result of Western blotting analysis showing the state of kinase activity of SRC in HCT116 and HT29 cells. GAPDH was used as an internal standard.
  • the activated phosphorylation network reconstructed from phosphorylated proteomics data is shown.
  • FIG. 4c, d activated phosphorylation network in HT29 cells.
  • Black square activated kinase identified by phosphorylation status.
  • Blue squares with white background Kinases upstream of activated kinases linked by KSR in PhosphositePlus.
  • FIG. 6A is a workflow for phosphorylated proteomics by endoscopic biopsy.
  • FIG. 6B is a graph showing changes in the sample amount of protein lysate before and after methanol / chloroform precipitation.
  • FIG. 7A shows the number of phosphorylated peptides, phosphorylated sites, class 1 phosphorylated sites, quantified class 1 phosphorylated sites, and phosphorylated protein groups.
  • FIG. 7B is a pie chart showing the proportion of phosphorylated serine (12,062), phosphorylated threonine (2,531), and phosphorylated tyrosine (94) among the identified phosphorylation sites.
  • FIG. 7C is a pie chart showing the proportion of phosphorylated sites assigned to the PhosphositePlus database (13,341) and the unassigned (1,346) of the 14,687 identified phosphorylated sites.
  • FIG. 7D is a Venn diagram showing a comparison of identified phosphopeptides between the surgical tissue in rumen cancer (Jong-Moon, P. et al) and this study.
  • FIG. 8A shows a principal component analysis (PCA) of phosphoprotein data from cancer biopsy (cancer 1: lower right, other cancer biopsy: cancer 2-5) and normal tissue (normal 1-5). ) Result. 1 shows quantitative features of phosphorylated proteomics by endoscopic biopsy.
  • FIG. 8B shows the correlation matrix of the Pearson correlation coefficient of phosphorylated proteome data. Here, a dark part shows a high correlation. 1 shows quantitative features of phosphorylated proteomics by endoscopic biopsy.
  • FIG. 8C is a comparison of Pearson's coefficients between correlations with and without the “Cancer 1” sample. Mann-Whitney U test was performed to confirm statistical significance.
  • FIG. 9A shows a volcano plot of phosphorylated proteomics. Individual circles in the right and left wings in the Volcano plot indicate phosphorylation sites with significant increases and decreases, respectively. Gray circles are phosphoric oxides with no significant difference. It is the result of the pathway analysis by comparing the phosphorylated proteome data derived from a cancer biopsy and a normal tissue.
  • FIG. 9B shows the result of pathway analysis using pathway information of KEGG (upper graph) and WikiPathway (lower graph). It is the result of the pathway analysis by comparing the phosphorylated proteome data derived from a cancer biopsy and a normal tissue.
  • FIG. 9C shows a versus dot plot using the nominal intensity of two phosphorylation sites (ATR T1989 and NBN S343).
  • Figure 5 shows kinome profiling results using phosphorylated proteome data from endoscopic biopsy.
  • FIG. 10A is a pie chart showing the proportion of phosphorylated proteins having Ser / Thr kinase (A on the left) and Tyr kinase (A on the right) activities.
  • FIG. 10B shows that the right bar predicts kinase activation in cancer biopsy, and the left bar indicates that inactivation of kinase is in cancer biopsy compared to that from normal tissue. It is the result of KSEA which shows what is predicted.
  • FIG. 10C shows changes in ERBB2 Y877, Y1248, and CDK1 Y15 analyzed for variation in the ERBB2 substrate phosphorylation sites used in the KSEA calculations.
  • One aspect of the present invention is a method for screening a responsible kinase that can be a therapeutic target or a drug efficacy prediction target by performing phosphorylation proteomics. Specifically, phosphorylation modifying activity is significantly increased by performing phosphorylation proteomics.
  • the present invention relates to a screening method for responsible kinases, in which a kinase having significantly increased phosphorylation-modifying activity is selected by identifying an increased phosphorylation site, and the kinase is selected as a responsible kinase that can be a therapeutic target or a drug efficacy prediction target. .
  • phosphorylated proteomic analysis or “phosphorylated proteomics” refers to a peptide having a phosphorylated serine (pS), phosphorylated threonine (pT) and / or tyrosine phosphorylated (pY) site.
  • pS phosphorylated serine
  • pT phosphorylated threonine
  • pY tyrosine phosphorylated site.
  • the measurement method includes mass spectrometry, and the details thereof may be a detection method by shotgun proteomics combining a nano flow rate LC and a high resolution mass spectrometer.
  • Peptide identification from raw data obtained with a mass spectrometer is performed using a peptide search engine using a standard amino acid sequence database. Specifically, peptide identification from raw data may be performed using, for example, MaxQuant.
  • a class 1 phosphorylation site (Localization ⁇ ⁇ Probability> 0.75) is selected from the obtained phosphorylation sites and used for analysis.
  • Class 1 phosphorylation site (Localization Probability> 0.75)” or simply “class 1 phosphorylation site” used in this specification will be described below.
  • “Localization Probability” indicates the certainty of whether the phosphorylation modification is really localized at the corresponding amino acid site where it was identified.
  • Phosphorylation modifications with “Probability” are defined as “class 1 phosphorylation sites” (Jesper V. Olsen et al., 2006, Cell).
  • “Tyrosine phosphorylation proteomics analysis” or “tyrosine phosphorylation proteomics” refers to the concentration of peptides with tyrosine phosphorylation sites among phosphorylated serine (pS), phosphorylated threonine (pT), and tyrosine phosphorylated (pY). This is a measurement method for obtaining highly sensitive tyrosine phosphorylation information. Specifically, in the present invention, tyrosine phosphorylation (pY) proteomics is performed by immunoprecipitation from a phosphorylated peptide for highly sensitive phosphorylation (pSTY) proteomics prepared by metal affinity chromatography.
  • identifying a phosphorylation site having a significantly increased phosphorylation-modifying activity means using trypsin, pepsin, chymotrypsin, glutamyl endopeptidase, lysyl endopeptidase, and the like. This means an operation of performing phosphorylation proteomics analysis on the digested protein peptide fragment and identifying a peptide fragment containing a phosphorylation site where the phosphorylation modifying activity is significantly increased as compared with the subject.
  • phosphorylation-modifying activity phosphorylation sites are specified, and then kinases whose phosphorylation-modifying activity is significantly increased are selected.
  • the method is based on screening kinases using actual values of kinase activity-regulated phosphorylation sites in protein function information databases and / or kinase activity prediction values obtained by computational scientific methods using kinase substrate related information. Become. In selecting responsible kinases, the measured values of kinase activity-regulated phosphorylation sites and the predicted kinase activity may be used separately, but if both are used, more accurate responsible kinases can be selected. .
  • the “protein function information database” means a database storing function information of protein post-translational modifications, such as databases Uniprot, Reactome, GPS, PhosphositePlus (Hornbeck, P. V. et al., Nucleic Acids Res 40, D261-70 (2012)), PhosphoNetworks, Phospho.ELM (Diella, F., et al., Nucleic Acids Res 36, D240-4 (2008).), PHOSIDA (Gnad, F.
  • kinase having a significantly increased phosphorylation-modifying activity is selected. That is, a statistical method for selecting kinases exhibiting significant activation in a specific group using kinase activity control phosphorylation information on the protein function information database and / or kinase activity prediction information using kinase substrate related information. is there. For example, NetPhos, NetworKIN, PhosphositePlus, Phospho.ELM, GPS, NetPhorest (30. Miller, M. L. et al., Linear Motif Atlas for Phosphorylation-Dependent Signaling.1, Science signaling 1, Science signaling (2008).).
  • actually measured value of kinase activity-regulated phosphorylation site means an actual value of a phosphorylation site to which functional information for controlling kinase activity is added in the database.
  • the information regarding the phosphorylation modification on the kinase which controls the kinase activity registered in Uniprot http://www.uniprot.org/) is mentioned.
  • Other examples include PhosphositePlus and PhosphoELM.
  • the “predicted value of kinase activity obtained by a computational scientific method using kinase substrate-related information” means that the phosphorylation modification site modified by a specific kinase is an all-detection phosphorylation modification site.
  • KSEA kinase substrate enrichment analysis
  • the selected kinase is assigned as a responsible kinase that can be a therapeutic target or a drug efficacy prediction target.
  • therapeutic target refers to a disease selected from among diseases for which there is no effective therapeutic agent, advanced cancer with high malignancy, and cancer having characteristic cancer characteristics for individuals. It means the responsible kinase that is responsible for.
  • drug predictive target is selected from diseases for which there is no effective therapeutic drug, advanced cancer with high malignancy, and cancer that has individual cancer characteristics By a responsible kinase used to predict the effectiveness of a therapeutic agent to treat or prevent the disease in a subject suffering from the disease.
  • response kinase refers to about 520 protein kinases in humans, such as EGFR, Src, ERK1 / 2, etc., which control various types of cell functions including cell cycle and cell motility. In an embodiment, it means a causal kinase that contributes to the activation of survival proliferation signals and / or inflammatory signals and causes the disease.
  • disease without an effective therapeutic agent means a drug resistant disease or an intractable disease involving responsible kinase.
  • a “drug resistant disease” is an effective molecular targeted therapeutic for a disease, specifically a kinase inhibitor that targets survival and / or inflammatory signals, but is resistant to that therapeutic from some point in time. Means disease in the patient. The mechanism of becoming resistant in drug-resistant diseases is believed to be responsible kinase involvement, as shown in the Examples herein.
  • the “refractory disease in which responsible kinase is involved” means a proliferative disease or inflammatory disease in which responsible kinase is involved in activation of a survival proliferation signal and / or an inflammatory signal.
  • proliferative diseases are insulinoma, enamel epithelioma, transplantable genital tumor, Cowden syndrome, pituitary adenoma, familial colorectal adenoma, pheochromocytoma, ganglion, teratoma, myoma, Cushing syndrome, cronkite Canada syndrome, keloid, primary aldosteronism, chronic eosinophilic leukemia / idiopathic eosinophilia syndrome, perianal adenoma, myelodysplasia / myeloproliferative disorder, myelofibrosis, osteochondroma, mixed tumor, Odontoma, odontogenic myxoma, lipoma, juvenile myelomonocytic leukemia, gastrointestinal stromal tumor, small intestine tumor, schwannoma, polycythemia vera, leukoplakia, calcified cystic odon
  • inflammatory diseases include ulcerative colitis, inflammatory bowel diseases represented by Crohn's disease, aphthous stomatitis, erythema nodosum, gangrenous pustulosis, psoriasis, lichen, pemphigoid, blisters Pemphigus vulgaris, peripheral arthritis, ankylosing spondylitis, primary sclerosing cholangitis, pancreatitis, fatty liver, hepatitis, cirrhosis, nephritis, nephrotic syndrome, scleritis, uveitis, ulceris, corneal ulcer, thrombotic Phlebitis, chronic thyroiditis, SLE, Sjogren's syndrome, rheumatoid arthritis, spondyloarthritis, atherosclerosis, polymyalgia rheumatica, giant cell arteritis, asbestosis / silicosis, cryopyrin-related periodic
  • High-grade advanced cancer refers to disruption of this regulatory order due to the emergence of responsible kinases involved in the activation of survival and / or inflammatory signals. It means a tumor with a significantly worse prognosis because it invades or metastasizes.
  • Possible cancers include leukemia, lymphoma, Hodgkin's disease, non-Hodgkin's lymphoma, multiple myeloma, brain tumor, breast cancer, endometrial cancer, cervical cancer, ovarian cancer, esophageal cancer, stomach cancer, and appendix.
  • Cancer colon cancer, hepatocellular carcinoma, gallbladder cancer, bile duct cancer, pancreatic cancer, adrenal cancer, gastrointestinal stromal tumor, mesothelioma, head and neck cancer, laryngeal cancer, oral cancer, Oral cavity cancer, gingival cancer, tongue cancer, buccal mucosa cancer, salivary gland cancer, sinus cancer, maxillary sinus cancer, frontal sinus cancer, ethmoid sinus cancer, sphenoid sinus cancer, Thyroid cancer, lung cancer, osteosarcoma, prostate cancer, testicular cancer, renal cell cancer, bladder cancer, rhabdomyosarcoma, skin cancer, anal cancer, responsible kinase is a survival proliferative signal and / or inflammation It is involved in signal activation.
  • a “cancer having personal cancer characteristics” refers to a survival growth signal and / or an inflammatory signal in a cancer patient population due to a responsible kinase specific to the individual patient. It means a tumor in which activation is occurring. Possible cancers include leukemia, lymphoma, Hodgkin's disease, non-Hodgkin's lymphoma, multiple myeloma, brain tumor, breast cancer, endometrial cancer, cervical cancer, ovarian cancer, esophageal cancer, stomach cancer, and appendix.
  • Cancer colon cancer, hepatocellular carcinoma, gallbladder cancer, bile duct cancer, pancreatic cancer, adrenal cancer, gastrointestinal stromal tumor, mesothelioma, head and neck cancer, laryngeal cancer, oral cancer, Oral cavity cancer, gingival cancer, tongue cancer, buccal mucosa cancer, salivary gland cancer, sinus cancer, maxillary sinus cancer, frontal sinus cancer, ethmoid sinus cancer, sphenoid sinus cancer, Thyroid cancer, lung cancer, osteosarcoma, prostate cancer, testicular cancer, renal cell cancer, bladder cancer, rhabdomyosarcoma, skin cancer, anal cancer, responsible kinase is a survival proliferative signal and / or inflammation It is involved in signal activation.
  • a phosphorylated proteome method specialized for endoscopic biopsy is provided.
  • sample loss can be reduced in the experimental procedure of phosphorylated proteomics.
  • Tissue samples may contain large amounts of contaminants that interfere with liquid chromatography tandem mass spectrometry (LC-MS / MS) analysis, so methanol / chloroform precipitation may be performed prior to protein digestion.
  • LC-MS / MS liquid chromatography tandem mass spectrometry
  • methanol / chloroform precipitation may be performed prior to protein digestion.
  • immobilized metal affinity chromatography (IMAC) / C18 stage chip rather than fractionation of IMAC-enriched peptides by conventional offline LC [18] can be adopted [5, 6].
  • the present invention selects, as a specific embodiment, a kinase having a significantly increased phosphorylation-modifying activity by identifying a phosphorylation site that is significantly increased based on data obtained from phosphorylated proteomics,
  • a control sample including a control such as a normal state and a target sample including a target in an abnormal state such as a disease state are compared, and a kinase in which phosphorylation modifying activity is significantly increased in the latter is selected.
  • a control sample in the field including controls such as normal conditions
  • phosphorylation is performed only on the target sample.
  • Proteomics can be performed to select responsible kinases.
  • the presence of a kinase whose phosphorylation-modifying activity is significantly increased in an abnormal state causes resistance.
  • Typical examples in the control state are normal cells and sensitive cells, and typical examples in the abnormal state are cells to be treated.
  • control and target samples include cells sensitive to certain molecular targeted drugs and resistant cancer cells, early and advanced cancer cells, cells and individuals with average cancer characteristics Cells that exhibit typical cancer properties include, but are not limited to.
  • the present invention relates to a method for screening a responsible kinase, wherein a kinase having significantly increased phosphorylation-modifying activity is selected as a responsible kinase that can be a therapeutic target or a target for predicting drug efficacy.
  • the present invention also provides another more specific embodiment as follows. 1) Obtain phosphorylated proteomics data for phosphorylated serine, phosphorylated threonine and / or phosphorylated tyrosine peptide concentrated from cell lysates of endoscopic specimens, 2) Based on the obtained data, statistical methods were used to identify phosphorylation sites that were significantly increased compared to the average cancer patient population.
  • the present invention relates to a method of screening for a responsible kinase, which is a responsible kinase that can be a target or a target for predicting drug efficacy.
  • the “statistical method” in step 2) in the more specific embodiment described above is for extracting a phosphorylation site showing significant variation in two groups, or a phosphorylation site showing significance in multiple groups. It is a technique. For example, it means t-test, welch-t-test, Mann-Whiteney 'U ⁇ ⁇ ⁇ test, and / or ANOVA that can identify phosphorylation sites that are significantly increased in treated cells compared to control cells.
  • the “phosphorylation site” means an amino acid site having phosphorylation modification detected by a mass spectrometer.
  • “Concentration of phosphorylated tyrosine” in step 1) in the more specific embodiment above means that phosphorylated tyrosine is extracted from a sample obtained by enzymatic digestion of a biological sample, for example, trypsin digestion. Typically, enzyme-digested samples are first subjected to metal affinity chromatography to extract phosphopeptides and then phosphotyrosine peptides are collected by immunoprecipitation using anti-phosphotyrosine antibodies.
  • mass spectrometry is a method in which a peptide sample is converted into gaseous ions using an ion source (ionization), and is moved in a vacuum in an analysis section using electromagnetic force or flying. This refers to a measurement method using a mass spectrometer capable of separating and detecting a peptide sample ionized by a time difference according to the mass-to-charge ratio.
  • an ionization method using an ion source an EI method, CI method, FD method, FAB method, MALDI method, ESI method or the like can be selected as appropriate.
  • a separation method such as a magnetic field deflection type, a quadrupole type, an ion trap type, a time of flight (TOF) type, a Fourier transform ion cyclotron resonance type, or the like can be selected as appropriate.
  • tandem mass spectrometry (MS / MS) or triple quadrupole mass spectrometry combining two or more mass spectrometry methods can be used.
  • the sample contains a phosphorylated peptide
  • the sample can be concentrated using iron ion-immobilized affinity chromatography (Fe-IMAC) before introducing the sample into the mass spectrometer.
  • Fe-IMAC iron ion-immobilized affinity chromatography
  • variable peptide and the stable peptide according to the present invention can be separated and purified to form a sample by liquid chromatography (LC) or HPLC.
  • a detection part and a data processing method can also be selected suitably.
  • a peptide labeled with a stable isotope having a known amino acid sequence and a known concentration may be used as the internal standard. it can.
  • one or more of the amino acids in the variable peptide and the stable peptide according to the present invention is a stable isotope labeled peptide containing any one or more of 15N, 13C, 18O, and 2H.
  • the type, position, number, and the like of amino acids can be appropriately selected, and the stable isotope-labeled peptide can be obtained by using the F-moc method (Amblard., Et al. Methods Mol Biol.
  • iTRAQ registered trademark
  • ICAT registered trademark
  • ICPL registered trademark
  • NBS registered trademark
  • TMT Tandem Mass Tag
  • High-sensitivity phosphorylated proteomics data used in the present specification refers to intracellular large-scale phosphorylation information data using the phosphorylated peptide fractionation method and tyrosine phosphorylated peptide enrichment method developed by the present inventors. Point to. This is essential for the activity profiling of cellular kinomes to overcome the resistance of molecular targeted drugs.
  • kinome is a generic name for 518 kinases encoded in the human genome.
  • kinome activity profiling refers to a method of predicting intracellular kinase activity with high sensitivity from highly sensitive phosphorylated proteomics data. This is important for efficiently implementing anticancer drug treatment based on prediction of drug sensitivity.
  • the present invention provides a method for screening responsible kinases as a cause of a disease to be treated, specifically, a disease in which there is no effective therapeutic agent, a highly malignant advanced cancer, and an individual.
  • the present invention relates to a screening method for a responsible kinase in a therapeutic target, which is a responsible kinase responsible for a disease selected from cancers having characteristic cancer characteristics, and the control sample is a normal cell and the target sample is the disease cell. .
  • the present invention provides a method for screening a responsible kinase for determining whether a certain therapeutic drug is effective or ineffective in a subject, specifically, a therapeutic drug whose effective drug target is effective.
  • a responsible kinase used to predict gender, and the control sample is sensitive or non-sensitive to the therapeutic agent
  • the target sample is from tissue from the subject, circulating blood cells and extracellular vesicles
  • the present invention relates to a screening method for a responsible kinase in a target for predicting drug efficacy.
  • a therapeutic-sensitive cell refers to a cell in which cancer growth is stopped by a specific therapeutic agent, or cancer disappears or shrinks if the cell is a cancer cell, for example. means.
  • subject-derived tissue means blood, surgical tissue, biopsy specimen.
  • blood circulating cells refers to cancerous lesions derived from the cancerous lesions that have migrated from the cancerous lesions, including the primary tumor and cancerous metastatic lesions, into the blood vessels. Means a cell.
  • extracellular vesicle is a granular vesicle of several tens of nanometers to several micrometers secreted from a cell, and is a generic term for exosomes, microvesicles, apoptotic bodies, etc. is there. It contains nucleic acids (micro RNA, messenger RNA, DNA, etc.) and proteins, and is thought to function as a cell-to-cell information transmission tool.
  • control sample is a cell sensitive to a therapeutic agent
  • phosphorylation proteomics is performed on the sensitive cell and the target sample, and the phosphorylation-modifying activity is significantly increased in the target sample as compared with the sensitive cell.
  • the present invention relates to a method for screening for a responsible kinase in a drug efficacy prediction target by selecting an increased kinase and using it as a responsible kinase.
  • phosphorylation proteomics is performed on the target sample, and the kinase activity average value of the cancer population is determined by pan-cancer analysis of the kinase activity level.
  • the present invention relates to a method for screening a responsible kinase in a drug efficacy prediction target, which comprises selecting a kinase exhibiting a significant increase in phosphorylation modifying activity value when used as a control.
  • “Pan-cancer Analysis of Kinase Activity Level” is a technique for extracting a kinase showing an activation pattern specific to a cancer subtype or a specific cancer patient from a cancer population (The Cancer Genome Atlas Research Network et al., 2013, Nat. Genetics). For example, an average is acquired from data derived from 1000 subjects, and new subjects after the 1001st are determined based on the average.
  • a control sample containing cells sensitive to a therapeutic agent is compared with a target sample containing a target in a subject who is a target of drug efficacy, and a kinase with significantly increased phosphorylation-modifying activity is selected in the latter.
  • a kinase with significantly increased phosphorylation-modifying activity it is determined that the therapeutic agent is not effective for that subject.
  • the value of the phosphorylation-modifying activity of the sensitive cells is standardized and the value of the target sample can be evaluated based on that standard value, phosphorylation proteomics is only applied to the target sample Can be screened for responsible kinases.
  • the subject when the responsible kinase used to predict the effectiveness of the therapeutic agent for treating or preventing the disease is absent, the subject is effective for the therapeutic agent. It is determined that
  • Another aspect of the present invention is a method for screening a substance that inhibits the phosphorylation-modifying activity of a responsible kinase screened by the method of the present invention, 1) A candidate substance capable of inhibiting the phosphorylation-modifying activity of the responsible kinase is added to the medium of the target sample having the responsible kinase, 2) Compare the cell proliferation activity of the candidate substance-treated group and the untreated group in the target sample having the responsible kinase, 3) The present invention relates to a method for evaluating a candidate substance as a substance that inhibits the phosphorylation-modifying activity of a responsible kinase if the cell growth activity of the candidate substance-treated group is lower than that of the untreated group.
  • Candidate substances that can inhibit the phosphorylation-modifying activity of the responsible kinase are selected from diseases for which there is no effective therapeutic agent, advanced malignant cancers, and cancers with individual cancer characteristics
  • a therapeutic agent capable of treating or preventing a disease preferably a therapeutic agent already used in therapy, preferably a molecular target drug is used.
  • Examples of these include Rituximab / Rituxan, Trastuzumab / Herceptin, Gemtuzumab, ozogamicin / Mylotarg, Alemtuzumab / Campath, Imatinib / Gleevec, Bcr-Abl / Kit, Ibritumomab, tiuxetan / Zevalin, Tositumomabfiti Velcade, Bevacizumab / Avastin, Cetuximab / Erbitux, Erlotinib / Tarceva, Azacitidine / Vidaza, Sorafenib / Nexavar, Sunitinib / Sutent, Dasatinib / Sprycel, Panitumumab / Vectibix, Vorinostat / Zolinza, Decitabpat / Dolin, T Nilotinib / Tasigna, Everolimus / Afinitor, Pazopanib /
  • the present invention provides a phosphorylation of at least one responsible kinase selected from ABL1, CDK12, HCK, JAK2, LCK, LYN, MAP2K6, MAPK12, MAPK14, PRKCD, YES1, and DYRK4 in colon cancer cells.
  • the present invention relates to a method for screening a substance that inhibits oxidation-modifying activity. Phosphorylation-modifying activity inhibitors for these kinases are likely to treat / prevent cetuximab-resistant patients.
  • the present invention provides a subject suffering from a disease selected from among diseases for which there is no effective therapeutic agent, advanced cancer with high malignancy, and cancer having characteristic cancer characteristics.
  • a method for stratifying subjects by determining whether a therapeutic agent for treating or preventing the disease is effective or ineffective comprising: 1) screening for a responsible kinase that is a target for predicting drug efficacy by the method of the present invention for screening a responsible kinase for determining whether a therapeutic agent is effective or ineffective in a subject; 2) If the responsible kinase used to predict the effectiveness of a therapeutic agent to treat or prevent the disease in the subject is absent, the subject is assigned to the group for which the therapeutic agent is effective, and the responsible kinase If the subject is present, the subject is assigned to a group where the therapeutic agent is not effective and the subject is stratified.
  • the stratification methods herein are useful for personalized medicine.
  • Traditional treatments for traditional patients are administered the same therapeutic agent when diagnosed with the same disease, and this method is effective for some patients but not for others, or May cause serious side effects. Therefore, personalized medicine is attracting attention.
  • genes and proteins related to the cause and pathology of diseases have been elucidated at the molecular level, and even patients diagnosed with the same disease are actually classified into various types according to differences in the molecules related to the cause and pathology of the disease. I know I can do it. It is personalized medicine that examines the causative molecules of such diseases and pathologies for each patient and administers directly acting drugs to cure the disease and improve the pathology.
  • the method of stratification of patients according to the present invention is useful for personalized medicine that can be expected to have a high therapeutic effect and suppress side effects, gives the patient a sense of security, and is expected to improve QOL. Can be provided to patients. And the ability to provide reliable treatments that are effective results in a reduction in the overall cost of medical care for the public due to cost effectiveness.
  • Lipofectamine RNAiMax penicillin-streptomycin, tandem mass tag (TMT) 10plex isobaric label reagent set, magnetic dynabead protein G and FBS for immunoprecipitation were obtained from Thermo Fisher Scientific (Waltham, MA, USA).
  • Chemi-Lumi Super and DMEM were purchased from Nacalai Tesque (Kyoto, Japan).
  • KX-391 and SU6656 were purchased from Selleck (Houston, TX, USA).
  • PhosSTOP phosphatase inhibitor cocktail PhosSTOP phosphatase inhibitor cocktail, trypsin and cOmplete protease inhibitor cocktail were obtained from Roche (Basel, Switzerland).
  • the detergent compatible (DC) protein assay was purchased from Bio-Rad (Hercules, CA, USA).
  • XV Pantera gel (5-20%) for sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) was purchased from DRC (Tokyo, Japan).
  • RNA-direct SYBR green real-time PCR master mix was obtained from Toyobo (Osaka, Japan).
  • the Prism 6 software package was purchased from GraphPad Software (La Jolla, CA, USA). Cell Counting Kit-8 was obtained from Dojindo (Kumamoto, Japan). Cetuximab was a gift from Merck KGaA (Darmstadt, Germany).
  • pMEK1 / 2 S217 / 221 (41G9), pERK1 / 2 T202 / Y204 (D13.14.4E), and phosphorylated tyrosine (P-Tyr-1000) MultiMab antibody are available from Cell Signaling Technology (Danvers, MA, USA). Obtained from MEK1 / 2 (9G3) and ERK1 / 2 (MK1) were purchased from SantaCruz (Dallas, TX, USA). GAPDH (6C5) antibody was obtained from Abcam (Cambridge, UK). SRC (327) antibody was obtained from Merck KGaA. The pSRC Y418 antibody was purchased from Thermo Fisher Scientific.
  • Example 1 Phosphorylated proteomics analysis of cetuximab-sensitive or resistant colorectal cancer cell lines
  • a combination of high-sensitivity tyrosine phosphorylation proteomics analysis and high-sensitivity phosphorylation proteomics analysis based on IMAC resulted in large amounts of phosphorylated proteomics data in colorectal cancer cell lines .
  • 1.1 Cell culture and sample collection DLD1, LIM1215, HT29, HCT116, Colo205 and SW480 cells purchased from ATCC were cultured at 37 ° C. under 5% CO 2 . These colon cell lines were maintained in Dulbecco's Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and penicillin-streptomycin.
  • DMEM Dulbecco's Modified Eagle Medium
  • FBS fetal bovine serum
  • the first concentration of phosphopeptide from 2.0 mg protein solution was performed using Fe 3+ IMAC resin.
  • the phosphorylated peptide was labeled with TMT 10 plex reagent according to the manufacturer's protocol.
  • a total of 20 mg of labeled phosphopeptide mixture was prepared and lyophilized. Of the 20 mg mixture, 4.0 mg was used for fractionation in pSTY proteomics and the rest (16 mg) was used for phosphorylated tyrosine immunoprecipitation (pY-IP) experiments.
  • the phosphorylated peptide in pSTY proteomics was divided into seven fractions according to a previously published protocol (36). In the pY-IP experiment, phosphorylated tyrosine peptides were enriched according to the protocol of the previous study (14).
  • LC-MS / MS analysis was performed on a Q Exactive Plus mass spectrometer (Thermo Scientific) equipped with an UltiMate 3000 nano LC system (Thermo Scientific) and HTC-PAL (CTC Analytics, Zwingen, Switzerland). It was performed using. In the LC mobile phase, buffer A (0.1% formic acid, 2% acetonitrile) and buffer B (0.1% formic acid, 90% acetonitrile) were used.
  • the Q Exactive Plus apparatus was operated in the data dependent mode under the following conditions: Heated capillary temperature, 250 ° C .; spray voltage, 2 kV.
  • peptides in pSTY and pY proteomics were trapped on an Acclaim PepMap RSLC nanotrap column (0.1 mm ⁇ 20 mm, Thermo Fisher Scientific) and then analyzed column (75 ⁇ m ⁇ 30 cm, ReproSil-Pur C18- AQ, filled with 1.9 ⁇ m resin). Peptides were separated at a flow rate of 280 nL / min using Buffer B from 5 minutes to 30 minutes with a gradient of 135 minutes (pSTY proteomics) or 45 minutes (pY proteomics). Survey-scan MS spectra were acquired with orbitrap at 350-1800 m / z, resolution of 70,000, and AGC at 1E6.
  • As the cleavage method a high energy collision dissociation (HCD) method was adopted.
  • the isolation window was 2.0 Da for pSTY proteomics and 3.0 Da for pY proteomics. Collision energy was 25% (pSTY proteomics) or 30% (pY proteomics).
  • N 6, average of DLD1 and LIM1215 cells
  • N 3, HCT116 cells or HT29 cells
  • the average SD values for pSTY proteomics and tyrosine phosphorylated proteomics were 0.494 and 0.277, respectively. Increased phosphorylation sites were identified as being accompanied by expression of phosphorylation sites more than twice SD from the mean, which is a fold change of 0.989 (pSTY proteomics) and 0.554 (tyrosine phosphorylated proteomics) Corresponded to.
  • cetuximab is an anti-EGFR antibody
  • cetuximab treatment inhibited phosphorylation of downstream kinases (ERK1 / 2 T202 / Y204 and MEK1 / 2 S217 / S221) in the cetuximab sensitive group, but uniform downstream kinases in the cetuximab resistant group
  • cetuximab treatment reduced the expression level of pMEK1 / 2 in HT29, but not in HCT116 (FIG. 1c).
  • Example 2 Identification of kinases activated in cetuximab-resistant cells 2.1 Identification of phosphorylation sites that are modified on kinases in cetuximab-resistant cells
  • Kinome activity profiling is effective for anticancer drug treatment based on prediction of drug sensitivity Is important to do. Therefore, in order to identify the kinase activated in cetuximab-resistant cells from the highly sensitive phosphorylated proteomics data obtained in Example 1, phosphorylation showing a significant difference between the cetuximab-sensitive group and the cetuximab-resistant group first. The site was searched. It is well known that the activity of many kinases is controlled by its own phosphorylation state (autophosphorylation) (12). Thus, for kinome activity profiling, we first focused on the phosphorylation sites modified on the kinase.
  • a cut-off value was defined based on statistical significance by fold change and t-test.
  • the criteria for the magnification change cutoff was defined based on experimental errors calculated using standard samples.
  • the average two SD values in triplicate pSTY and tyrosine phosphorylated proteomics analyzes were 0.989 and 0.556, respectively.
  • the cutoff of the change in magnification was set to 1.985 for pSTY proteomics corresponding to 2SD, and 1.470 for tyrosine phosphorylated proteomics.
  • the statistical significance cutoff was set at a uniform q value (q ⁇ 0.05). Based on these two thresholds, we searched for a phosphorylation site that significantly increased in HCT116 and HT29 cells relative to the mean value of the cetuximab-sensitive cell population (FIGS. 2a and b).
  • HCT116 cells phosphorylation sites 31 and 29 on the kinase were significantly increased either with or without cetuximab treatment.
  • the results for HT29 cells also increased the 15 and 19 phosphorylation sites on the kinase, respectively, when treated or untreated with cetuximab.
  • kinases with an increased number of phosphorylation sites having an activity control function on the kinase were selected.
  • KSR kinase-substrate relationship predicted by NetworKIN (40) was used.
  • FOG. 3b Information about the function of each phosphorylation site was obtained from the Uniprot database (16).
  • activated kinases were predicted from the entire phosphorylated proteomic data including pSTY and tyrosine phosphorylated proteomics using bioinformatics methods.
  • Kinase-substrate enrichment analysis was applied to select kinases activated in resistant cell lines compared to sensitive cell lines (17).
  • Comparison in cetuximab untreated conditions predicted that the two kinases in HCT116 cells were more active than the cetuximab sensitive cell population.
  • one kinase was predicted to be highly active 24 hours after cetuximab treatment (FIG. 3b).
  • the phosphorylation state related to the enzyme activity of these kinases was verified by performing Western blotting, one of the phosphorylation sites (Y418) increased on the SRC even though the protein expression of the SRC was equivalent. (Fig. 3d).
  • Example 3 Construction of a kinase network by KSR It has been reported that rewriting of phosphorylation signaling is one of the causes of drug resistance in anticancer therapy (4). For example, bypass signaling caused by constitutive activation of kinases downstream of therapeutic targets or unexpected activation of other kinases causes (or is involved in) drug resistance (4).
  • a phosphorylated signaling network was constructed. The active kinase candidates shown in FIG. 3 were used as the constituent factors of the kinase network, and they were linked with the experimentally verified KSR registered in the PhosphositePlus database (15).
  • Figures 4a and b show the phosphorylation network in HCT116 cells by linking 13 activated kinases and their 21 KSRs.
  • phosphorylation signaling from SRC to PRKCD was constitutively activated with or without cetuximab treatment.
  • activation phosphorylation network construction was limited due to insufficient number of activated kinases (FIGS. 4c, d).
  • Test example 1 Effect on cell proliferation of resistant cells in inhibition of activated kinase
  • the functional role of active kinase candidates in cell proliferation of HCT116 cells was confirmed.
  • siRNA was purchased from Thermo Scientific. The list of purchased siRNAs is described below.
  • HCT116 cells were treated with three siRNAs specific to each kinase, MAPK1, MAPK3, and MAPK13, and the viability of HCT116 cells was analyzed by quantitative reverse transcription polymerase chain reaction (qRT-PCR).
  • siRNA was transfected with Lipofectamine RNAiMax according to manufacturer's instructions. HCT116 cells were seeded 24 hours before the introduction of siRNA, and then the culture medium was replaced with a new culture medium containing 20 nM siRNA. After the treatment was started, HCT116 cells were cultured at 37 ° C. for 72 hours, and the influence on cell proliferation ability was examined. If chemicals were used, HCT116 cells were seeded 24 hours prior to the start of the assay, and the media was replaced with fresh media containing each dose of chemical.
  • MAPK1, MAPK3, MAPK13 knockdown of three kinases significantly reduced cell proliferation in all three siRNAs of each kinase.
  • two of the three siRNAs targeting six kinases CDK12, MAPK12, MAPK14, PRKCD, SRC, YES1 significantly inhibited the proliferation of HCT116 cells (FIG. 5a, Table S7).
  • MAPK1 and MAPK3 are kinases that are downstream factors of EGFR signaling (19).
  • MAPK13 (p38 delta) is a member of the p38 kinase family (20). To date, p38 kinase signaling has been reported to be important for the development of colon cancer and resistance to cetuximab (21). Therefore, our results from kinome activity profiling are consistent with previously reported data. This fact suggests that our phosphorylated proteomic approach can accurately capture phosphorylated signaling, including known mechanisms associated with drug resistance in cancer cells.
  • Test example 2 Confirmation that the identified kinase is a drug target
  • a kinase inhibitor Treatment of HCT116 cells with two TKIs targeting SRC and YES1 (KX2-391 and SU6656, respectively) revealed that these TKIs are not only proliferating in HCT116 but also in other cetuximab resistant cell lines such as HT29, SW480 and Colo205. It was found to also inhibit proliferation (FIG. 5b).
  • the 50% inhibitory concentration (IC50) of the SRC inhibitor KX2-391 was HCT116 (IC50: 19 nM), HT29 (IC50: 30 nM), SW480 (IC50: 36 nM), and Colo205 cells (IC50: 29 nM).
  • IC50 50% inhibitory concentration
  • SU6656 a YES1 inhibitor
  • Sensitive phosphorylated proteomics data were obtained by performing phosphorylated proteomics based on immobilized metal ion affinity chromatography and sensitive tyrosine phosphorylated proteomics analysis. Comparison of sensitive cell lines (LIM1215 and DLD1) and resistant cell lines (HCT116 and HT29) reveals kinase candidates that are highly active in resistant cell lines, most of which are identified by tyrosine phosphorylated proteomics analysis It was done. Surprisingly, no genomic variation was observed in most of these kinases.
  • Activation kinase network analysis using activated kinase candidates indicated that the growth of HCT116 cells was significantly inhibited by SRC knockdown and treatment with SRC inhibitors, which suggested constitutive activity of the SRC-PRKCD cascade in HCT116 cells. It was confirmed.
  • Example 4 Kinase activity profiling from gastric cancer endoscopic specimens 1.1 Collection of endoscopic biopsies in gastric cancer All patients were treated at National Cancer Center Hospital (Tokyo, Japan). The collection and analysis of endoscopy samples was approved by the Ethics Committee of the National Cancer Center Hospital and the National Institute of Biomedical Research (Osaka, Japan). Written consent was obtained from all patients. Three tumor biopsies and three normal gastric biopsies were collected from one patient at a time by endoscopic treatment. After collection, each sample was placed separately in a screw cap tube and immediately snap frozen in liquid nitrogen. Frozen samples were stored at ⁇ 80 ° C. until further sample preparation.
  • TMT labeling was performed to quantify phosphorylation sites in each biopsy.
  • the TMT labeling procedure corresponded to the manufacturer's protocol.
  • Labeled phosphopeptides were fractionated into 7 fractions on a C18 / SCX stage chip according to previously reported techniques (Adachi et al., Anal Chem, 2016, Improved Proteome and Phosphoproteome Analysis on a Cation Exchanger by a Combined Acid and Salt Gradient).
  • Quantitative analysis of phosphorylated proteomics was performed in order to confirm whether the cancer-specific phosphorylation signal pathway was reflected at the endoscopic biopsy cancer site.
  • As the phosphorylation site used for the quantitative analysis at least one sample out of the 10 samples analyzed by the mass spectrometer was selected with a quantitative value. Quantitative data of these 8,340 phosphorylation sites was used for the following quantitative analysis including pathway analysis and kinome profiling.
  • phosphorylation sites that showed a significant difference between cancer biopsy and normal gastric biopsy were selected.
  • 382 and 345 phosphorylation sites were selected as increased (right wing) and decreased phosphorylation sites (left wing) in cancer, respectively (FIG. 9A).
  • the Volcano plot is expressed by Log2 fold change and q value of each phosphorylation site by performing Welch t-test and substitution test.
  • these phosphorylation sites were subjected to WebGestalt pathway analysis workflow [21]. Pathway analysis was performed using two types of databases, KEGG [22] and WikiPathway [23]. All pathways in the two graphs have q values less than 0.01.
  • the cancer growth bar graph on the right shows that pathways rich in phosphorylation sites increased by cancer biopsy are abundant.
  • the cancer reduction bar graph on the left shows that the pathway is rich in phosphorylation sites that are reduced in cancer biopsies compared to normal tissues. Comparing the results obtained from the two types of analyses, we found common variations associated with the well-known “Cancer Hallmarks” [2]. Among the activated pathways in cancer, “genomic instability and mutation” were suggested in both KEGG and Wikipathway (FIG. 9B, right wing). Furthermore, it was confirmed that the activation-regulated phosphorylation site of ATR kinase was also increased in cancer specimens (FIG. 9C) [24].
  • kinome profiling was performed as reported in previous studies [15]. Initially, we found that phosphorylation sites were detected in 187 of 428 serine / threonine kinases and 30 of 90 tyrosine kinases (FIG. 10A). This data demonstrates that the phosphorylated proteome protocol in this study makes it possible to monitor the activity of many kinases in terms of the state of phosphorylation modification.
  • KSEA was performed to infer kinase activity using the kinase-substrate relationship [17]. The KSEA algorithm showed a variation in enzyme activation among 68 kinases. All kinases with significant difference from the KSEA algorithm (q value ⁇ 0.05) were plotted as a bar graph. KSEA results showed that the activity of 14 kinases was significantly altered between gastric cancer and normal regions (FIG. 10B).
  • FIG. 10B Among the kinases that are expected to increase the enzyme activity in cancer, ERBB2 [27] whose inhibitor has already been used in clinical practice was included (FIG. 10B).
  • KSEA Her2
  • ERBB synonyms Her2 intensity from biopsy immunostaining
  • FIG. 10C Changes in ERBB2 Y877, Y1248, and CDK1 Y15 (including Y15 of CDK2 and CDK3) are plotted in FIG. 10C.
  • FIG. 10C In the Her2 positive patient (No. 2) sample, among the four patients analyzed in this example, all three substrates showed the highest increase (FIG. 10C, leftmost bar). Each leftmost bar in FIG. 10C shows the fold change of patient No. 2 in which gastric cancer was Her2 positive.
  • Cetuximab-induced MET activation acts as a novel resistance mechanism in colon cancer cells.International journal of molecular sciences 15, 5838.5851, doi: 10.3390 / ijms15045838 (2014). 29. Khan, E. M. et al. Epidermal growth factor receptor exposed to oxidative stress undergoes Src- and caveolin-1-dependent perinuclear trafficking. The Journal of biological chemistry 281, 14486.14493, doi: 10.1074 / jbc.M509332200 (2006). 30. Dittmann, K., Mayer, C., Kehlbach, R.
  • MaxQuant enables high peptide identification rates, individualized ppb-range mass accuracies and proteomewide protein quantification.Nature biotechnology 26, 1367.1372, doi: 10.1038 / nbt.1511 (2008). 38. Sharma, K. et al. Ultradeep human phosphoproteome reveals a distinct regulatory nature of Tyr and Ser / Thr-based signaling.Cell reports 8, 1583.1594, doi: 10.1016 / j.celrep.2014.07.036 (2014). 39. Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote) omics data.Nature methods 13, 731.740, doi: 10.1038 / nmeth.3901 (2016). 40.
  • the method for screening a responsible kinase of the present invention can find a new therapeutic target or a drug effect prediction target that cannot be found by genome analysis, and can contribute to personalized medicine.
  • a responsible kinase of the present invention in addition to the application to patient cancer-derived experimental models, it will lead to the development of diagnostic methods for noninvasive therapeutic targets and drug efficacy prediction targets with a view to responsible kinase screening of circulating tumor cells purified from blood Expected.

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Abstract

One purpose of the present invention is to select a responsible kinase which causes not only drug-resistant cancer but also a disease for which no efficacious therapeutic drug is known. Another purpose thereof is to select a responsible kinase which causes cancer with cancer properties characteristic to an individual person from an endoscopic specimen. The present invention pertains to a method for screening a responsible kinase, which potentially serves as a target of therapy or a target of drug efficacy estimation, by conducting phosphoproteomics.

Description

治療標的である活性化キナーゼのスクリーニング方法Screening method for activated kinases that are therapeutic targets
　本発明は、標的となり得る活性化キナーゼのスクリーニング方法を基本とする、一連の発明に関する。詳細には、本発明は、リン酸化プロテオミクスによって選別される、治療標的または薬効予測標的となり得る責任キナーゼのスクリーニング方法、特に、治療標的または薬効予測標的が、有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患の原因である責任キナーゼのスクリーニング方法に関する。 The present invention relates to a series of inventions based on a screening method for an activated kinase that can be a target. Specifically, the present invention relates to a method for screening a responsible kinase that can be a therapeutic target or a drug efficacy prediction target selected by phosphorylation proteomics, in particular, a disease, malignancy, for which the therapeutic target or drug efficacy prediction target has no effective therapeutic drug. The present invention relates to a screening method for a responsible kinase that is a cause of a disease selected from among cancers with high advanced cancer and cancers having characteristic cancer characteristics.
　個別化医療は、がんの特性を標的とした最適な薬剤を選択することによって臨床効果の改善が期待され、がん治療における次世代戦略として注目されている（非特許文献２）。各患者のがん特性に応じて治療標的を同定するための分子マーカーは、精密医療を実現することの重要な要素である。最近、ゲノミクスを用いた様々なプロジェクトで、臨床がん組織からの分子プロファイリングの包括的測定が実施されている（非特許文献３）。ゲノミクスは、様々ながんにおける新規サブタイプを同定したが、サブタイプに基づく治療戦略は、各患者の腫瘍学的表現型と遺伝子型との間に存在する大きな隔たりにより未だ制限されてきた（非特許文献７）。 Personalized medicine is expected to improve clinical effects by selecting optimal drugs that target cancer characteristics, and is attracting attention as a next-generation strategy in cancer treatment (Non-patent Document 2). Molecular markers for identifying therapeutic targets according to the cancer characteristics of each patient are an important element in realizing precision medicine. Recently, comprehensive measurements of molecular profiling from clinical cancer tissues have been carried out in various projects using genomics (Non-patent Document 3). Although genomics has identified new subtypes in various cancers, subtype-based treatment strategies have still been limited by the large gap that exists between each patient's oncological phenotype and genotype ( Non-patent document 7).
　リン酸化修飾はタンパク質機能の重要な調節因子であり、発がん・悪性化の制御に深く関与している（非特許文献２）。したがって、がん生物学では、がん細胞におけるリン酸化シグナル経路の変動に焦点をあて、解析が進められてきた（非特許文献８）。 Phosphorylation modification is an important regulator of protein function and is deeply involved in the control of carcinogenesis / malignancy (Non-patent Document 2). Therefore, in cancer biology, analysis has been advanced with a focus on fluctuations in phosphorylation signal pathways in cancer cells (Non-patent Document 8).
　タンパク質キナーゼは、タンパク質へのリン酸化修飾反応を介して細胞周期および細胞運動を含む様々な細胞機能を制御する。例としてＥＧＦＲ（epidermal growth factor receptor：上皮増殖因子レセプター）シグナル伝達経路は重要なリン酸化シグナル伝達経路として数多くの先行研究が行われてきた（非特許文献１）。それゆえ、キナーゼの調節異常は発がんと密接に関連する（非特許文献２）。ヒトゲノムにコードされる５１８のキナーゼは「キノーム」として定義されており（非特許文献１）、キノーム解析によって、がん生物学における本質的な知見が得られると期待される。これまでに、ゲノム解析によって、いくつかのがんドライバーとしてキナーゼ変異ならびに抗がん剤に対する耐性機構が明らかとなっている（非特許文献３、４）。さらに、ゲノムの不安定性に起因するＥＭＬ４－ＡＬＫなどのキメラキナーゼは細胞リン酸化状態を再構築し、がんに特徴的なサブタイプを発達させる（非特許文献５）。 Protein kinases control various cell functions including cell cycle and cell movement through phosphorylation modification reaction to proteins. As an example, EGFR (epidermal growth factor receptor) signaling pathway has been studied as an important phosphorylation signaling pathway (Non-patent Document 1). Therefore, dysregulation of kinase is closely related to carcinogenesis (Non-patent Document 2). 518 kinases encoded in the human genome are defined as “kinome” (Non-patent Document 1), and it is expected that essential knowledge in cancer biology will be obtained by kinome analysis. So far, genome analysis has revealed kinase mutations and resistance mechanisms against anticancer agents as some cancer drivers (Non-Patent Documents 3 and 4). Furthermore, chimeric kinases such as EML4-ALK resulting from genomic instability reconstruct the cellular phosphorylation state and develop subtypes characteristic of cancer (Non-Patent Document 5).
　ゲノム解析は、多くのキナーゼを含むドライバー遺伝子の同定などがん生物学における多大な貢献を果たしてきたが、ゲノム解析のみでは抗がん剤の耐性機構を完全に説明することはできない。例えば、バイパス経路によるリン酸化シグナルの異常やＥＧＦＲの核局在化などの細胞内局在変化が、薬剤耐性の原因として報告されている（非特許文献６、７）。また、抗がん剤として使用されている分子標的治療薬のひとつであるセツキシマブ(Cetuximab)など、大腸がんの薬剤感受性に関する先行研究においてゲノム解析が広く適用され、セツキシマブのマーカーを含む多くのマーカーが明らかにされている。例えば、ＫＲＡＳ変異（Ｇ１３Ｄなど）、ＢＲＡＦ変異（Ｖ６００Ｅ）はセツキシマブに対する感受性を変化させることが報告されている（非特許文献８）。しかしながら、本発明において「感受性群」と位置付けられたＤＬＤ１（図１ｂ）はＫＲＡＳの耐性に関連する変異（Ｇ１３Ｄ）を含むことが分かり、このことは、ゲノムレベルの特徴ではセツキシマブに対する感受性を完全には予測できないことを示している。
　したがって、プロテオミクスの手法はゲノムの手法とともに、キノームの状態を特徴付けるために重要である。 Genome analysis has contributed greatly in cancer biology, including identification of driver genes including many kinases, but genome analysis alone cannot fully explain the resistance mechanisms of anticancer drugs. For example, changes in intracellular localization such as abnormal phosphorylation signals by the bypass pathway and nuclear localization of EGFR have been reported as causes of drug resistance (Non-Patent Documents 6 and 7). In addition, genome analysis has been widely applied in previous studies on drug susceptibility of colorectal cancer, such as cetuximab, one of the molecular targeted therapeutics used as an anticancer drug, and many markers including cetuximab marker Has been revealed. For example, KRAS mutation (G13D etc.) and BRAF mutation (V600E) have been reported to change the sensitivity to cetuximab (Non-patent Document 8). However, DLD1 (FIG. 1b), which is positioned as a “susceptibility group” in the present invention, was found to contain a mutation associated with resistance to KRAS (G13D), which fully characterizes susceptibility to cetuximab at the genomic level. Indicates that it cannot be predicted.
Therefore, proteomics techniques, as well as genomic techniques, are important for characterizing the state of kinomes.
　プロテオミクス、すなわちプロテオーム解析では、薬剤の直接的な標的であるタンパク質の定量・翻訳後修飾データの高感度測定を対象としている。例えば細胞内タンパク質の大規模リン酸化修飾データは、発がんにおいて重要なリン酸化シグナル伝達経路の状態や、リン酸化シグナル制御因子であるキナーゼの活性化状態を示す指標となる。したがって、薬剤感受性データとがんプロテオームデータの統合は、キナーゼを標的とする分子標的薬の感受性予測において多くの有効な情報をもたらすと言える。 Proteomics, that is, proteomic analysis, is intended for highly sensitive measurement of protein quantification and post-translational modification data that are direct targets of drugs. For example, large-scale phosphorylation modification data of intracellular proteins is an index indicating the state of a phosphorylation signal transduction pathway important for carcinogenesis and the activation state of a kinase that is a phosphorylation signal regulator. Therefore, it can be said that the integration of drug sensitivity data and cancer proteome data provides a lot of useful information in predicting the sensitivity of molecular target drugs targeting kinases.
　プロテオミクスの方法、特に固定化金属アフィニティクロマトグラフィー（ＩＭＡＣ）（非特許文献９）、酸化金属アフィニティクロマトグラフィー（非特許文献１０）、およびヒドロキシ酸修飾酸化金属アフィニティクロマトグラフィー（非特許文献１１）を用いるリン酸化プロテオミクスは、キノームで制御される高感度なリン酸化状態を解析するために広く適用されている。タンパク質におけるセリン、スレオニンおよびチロシン残基のリン酸化、とくにリン酸化チロシン（ｐＹ）残基は、腫瘍発生に重要な役割を担うことが報告されている（非特許文献１２）。それゆえ、リン酸化チロシンシグナル伝達を標的とする抗がん剤を開発するために多くの試みがなされており、実用化もされている。例えば、セツキシマブ（商品名：アービタックス）や、ＥＧＦＲのチロシンキナーゼの働きを阻害する作用を持つ、非小細胞肺がん（ＮＳＣＬＣ）に対する分子標的治療薬、ゲフィチニブ（商品名：イレッサ）がある。 Proteomics methods are used, in particular immobilized metal affinity chromatography (IMAC) (Non-patent document 9), metal oxide affinity chromatography (Non-patent document 10), and hydroxy acid-modified metal oxide affinity chromatography (Non-patent document 11). Phosphorylated proteomics has been widely applied to analyze highly sensitive phosphorylation states controlled by kinomes. It has been reported that phosphorylation of serine, threonine and tyrosine residues in proteins, particularly phosphorylated tyrosine (pY) residues, play an important role in tumor development (Non-patent Document 12). Therefore, many attempts have been made to develop anticancer agents that target phosphorylated tyrosine signaling, and they have been put into practical use. For example, there are cetuximab (trade name: Irbitax) and gefitinib (trade name: Iressa), a molecular target therapeutic agent for non-small cell lung cancer (NSCLC), which has an action of inhibiting the action of EGFR tyrosine kinase.
　しかしながら、リン酸化セリンおよびリン酸化スレオニン部位と比べて、リン酸化チロシン部位の存在量が非常に少ないために、同定された全てのリン酸化ペプチド内に占めるリン酸化チロシンペプチドの割合は非常に小さい（1％未満）。そのため、既存のリン酸化ペプチド濃縮法によるチロシンリン酸化プロテオミクスは網羅性に限界が存在していた（非特許文献１３）。 However, since the abundance of phosphorylated tyrosine sites is very small compared to phosphorylated serine and phosphorylated threonine sites, the proportion of phosphorylated tyrosine peptides in all identified phosphorylated peptides is very small ( Less than 1%). Therefore, the existing tyrosine phosphorylated proteomics by the phosphopeptide enrichment method has a limit in completeness (Non-patent Document 13).
　液体クロマトグラフィー－タンデム型質量分析法（ＬＣ－ＭＳ／ＭＳ）を組み合わせた定量的なプロテオミクスは、セツキシマブ耐性大腸がんの分析に用いられている（非特許文献１４、１５）。しかしながら、タンパク質発現の情報は、有望な薬剤標的としてのキナーゼのリン酸化修飾活性と必ずしも一致しない。そのためキノーム活性プロファイリングを目的として、逆相タンパク質アレイ（ＲＰＰＡ）を適用し、薬剤感受性に関係するリン酸化シグナル伝達経路の活性化状態が明らかにされている（非特許文献１６）。しかしＲＰＰＡは確立したシグナル伝達経路の測定には使用できるが、抗体の制限のため、未知の経路を含む高感度なリン酸化の状態を得ることは難しい。 Quantitative proteomics combined with liquid chromatography-tandem mass spectrometry (LC-MS / MS) has been used for analysis of cetuximab-resistant colorectal cancer (Non-patent Documents 14 and 15). However, protein expression information is not necessarily consistent with the phosphorylation modifying activity of kinases as promising drug targets. Therefore, reverse phase protein array (RPPA) is applied for the purpose of kinome activity profiling, and the activation state of phosphorylation signal transduction pathway related to drug sensitivity has been clarified (Non-patent Document 16). However, although RPPA can be used to measure established signal transduction pathways, it is difficult to obtain a highly sensitive phosphorylation state including unknown pathways due to antibody limitations.
　リン酸化プロテオミクスの手法を用いるキノームの網羅的な解析は、治療標的または薬効予測標的となり得る責任キナーゼの選別等、特に抗がん剤に対する効果予測・薬剤耐性機構についての情報を提供でき、薬剤耐性がんの克服に貢献できると考えられる。 Comprehensive analysis of kinomes using phosphorylated proteomics can provide information on anti-cancer drug effects prediction and drug resistance mechanisms, including selection of responsible kinases that can be therapeutic targets or drug efficacy prediction targets. It is thought that it can contribute to overcoming cancer.
　特に臨床検体からのリン酸化プロテオミクスの重要性が認められてきているにもかかわらず、臨床検体に対するリン酸化プロテオミクスの応用は、１ｍｇ以上という大量のタンパク質を必要とするために依然として限定されている。大量の検体が採取可能な手術検体の大規模リン酸化プロテオミクス解析は実施されてきたが、外科処置中の虚血によって引き起こされる細胞内リン酸化状態の人工的変化はリン酸化プロテオームデータの直接的な解釈を妨げている。外科組織とは対照的に、内視鏡で採取した生検標本は、１分未満の短い時間での凍結、および治療過程のリン酸化プロテオームデータの時系列変化をモニターするためには、非常に適したサンプルである。 Despite the recognition of the importance of phosphorylated proteomics from clinical specimens in particular, the application of phosphorylated proteomics to clinical specimens is still limited because it requires a large amount of protein of 1 mg or more. Although large-scale phosphorylation proteomic analysis of surgical specimens capable of collecting a large number of specimens has been performed, artificial alterations in intracellular phosphorylation status caused by ischemia during surgery are a direct indication of phosphorylated proteome data. Interpretation is hindered. In contrast to surgical tissue, biopsy specimens taken endoscopically are very useful for monitoring time-lapse changes in phosphoproteome data during freezing and treatment in less than a minute. A suitable sample.
　そこで、本発明者らは、具体的には、チロシンリン酸化プロテオミクスと既存のリン酸化プロテオミクスを併用してキノーム活性のプロファイルを作成し、未知のキナーゼ標的を同定することを目指した。また、内視鏡で採取した生検標本（内視鏡検体）について既存のリン酸化プロテオミクスを行うことにより、キノーム活性プロファイルを作成し、正常部位に比べ活性化しているリン酸化シグナルの同定を目指した。 Therefore, the present inventors specifically aimed to identify an unknown kinase target by creating a profile of kinome activity using a combination of tyrosine phosphorylated proteomics and existing phosphorylated proteomics. In addition, by performing existing phosphorylation proteomics on biopsy specimens (endoscopic specimens) collected with an endoscope, a kinome activity profile is created, aiming to identify phosphorylation signals that are activated compared to normal sites. It was.
　本発明者らはまず、セツキシマブ感受性および耐性大腸がん細胞株の高感度リン酸化プロテオミクス解析を行い、セツキシマブ耐性がんにおける新規薬剤標的を探索した。既存のリン酸化プロテオミクス（リン酸化セリン、リン酸化スレオニンおよびリン酸化チロシン（ｐＳＴＹ）ペプチドのIMAC濃縮）および、リン酸化チロシンペプチドの免疫沈降法によるチロシンリン酸化プロテオミクスを併用し、高感度リン酸化プロテオミクスデータを得た。取得したデータから、キナーゼ上の活性制御リン酸化情報およびキナーゼ－基質関係(Kinase-Substrate Relationships)（ＫＳＲ）に基づくキナーゼ－基質エンリッチメント解析（ＫＳＥＡ）情報を用いることで活性なキナーゼ候補、責任キナーゼの候補を選別し、耐性細胞株において活性化しているリン酸化ネットワークを再構築した。また、耐性細胞株の細胞増殖に対するキナーゼ候補のｓｉＲＮＡまたは特異的な阻害剤の効果を検証した。これらにより、薬剤耐性がん活性化キナーゼスクリーニングにおける、高感度リン酸化チロシン修飾情報を組み合わせた高感度リン酸化プロテオミクスデータを基盤とする、我々の戦略の優位性が示された。 The present inventors first conducted high-sensitivity phosphorylated proteomic analysis of cetuximab-sensitive and resistant colon cancer cell lines to search for novel drug targets in cetuximab-resistant cancer. Highly sensitive phosphorylated proteomics data using existing phosphorylated proteomics (IMAC enrichment of phosphorylated serine, phosphorylated threonine and phosphorylated tyrosine (pSTY) peptide) and tyrosine phosphorylated proteomics by immunoprecipitation of phosphorylated tyrosine peptide Got. From the acquired data, active kinase candidates and responsible kinases can be obtained by using activity-regulated phosphorylation information on kinases and kinase-substrate enrichment analysis (KSEA) information based on Kinase-Substrate Relationships (KSR) Were selected and the phosphorylated network activated in resistant cell lines was reconstructed. In addition, the effects of siRNA or specific inhibitors of candidate kinases on cell proliferation of resistant cell lines were verified. These demonstrated the superiority of our strategy based on sensitive phosphoproteomic data combined with sensitive phosphotyrosine modification information in drug-resistant cancer-activated kinase screening.
　次に、胃がん患者から採取したがん部位および正常部位における内視鏡検体に対してリン酸化プロテオミクス解析を行い、がん部位特異的な活性化リン酸化シグナルの探索を試みた。これにより、リン酸化プロテオミクス解析結果から、がん部位で活性化している既知のリン酸化シグナル経路ならびにシグナル上のキナーゼが選別された。 Next, phosphorylated proteomics analysis was performed on endoscopic specimens in cancer sites and normal sites collected from stomach cancer patients, and an attempt was made to search for cancer site-specific activated phosphorylation signals. As a result, known phosphorylated signal pathways activated at the cancer site and kinases on the signal were selected from the phosphorylated proteomic analysis results.
　すなわち、本発明は、以下の態様を含む。
＜責任キナーゼをスクリーニングする方法＞
［１］
　リン酸化プロテオミクスから得られたデータに基づき、リン酸化修飾活性が有意に増加しているリン酸化部位を特定し、タンパク質機能情報データベース上におけるキナーゼ活性制御リン酸化部位の実測値、および／またはキナーゼ基質関連情報を使用する計算科学的手法によって得られるキナーゼ活性予測値によって、リン酸化修飾活性が有意に増加しているキナーゼを選別する、治療標的または薬効予測標的となり得る責任キナーゼをスクリーニングする方法；
［２］
　対照を含む対照試料および標的を含む標的試料、または標的を含む標的試料に対し、リン酸化プロテオミクスを行う、［１］記載の方法；
［３］
　標的試料が生検である、［２］記載の方法；
［４］
　標的試料が内視鏡検体である、［３］記載の方法； That is, the present invention includes the following aspects.
<Method of screening for responsible kinase>
[1]
Based on the data obtained from phosphorylation proteomics, the phosphorylation site where phosphorylation modification activity is significantly increased is identified, the actual value of the kinase activity control phosphorylation site in the protein function information database, and / or the kinase substrate A method for screening a responsible kinase that can be a therapeutic target or a drug efficacy prediction target, by selecting a kinase having a significantly increased phosphorylation-modifying activity based on a predicted kinase activity obtained by a computational scientific method using related information;
[2]
The method according to [1], wherein phosphorylation proteomics is performed on a control sample including a control and a target sample including a target, or a target sample including a target;
[3]
The method according to [2], wherein the target sample is a biopsy;
[4]
The method according to [3], wherein the target sample is an endoscopic specimen;
［５］
　１）対照試料として対照細胞および標的試料として治療対象細胞の細胞溶解物から濃縮したリン酸化セリン、リン酸化スレオニンおよび／またはリン酸化チロシンペプチドについてリン酸化プロテオミクスデータを取得し、
　２）得られたデータに基づき、統計学的手法により、対照細胞と比較して治療対象細胞において有意に増加しているリン酸化部位を特定し、
　３）タンパク質機能情報データベース上におけるキナーゼ活性制御リン酸化部位の実測値、および／またはキナーゼ基質関連情報を使用する計算科学的手法によって得られるキナーゼ活性予測値によって、対照細胞と比較して治療対象細胞において有意にリン酸化修飾活性が増加しているキナーゼを選別し、それを責任キナーゼとする、［２］から［４］いずれか記載の方法；
［６］
　１）内視鏡検体の細胞溶解物から濃縮したリン酸化セリン、リン酸化スレオニンおよび／またはリン酸化チロシンペプチドについてリン酸化プロテオミクスデータを取得し、
　２）得られたデータに基づき、統計学的手法により、癌患者母集団平均と比較して有意に増加しているリン酸化部位を特定し
　３）タンパク質機能情報データベース上におけるキナーゼ活性制御リン酸化部位の実測値、および／またはキナーゼ基質関連情報を使用する計算科学的手法によって得られるキナーゼ活性予測値によって、内視鏡検体において有意にリン酸化活性が増加しているキナーゼを選別し、それを責任キナーゼとする、請求項１記載の方法。 [5]
1) Obtain phosphorylated proteomics data for phosphorylated serine, phosphorylated threonine and / or phosphorylated tyrosine peptide concentrated from cell lysates of control cells as control samples and treated cells as target samples;
2) Based on the obtained data, a statistical method is used to identify phosphorylation sites that are significantly increased in the cells to be treated compared to the control cells,
3) Treatment target cells compared to control cells based on actual values of kinase activity-regulated phosphorylation sites on the protein function information database and / or kinase activity prediction values obtained by computational scientific methods using kinase substrate related information The method according to any one of [2] to [4], wherein a kinase having a significantly increased phosphorylation-modifying activity is selected as a responsible kinase;
[6]
1) Obtain phosphorylated proteomics data for phosphorylated serine, phosphorylated threonine and / or phosphorylated tyrosine peptide concentrated from cell lysates of endoscopic specimens,
2) Based on the obtained data, statistical methods were used to identify phosphorylation sites that were significantly increased compared to the average cancer patient population. 3) Kinase activity-regulated phosphorylation sites on the protein function information database Of kinases with significantly increased phosphorylation activity in endoscopic specimens and responsible for them based on the actual measured values of and / or predicted kinase activity obtained by computational scientific methods using kinase substrate related information The method according to claim 1, wherein the method is a kinase.
［７］
　工程２）における統計学的手法が、２群で有意な変動を示すリン酸化部位、または多群の中で有意さを示すリン酸化部位を抽出するための手法である、［５］または［６］記載の方法；
［８］
　工程１）におけるリン酸化チロシンの濃縮を、金属アフィニティクロマトグラフィーを用いるリン酸化ペプチド濃縮、次いで抗リン酸化チロシン抗体を用いた免疫沈降法によって行う、［５］から［７］のいずれか記載の方法；
［９］
　金属アフィニティクロマトグラフィーを用いたリン酸化セリン、リン酸化スレオニン、およびリン酸化チロシンを包括的に解析し、高感度リン酸化プロテオミクスデータを取得する、［５］から［８］のいずれか記載の方法； [7]
The statistical method in step 2) is a method for extracting phosphorylation sites showing significant variation in group 2 or phosphorylation sites showing significance in multiple groups, [5] or [6 ] The method according to
[8]
The method according to any one of [5] to [7], wherein the concentration of phosphorylated tyrosine in step 1) is performed by concentration of phosphorylated peptide using metal affinity chromatography and then immunoprecipitation using an anti-phosphotyrosine antibody. ;
[9]
The method according to any one of [5] to [8], wherein phosphorylated serine, phosphorylated threonine, and phosphorylated tyrosine using metal affinity chromatography are comprehensively analyzed to obtain highly sensitive phosphorylated proteomics data;
［１０］
　治療標的が、有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患の原因である責任キナーゼであり、そして対照試料が正常細胞、標的試料が当該疾患細胞である、［１］から［９］のいずれか記載の方法；
［１１］
　有効な治療薬がない疾患が薬剤耐性疾患または、責任キナーゼが関与する難治性疾患である、［１０］記載の方法；
［１２］
　薬剤耐性疾患が、有効な分子標的治療薬はあるが、その治療薬に耐性になった患者における疾患である、［１１］記載の方法；
［１３］
　分子標的治療薬がキナーゼ阻害剤である、［１２］記載の方法。 [10]
The therapeutic target is a responsible kinase responsible for the disease selected from among diseases for which there is no effective therapeutic agent, advanced malignant cancer, and cancer with characteristic cancer characteristics, and controls The method according to any one of [1] to [9], wherein the sample is a normal cell and the target sample is the disease cell;
[11]
The method according to [10], wherein the disease for which there is no effective therapeutic agent is a drug resistant disease or an intractable disease involving responsible kinase;
[12]
The method according to [11], wherein the drug resistant disease is a disease in a patient who has an effective molecular targeted therapeutic agent but has become resistant to the therapeutic agent;
[13]
[12] The method according to [12], wherein the molecular targeted therapeutic agent is a kinase inhibitor.
［１４］
　薬効予測標的が、有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患に罹患している被験者において、当該疾患を処置または予防する治療薬の有効性を予測するために使用される責任キナーゼであり、そして対照試料が当該治療薬に感受性の細胞または不存在、標的試料が、被験者由来の組織、血中循環細胞および細胞外小胞の中から選ばれる、［１］から［９］のいずれか記載の方法；
［１５］
　有効な治療薬がない疾患が薬剤耐性疾患または、責任キナーゼが関与する難治性疾患である、［１４］記載の方法；
［１６］
　薬剤耐性疾患が、有効な分子標的治療薬はあるが、その治療薬に耐性になった患者における疾患である、［１５］記載の方法；
［１７］
　分子標的治療薬がキナーゼ阻害剤である、［１６］記載の方法；
［１８］
　対照試料が治療薬に感受性の細胞の場合、感受性細胞および標的試料に対し、リン酸化プロテオミクスを行い、感受性細胞と比較し標的試料において有意にリン酸化修飾活性が増加しているキナーゼを選別し、それを責任キナーゼとする、［１４］から［１７］いずれか記載の方法；
［１９］
　対照試料が不存在の場合、標的試料に対し、リン酸化プロテオミクスを行い、キナーゼ活性レベルのPan-cancer Analysisによって、がん母集団のキナーゼ活性平均値を対照とし、リン酸化修飾活性値の有意な増加を示すキナーゼを選別し、それを責任キナーゼとする、［１４］から［１７］いずれか記載の方法；
［２０］
　当該被験者において、当該疾患を処置または予防する治療薬の有効性を予測するために使用される責任キナーゼが不存在の場合、当該被験者は当該治療薬が有効であると判定する、［１４］から［１９］いずれか記載の方法； [14]
In a subject whose drug efficacy prediction target is a disease selected from among diseases for which there is no effective therapeutic drug, advanced malignant cancer, and cancer having characteristic cancer characteristics, Is a responsible kinase used to predict the effectiveness of a therapeutic agent to treat or prevent, and the control sample is cells or absence sensitive to the therapeutic agent, the target sample is tissue from the subject, blood circulation The method according to any one of [1] to [9], which is selected from cells and extracellular vesicles;
[15]
The method according to [14], wherein the disease for which there is no effective therapeutic agent is a drug resistant disease or an intractable disease involving responsible kinase;
[16]
The method according to [15], wherein the drug resistant disease is a disease in a patient who has an effective molecular targeted therapeutic agent but has become resistant to the therapeutic agent;
[17]
The method according to [16], wherein the molecular targeted therapeutic agent is a kinase inhibitor;
[18]
When the control sample is a cell sensitive to a therapeutic agent, phosphorylation proteomics is performed on the sensitive cell and the target sample, and a kinase whose phosphorylation modifying activity is significantly increased in the target sample as compared with the sensitive cell is selected. The method according to any one of [14] to [17], wherein it is a responsible kinase;
[19]
In the absence of a control sample, phosphorylation proteomics is performed on the target sample, and the average kinase activity of the cancer population is used as a control by pan-cancer analysis of the kinase activity level. The method according to any one of [14] to [17], wherein a kinase exhibiting an increase is selected and used as a responsible kinase;
[20]
If the subject does not have a responsible kinase used to predict the effectiveness of a therapeutic agent to treat or prevent the disease, the subject determines that the therapeutic agent is effective; [14] [19] The method according to any one of the above;
＜治療標的であるキナーゼの活性を阻害する物質をスクリーニングする方法＞
［２１］
　［１］から［２０］記載の方法によってスクリーニングされた責任キナーゼのリン酸化修飾活性を阻害する物質をスクリーニングするための方法であって、
　１）責任キナーゼを有する標的試料の培地中に責任キナーゼのリン酸化修飾活性を阻害し得る候補物質を添加し、
　２）責任キナーゼを有する標的試料における候補物質処理群と未処理群との細胞増殖活性における比較を行い、
　３）候補物質処理群の細胞増殖活性が未処理群よりも低ければ、その候補物質を責任キナーゼのリン酸化修飾活性を阻害する物質であると評価する、方法；
［２２］
　責任キナーゼのリン酸化修飾活性を阻害する物質が分子標的薬である、［２１］記載の方法；
［２３］
　大腸がん細胞におけるABL1、CDK12、HCK、JAK2、LCK、LYN、MAP2K6、MAPK12、MAPK14、PRKCD、YES1、およびDYRK4の中から選ばれる少なくとも１つの責任キナーゼのリン酸化修飾活性を阻害する物質をスクリーニングするための方法である、［２２］記載の方法。
［２４］
　胃がん細胞におけるCDK1、ERBB2、PRKACA、MAPK13、CKD2、CHEK2、MAPKAPK2、ATR、CAMK2A、PRKAA1、MAP2K1、GSK3B、RET、およびMTORの中から選ばれる少なくとも１つの責任キナーゼのリン酸化修飾活性を阻害する物質をスクリーニングするための方法である、［２２］記載の方法。
＜被験者の層別化など＞
［２５］
　有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患に罹患している被験者において、当該疾患を処置または予防する治療薬が有効か、有効でないかを判定することによって、被験者を層別化する方法であって、
　１）［１３］から［１９］いずれか記載の方法によって薬効予測標的である責任キナーゼをスクリーニングし、
　２）当該被験者において、当該疾患を処置または予防する治療薬の有効性を予測するために使用される責任キナーゼが不存在の場合、当該被験者は当該治療薬が有効である群に割り付け、責任キナーゼが存在する場合、当該被験者は当該治療薬が有効でない群に割り付け、被験者を層別化する方法。 <Method of screening for a substance that inhibits the activity of kinase as a therapeutic target>
[21]
A method for screening a substance that inhibits the phosphorylation-modifying activity of a responsible kinase screened by the method according to [1] to [20],
1) A candidate substance capable of inhibiting the phosphorylation-modifying activity of the responsible kinase is added to the medium of the target sample having the responsible kinase,
2) Compare the cell proliferation activity of the candidate substance-treated group and the untreated group in the target sample having the responsible kinase,
3) A method for evaluating a candidate substance as a substance that inhibits the phosphorylation-modifying activity of a responsible kinase if the cell growth activity of the candidate substance-treated group is lower than that of the untreated group;
[22]
The method according to [21], wherein the substance that inhibits the phosphorylation-modifying activity of the responsible kinase is a molecular target drug;
[23]
Screening for substances that inhibit the phosphorylation-modifying activity of at least one responsible kinase selected from ABL1, CDK12, HCK, JAK2, LCK, LYN, MAP2K6, MAPK12, MAPK14, PRKCD, YES1, and DYRK4 in colorectal cancer cells The method according to [22], which is a method for
[24]
Substance that inhibits the phosphorylation-modifying activity of at least one responsible kinase selected from CDK1, ERBB2, PRKACA, MAPK13, CKD2, CHEK2, MAPKAPK2, ATR, CAMK2A, PRKAA1, MAP2K1, GSK3B, RET, and MTOR in gastric cancer cells The method according to [22], which is a method for screening
<Subject stratification, etc.>
[25]
Treat or prevent the disease in a subject who has a disease selected from among diseases for which there is no effective therapeutic agent, advanced cancer with high malignancy, and cancer with characteristic cancer characteristics. A method of stratifying subjects by determining whether a therapeutic is effective or not,
1) Screening a responsible kinase which is a drug efficacy prediction target by the method according to any one of [13] to [19],
2) If the responsible kinase used to predict the effectiveness of a therapeutic agent to treat or prevent the disease in the subject is absent, the subject is assigned to the group for which the therapeutic agent is effective, and the responsible kinase If the subject is present, the subject is assigned to a group where the therapeutic agent is not effective, and the subject is stratified.
　細胞内リン酸化の異常は発がんと密接に関連する。したがって、キナーゼ阻害剤、特にチロシンキナーゼ阻害剤（ＴＫＩ）の、抗がん剤として研究・開発が特に進められてきた。ＴＫＩ感受性に対する研究では従来、ゲノム解析が用いられてきたが、ＴＫＩ耐性のなかにはゲノムデータで予測不可能なものがある。それゆえ、本発明の高感度なリン酸化プロテオミクス解析、特にチロシンリン酸化（ｐＹ）プロテオミクス解析は、ＴＫＩ感受性の予測および耐性克服に貢献できる。本発明の高感度リン酸化プロテオミクス解析法は、未知のリン酸化チロシンシグナル伝達ネットワークを明らかにし、リン酸化チロシンシグナル伝達の解析における困難を克服した。さらに、ＩＭＡＣに基づくリン酸化プロテオミクスと高感度チロシンリン酸化プロテオミクスの組み合わせは、ゲノムデータを用いては同定できない新薬につながる新規な標的の解明に貢献し得る。加えて、本発明の高感度リン酸化プロテオミクス解析法は、薬剤耐性がんのみならず、有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患の原因である責任キナーゼに応用することができる。 An abnormality in intracellular phosphorylation is closely related to carcinogenesis. Therefore, research and development of kinase inhibitors, particularly tyrosine kinase inhibitors (TKIs), have been particularly advanced as anticancer agents. Conventionally, genome analysis has been used in studies on TKI sensitivity, but some TKI resistance cannot be predicted from genomic data. Therefore, the highly sensitive phosphorylated proteomic analysis of the present invention, in particular, tyrosine phosphorylation (pY) proteomic analysis, can contribute to predicting TKI sensitivity and overcoming resistance. The highly sensitive phosphorylated proteomic analysis method of the present invention revealed an unknown phosphorylated tyrosine signaling network and overcame difficulties in analyzing phosphorylated tyrosine signaling. Furthermore, the combination of IMAC-based phosphorylation proteomics and sensitive tyrosine phosphorylation proteomics can contribute to the elucidation of new targets that lead to new drugs that cannot be identified using genomic data. In addition, the high-sensitivity phosphorylated proteomic analysis method of the present invention has not only drug-resistant cancer but also diseases with no effective therapeutic drug, advanced cancer with high malignancy, and cancer characteristics characteristic of individuals. It can be applied to responsible kinase, which is the cause of diseases selected from cancer.
　さらに、内視鏡生検を用いて個々のがん患者の包括的リン酸化状態を経時的に測定できれば、本発明のスクリーニング方法によって、リン酸化プロテオミクスデータからがんにおける責任キナーゼをリアルタイムに予測することができる。したがって、個々の患者にとって最も適切な治療戦略の決定、例えば最も適切なキナーゼ阻害剤の選択を可能にすることが期待される。ここに、リアルタイムな予測とは、抗がん剤治療期間のある時点におけるキナーゼ活性状態の予測を意味する。 Furthermore, if comprehensive phosphorylation status of individual cancer patients can be measured over time using endoscopic biopsy, the responsible kinase in cancer can be predicted in real time from the phosphorylated proteomics data using the screening method of the present invention. be able to. It is therefore expected to allow the determination of the most appropriate treatment strategy for an individual patient, for example the selection of the most appropriate kinase inhibitor. Here, real-time prediction means prediction of the kinase activity state at a certain point in the anticancer drug treatment period.
　さらに、本研究で使用した培養細胞ゲノム中に存在する変異をCOSMICデータベースで調査した結果、リン酸化プロテオミクスで同定された１５の活性化キナーゼの内１３のキナーゼは、ゲノム変異が存在しなかった（表１）。この事実は、本発明のリン酸化プロテオミクスを基盤とするキノーム活性プロファイリングが、ゲノムの手法によって特定できない新規のキナーゼ阻害剤コンパニオンマーカー(companion marker)の発見に有用であることを示している。 Furthermore, as a result of investigating mutations in the cultured cell genome used in this study in the COSMIC database, 13 of the 15 activated kinases identified by phosphorylated proteomics did not have genomic mutations ( Table 1). This fact indicates that the kinome activity profiling based on the phosphorylated proteomics of the present invention is useful for the discovery of novel kinase inhibitor companion markers that cannot be identified by genomic techniques.
　本発明は精密医療に資することができ、効果が高く副作用が少ない薬物、特にがん治療で利用される分子標的薬を提供できる。そして、効果の見込めない治療を避けることで、患者自身だけでなく、医療従事者、規制当局・保健当局にも経済的なメリットをもたらし、これは、国民の医療費負担という観点からも有益である。 The present invention can contribute to precision medicine, and can provide a drug that is highly effective and has few side effects, particularly a molecular target drug used in cancer treatment. By avoiding treatments that are not expected to be effective, it brings economic benefits not only to patients themselves, but also to healthcare professionals, regulatory authorities, and health authorities, which is also beneficial from the perspective of public health care costs. is there.
セツキシマブ感受性または耐性の大腸がん細胞株のリン酸化プロテオミクスを表す。図１ａは、二つのセツキシマブ感受性細胞株と二つのセツキシマブ耐性細胞株とを比較する定量的なプロテオミクス解析のワークフローを示す。図１ｂは、セツキシマブ処理された細胞株の細胞生存率を細胞増殖アッセイによって得たグラフである。エラーバーはＳＤを示す；Ｎ＝３。図１ｃは、セツキシマブ処理または未処理の大腸細胞株間のＥＧＦＲシグナル伝達経路におけるキナーゼの活性化状態を比較したウエスタンブロッティングの結果を示す。リン酸化したＥＲＫ１／２およびＭＥＫ１／２のレベル、およびタンパク質発現量をそれぞれ解析した。ＧＡＰＤＨを内部標準として用いた。図１ｄは、リン酸化プロテオミクスおよびチロシンリン酸化プロテオミクスによるリン酸化部位の同定結果を示すベン図である。各プロテオミクス解析は三回行った。図１ｅは、リン酸化プロテオミクスおよびチロシンリン酸化プロテオミクスによるクラス１リン酸化チロシン部位の同定結果を示すベン図である。ｐＳＴＹリン酸化プロテオミクスから同定されたリン酸化チロシン部位は小円、およびチロシンリン酸化プロテオミクスから同定されたリン酸化チロシン部位は大円で示す。ベン図内にプロットされたリン酸化チロシン部位は各三回の全ての実験で同定された。Represents phosphorylated proteomics of cetuximab sensitive or resistant colorectal cancer cell lines. FIG. 1a shows a quantitative proteomic analysis workflow comparing two cetuximab sensitive and two cetuximab resistant cell lines. FIG. 1b is a graph showing cell viability of cell lines treated with cetuximab by cell proliferation assay. Error bars indicate SD; N = 3. FIG. 1c shows the results of Western blotting comparing the activation states of kinases in the EGFR signaling pathway between cetuximab-treated or untreated colon cell lines. The levels of phosphorylated ERK1 / 2 and MEK1 / 2 and the protein expression level were analyzed, respectively. GAPDH was used as an internal standard. FIG. 1d is a Venn diagram showing the results of identification of phosphorylation sites by phosphorylation proteomics and tyrosine phosphorylation proteomics. Each proteomic analysis was performed three times. FIG. 1e is a Venn diagram showing the results of identification of class 1 phosphorylated tyrosine sites by phosphorylated proteomics and tyrosine phosphorylated proteomics. Phosphorylated tyrosine sites identified from pSTY phosphorylated proteomics are shown as small circles, and phosphorylated tyrosine sites identified from tyrosine phosphorylated proteomics are shown as large circles. Phosphotyrosine sites plotted in the Venn diagram were identified in all three experiments.
ｐＳＴＹプロテオミクスデータおよびチロシンリン酸化プロテオミクスデータを用いることによる、セツキシマブ処理または未処理のＨＣＴ１１６（ａ）およびＨＴ２９（ｂ）細胞株における、リン酸化プロテオミクスデータのボルケーノプロット（Volcano plot）を示す。Figure 5 shows a volcano plot of phosphorylated proteomics data in cetuximab treated or untreated HCT116 (a) and HT29 (b) cell lines by using pSTY proteomics data and tyrosine phosphorylated proteomics data.
リン酸化プロテオミクスデータからの、有望な薬剤標的としての活性なキナーゼ候補の同定を示す。図３ａは、キナーゼネットワークの再構築のための手順を示す。図３ｂは、キナーゼ上の活性制御リン酸化情報、およびキナーゼ－基質関係（ＫＳＲ）に基づくキナーゼ基質エンリッチメント解析（ＫＳＥＡ）情報に基づく二つの異なる手法から得た、セツキシマブ処理または未処理のＨＣＴ１１６細胞およびＨＴ２９細胞における活性なキナーゼ候補の数を示す棒グラフである。図３ｃは、ｐＳＴＹプロテオミクスデータおよびチロシンリン酸化プロテオミクスデータからそれぞれ得られた活性化キナーゼ候補の数を示す棒グラフである。図３ｄは、ＨＣＴ１１６およびＨＴ２９細胞におけるＳＲＣのキナーゼ活性の状態を示すウエスタンブロッティング解析の結果である。ＧＡＰＤＨを内部標準として用いた。Figure 3 shows identification of active kinase candidates as potential drug targets from phosphorylated proteomics data. FIG. 3a shows the procedure for the reconstruction of the kinase network. FIG. 3b shows cetuximab-treated or untreated HCT116 cells obtained from two different approaches based on activity-regulated phosphorylation information on the kinase and kinase substrate enrichment analysis (KSEA) information based on the kinase-substrate relationship (KSR) And is a bar graph showing the number of active kinase candidates in HT29 cells. FIG. 3c is a bar graph showing the number of activated kinase candidates obtained from pSTY proteomics data and tyrosine phosphorylated proteomics data, respectively. FIG. 3d is the result of Western blotting analysis showing the state of kinase activity of SRC in HCT116 and HT29 cells. GAPDH was used as an internal standard.
リン酸化プロテオミクスデータから再構築した活性化リン酸化ネットワークを示す。図４ａ、ｂ：ＨＣＴ１１６における活性化リン酸化ネットワーク、図４ｃ、ｄ：ＨＴ２９細胞における活性化リン酸化ネットワーク。黒塗りの四角形：リン酸化状態によって同定された活性化キナーゼ。黒塗りの五角形（ＪＡＫ２）：ＫＳＥＡによって予測された活性化キナーゼ。黒塗りの文字および黒塗り六角形（処理の２４時間後のＬｙｎ）：リン酸化状態およびＫＳＥＡアルゴリズムの組み合わせで同定されたキナーゼ。白色の背景の青い四角形：PhosphositePlusにおけるＫＳＲによって結び付けられた、活性化キナーゼの上流のキナーゼ。The activated phosphorylation network reconstructed from phosphorylated proteomics data is shown. 4a, b: activated phosphorylation network in HCT116, FIG. 4c, d: activated phosphorylation network in HT29 cells. Black square: activated kinase identified by phosphorylation status. Black pentagon (JAK2): activated kinase predicted by KSEA. Black letters and black hexagons (Lyn 24 hours after treatment): kinases identified by a combination of phosphorylation status and KSEA algorithm. Blue squares with white background: Kinases upstream of activated kinases linked by KSR in PhosphositePlus.
細胞増殖に対する活性化キナーゼ候補のノックダウンの効果を示す。図５ａは、各活性化キナーゼに特異的な三つのｓｉＲＮＡでの処理後、ＨＣＴ１１６細胞の生存率を示す結果である。灰色棒は、細胞増殖に対して有意な効果（ｑ＜０．０５）を持つｓｉＲＮＡの結果、黒色棒は、対照のｓｉＲＮＡおよび有意な効果を持たない（ｑ＞０．０５）ｓｉＲＮＡの結果、白色棒は、ｓｉＲＮＡ実験の正の対照であるＣＤＫ１ ｓｉＲＮＡの結果を示す。エラーバーはＳＤを示す；Ｎ＝３。図５ｂは、用量依存的な様式でのＳＲＣおよびＹＥＳ１を標的とする二つのＴＫＩ、ＫＸ２－３９１およびＳＵ６６５６処理下における、セツキシマブ耐性細胞の細胞生存率を示すグラフである。増殖アッセイによるデータに対してカーブフィッティングを行った。エラーバーはＳＤを示す；Ｎ＝３。Figure 3 shows the effect of knocking down activated kinase candidates on cell proliferation. FIG. 5a is a result showing the viability of HCT116 cells after treatment with three siRNAs specific for each activated kinase. Gray bars are siRNA results with significant effects on cell proliferation (q <0.05), black bars are siRNA results with control and no significant effects (q> 0.05), White bars show the results for CDK1 siRNA, which is a positive control for siRNA experiments. Error bars indicate SD; N = 3. FIG. 5b is a graph showing cell viability of cetuximab resistant cells under two TKI, KX2-391 and SU6656 treatments targeting SRC and YES1 in a dose-dependent manner. Curve fitting was performed on the data from the proliferation assay. Error bars indicate SD; N = 3.
リン酸化プロテオミクスの実験手順の要約とサンプル量の情報を示す。図６Ａは、内視鏡生検によるリン酸化プロテオミクスのワークフローである。図６Ｂは、メタノール/クロロホルム沈殿の前後のタンパク質溶解物の試料量の変化を示すグラフである。A summary of the experimental procedure for phosphorylated proteomics and sample volume information are presented. FIG. 6A is a workflow for phosphorylated proteomics by endoscopic biopsy. FIG. 6B is a graph showing changes in the sample amount of protein lysate before and after methanol / chloroform precipitation. 内視鏡生検からのリン酸化プロテオミクス解析の結果の要約を示す。図７Ａは、リン酸化ペプチド、リン酸化部位、クラス1リン酸化部位、定量によるクラス1リン酸化部位、およびリン酸化タンパク質グループの数を示している。図７Ｂは、同定されたリン酸化部位のうち、リン酸化セリン（12,062個）、リン酸化トレオニン（2,531個）、リン酸化チロシン（94個）の割合を示す円グラフである。図７Ｃは、同定された14,687個のリン酸化部位のうち、PhosphositePlusデータベースに割り当てられたリン酸化部位の割合（13,341個）と割り当てられていないもの（1,346個）を示す円グラフである。図７Ｄは、 胃がんにおける手術組織（Jong-Moon,P. et al）と本研究との間の同定されたリンペプチドの比較を示すベンダイアグラムである。A summary of the results of phosphorylated proteomic analysis from endoscopic biopsy is presented. FIG. 7A shows the number of phosphorylated peptides, phosphorylated sites, class 1 phosphorylated sites, quantified class 1 phosphorylated sites, and phosphorylated protein groups. FIG. 7B is a pie chart showing the proportion of phosphorylated serine (12,062), phosphorylated threonine (2,531), and phosphorylated tyrosine (94) among the identified phosphorylation sites. FIG. 7C is a pie chart showing the proportion of phosphorylated sites assigned to the PhosphositePlus database (13,341) and the unassigned (1,346) of the 14,687 identified phosphorylated sites. FIG. 7D is a Venn diagram showing a comparison of identified phosphopeptides between the surgical tissue in rumen cancer (Jong-Moon, P. et al) and this study.
内視鏡的生検によるリン酸化プロテオミクスの定量的特徴を示す。図８Ａは、がん生検（がん1：右下、他のがん生検：がん２－５）および正常組織（正常１－５）由来のリン酸化タンパク質データの主成分分析（PCA）の結果を示す。1 shows quantitative features of phosphorylated proteomics by endoscopic biopsy. FIG. 8A shows a principal component analysis (PCA) of phosphoprotein data from cancer biopsy (cancer 1: lower right, other cancer biopsy: cancer 2-5) and normal tissue (normal 1-5). ) Result. 内視鏡的生検によるリン酸化プロテオミクスの定量的特徴を示す。図８Ｂは、リン酸化プロテオームデータのピアソン相関係数の相関行列を示す。ここでは、濃い部分が高相関を示す。1 shows quantitative features of phosphorylated proteomics by endoscopic biopsy. FIG. 8B shows the correlation matrix of the Pearson correlation coefficient of phosphorylated proteome data. Here, a dark part shows a high correlation. 内視鏡的生検によるリン酸化プロテオミクスの定量的特徴を示す。図８Ｃは、「がん1」試料の有無による相関の間のピアソンの係数の比較である。統計的有意性を確認するためにMann-Whitney U検定を行った。1 shows quantitative features of phosphorylated proteomics by endoscopic biopsy. FIG. 8C is a comparison of Pearson's coefficients between correlations with and without the “Cancer 1” sample. Mann-Whitney U test was performed to confirm statistical significance. がん生検と正常組織由来のリン酸化プロテオームデータを比較することによるパスウェイ解析の結果である。図９Ａは、リン酸化プロテオミクスのボルケーノプロットを示す。ボルケーノプロットにおける右翼および左翼における個々の円は、有意な増加および減少をそれぞれ有するリン酸化部位を示す。灰色の円は、有意差のないリン酸化物である。It is the result of the pathway analysis by comparing the phosphorylated proteome data derived from a cancer biopsy and a normal tissue. FIG. 9A shows a volcano plot of phosphorylated proteomics. Individual circles in the right and left wings in the Volcano plot indicate phosphorylation sites with significant increases and decreases, respectively. Gray circles are phosphoric oxides with no significant difference. がん生検と正常組織由来のリン酸化プロテオームデータを比較することによるパスウェイ解析の結果である。図９Ｂは、KEGG（上のグラフ）とWikiPathway（下のグラフ）のパスウェ情報を用いたパスウェ解析の結果を示す。It is the result of the pathway analysis by comparing the phosphorylated proteome data derived from a cancer biopsy and a normal tissue. FIG. 9B shows the result of pathway analysis using pathway information of KEGG (upper graph) and WikiPathway (lower graph). がん生検と正常組織由来のリン酸化プロテオームデータを比較することによるパスウェイ解析の結果である。図９Ｃは、2つのリン酸化部位（ATR T1989およびNBN S343）の名目上の強度を使用した対ドットプロットを示す。It is the result of the pathway analysis by comparing the phosphorylated proteome data derived from a cancer biopsy and a normal tissue. FIG. 9C shows a versus dot plot using the nominal intensity of two phosphorylation sites (ATR T1989 and NBN S343). 内視鏡生検からのリン酸化プロテオームデータを用いたキノムプロファイリングの結果を示す。図１０Ａは、Ser / Thrキナーゼ（Ａの左図）およびTyrキナーゼ（Ａの右図）の活性を有するリン酸化タンパク質の割合を示す円グラフである。図１０Ｂは、右側の棒ががん生検でキナーゼの活性化が予測されることを示し、左側の棒は、キナーゼの不活性化が正常組織由来のものと比較してがん生検で予測されることを示すKSEAの結果である。図１０Ｃは、KSEAの計算で使用されたERBB2基質リン酸化部位の変動を分析した、ERBB2 Y877、Y1248、およびCDK1 Y15の変化を示す。Figure 5 shows kinome profiling results using phosphorylated proteome data from endoscopic biopsy. FIG. 10A is a pie chart showing the proportion of phosphorylated proteins having Ser / Thr kinase (A on the left) and Tyr kinase (A on the right) activities. FIG. 10B shows that the right bar predicts kinase activation in cancer biopsy, and the left bar indicates that inactivation of kinase is in cancer biopsy compared to that from normal tissue. It is the result of KSEA which shows what is predicted. FIG. 10C shows changes in ERBB2 Y877, Y1248, and CDK1 Y15 analyzed for variation in the ERBB2 substrate phosphorylation sites used in the KSEA calculations.
＜責任キナーゼをスクリーニングする方法＞
　本発明はひとつの態様として、リン酸化プロテオミクスを行うことによって、治療標的または薬効予測標的となり得る責任キナーゼをスクリーニングする方法、具体的には、リン酸化プロテオミクスを行うことによってリン酸化修飾活性が有意に増加しているキナーゼを選別し、それを、治療標的または薬効予測標的となり得る責任キナーゼとする、責任キナーゼのスクリーニング方法、より具体的には、リン酸化プロテオミクスから得られたデータに基づき、有意に増加しているリン酸化部位を特定することによってリン酸化修飾活性が有意に増加しているキナーゼを選別し、それを、治療標的または薬効予測標的となり得る責任キナーゼとする、責任キナーゼのスクリーニング方法に関する。 <Method of screening for responsible kinase>
One aspect of the present invention is a method for screening a responsible kinase that can be a therapeutic target or a drug efficacy prediction target by performing phosphorylation proteomics. Specifically, phosphorylation modifying activity is significantly increased by performing phosphorylation proteomics. Based on data obtained from screening methods for responsible kinases, and more specifically from phosphorylated proteomics, screening for increased kinases and making them responsible kinases that can be therapeutic targets or predictive targets The present invention relates to a screening method for responsible kinases, in which a kinase having significantly increased phosphorylation-modifying activity is selected by identifying an increased phosphorylation site, and the kinase is selected as a responsible kinase that can be a therapeutic target or a drug efficacy prediction target. .
　本明細書に使用されている「リン酸化プロテオミクス解析」または「リン酸化プロテオミクス」とは、リン酸化セリン(pS)、リン酸化スレオニン(pT)および／またはチロシンリン酸化(pY)部位を持つペプチドを濃縮し、高感度リン酸化情報の取得を行う測定方法である。測定方法には質量分析を含み、その詳細は、ナノ流速LCと、高分解能質量分析計とを組み合わせたショットガンプロテオミクスによる検出法であり得る。例えば、UltiMate 3000ナノＬＣシステム(Thermo Scientific)およびHTC-PAL(CTC Analytics, Zwingen, Switzerland)を備えるQ Exactive Plus質量分析計(Thermo Scientific)にてリン酸化プロテオミクスおよび／またはチロシンリン酸化プロテオミクスをそれぞれ行うことができる。質量分析計で得られた生データからのペプチド同定は、標準アミノ酸配列データベースを使用したペプチドサーチエンジンを使用して実行する。具体的には、生データからのペプチド同定は例えば、MaxQuantを用いて処理すればよい。得られたリン酸化部位から、クラス１リン酸化部位(Localization Probability > 0.75)を選定し、解析に使用する。 As used herein, “phosphorylated proteomic analysis” or “phosphorylated proteomics” refers to a peptide having a phosphorylated serine (pS), phosphorylated threonine (pT) and / or tyrosine phosphorylated (pY) site. This is a measurement method for concentrating and acquiring highly sensitive phosphorylation information. The measurement method includes mass spectrometry, and the details thereof may be a detection method by shotgun proteomics combining a nano flow rate LC and a high resolution mass spectrometer. For example, perform phosphorylation proteomics and / or tyrosine phosphorylation proteomics on a Q Exactive Plus mass spectrometer (Thermo Scientific) with UltiMateM3000 nano LC system (Thermo Scientific) and HTC-PAL (CTC Analytics, sZwingen, Switzerland), respectively be able to. Peptide identification from raw data obtained with a mass spectrometer is performed using a peptide search engine using a standard amino acid sequence database. Specifically, peptide identification from raw data may be performed using, for example, MaxQuant. A class 1 phosphorylation site (Localization リ ン Probability> 0.75) is selected from the obtained phosphorylation sites and used for analysis.
　本明細書に使用される「クラス１リン酸化部位(Localization Probability > 0.75)」または、単に「クラス１リン酸化部位」について以下説明する。各タンパク質上で同定されたリン酸化修飾について、リン酸化修飾が同定された該当アミノ酸箇所に本当に局在しているかどうかの確実性を示すのが「Localization Probability」であるところ、0.75以上の「Localization Probability」を持つリン酸化修飾が「クラス１リン酸化部位」と定義される（Jesper V. Olsen et al., 2006, Cell）。「チロシンリン酸化プロテオミクス解析」または「チロシンリン酸化プロテオミクス」とは、リン酸化セリン(pS)、リン酸化スレオニン(pT)、チロシンリン酸化(pY)の内、チロシンリン酸化部位を持つペプチドを濃縮し、高感度チロシンリン酸化情報の取得を行う測定方法である。本発明では具体的には、金属アフィニティクロマトグラフィーで調整した高感度リン酸化(pSTY)プロテオミクス用リン酸化ペプチドから、免疫沈降法によりチロシンリン酸化(pY)プロテオミクスを実施している。 “Class 1 phosphorylation site (Localization Probability> 0.75)” or simply “class 1 phosphorylation site” used in this specification will be described below. For the phosphorylation modification identified on each protein, “Localization Probability” indicates the certainty of whether the phosphorylation modification is really localized at the corresponding amino acid site where it was identified. Phosphorylation modifications with “Probability” are defined as “class 1 phosphorylation sites” (Jesper V. Olsen et al., 2006, Cell). “Tyrosine phosphorylation proteomics analysis” or “tyrosine phosphorylation proteomics” refers to the concentration of peptides with tyrosine phosphorylation sites among phosphorylated serine (pS), phosphorylated threonine (pT), and tyrosine phosphorylated (pY). This is a measurement method for obtaining highly sensitive tyrosine phosphorylation information. Specifically, in the present invention, tyrosine phosphorylation (pY) proteomics is performed by immunoprecipitation from a phosphorylated peptide for highly sensitive phosphorylation (pSTY) proteomics prepared by metal affinity chromatography.
　本明細書に使用されている「リン酸化修飾活性が有意に増加しているリン酸化部位を特定し」とは、トリプシン、ペプシン、キモトリプシン、グルタミルエンドペプチダーゼ、リシルエンドペプチダーゼ等の酵素を使用して消化されたタンパク質のペプチド断片について、リン酸化プロテオミクス解析を行い、対象と比較し、リン酸化修飾活性が有意に増加しているリン酸化部位を含むペプチド断片を特定する操作を意味する。 As used herein, “identifying a phosphorylation site having a significantly increased phosphorylation-modifying activity” means using trypsin, pepsin, chymotrypsin, glutamyl endopeptidase, lysyl endopeptidase, and the like. This means an operation of performing phosphorylation proteomics analysis on the digested protein peptide fragment and identifying a peptide fragment containing a phosphorylation site where the phosphorylation modifying activity is significantly increased as compared with the subject.
　本発明では、リン酸化修飾活性リン酸化部位を特定し、次いで、リン酸化修飾活性が有意に増加しているキナーゼを選別する。その手段は、タンパク質機能情報データベース上におけるキナーゼ活性制御リン酸化部位の実測値、および／またはキナーゼ基質関連情報を使用する計算科学的手法によって得られるキナーゼ活性予測値を用い、キナーゼを選別することからなる。責任キナーゼを選別するに当たり、キナーゼ活性制御リン酸化部位の実測値およびキナーゼ活性予測値はそれぞれ別個に使用してもよいが、両者共に使用すれば、より精度の高い責任キナーゼを選別することができる。 In the present invention, phosphorylation-modifying activity phosphorylation sites are specified, and then kinases whose phosphorylation-modifying activity is significantly increased are selected. The method is based on screening kinases using actual values of kinase activity-regulated phosphorylation sites in protein function information databases and / or kinase activity prediction values obtained by computational scientific methods using kinase substrate related information. Become. In selecting responsible kinases, the measured values of kinase activity-regulated phosphorylation sites and the predicted kinase activity may be used separately, but if both are used, more accurate responsible kinases can be selected. .
　本明細書に使用されている「タンパク質機能情報データベース上におけるキナーゼ活性制御リン酸化部位の実測値」について説明する。本発明の一態様では、「タンパク質機能情報データベース」とは、タンパク質翻訳後修飾の機能情報を格納したデータベースを意味し、それには例えば、データベースUniprot、Reactome、GPS、PhosphositePlus（Hornbeck, P. V. et al., Nucleic Acids Res 40, D261-70 (2012)）、PhosphoNetworks、Phospho.ELM（Diella, F., et al., Nucleic Acids Res 36, D240-4 (2008).）、PHOSIDA（Gnad, F. et al., Genome Biol 8, R250 (2007).）、HPRD：Human Protein Reference Database（Amanchy, R. et al., Nat Biotechnol 25, 285-286 (2007).）がある。データベース上の情報を利用し、有意にリン酸化修飾活性が増加しているキナーゼを選別する。すなわち、タンパク質機能情報データベース上におけるキナーゼ活性制御リン酸化情報、および／またはキナーゼ基質関連情報を使用するキナーゼ活性予測情報を用いる、特定の群において有意な活性化を示すキナーゼを選別する統計的方法である。キナーゼ基質関連情報データベースとして、例えば、NetPhos、NetworKIN、、 PhosphositePlus、Phospho.ELM、GPS、NetPhorest（30. Miller, M. L. et al., Linear Motif Atlas for Phosphorylation-Dependent Signaling. Science signaling 1, ra2 (2008).）が挙げられる。 “Measured values of kinase activity-regulated phosphorylation sites on the protein function information database” used in this specification will be described. In one embodiment of the present invention, the “protein function information database” means a database storing function information of protein post-translational modifications, such as databases Uniprot, Reactome, GPS, PhosphositePlus (Hornbeck, P. V. et al., Nucleic Acids Res 40, D261-70 (2012)), PhosphoNetworks, Phospho.ELM (Diella, F., et al., Nucleic Acids Res 36, D240-4 (2008).), PHOSIDA (Gnad, F. et al., Genome Biol 8, R250 (2007).), HPRD: Human Protein Reference Database (Amanchy, R. et al., Nat Biotechnol 25, 285-286 (2007).). Using information on the database, a kinase having a significantly increased phosphorylation-modifying activity is selected. That is, a statistical method for selecting kinases exhibiting significant activation in a specific group using kinase activity control phosphorylation information on the protein function information database and / or kinase activity prediction information using kinase substrate related information. is there. For example, NetPhos, NetworKIN, PhosphositePlus, Phospho.ELM, GPS, NetPhorest (30. Miller, M. L. et al., Linear Motif Atlas for Phosphorylation-Dependent Signaling.1, Science signaling 1, Science signaling (2008).).
　本明細書に使用されている「キナーゼ活性制御リン酸化部位の実測値」とは、上記データベースにおいて、キナーゼの活性を制御する機能情報を付加されたリン酸化部位の実測値を意味する。例えば、Uniprot (http://www.uniprot.org/)に登録されているキナーゼ活性を制御するキナーゼ上のリン酸化修飾に関する情報が挙げられる。他に、PhosphositePlus、PhosphoELMを挙げることができる。 As used herein, “actually measured value of kinase activity-regulated phosphorylation site” means an actual value of a phosphorylation site to which functional information for controlling kinase activity is added in the database. For example, the information regarding the phosphorylation modification on the kinase which controls the kinase activity registered in Uniprot (http://www.uniprot.org/) is mentioned. Other examples include PhosphositePlus and PhosphoELM.
　本明細書に使用されている「キナーゼ基質関連情報を使用する計算科学的手法によって得られるキナーゼ活性予測値」とは、特定のキナーゼによって修飾されるリン酸化修飾部位が、全検出リン酸化修飾部位に対してある条件下で有意に上昇/下降しているのかを統計的に検定する手法によって得られるキナーゼ活性予測を示す情報であり、具体的にはキナーゼ基質エンリッチメント解析（ＫＳＥＡ）によって得られる情報がある（１７）。NetworKIN（４０）で予測したキナーゼ-基質関係（ＫＳＲ）とは、リン酸化部位前後のアミノ酸配列、タンパク質相互作用情報、タンパク質局在情報、タンパク質相互作用ネットワーク構造の観点から予測される。
　ＫＳＥＡの他には、ＫＥＡ、ＩＣＡＰが挙げられる。 As used herein, the “predicted value of kinase activity obtained by a computational scientific method using kinase substrate-related information” means that the phosphorylation modification site modified by a specific kinase is an all-detection phosphorylation modification site. Is information indicating the prediction of kinase activity obtained by a method of statistically testing whether it is significantly elevated / decreased under certain conditions, specifically obtained by kinase substrate enrichment analysis (KSEA) There is information (17). The kinase-substrate relationship (KSR) predicted by NetworKIN (40) is predicted from the viewpoints of amino acid sequences before and after phosphorylation sites, protein interaction information, protein localization information, and protein interaction network structure.
In addition to KSEA, KEA and ICAP may be mentioned.
　本発明では、選別されたキナーゼを、治療標的または薬効予測標的となり得る責任キナーゼと割り当てる。 In the present invention, the selected kinase is assigned as a responsible kinase that can be a therapeutic target or a drug efficacy prediction target.
　本明細書に使用されている「治療標的」とは、有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患の原因である責任キナーゼを意味する。本明細書に使用されている「薬効予測標的」とは、有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患に罹患している被験者において、当該疾患を処置または予防する治療薬の有効性を予測するために使用される責任キナーゼを意味する。 As used herein, “therapeutic target” refers to a disease selected from among diseases for which there is no effective therapeutic agent, advanced cancer with high malignancy, and cancer having characteristic cancer characteristics for individuals. It means the responsible kinase that is responsible for. As used herein, the “drug predictive target” is selected from diseases for which there is no effective therapeutic drug, advanced cancer with high malignancy, and cancer that has individual cancer characteristics By a responsible kinase used to predict the effectiveness of a therapeutic agent to treat or prevent the disease in a subject suffering from the disease.
　ここに、「責任キナーゼ」とは、細胞周期および細胞運動を含む様々な種類の細胞機能を制御する、ＥＧＦＲ、Ｓｒｃ、ＥＲＫ１／２など、ヒトにおける約５２０種類のタンパク質キナーゼであって、特定の態様において生存増殖シグナルおよび／または炎症シグナルの活性化に寄与して当該疾患を引き起こす原因キナーゼを意味する。 As used herein, “responsible kinase” refers to about 520 protein kinases in humans, such as EGFR, Src, ERK1 / 2, etc., which control various types of cell functions including cell cycle and cell motility. In an embodiment, it means a causal kinase that contributes to the activation of survival proliferation signals and / or inflammatory signals and causes the disease.
　本明細書に使用されている「有効な治療薬がない疾患」とは、薬剤耐性疾患または、責任キナーゼが関与する難治性疾患を意味する。「薬剤耐性疾患」とは、ある疾患に対する有効な分子標的治療薬、具体的には生存増殖シグナルおよび／または炎症シグナルを標的としたキナーゼ阻害剤はあるが、ある時点からその治療薬に耐性になった患者における疾患を意味する。薬剤耐性疾患において耐性になる機構は本明細書の実施例にて示している通り、責任キナーゼの関与にあると考えられる。「責任キナーゼが関与する難治性疾患」とは、責任キナーゼが生存増殖シグナルおよび／または炎症シグナルの活性化に関与している増殖性疾患や炎症性疾患などを意味する。 As used herein, “disease without an effective therapeutic agent” means a drug resistant disease or an intractable disease involving responsible kinase. A “drug resistant disease” is an effective molecular targeted therapeutic for a disease, specifically a kinase inhibitor that targets survival and / or inflammatory signals, but is resistant to that therapeutic from some point in time. Means disease in the patient. The mechanism of becoming resistant in drug-resistant diseases is believed to be responsible kinase involvement, as shown in the Examples herein. The “refractory disease in which responsible kinase is involved” means a proliferative disease or inflammatory disease in which responsible kinase is involved in activation of a survival proliferation signal and / or an inflammatory signal.
　本明細書において、増殖性疾患は、インスリノーマ、エナメル上皮腫、可移植性性器腫瘍、カウデン症候群、下垂体腺腫、家族性大腸腺腫症、褐色細胞腫、ガングリオン、奇形腫、筋腫、クッシング症候群、クロンカイト・カナダ症候群、ケロイド、原発性アルドステロン症、慢性好酸球性白血病/特発性好酸球増加症候群、肛門周囲腺腫、骨髄異形成/骨髄増殖性疾患、骨髄線維症、骨軟骨腫、混合腫瘍、歯牙腫、歯原性粘液腫、脂肪腫、若年性骨髄単球性白血病、消化管間質腫瘍、小腸腫瘍、神経鞘腫、真性多血症、紅板症、石灰化嚢胞性歯原性腫瘍、腺腫様歯原性腫瘍、腺リンパ腫、造血リンパ組織腫瘍、組織型、唾液腺腫瘍、多形腺腫、乳管内乳頭腫、乳腺線維腺腫、白板症、肥厚性瘢痕、非定型慢性骨髄性白血病、肥満細胞腫、副腎腫瘍、プロラクチノーマ、扁平苔癬、ポイツ・ジェガーズ症候群、ほくろ、本態性血小板血症、慢性好中球性白血病、慢性骨髄単球性白血病、良性セメント芽細胞腫、リンパ芽球、類皮嚢胞、老人性角化腫であって、責任キナーゼが生存増殖シグナルの活性化に関与しているものである。 In the present specification, proliferative diseases are insulinoma, enamel epithelioma, transplantable genital tumor, Cowden syndrome, pituitary adenoma, familial colorectal adenoma, pheochromocytoma, ganglion, teratoma, myoma, Cushing syndrome, cronkite Canada syndrome, keloid, primary aldosteronism, chronic eosinophilic leukemia / idiopathic eosinophilia syndrome, perianal adenoma, myelodysplasia / myeloproliferative disorder, myelofibrosis, osteochondroma, mixed tumor, Odontoma, odontogenic myxoma, lipoma, juvenile myelomonocytic leukemia, gastrointestinal stromal tumor, small intestine tumor, schwannoma, polycythemia vera, leukoplakia, calcified cystic odontogenic tumor Adenomatous odontogenic tumor, Adenolymphoma, Hematopoietic lymphoid tissue tumor, Histological type, Salivary gland tumor, Polymorphic adenoma, Intraductal papilloma, Breast fibroadenoma, Leukoplakia, Hypertrophic scar, Atypical chronic myelogenous leukemia, Obesity Cytoma, vice Tumor, prolactinoma, lichen planus, Poit's Jegger's syndrome, mole, essential thrombocythemia, chronic neutrophil leukemia, chronic myelomonocytic leukemia, benign cementoblastoma, lymphoblast, dermoid cyst, elderly A keratoma that is responsible for the activation of survival proliferative signals.
　本明細書において、炎症性疾患は、潰瘍性大腸炎，クローン病に代表される炎症性腸疾患、アフタ性口内炎，結節性紅斑，壊疽性膿 皮症，乾癬，苔癬，類天疱瘡，水疱性天疱瘡、末梢性関節炎，強直性脊椎炎、原発性硬化性胆管炎，膵炎，脂肪肝，肝炎，肝硬変、腎炎，ネフローゼ症候群、強膜炎，ブドウ膜炎，虹彩炎，角膜潰瘍、血栓性静脈炎，慢性甲状腺炎，SLE，シェー グレン症候群，関節リウマチ、脊椎関節炎、アテローム性動脈硬化症、リウマチ性多発筋痛症、巨細胞性動脈炎、石綿肺/珪肺、クリオピリン関連周期熱症候群(CAPS)、家族性寒冷蕁麻疹、Muckle-Wells症候群、CINCA症候群／NOMID、TNF 受容体関連周期性症候群 (TRAPS）、高ＩｇＤ症候群（メバロン酸キナーゼ欠損症）、ブラウ症候群／若年発症サルコイドーシス、家族性地中海熱、ＰＡＰＡ（化膿性関節炎・壊疽性膿皮症・座瘡）症候群、中條-西村症候群、Majeed症候群、NLRP12関連周期熱症候群(NAPS12)、インターロイキン１受容体アンタゴニスト欠損症 (DIRA)、インターロイキン３６受容体アンタゴニスト欠損症（DITRA)、フォスフォリパーゼＣγ２関連抗体欠損・免疫異常症（PLAID）、HOIL-1欠損症、SLC29A3欠損症、CARD14異常症、ADA2欠損症、STING-Associated Vasculopathy with Onset in Infancy (SAVI)、NLRC4異常症、全身型若年性特発性関節炎、周期性発熱・アフタ性口内炎・咽頭炎・リンパ節炎症候群 (PFAPA) 、成人発症型スティル病、ベーチェット病、痛風、偽痛風、Schnitzler症候群、II型糖尿病、慢性再発性多発性骨髄炎（ＣＲＭＯ）であって、責任キナーゼが炎症シグナルの活性化に関与しているものである。 In the present specification, inflammatory diseases include ulcerative colitis, inflammatory bowel diseases represented by Crohn's disease, aphthous stomatitis, erythema nodosum, gangrenous pustulosis, psoriasis, lichen, pemphigoid, blisters Pemphigus vulgaris, peripheral arthritis, ankylosing spondylitis, primary sclerosing cholangitis, pancreatitis, fatty liver, hepatitis, cirrhosis, nephritis, nephrotic syndrome, scleritis, uveitis, iritis, corneal ulcer, thrombotic Phlebitis, chronic thyroiditis, SLE, Sjogren's syndrome, rheumatoid arthritis, spondyloarthritis, atherosclerosis, polymyalgia rheumatica, giant cell arteritis, asbestosis / silicosis, cryopyrin-related periodic fever syndrome (CAPS) ), Familial cold urticaria, Muckle-Wells syndrome, CINCA syndrome / NOMID, TNF-receptor-related periodic syndrome (TRAPS), high IgD syndrome (mevalonate kinase deficiency), Blau syndrome / juvenile sarcoidosis, familial location Nakaumi fever, PAPA (suppurative arthritis, gangrenous pyoderma, acne) syndrome, Nakatsuji-Nishimura syndrome, Majeed syndrome, NLRP12-related periodic fever syndrome (NAPS12), interleukin 1 receptor antagonist deficiency fistula (DIRA), inter Leukine 36 receptor antagonist deficiency (DITRA), Phospholipase Cγ2-related antibody deficiency / immunopathy (PLAID), HOIL-1 deficiency, SLC29A3 deficiency, CARD14 deficiency, ADA2 deficiency, STING-Associated Vasculopathy with Onset in Infancy (SAVI), NLRC4 abnormality, systemic juvenile idiopathic arthritis, periodic fever, aphthous stomatitis, pharyngitis, lymphadenitis syndrome (PFAPA), adult-onset Still's disease, Behcet's disease, gout, pseudogout Schnitzler syndrome, type II diabetes, chronic relapsing multiple osteomyelitis (CRMO), where the responsible kinase is involved in the activation of inflammatory signals.
　正常細胞における細胞の成長と分裂は組織が新しい細胞を必要とするときに引き起こされ、すなわち必要に応じて組織の機能維持に十分な新しい細胞が生じるよう制御されている。本明細書に使用されている「悪性度が高い進行がん」とは、生存増殖シグナルおよび／または炎症シグナルの活性化に関与する責任キナーゼの出現により、この制御秩序が乱れ、周囲の組織に浸潤しまたは転移を起こすために、予後の著しく悪い段階の腫瘍を意味する。対象となり得るがん腫は、白血病、リンパ腫、ホジキン病、非ホジキンリンパ腫、多発性骨髄腫、脳腫瘍、乳がん、子宮体がん、子宮頚がん、卵巣がん、食道がん、胃がん、虫垂がん、大腸がん、肝細胞がん、胆嚢がん、胆管がん、膵臓がん、副腎がん、消化管間質腫瘍、中皮腫、頭頚部がん、喉頭がん、口腔がん、口腔底がん、歯肉がん、舌がん、頬粘膜がん、唾液腺がん、副鼻腔がん、上顎洞がん、前頭洞がん、篩骨洞がん、蝶型骨洞がん、甲状腺がん、肺がん、骨肉腫、前立腺がん、精巣腫瘍、腎細胞がん、膀胱がん、横紋筋肉腫、皮膚がん、肛門がんであって、責任キナーゼが生存増殖シグナルおよび／または炎症シグナルの活性化に関与しているものである。 Cell growth and division in normal cells is triggered when the tissue requires new cells, that is, it is controlled as necessary to generate new cells sufficient to maintain the function of the tissue. As used herein, “high-grade advanced cancer” refers to disruption of this regulatory order due to the emergence of responsible kinases involved in the activation of survival and / or inflammatory signals. It means a tumor with a significantly worse prognosis because it invades or metastasizes. Possible cancers include leukemia, lymphoma, Hodgkin's disease, non-Hodgkin's lymphoma, multiple myeloma, brain tumor, breast cancer, endometrial cancer, cervical cancer, ovarian cancer, esophageal cancer, stomach cancer, and appendix. Cancer, colon cancer, hepatocellular carcinoma, gallbladder cancer, bile duct cancer, pancreatic cancer, adrenal cancer, gastrointestinal stromal tumor, mesothelioma, head and neck cancer, laryngeal cancer, oral cancer, Oral cavity cancer, gingival cancer, tongue cancer, buccal mucosa cancer, salivary gland cancer, sinus cancer, maxillary sinus cancer, frontal sinus cancer, ethmoid sinus cancer, sphenoid sinus cancer, Thyroid cancer, lung cancer, osteosarcoma, prostate cancer, testicular cancer, renal cell cancer, bladder cancer, rhabdomyosarcoma, skin cancer, anal cancer, responsible kinase is a survival proliferative signal and / or inflammation It is involved in signal activation.
　本明細書に使用されている「個人に特徴的ながん特性を有するがん」とは、がん患者集団において、個々の患者に特有の責任キナーゼを原因として生存増殖シグナルおよび／または炎症シグナルの活性化が起こっている腫瘍を意味する。対象となり得るがん腫は、白血病、リンパ腫、ホジキン病、非ホジキンリンパ腫、多発性骨髄腫、脳腫瘍、乳がん、子宮体がん、子宮頚がん、卵巣がん、食道がん、胃がん、虫垂がん、大腸がん、肝細胞がん、胆嚢がん、胆管がん、膵臓がん、副腎がん、消化管間質腫瘍、中皮腫、頭頚部がん、喉頭がん、口腔がん、口腔底がん、歯肉がん、舌がん、頬粘膜がん、唾液腺がん、副鼻腔がん、上顎洞がん、前頭洞がん、篩骨洞がん、蝶型骨洞がん、甲状腺がん、肺がん、骨肉腫、前立腺がん、精巣腫瘍、腎細胞がん、膀胱がん、横紋筋肉腫、皮膚がん、肛門がんであって、責任キナーゼが生存増殖シグナルおよび／または炎症シグナルの活性化に関与しているものである。 As used herein, a “cancer having personal cancer characteristics” refers to a survival growth signal and / or an inflammatory signal in a cancer patient population due to a responsible kinase specific to the individual patient. It means a tumor in which activation is occurring. Possible cancers include leukemia, lymphoma, Hodgkin's disease, non-Hodgkin's lymphoma, multiple myeloma, brain tumor, breast cancer, endometrial cancer, cervical cancer, ovarian cancer, esophageal cancer, stomach cancer, and appendix. Cancer, colon cancer, hepatocellular carcinoma, gallbladder cancer, bile duct cancer, pancreatic cancer, adrenal cancer, gastrointestinal stromal tumor, mesothelioma, head and neck cancer, laryngeal cancer, oral cancer, Oral cavity cancer, gingival cancer, tongue cancer, buccal mucosa cancer, salivary gland cancer, sinus cancer, maxillary sinus cancer, frontal sinus cancer, ethmoid sinus cancer, sphenoid sinus cancer, Thyroid cancer, lung cancer, osteosarcoma, prostate cancer, testicular cancer, renal cell cancer, bladder cancer, rhabdomyosarcoma, skin cancer, anal cancer, responsible kinase is a survival proliferative signal and / or inflammation It is involved in signal activation.
　本発明では、一つの態様として、内視鏡生検に特化したリン酸化プロテオーム法を提供する。簡単に説明すると、本発明では、リン酸化プロテオミクスの実験手順において、試料損失の低減を行うことができる。組織試料には、液体クロマトグラフィータンデム質量分析（LC-MS / MS）分析を妨害する大量の汚染物質が含まれることがあるため、タンパク質消化の前にメタノール/クロロホルム沈殿を行えばよい。次に、生検試料中の少量のリン酸化ペプチドの損失を減少させるために、従来法であるオフラインLCによるIMAC濃縮ペプチドの分画ではなく、固定化金属アフィニティークロマトグラフィー（IMAC）/ C18 ステージチップ[18]を採用することができる [5,6]。 In the present invention, as one embodiment, a phosphorylated proteome method specialized for endoscopic biopsy is provided. Briefly, in the present invention, sample loss can be reduced in the experimental procedure of phosphorylated proteomics. Tissue samples may contain large amounts of contaminants that interfere with liquid chromatography tandem mass spectrometry (LC-MS / MS) analysis, so methanol / chloroform precipitation may be performed prior to protein digestion. Second, to reduce the loss of small amounts of phosphopeptides in biopsy samples, immobilized metal affinity chromatography (IMAC) / C18 stage chip rather than fractionation of IMAC-enriched peptides by conventional offline LC [18] can be adopted [5, 6].
　本発明は具体的な態様として、リン酸化プロテオミクスから得られたデータに基づき、有意に増加しているリン酸化部位を特定することによってリン酸化修飾活性が有意に増加しているキナーゼを選別し、それを、治療標的または薬効予測標的となり得る責任キナーゼとする、責任キナーゼのスクリーニング方法であって、対照を含む対照試料および標的を含む標的試料、または標的を含む標的試料に対し、リン酸化プロテオミクスを行う方法に関する。 As a specific embodiment, the present invention selects, as a specific embodiment, a kinase having a significantly increased phosphorylation-modifying activity by identifying a phosphorylation site that is significantly increased based on data obtained from phosphorylated proteomics, A method for screening a responsible kinase, which is a responsible kinase that can be a therapeutic target or a target for predicting drug efficacy, wherein phosphorylated proteomics is applied to a control sample including a control and a target sample including a target or a target sample including a target. On how to do.
　本発明においては、正常状態などの対照を含む対照試料、および疾患状態などの異常状態における標的を含む標的試料を対比し、後者において有意にリン酸化修飾活性が増加しているキナーゼを選別する。あるいは、正常状態などの対照を含む対照試料が現場に無くても、その値が標準化されており、その標準値に基づき、標的試料の値を評価できる場合は、標的試料に対してのみリン酸化プロテオミクスを行い、責任キナーゼの選別を行うことができる。
　本発明においては、疾患状態などの異常状態においてリン酸化修飾活性が有意に増加しているキナーゼの存在が、耐性を生じさせている状態を想定する。対照状態における典型例は正常細胞、感受性細胞であり、異常状態における典型例は治療対象細胞である。 In the present invention, a control sample including a control such as a normal state and a target sample including a target in an abnormal state such as a disease state are compared, and a kinase in which phosphorylation modifying activity is significantly increased in the latter is selected. Alternatively, even if there is no control sample in the field, including controls such as normal conditions, if the value is standardized and the value of the target sample can be evaluated based on the standard value, phosphorylation is performed only on the target sample. Proteomics can be performed to select responsible kinases.
In the present invention, it is assumed that the presence of a kinase whose phosphorylation-modifying activity is significantly increased in an abnormal state such as a disease state causes resistance. Typical examples in the control state are normal cells and sensitive cells, and typical examples in the abnormal state are cells to be treated.
　対照試料および標的試料を例示すれば、ある分子標的薬に感受性を示す細胞および耐性を示すがん細胞、初期がん細胞および進行がん細胞、平均的ながん特性を示す細胞および個人に特徴的ながん特性を示す細胞が含まれるが、これらに限定されない。 Examples of control and target samples include cells sensitive to certain molecular targeted drugs and resistant cancer cells, early and advanced cancer cells, cells and individuals with average cancer characteristics Cells that exhibit typical cancer properties include, but are not limited to.
　本発明はより具体的な態様として、
　１）対照試料として対照細胞および標的試料として治療対象細胞の細胞溶解物から濃縮したリン酸化セリン、リン酸化スレオニンおよび／またはリン酸化チロシンペプチドについてリン酸化プロテオミクスデータを取得し、
　２）得られたデータに基づき、統計学的手法により、対照細胞と比較して治療対象細胞において有意に増加しているリン酸化部位を特定し、
　３）タンパク質機能情報データベース上におけるキナーゼ活性制御リン酸化部位の実測値、および／またはキナーゼ基質関連情報を使用する計算科学的手法によって得られるキナーゼ活性予測値によって、対照細胞と比較して治療対象細胞において有意にリン酸化修飾活性が増加しているキナーゼを選別し、それを治療標的または薬効予測標的となり得る責任キナーゼとする、責任キナーゼをスクリーニングする方法に関する。 As a more specific aspect of the present invention,
1) Obtain phosphorylated proteomics data for phosphorylated serine, phosphorylated threonine and / or phosphorylated tyrosine peptide concentrated from cell lysates of control cells as control samples and treated cells as target samples;
2) Based on the obtained data, a statistical method is used to identify phosphorylation sites that are significantly increased in the cells to be treated compared to the control cells,
3) Treatment target cells compared to control cells based on actual values of kinase activity-regulated phosphorylation sites on the protein function information database and / or kinase activity prediction values obtained by computational scientific methods using kinase substrate related information The present invention relates to a method for screening a responsible kinase, wherein a kinase having significantly increased phosphorylation-modifying activity is selected as a responsible kinase that can be a therapeutic target or a target for predicting drug efficacy.
　本発明はまた、より具体的な別の態様として、
１）内視鏡検体の細胞溶解物から濃縮したリン酸化セリン、リン酸化スレオニンおよび／またはリン酸化チロシンペプチドについてリン酸化プロテオミクスデータを取得し、
　２）得られたデータに基づき、統計学的手法により、癌患者母集団平均と比較して有意に増加しているリン酸化部位を特定し
　３）タンパク質機能情報データベース上におけるキナーゼ活性制御リン酸化部位の実測値、および／またはキナーゼ基質関連情報を使用する計算科学的手法によって得られるキナーゼ活性予測値によって、内視鏡検体において有意にリン酸化活性が増加しているキナーゼを選別し、それを治療標的または薬効予測標的となり得る責任キナーゼとする、責任キナーゼをスクリーニングする方法に関する。 The present invention also provides another more specific embodiment as follows.
1) Obtain phosphorylated proteomics data for phosphorylated serine, phosphorylated threonine and / or phosphorylated tyrosine peptide concentrated from cell lysates of endoscopic specimens,
2) Based on the obtained data, statistical methods were used to identify phosphorylation sites that were significantly increased compared to the average cancer patient population. 3) Kinase activity-regulated phosphorylation sites on the protein function information database Of kinases with significantly increased phosphorylation activity in endoscopic specimens based on measured values of and / or predicted kinase activity obtained by computational scientific methods using kinase substrate related information and treating them The present invention relates to a method of screening for a responsible kinase, which is a responsible kinase that can be a target or a target for predicting drug efficacy.
　上記より具体的な態様における工程２）の「統計学的手法」とは、２群で有意な変動を示すリン酸化部位、または多群の中で有意さを示すリン酸化部位を抽出するための手法である。例えば、対照細胞と比較して治療対象細胞において有意に増加しているリン酸化部位を特定できるt-test、welch t-test、Mann-Whiteney' U test、および／またはANOVAを意味する。ここに「リン酸化部位」とは、質量分析計で検出されたリン酸化修飾をもつアミノ酸部位を意味する。 The “statistical method” in step 2) in the more specific embodiment described above is for extracting a phosphorylation site showing significant variation in two groups, or a phosphorylation site showing significance in multiple groups. It is a technique. For example, it means t-test, welch-t-test, Mann-Whiteney 'U で き る test, and / or ANOVA that can identify phosphorylation sites that are significantly increased in treated cells compared to control cells. Here, the “phosphorylation site” means an amino acid site having phosphorylation modification detected by a mass spectrometer.
　上記より具体的な態様における工程１）の「リン酸化チロシンの濃縮」とは、生体検体を酵素消化、例えば、トリプシン消化して得られる試料からリン酸化チロシンンを抽出することを意味する。典型的には、まず、酵素消化試料を金属アフィニティクロマトグラフィーにかけ、リン酸化ペプチドを抽出し、次いで抗リン酸化チロシン抗体を用いる免疫沈降によって、リン酸化チロシンペプチドを収集する。 “Concentration of phosphorylated tyrosine” in step 1) in the more specific embodiment above means that phosphorylated tyrosine is extracted from a sample obtained by enzymatic digestion of a biological sample, for example, trypsin digestion. Typically, enzyme-digested samples are first subjected to metal affinity chromatography to extract phosphopeptides and then phosphotyrosine peptides are collected by immunoprecipitation using anti-phosphotyrosine antibodies.
　本明細書に使用されている「質量分析」とは、ペプチド試料を、イオン源を用いて気体状のイオンとし（イオン化）、分析部において、真空中で運動させ電磁気力を用いて、あるいは飛行時間差によりイオン化したペプチド試料を質量電荷比に応じて分離し、検出できる質量分析計を用いた測定方法のことをいう。イオン源を用いてイオン化する方法としては、EI法、CI法、FD法、FAB法、MALDI法、ESI法等の方法を適宜選択することができ、また、分析部において、イオン化したペプチド試料を分離する方法としては、磁場偏向型、四重極型、イオントラップ型、飛行時間（TOF）型、フーリエ変換イオンサイクロトロン共鳴型等の分離方法を適宜選択することができる。また、2以上の質量分析法を組み合わせたタンデム型質量分析（MS/MS）やトリプル四重極型質量分析を利用することができる。また、試料がリン酸化したペプチドを含む試料の場合、質量分析計への試料導入前に、試料を鉄イオン固定化アフィニティークロマトグラフィー（Fe-IMAC）を用いて濃縮することができる。また、液体クロマトグラフ（LC）やHPLCにより、本発明に係る変動ペプチドおよび安定ペプチドを分離・精製して試料とすることができる。また、検出部やデータ処理方法も適宜選択することができる。質量分析法を用いて変動ペプチドおよび安定ペプチドを質量分析法で検出・定量する場合、当該ペプチドと同一のアミノ酸配列からなる、濃度が既知の安定同位体で標識したペプチドを内部標準とすることができる。当該安定同位体標識ペプチドとしては、本発明に係る変動ペプチドおよび安定ペプチドにおけるアミノ酸の1つ以上が、15N、13C、18O、および2Hのいずれか1以上を含む安定同位体標識ペプチドであれば、アミノ酸の種類、位置、数などは適宜選択することができ、当該安定同位体標識ペプチドは、安定同位元素により標識されたアミノ酸を用いてF-moc法（Amblard., et al. Methods Mol Biol.298:3-24(2005)）等の適当な手段で化学合成することができるが、iTRAQ（登録商標）試薬、ICAT（登録商標）試薬、ICPL（登録商標）試薬、NBS（登録商標）試薬、Tandem Mass Tag（TMT）（登録商標）試薬等の標識試薬を用いて作製することもできる。 As used herein, “mass spectrometry” is a method in which a peptide sample is converted into gaseous ions using an ion source (ionization), and is moved in a vacuum in an analysis section using electromagnetic force or flying. This refers to a measurement method using a mass spectrometer capable of separating and detecting a peptide sample ionized by a time difference according to the mass-to-charge ratio. As an ionization method using an ion source, an EI method, CI method, FD method, FAB method, MALDI method, ESI method or the like can be selected as appropriate. As a separation method, a separation method such as a magnetic field deflection type, a quadrupole type, an ion trap type, a time of flight (TOF) type, a Fourier transform ion cyclotron resonance type, or the like can be selected as appropriate. In addition, tandem mass spectrometry (MS / MS) or triple quadrupole mass spectrometry combining two or more mass spectrometry methods can be used. When the sample contains a phosphorylated peptide, the sample can be concentrated using iron ion-immobilized affinity chromatography (Fe-IMAC) before introducing the sample into the mass spectrometer. Moreover, the variable peptide and the stable peptide according to the present invention can be separated and purified to form a sample by liquid chromatography (LC) or HPLC. Moreover, a detection part and a data processing method can also be selected suitably. When fluctuating peptides and stable peptides are detected and quantified by mass spectrometry using mass spectrometry, a peptide labeled with a stable isotope having a known amino acid sequence and a known concentration may be used as the internal standard. it can. As the stable isotope labeled peptide, one or more of the amino acids in the variable peptide and the stable peptide according to the present invention is a stable isotope labeled peptide containing any one or more of 15N, 13C, 18O, and 2H. The type, position, number, and the like of amino acids can be appropriately selected, and the stable isotope-labeled peptide can be obtained by using the F-moc method (Amblard., Et al. Methods Mol Biol. 298: 3-24 (2005)), etc., iTRAQ (registered trademark) reagent, ICAT (registered trademark) reagent, ICPL (registered trademark) reagent, NBS (registered trademark) reagent It can also be produced using a labeling reagent such as Tandem Mass Tag (TMT) (registered trademark) reagent.
　本明細書に使用されている「高感度リン酸化プロテオミクスデータ」とは、本発明者らが開発したリン酸化ペプチド分画法・チロシンリン酸化ペプチド濃縮法を併用した細胞内大規模リン酸化情報データを指す。これは、分子標的薬の耐性を克服するため、細胞のキノームの活性プロファイリングに必須である。 “High-sensitivity phosphorylated proteomics data” used in the present specification refers to intracellular large-scale phosphorylation information data using the phosphorylated peptide fractionation method and tyrosine phosphorylated peptide enrichment method developed by the present inventors. Point to. This is essential for the activity profiling of cellular kinomes to overcome the resistance of molecular targeted drugs.
　本明細書に使用されている「キノーム」とは、ヒトゲノムにコードされている５１８個のキナーゼを総称する名称である。
　本明細書に使用されている「キノームの活性プロファイリング」とは、細胞内キナーゼ活性を、高感度リン酸化プロテオミクスデータから高感度に予測する方法を指す。これは、薬剤感受性の予測に基づき抗がん剤治療を効率的に実施するために重要である。 As used herein, “kinome” is a generic name for 518 kinases encoded in the human genome.
As used herein, “kinome activity profiling” refers to a method of predicting intracellular kinase activity with high sensitivity from highly sensitive phosphorylated proteomics data. This is important for efficiently implementing anticancer drug treatment based on prediction of drug sensitivity.
＜治療標的を規定する方法＞
　本発明は別の態様として、治療する疾患の原因としての責任キナーゼをスクリーニングする方法、具体的には、治療標的が、有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患の原因である責任キナーゼであり、そして対照試料が正常細胞、標的試料が当該疾患細胞である、治療標的における責任キナーゼのスクリーニング方法に関する。 <Method of defining treatment target>
As another aspect, the present invention provides a method for screening responsible kinases as a cause of a disease to be treated, specifically, a disease in which there is no effective therapeutic agent, a highly malignant advanced cancer, and an individual. The present invention relates to a screening method for a responsible kinase in a therapeutic target, which is a responsible kinase responsible for a disease selected from cancers having characteristic cancer characteristics, and the control sample is a normal cell and the target sample is the disease cell. .
　また、本発明は別の態様として、ある被験者においてある治療薬が有効なのか有効でないのか、を判定するための責任キナーゼをスクリーニングする方法、具体的には、薬効予測標的が、有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患に罹患している被験者において、当該疾患を処置または予防する治療薬の有効性を予測するために使用される責任キナーゼであり、そして対照試料が当該治療薬に感受性の細胞または不存在、標的試料が、被験者由来の組織、血中循環細胞および細胞外小胞の中から選ばれる、薬効予測標的における責任キナーゼのスクリーニング方法に関する。
　本明細書に使用される「治療薬に感受性の細胞」とは、例えば、細胞ががん細胞であれば、特定の治療薬によってがん増殖が停止、あるいはがんが消失または縮小する細胞を意味する。本明細書に使用される「被験者由来の組織」とは血液、手術組織、生検検体、を意味する。本明細書に使用される「血中循環細胞」とは、がん原発巣およびがん転移巣を含むがん病巣から血管内へと遊走し、血中を流れている当該がん病巣由来の細胞を意味する。本明細書に使用される「細胞外小胞」とは、細胞から分泌される数十ナノメートルから数マイクロメートルの顆粒状の小胞体であり、エクソソーム、マイクロベシクル、アポトーシス小体などの総称である。その内部には、核酸（マイクロRNA、メッセンジャーRNA、DNAなど）やタンパク質を含み、細胞間情報伝達のツールとして働いていると考えられている。 In another aspect, the present invention provides a method for screening a responsible kinase for determining whether a certain therapeutic drug is effective or ineffective in a subject, specifically, a therapeutic drug whose effective drug target is effective. Effectiveness of therapeutic drugs to treat or prevent the disease in subjects with a disease selected from among those with no cancer, advanced cancer with high malignancy, and cancer with characteristic cancer characteristics A responsible kinase used to predict gender, and the control sample is sensitive or non-sensitive to the therapeutic agent, the target sample is from tissue from the subject, circulating blood cells and extracellular vesicles The present invention relates to a screening method for a responsible kinase in a target for predicting drug efficacy.
As used herein, “a therapeutic-sensitive cell” refers to a cell in which cancer growth is stopped by a specific therapeutic agent, or cancer disappears or shrinks if the cell is a cancer cell, for example. means. As used herein, “subject-derived tissue” means blood, surgical tissue, biopsy specimen. As used herein, “blood circulating cells” refers to cancerous lesions derived from the cancerous lesions that have migrated from the cancerous lesions, including the primary tumor and cancerous metastatic lesions, into the blood vessels. Means a cell. As used herein, “extracellular vesicle” is a granular vesicle of several tens of nanometers to several micrometers secreted from a cell, and is a generic term for exosomes, microvesicles, apoptotic bodies, etc. is there. It contains nucleic acids (micro RNA, messenger RNA, DNA, etc.) and proteins, and is thought to function as a cell-to-cell information transmission tool.
　本発明は具体的な態様として、対照試料が治療薬に感受性の細胞の場合、感受性細胞および標的試料に対し、リン酸化プロテオミクスを行い、感受性細胞と比較し標的試料において有意にリン酸化修飾活性が増加しているキナーゼを選別し、それを責任キナーゼとする、薬効予測標的における責任キナーゼをスクリーニングする方法に関する。
　本発明は別の具体的な態様として、対照試料が不存在の場合、標的試料に対し、リン酸化プロテオミクスを行い、キナーゼ活性レベルのPan-cancer Analysisによって、がん母集団のキナーゼ活性平均値を対照とした際に、リン酸化修飾活性値の有意な増加を示すキナーゼの選別を行う、薬効予測標的における責任キナーゼのスクリーニング方法に関する。ここに、「キナーゼ活性レベルのPan-cancer Analysis」とは、がん母集団から、がんサブタイプもしくは特定のがん患者に特有の活性化パターンを示すキナーゼを抽出する手法である（The Cancer Genome Atlas Research Network et al., 2013, Nat. Genetics）。例えば、１０００人の被験者由来のデータから平均を取得し、それに基づき、１００１人目以降の新たな被験者の判定を行う。 In a specific embodiment of the present invention, when the control sample is a cell sensitive to a therapeutic agent, phosphorylation proteomics is performed on the sensitive cell and the target sample, and the phosphorylation-modifying activity is significantly increased in the target sample as compared with the sensitive cell. The present invention relates to a method for screening for a responsible kinase in a drug efficacy prediction target by selecting an increased kinase and using it as a responsible kinase.
In another specific embodiment of the present invention, in the absence of a control sample, phosphorylation proteomics is performed on the target sample, and the kinase activity average value of the cancer population is determined by pan-cancer analysis of the kinase activity level. The present invention relates to a method for screening a responsible kinase in a drug efficacy prediction target, which comprises selecting a kinase exhibiting a significant increase in phosphorylation modifying activity value when used as a control. Here, “Pan-cancer Analysis of Kinase Activity Level” is a technique for extracting a kinase showing an activation pattern specific to a cancer subtype or a specific cancer patient from a cancer population (The Cancer Genome Atlas Research Network et al., 2013, Nat. Genetics). For example, an average is acquired from data derived from 1000 subjects, and new subjects after the 1001st are determined based on the average.
　本発明においては、治療薬に感受性の細胞を含む対照試料、および薬効予測の対象である被験者における標的を含む標的試料を対比し、後者において有意にリン酸化修飾活性が増加しているキナーゼを選別する。この態様において、有意にリン酸化修飾活性が増加しているキナーゼが存在する場合、当該治療薬はその被験者には有効でないと判断する。対照試料が不存在であっても、感受性細胞のリン酸化修飾活性の値が標準化されており、その標準値に基づき、標的試料の値を評価できる場合、標的試料に対してのみリン酸化プロテオミクスを行い、責任キナーゼの選別を行うことができる。
　本発明はより具体的な態様として、当該被験者において、当該疾患を処置または予防する治療薬の有効性を予測するために使用される責任キナーゼが不存在の場合、当該被験者は当該治療薬が有効であると判定する。 In the present invention, a control sample containing cells sensitive to a therapeutic agent is compared with a target sample containing a target in a subject who is a target of drug efficacy, and a kinase with significantly increased phosphorylation-modifying activity is selected in the latter. To do. In this embodiment, if there is a kinase with significantly increased phosphorylation modifying activity, it is determined that the therapeutic agent is not effective for that subject. Even in the absence of the control sample, if the value of the phosphorylation-modifying activity of the sensitive cells is standardized and the value of the target sample can be evaluated based on that standard value, phosphorylation proteomics is only applied to the target sample Can be screened for responsible kinases.
In a more specific aspect of the present invention, in the subject, when the responsible kinase used to predict the effectiveness of the therapeutic agent for treating or preventing the disease is absent, the subject is effective for the therapeutic agent. It is determined that
＜治療標的であるキナーゼの活性を阻害する物質をスクリーニングする方法＞
　本発明は別の態様として、本発明の方法によってスクリーニングされた責任キナーゼのリン酸化修飾活性を阻害する物質をスクリーニングするための方法であって、
　１）責任キナーゼを有する標的試料の培地中に責任キナーゼのリン酸化修飾活性を阻害し得る候補物質を添加し、
　２）責任キナーゼを有する標的試料における候補物質処理群と未処理群との細胞増殖活性における比較を行い、
　３）候補物質処理群の細胞増殖活性が未処理群よりも低ければ、その候補物質を責任キナーゼのリン酸化修飾活性を阻害する物質であると評価する、方法に関する。
　責任キナーゼのリン酸化修飾活性を阻害し得る候補物質としては、有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患を処置または予防できる治療薬、好ましくは、既に治療に用いられている治療薬、好ましくは分子標的薬を用いる。これらの例としては、Rituximab/Rituxan、Trastuzumab/Herceptin、Gemtuzumab、ozogamicin/Mylotarg、Alemtuzumab/Campath、Imatinib/Gleevec、Bcr-Abl/Kit、Ibritumomab、tiuxetan/Zevalin 、Tositumomab/Bexxar、Gefitinib/Iressa、Bortezomib/Velcade、Bevacizumab/Avastin、Cetuximab/Erbitux、Erlotinib/Tarceva、Azacitidine/Vidaza、Sorafenib/Nexavar、Sunitinib/Sutent、Dasatinib/Sprycel、Panitumumab/Vectibix、Vorinostat/Zolinza、Decitabine/Dacogen、Lapatinib/Tykerb、Temsirolimus/Torisel、Nilotinib/Tasigna、Everolimus/Afinitor、Pazopanib/Votrient、Ofatumumab/Arzerra、Romidepsin/Istodax、Denosumab/Ranmark、Ipilimumab/Yervoy、Vandetanib/Caprelsa、Vemurafenib/Zelboraf、Brentuximab vedotin/Adcetris、Crizotinib/Xalkori、Ruxolitinib /Jakafi、Axitinib/Inlyta、Vismodegib/Erivedge、Mogamulizumab/Poteligeo、Pertuzumab/Perjeta、Carfilzomib/Kyprolis、Ziv-aflibercept/Zaltrap、Bosutinib/Bosulif、Regorafenib/Stivarga、Cabozantinib/Cometriq、Ponatinib/Iclusig、Trastuzumab emtansine/ Kadcyla、Dabrafenib/Tafinlar、Trametinib/Mekinist、Afatinib/Gilotrif、Obinutuzumab/Gazyva、Ibrutinib/Imbruvica、Ramucirumab/Cyramza、Ceritinib/Zykadia、Belinostat/Beleodaq、Nivolumab/Opdivo、Alectinib/Alecensa、Idelalisib/Zydelig、Pembrolizumab/Keytruda、Nintedanib/Vargatef、Blinatumomab/Blincyto、Olaparib/Lynparza、Palbociclib/Ibrance、Lenvatinib/Lenvima、Panobinostat/Farydak、Dinutuximab/Unituxin、Sonidegib/Odomzo、Cobimetinib/Cotellic、Osimertinib/Tagrisso、Daratumumab/Darzalex、Necitumumab/Portrazza、Elotsuzumab/Empliciti、Ixazomib/Ninlaro等が挙げられる。 <Method of screening for a substance that inhibits the activity of kinase as a therapeutic target>
Another aspect of the present invention is a method for screening a substance that inhibits the phosphorylation-modifying activity of a responsible kinase screened by the method of the present invention,
1) A candidate substance capable of inhibiting the phosphorylation-modifying activity of the responsible kinase is added to the medium of the target sample having the responsible kinase,
2) Compare the cell proliferation activity of the candidate substance-treated group and the untreated group in the target sample having the responsible kinase,
3) The present invention relates to a method for evaluating a candidate substance as a substance that inhibits the phosphorylation-modifying activity of a responsible kinase if the cell growth activity of the candidate substance-treated group is lower than that of the untreated group.
Candidate substances that can inhibit the phosphorylation-modifying activity of the responsible kinase are selected from diseases for which there is no effective therapeutic agent, advanced malignant cancers, and cancers with individual cancer characteristics A therapeutic agent capable of treating or preventing a disease, preferably a therapeutic agent already used in therapy, preferably a molecular target drug is used. Examples of these include Rituximab / Rituxan, Trastuzumab / Herceptin, Gemtuzumab, ozogamicin / Mylotarg, Alemtuzumab / Campath, Imatinib / Gleevec, Bcr-Abl / Kit, Ibritumomab, tiuxetan / Zevalin, Tositumomabfiti Velcade, Bevacizumab / Avastin, Cetuximab / Erbitux, Erlotinib / Tarceva, Azacitidine / Vidaza, Sorafenib / Nexavar, Sunitinib / Sutent, Dasatinib / Sprycel, Panitumumab / Vectibix, Vorinostat / Zolinza, Decitabpat / Dolin, T Nilotinib / Tasigna, Everolimus / Afinitor, Pazopanib / Votrient, Ofatumumab / Arzerra, Romidepsin / Istodax, Denosumab / Ranmark, Ipilimumab / Yervoy, Vandetanib / Caprelsa, Vemurafenib / Zelboraf, Brentuximabristintin C / Inlyta, Vismodegib / Erivedge, Mogamulizumab / Poteligeo, Pertuzumab / Perjeta, Carfilzomib / Kyprolis, Ziv-aflibercept / Zaltrap, Bosutinib / Bosulif, Regorafenib / Stivarga, Cabozantinib / Cometriq, PontinibTrclus uzumab emtansine / Kadcyla, Dabrafenib / Tafinlar, Trametinib / Mekinist, Afatinib / Gilotrif, Obinutuzumab / Gazyva, Ibrutinib / Imbruvica, Ramucirumab / Cyramza, Ceritinib / Zykadia, Belinostat / BeleodabN / Keytruda, Nintedanib / Vargatef, Blinatumomab / Blincyto, Olaparib / Lynparza, Palbociclib / Ibrance, Lenvatinib / Lenvima, Panobinostat / Farydak, Dinutuximab / Unituxin, Sonidegib / Odomzo, Cobimetinib / Cotellicatum / Cotellicatum Elotsuzumab / Empliciti, Ixazomib / Ninlaro and the like.
　本発明はより具体的な態様として、大腸がん細胞におけるABL1、CDK12、HCK、JAK2、LCK、LYN、MAP2K6、MAPK12、MAPK14、PRKCD、YES1、DYRK4の中から選ばれる少なくとも１つの責任キナーゼのリン酸化修飾活性を阻害する物質をスクリーニングするための方法に関する。これらのキナーゼに対するリン酸化修飾活性阻害物質は、セツキシマブ耐性患者を処置・予防できる可能性が高い。 As a more specific embodiment, the present invention provides a phosphorylation of at least one responsible kinase selected from ABL1, CDK12, HCK, JAK2, LCK, LYN, MAP2K6, MAPK12, MAPK14, PRKCD, YES1, and DYRK4 in colon cancer cells. The present invention relates to a method for screening a substance that inhibits oxidation-modifying activity. Phosphorylation-modifying activity inhibitors for these kinases are likely to treat / prevent cetuximab-resistant patients.
＜被験者の層別化など＞
　本発明はさらなる別の態様として、有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患に罹患している被験者において、当該疾患を処置または予防する治療薬が有効か、有効でないかを判定することによって、被験者を層別化する方法であって、
　１）ある被験者においてある治療薬が有効なのか有効でないのか、を判定するための責任キナーゼをスクリーニングする本発明の方法によって薬効予測標的である責任キナーゼをスクリーニングし、
　２）当該被験者において、当該疾患を処置または予防する治療薬の有効性を予測するために使用される責任キナーゼが不存在の場合、当該被験者は当該治療薬が有効である群に割り付け、責任キナーゼが存在する場合、当該被験者は当該治療薬が有効でない群に割り付け、被験者を層別化する方法に関する。
　本明細書の層別化方法は、個別化医療に有益である。従来からの患者への標準的治療法は、同じ疾患と診断されると同じ治療薬が投与され、この方法では一部の患者に効果があっても、他の患者には効果がなく、または重篤な副作用をもたらす場合がある。そこで、注目されるのが、個別化医療である。近年、病気の原因や病態に関連する遺伝子やタンパク質などが分子レベルで解明され、同じ疾患と診断された患者でも、実際には病気の原因や病態に関連する分子の違いにより様々なタイプに分類できることが分かってきた。このような患者ごとの病気や病態の原因分子を調べ、直接作用する薬を投与して病気を治し病態を改善することが、個別化医療である。本発明による患者の層別化方法は、高い治療効果が期待でき、副作用を抑えられる個別化医療に有益であり、患者に安心感を与え、QOLの向上が見込め、なによりも最適な治療法を患者さんに提供できる利便性がある。そして、効果が得られる確実な治療法を提供できることは、費用対効果による国民の医療費全体の抑制をもたらす。 <Subject stratification, etc.>
In another aspect, the present invention provides a subject suffering from a disease selected from among diseases for which there is no effective therapeutic agent, advanced cancer with high malignancy, and cancer having characteristic cancer characteristics. A method for stratifying subjects by determining whether a therapeutic agent for treating or preventing the disease is effective or ineffective, comprising:
1) screening for a responsible kinase that is a target for predicting drug efficacy by the method of the present invention for screening a responsible kinase for determining whether a therapeutic agent is effective or ineffective in a subject;
2) If the responsible kinase used to predict the effectiveness of a therapeutic agent to treat or prevent the disease in the subject is absent, the subject is assigned to the group for which the therapeutic agent is effective, and the responsible kinase If the subject is present, the subject is assigned to a group where the therapeutic agent is not effective and the subject is stratified.
The stratification methods herein are useful for personalized medicine. Traditional treatments for traditional patients are administered the same therapeutic agent when diagnosed with the same disease, and this method is effective for some patients but not for others, or May cause serious side effects. Therefore, personalized medicine is attracting attention. In recent years, genes and proteins related to the cause and pathology of diseases have been elucidated at the molecular level, and even patients diagnosed with the same disease are actually classified into various types according to differences in the molecules related to the cause and pathology of the disease. I know I can do it. It is personalized medicine that examines the causative molecules of such diseases and pathologies for each patient and administers directly acting drugs to cure the disease and improve the pathology. The method of stratification of patients according to the present invention is useful for personalized medicine that can be expected to have a high therapeutic effect and suppress side effects, gives the patient a sense of security, and is expected to improve QOL. Can be provided to patients. And the ability to provide reliable treatments that are effective results in a reduction in the overall cost of medical care for the public due to cost effectiveness.
　以下、本発明を実施例により、詳細に説明するが、これらは本発明の範囲を限定するものでなく、単なる例示である。 Hereinafter, the present invention will be described in detail by way of examples, but these are not intended to limit the scope of the present invention but are merely examples.
　実施例で使用する試薬および抗体は以下の製造元から購入し、基本、製造元の教示に従って使用した。
　リポフェクタミンRNAiMax、ペニシリン－ストレプトマイシン、タンデム・マス・タグ (ＴＭＴ）１０プレックス等圧性ラベル試薬セット、免疫沈降のための磁性ダイナビーズタンパク質ＧおよびＦＢＳは、Thermo Fisher Scientific (Waltham, MA, USA)から入手した。ケミ－ルミスーパーおよびＤＭＥＭはナカライテスク（京都、日本）から購入した。ＫＸ－３９１およびＳＵ６６５６はSelleck (Houston, TX, USA)から購入した。PhosSTOPホスファターゼインヒビターカクテル、トリプシンおよびcOmpleteプロテアーゼインヒビターカクテルはRoche (Basel, Switzerland)から入手した。トリス緩衝生理食塩水（ＴＢＳ）およびリン酸緩衝生理食塩水（ＰＢＳ）錠はタカラ（滋賀、日本）から入手した。detergent compatible (DC)プロテインアッセイはBio-Rad (Hercules, CA, USA)から購入した。ドデシル硫酸ナトリウムポリアクリルアミドゲル電気泳動（ＳＤＳ－ＰＡＧＥ）用XV Pantera gel（５－２０％）はＤＲＣ（東京、日本）から購入した。RNA-direct SYBRグリーンリアルタイムＰＣＲマスターミックスは東洋紡（大阪、日本）から入手した。プリズム６ソフトウェアパッケージはGraphPad Software (La Jolla, CA, USA)から購入した。Cell Counting Kit-8はDojindo（熊本、日本）から入手した。セツキシマブはMerck KGaA (Darmstadt, Germany)からの贈り物であった。 Reagents and antibodies used in the examples were purchased from the following manufacturers and used according to the basic and manufacturer's instructions.
Lipofectamine RNAiMax, penicillin-streptomycin, tandem mass tag (TMT) 10plex isobaric label reagent set, magnetic dynabead protein G and FBS for immunoprecipitation were obtained from Thermo Fisher Scientific (Waltham, MA, USA). . Chemi-Lumi Super and DMEM were purchased from Nacalai Tesque (Kyoto, Japan). KX-391 and SU6656 were purchased from Selleck (Houston, TX, USA). PhosSTOP phosphatase inhibitor cocktail, trypsin and cOmplete protease inhibitor cocktail were obtained from Roche (Basel, Switzerland). Tris buffered saline (TBS) and phosphate buffered saline (PBS) tablets were obtained from Takara (Shiga, Japan). The detergent compatible (DC) protein assay was purchased from Bio-Rad (Hercules, CA, USA). XV Pantera gel (5-20%) for sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) was purchased from DRC (Tokyo, Japan). RNA-direct SYBR green real-time PCR master mix was obtained from Toyobo (Osaka, Japan). The Prism 6 software package was purchased from GraphPad Software (La Jolla, CA, USA). Cell Counting Kit-8 was obtained from Dojindo (Kumamoto, Japan). Cetuximab was a gift from Merck KGaA (Darmstadt, Germany).
　ｐＭＥＫ１／２のＳ２１７／２２１（４１Ｇ９）、ｐＥＲＫ１／２のＴ２０２／Ｙ２０４（Ｄ１３．１４．４Ｅ）、およびリン酸化チロシン（Ｐ－Ｔｙｒ－１０００）MultiMab抗体はCell Signaling Technology (Danvers, MA, USA)から入手した。ＭＥＫ１／２（９Ｇ３）およびＥＲＫ１／２（ＭＫ１）はSantaCruz (Dallas, TX, USA)から購入した。ＧＡＰＤＨ（６Ｃ５）抗体はAbcam (Cambridge, UK)から入手した。ＳＲＣ（３２７）抗体はMerck KGaAから入手した。ｐＳＲＣ Ｙ４１８抗体はThermo Fisher Scientificから購入した。 pMEK1 / 2 S217 / 221 (41G9), pERK1 / 2 T202 / Y204 (D13.14.4E), and phosphorylated tyrosine (P-Tyr-1000) MultiMab antibody are available from Cell Signaling Technology (Danvers, MA, USA). Obtained from MEK1 / 2 (9G3) and ERK1 / 2 (MK1) were purchased from SantaCruz (Dallas, TX, USA). GAPDH (6C5) antibody was obtained from Abcam (Cambridge, UK). SRC (327) antibody was obtained from Merck KGaA. The pSRC Y418 antibody was purchased from Thermo Fisher Scientific.
実施例１
セツキシマブ感受性または耐性の大腸がん細胞株のリン酸化プロテオミクス解析
　高感度チロシンリン酸化プロテオミクス解析とＩＭＡＣに基づく高感度リン酸化プロテオミクス解析を組み合わせ、大腸がん細胞株における大量のリン酸化プロテオミクスデータを得た。
１．１　細胞培養および試料収集
　ＤＬＤ１、ＬＩＭ１２１５、ＨＴ２９、ＨＣＴ１１６、Ｃｏｌｏ２０５およびＳＷ４８０細胞（ATCCより購入）を５％ＣＯ２下、３７℃で培養した。これら大腸細胞株を、１０％ウシ胎仔血清（ＦＢＳ）およびペニシリン－ストレプトマイシンを添加したダルベッコ改変イーグル培地（ＤＭＥＭ）中で維持した。各実験開始の一日前に培養液を１０％ＦＢＳを含むＤＭＥＭから１％ＦＢＳを含むＤＭＥＭに変えた。５％ウシ胎仔血清（ＦＢＳ）培地中に存在する多くの増殖因子は感受性細胞株におけるセツキシマブの効果を妨害するため、１％ＦＢＳを添加したＤＭＥＭ中で大腸がん細胞株を培養し、アッセイした。PhosSTOPおよびcOmpleteを含む氷冷ＰＢＳ緩衝液で洗浄後、大腸細胞を回収した。収集した細胞のペレットを液体窒素中で急速に凍結し、使用するまで－８０℃で保管した。続くリン酸化プロテオミクス解析およびチロシンリン酸化プロテオミクス解析のため、セツキシマブ処理前または後の各細胞株について、三回の生物学的反復を行った。 Example 1
Phosphorylated proteomics analysis of cetuximab-sensitive or resistant colorectal cancer cell lines A combination of high-sensitivity tyrosine phosphorylation proteomics analysis and high-sensitivity phosphorylation proteomics analysis based on IMAC resulted in large amounts of phosphorylated proteomics data in colorectal cancer cell lines .
1.1 Cell culture and sample collection DLD1, LIM1215, HT29, HCT116, Colo205 and SW480 cells (purchased from ATCC) were cultured at 37 ° C. under 5% CO 2 . These colon cell lines were maintained in Dulbecco's Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and penicillin-streptomycin. One day before the start of each experiment, the culture medium was changed from DMEM containing 10% FBS to DMEM containing 1% FBS. Because many growth factors present in 5% fetal bovine serum (FBS) medium interfere with the effects of cetuximab in sensitive cell lines, colon cancer cell lines were cultured and assayed in DMEM supplemented with 1% FBS. . After washing with an ice-cold PBS buffer containing PhosSTOP and cOmplete, colon cells were collected. Collected cell pellets were rapidly frozen in liquid nitrogen and stored at −80 ° C. until use. Three biological replicates were performed for each cell line before or after cetuximab treatment for subsequent phosphorylation proteomic analysis and tyrosine phosphorylation proteomic analysis.
１．２　各培養細胞におけるセツキシマブ処理後の細胞増殖能
　大腸がん細胞株に対するセツキシマブ処理にあたって、処理開始２４時間前に各細胞株を継代し、５％ＦＢＳ入り培地で培養した。セツキシマブ処理を７２時間行い、細胞増殖能に与える影響をCell Counting Kit-8により計測した。
　セツキシマブ処理は明らかにＤＬＤ１およびＬＩＭ１２１５細胞の増殖を阻害したが、高濃度（５０μｇ／ｍｌ）のセツキシマブを添加したときでさえ、セツキシマブ処理はＨＣＴ１１６およびＨＴ２９細胞の増殖には影響しなかった（図１ｂ）。それゆえ、我々はＤＬＤ１およびＬＩＭ１２１５細胞をセツキシマブ感受性群として定義し、ＨＣＴ１１６およびＨＴ２９細胞をセツキシマブ耐性群として定義した。 1.2 Cell proliferation ability after treatment with cetuximab in each cultured cell In the treatment with cetuximab for a colon cancer cell line, each cell line was subcultured 24 hours before the treatment and cultured in a medium containing 5% FBS. Cetuximab treatment was performed for 72 hours, and the effect on cell proliferation ability was measured with Cell Counting Kit-8.
Cetuximab treatment clearly inhibited the growth of DLD1 and LIM1215 cells, but cetuximab treatment did not affect the growth of HCT116 and HT29 cells, even when high concentrations (50 μg / ml) of cetuximab were added (FIG. 1b). ). Therefore, we defined DLD1 and LIM1215 cells as cetuximab sensitive groups and HCT116 and HT29 cells as cetuximab resistant groups.
１．３　高感度リン酸化（ｐＳＴＹ）プロテオミクスおよびチロシンリン酸化（ｐＹ）プロテオミクスのための試料調製
　既報のように（１４）、cOmpleteプロテアーゼインヒビターカクテルおよびPhosSTOPを添加した相間移動溶解緩衝液中で、細胞ペレットの溶解を行った。製造元のプロトコルに従って、ＤＣプロテインアッセイ(Bio-Rad)でタンパク質濃度を測定した。ｐＳＴＹおよびチロシンリン酸化プロテオミクスの実験手順を図１ａに要約する。既報のように（３４）、タンパク質溶解液２．０ｍｇを還元・アルキル化し、続いてトリプシン処理した。既報のように（３４）、界面活性剤を除去した。既報のように（３５）、タンパク質溶解液２．０ｍｇからリン酸化ペプチド（phosphopeptide）の第一の濃縮を、Ｆｅ３＋ ＩＭＡＣ樹脂を用いて行った。製造元のプロトコルに従って、リン酸化ペプチドをＴＭＴ １０プレックス試薬で標識した。全２０ｍｇの標識したリン酸化ペプチド混合物を調製し、凍結乾燥した。２０ｍｇの混合物の内、４．０ｍｇをｐＳＴＹプロテオミクスにおける分画に用い、残り（１６ｍｇ）をリン酸化チロシン免疫沈降（ｐＹ－ＩＰ）実験にそれぞれ用いた。以前に公開されたプロトコル（３６）に従って、ｐＳＴＹプロテオミクスにおけるリン酸化ペプチドを七つの分画に分割した。ｐＹ－ＩＰの実験において、先行研究（１４）のプロトコルに従って、リン酸化チロシンペプチドを濃縮した。 1.3 Sample Preparation for Sensitive Phosphorylation (pSTY) Proteomics and Tyrosine Phosphorylation (pY) Proteomics As previously reported (14), cells were transferred in phase transfer lysis buffer supplemented with cOmplete protease inhibitor cocktail and PhosSTOP. The pellet was dissolved. Protein concentration was measured with a DC protein assay (Bio-Rad) according to the manufacturer's protocol. The experimental procedure for pSTY and tyrosine phosphorylated proteomics is summarized in FIG. As previously reported (34), 2.0 mg of protein lysate was reduced and alkylated, followed by trypsinization. The surfactant was removed as previously reported (34). As previously reported (35), the first concentration of phosphopeptide from 2.0 mg protein solution was performed using Fe 3+ IMAC resin. The phosphorylated peptide was labeled with TMT 10 plex reagent according to the manufacturer's protocol. A total of 20 mg of labeled phosphopeptide mixture was prepared and lyophilized. Of the 20 mg mixture, 4.0 mg was used for fractionation in pSTY proteomics and the rest (16 mg) was used for phosphorylated tyrosine immunoprecipitation (pY-IP) experiments. The phosphorylated peptide in pSTY proteomics was divided into seven fractions according to a previously published protocol (36). In the pY-IP experiment, phosphorylated tyrosine peptides were enriched according to the protocol of the previous study (14).
１．４　ＬＣ－ＭＳ／ＭＳ分析
　ＬＣ－ＭＳ／ＭＳ分析を、UltiMate 3000ナノＬＣシステム(Thermo Scientific)およびHTC-PAL(CTC Analytics, Zwingen, Switzerland)を備えるQ Exactive Plus質量分析計(Thermo Scientific)を用いて行った。ＬＣ移動相において、緩衝液Ａ（０．１％ギ酸、２％アセトニトリル）および緩衝液Ｂ（0.1％ギ酸、90％アセトニトリル）を用いた。
　Q Exactive Plus装置をデータ依存モード下、以下の条件で操作した：加熱キャピラリー温度(Heated capillary temperature)、250℃；スプレー電圧(spray voltage)、2kV。測定の際には、pSTYおよびpYプロテオミクス中のペプチドを、Acclaim PepMap RSLCナノトラップカラム（0.1mm×20mm、Thermo Fisher Scientific）上にトラップし、次いで、分析カラム（75μm×30cm、ReproSil-Pur C18-AQ、1.9μm樹脂を充填したもの）に移した。ペプチドは、５分間から３０分間の緩衝液Ｂを１３５分間（pSTYプロテオミクス）または４５分間（pYプロテオミクス）勾配を用いて280nL/分の流速で分離した。サーベイフルスキャンMSスペクトルはオービトラップで350～1800m/zで、分解能は70,000、AGCは1E6で取得した。MSMSのTOPNはpSTYプロテオミクスで12(インジェクション・タイム、Injection time =120 msec)、pYプロテオミクスで6(インジェクション・タイム = 240 msec)に設定した。開裂法は高エネルギー衝突解離（ＨＣＤ）法を採用した。アイソレーション・ウインドウはpSTYプロテオミクスで2.0Da、pYプロテオミクスで3.0Daであった。コリジョンエナジーは25％（pSTYプロテオミクス）または30％（pYプロテオミクス）であった。 1.4 LC-MS / MS analysis LC-MS / MS analysis was performed on a Q Exactive Plus mass spectrometer (Thermo Scientific) equipped with an UltiMate 3000 nano LC system (Thermo Scientific) and HTC-PAL (CTC Analytics, Zwingen, Switzerland). It was performed using. In the LC mobile phase, buffer A (0.1% formic acid, 2% acetonitrile) and buffer B (0.1% formic acid, 90% acetonitrile) were used.
The Q Exactive Plus apparatus was operated in the data dependent mode under the following conditions: Heated capillary temperature, 250 ° C .; spray voltage, 2 kV. For measurement, the peptides in pSTY and pY proteomics were trapped on an Acclaim PepMap RSLC nanotrap column (0.1 mm × 20 mm, Thermo Fisher Scientific) and then analyzed column (75 μm × 30 cm, ReproSil-Pur C18- AQ, filled with 1.9 μm resin). Peptides were separated at a flow rate of 280 nL / min using Buffer B from 5 minutes to 30 minutes with a gradient of 135 minutes (pSTY proteomics) or 45 minutes (pY proteomics). Survey-scan MS spectra were acquired with orbitrap at 350-1800 m / z, resolution of 70,000, and AGC at 1E6. The MSMS TOPN was set to 12 (injection time, injection time = 120 msec) for pSTY proteomics and 6 (injection time = 240 msec) for pY proteomics. As the cleavage method, a high energy collision dissociation (HCD) method was adopted. The isolation window was 2.0 Da for pSTY proteomics and 3.0 Da for pY proteomics. Collision energy was 25% (pSTY proteomics) or 30% (pY proteomics).
１．５　ペプチド同定のためのデータ処理
　２６２のコモン・コンタミナント(common contaminant)を組み合わせたヒトプロテオームを精選するUniprotに対して検索を行うMaxQuant 1.5.1.2（2011_11公開）を用い、質量分析計生データを処理した（３７）。MaxQuantでのペプチド同定のパラメーターは以下の通りである。Fixed modification: Carbamidomethyl (システイン)、TMTタグ（リジンおよびペプチドN末端）。Variable modification: タンパク質N末端上のアセチル化、Oxidation(メチオニン)、リン酸化（セリン、スレオニンおよびチロシン）。Miss Cleavage: 2, タンパク質、ペプチド、およびPTMサイトレベルでのFDR < 0.01。「コンタミナントの可能性あり」のアノテーション(annotaion)を持つペプチドを後の分析（１．６以降）で処分した。「主要な(leading)タンパク質」として同定されたリン酸化部位を、後の解析で用いた。リン酸化部位の選定のためのカットオフの基準は既報のもの（３８）と同じであった：アンドロメダスコア、４０；アンドロメダデルタスコア、８；局在化確率、０．７５。 1.5 Data Processing for Peptide Identification Mass Spectrometer raw data using MaxQuant 1.5.1.2 (published on 2011_11) that searches Uniprot for selecting human proteomes that combine 262 common contaminants Was processed (37). The parameters for peptide identification with MaxQuant are as follows. Fixed modification: Carbamidomethyl (cysteine), TMT tag (lysine and peptide N-terminus). Variable modification: Acetylation, Oxidation (methionine), phosphorylation (serine, threonine and tyrosine) on the protein N-terminus. Miss Cleavage: 2, FDR <0.01 at the protein, peptide, and PTM site level. Peptides with the “possibility of contamination” annotation were discarded for later analysis (1.6 and later). The phosphorylation site identified as “leading protein” was used in subsequent analyses. Cut-off criteria for selection of phosphorylation sites were the same as previously reported (38): Andromeda score, 40; Andromeda Delta score, 8; Localization probability, 0.75.
１．６　同定されたクラス１リン酸化部位の統計解析
　リン酸化プロテオミクス解析からの定量データの統計解析を、Perseus 1.5.0.31 (www.perseus-framework.org)を用いて行った（３９）。強度(intensity)「０」のリン酸化部位を欠損値として後の解析から除外した。このデータをｌｏｇ２変換し、各試料における中央値補正を用いて正規化した。各TMTセットから得たデータをセット毎に標準試料（各細胞株の混合サンプル）のデータを用いて正規化した。耐性細胞株において有意な増加を示すリン酸化部位の精製のため、セツキシマブ感受性細胞株（Ｎ＝６、ＤＬＤ１およびＬＩＭ１２１５細胞の平均）またはセツキシマブ耐性大腸細胞株（Ｎ＝３、ＨＣＴ１１６細胞またはＨＴ２９細胞）の間で同定されたクラス１リン酸化部位の倍率変化およびｑ値を計算した。最初に、これらのプロテオミクス解析の実験誤差を評価し、感受性群と各耐性細胞株との間の定量的な差に関するカットオフ基準を設定した。二つの標準試料（１２６、１２７Ｎ）間の倍率変化のＳＤをTMTセット毎に計算し、３セットのＳＤの平均を計算した。ｐＳＴＹプロテオミクスおよびチロシンリン酸化プロテオミクスにおける平均のＳＤ値はそれぞれ０．４９４および０．２７７であった。増加したリン酸化部位を、平均値からＳＤの２倍以上のリン酸化部位の発現を伴うものとして同定し、これは０．９８９（ｐＳＴＹプロテオミクス）および０．５５４（チロシンリン酸化プロテオミクス）の倍率変化に対応した。 1.6 Statistical analysis of identified class 1 phosphorylation sites Statistical analysis of quantitative data from phosphorylated proteomics analysis was performed using Perseus 1.5.0.31 (www.perseus-framework.org) (39). A phosphorylation site of intensity “0” was excluded from later analysis as a missing value. This data was log2 transformed and normalized using median correction in each sample. Data obtained from each TMT set was normalized for each set using data of a standard sample (mixed sample of each cell line). For purification of phosphorylation sites that show a significant increase in resistant cell lines, cetuximab sensitive cell lines (N = 6, average of DLD1 and LIM1215 cells) or cetuximab resistant colon cell lines (N = 3, HCT116 cells or HT29 cells) The fold change and q value of the class 1 phosphorylation sites identified between were calculated. Initially, experimental errors in these proteomic analyzes were evaluated and a cut-off criterion for quantitative differences between sensitive groups and each resistant cell line was established. The SD of the fold change between the two standard samples (126, 127N) was calculated for each TMT set, and the average of the three sets of SDs was calculated. The average SD values for pSTY proteomics and tyrosine phosphorylated proteomics were 0.494 and 0.277, respectively. Increased phosphorylation sites were identified as being accompanied by expression of phosphorylation sites more than twice SD from the mean, which is a fold change of 0.989 (pSTY proteomics) and 0.554 (tyrosine phosphorylated proteomics) Corresponded to.
　次に、両側のウェルチのt検定を用いてｐ値を計算し、それらを並べ替え検定(permutation test)による多重検定補正を実行してｑ値に調整した。ｑ値のカットオフ基準は０．０５に設定した。図２に示すボルケーノプロットをRのパッケージ「ggplot2」を用いて作成した。
　図２ａ、ｂは、各リン酸化部位の倍率変化・q値を用いたボルケーノプロットを示した。各耐性群細胞株（ａ：ＨＣＴ１１６、Ｎ＝３、ｂ：ＨＴ２９、Ｎ＝３）のリン酸化プロテオミクスの発現データの平均を、各感受性群細胞株（ＤＬＤ１およびＬＩＭ１２１５、Ｎ＝６）におけるデータの平均と比較した。中間灰色は有意に増加したリン酸化部位を示す。濃い灰色は有意に減少したリン酸化部位を示す。薄い灰色の円は差がなかったリン酸化部位である。 Next, p-values were calculated using Welch's t-test on both sides, and they were adjusted to q-values by performing multiple test corrections by permutation test. The cut-off criterion for the q value was set to 0.05. The Volcano plot shown in FIG. 2 was created using the R package “ggplot2”.
2a and 2b show Volcano plots using the fold change and q value of each phosphorylation site. The average of the phosphorylated proteomic expression data of each resistant group cell line (a: HCT116, N = 3, b: HT29, N = 3) is the data of each sensitive group cell line (DLD1 and LIM1215, N = 6). Compared to the average. Middle gray indicates a significantly increased phosphorylation site. Dark gray indicates significantly reduced phosphorylation sites. The light gray circle is the phosphorylation site that was not different.
１．７　サンプル中のEGFRシグナル経路活性に関するウェスタンブロットによる評価
　ドデシル硫酸ナトリウムポリアクリルアミドゲル電気泳動（SDS-PAGE）のために、まずPTS緩衝液中の細胞溶解物をサンプル緩衝液（350mM Tris-HCl（pH6.8）、34.7mM SDS、30％グリセロール、60mMジチオスレイトール）と混合し、95℃で5分間煮沸した。細胞溶解物を適用し、120Vおよび400mAで35分間電気泳動し、タンパク質を分離した。タンパク質をポリビニリデンジフルオリド（PVDF）膜に40Vおよび400mAで70分間タンパク質を転写した。 PVDF膜を特異抗体およびホースラディッシュペルオキシダーゼ結合抗体で検出して処理し、タンパク質発現量・リン酸化修飾量を評価した。得られた結果を図１ｃに示す。 1.7 Evaluation by Western Blot for EGFR Signal Pathway Activity in Samples For sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), cell lysates in PTS buffer were first sampled in sample buffer (350 mM Tris-HCl). (PH 6.8), 34.7 mM SDS, 30% glycerol, 60 mM dithiothreitol) and boiled at 95 ° C. for 5 minutes. Cell lysates were applied and electrophoresed at 120V and 400mA for 35 minutes to separate proteins. The protein was transferred to a polyvinylidene difluoride (PVDF) membrane at 40 V and 400 mA for 70 minutes. The PVDF membrane was detected and treated with a specific antibody and a horseradish peroxidase-conjugated antibody, and the protein expression level and phosphorylation modification level were evaluated. The results obtained are shown in FIG.
　セツキシマブは抗ＥＧＦＲ抗体であるため、我々は最初に、各群におけるＥＧＦＲシグナル伝達経路内のキナーゼの活性状態を解析した。５μｇ／ｍｌセツキシマブ処理は、セツキシマブ感受性群において下流のキナーゼ（ＥＲＫ１／２のＴ２０２／Ｙ２０４およびＭＥＫ１／２のＳ２１７／Ｓ２２１）のリン酸化を阻害していたが、セツキシマブ耐性群では一様な下流キナーゼの低下は認められなかった。例えば、セツキシマブ処理はＨＴ２９においてｐＭＥＫ１／２の発現レベルを低下させたが、ＨＣＴ１１６ではそうではなかった（図１ｃ）。これらの結果は、セツキシマブ処理後のリン酸化シグナル伝達はセツキシマブ耐性細胞間で異なり得ることを示している。 Since cetuximab is an anti-EGFR antibody, we first analyzed the active state of kinases in the EGFR signaling pathway in each group. 5 μg / ml cetuximab treatment inhibited phosphorylation of downstream kinases (ERK1 / 2 T202 / Y204 and MEK1 / 2 S217 / S221) in the cetuximab sensitive group, but uniform downstream kinases in the cetuximab resistant group There was no decline. For example, cetuximab treatment reduced the expression level of pMEK1 / 2 in HT29, but not in HCT116 (FIG. 1c). These results indicate that phosphorylation signaling after cetuximab treatment can differ between cetuximab resistant cells.
１．８　結果
　各耐性細胞株で活性化するキナーゼを明らかにするため、セツキシマブ感受性および耐性大腸がん細胞株を用い、高感度リン酸化プロテオミクス解析を行った。図１ａに示すように、ｐＳＴＹおよびチロシンリン酸化プロテオミクス解析において、それぞれ４．０および１６．０ｍｇのタンパク質可溶化液を用いた。三回の実験において、ｐＳＴＹプロテオミクス解析は全体で１３，４１１のクラス１リン酸化部位(class 1 phosphosite)を同定し、チロシンリン酸化プロテオミクス解析は１，３０８のクラス１ リン酸化チロシン部位を同定した（図１ｄ）。ｐＳＴＹプロテオミクス・チロシンリン酸化プロテオミクスで同定されたリン酸化部位の内、PhosphositePlusで登録済みのものは、それぞれわずか5.2%（１３，４１１の部位中の６９９のｐＳＴＹ部位）および13.1%（１，３０８の部位中の１７２のリン酸化チロシン部位）であった。これは本発明におけるリン酸化プロテオミクス解析手法によって未知のリン酸化シグナル伝達に該当する情報を取得できたことを示している。さらなる統計解析のため、各三回の全ての実験においてクラス１部位として同定された、７，７２７のｐＳＴＹ部位および６８２のリン酸化チロシン部位をその後の解析に用いた。予想通り、ｐＳＴＹプロテオミクスから同定されたリン酸化チロシン部位の割合は低く（＜１％、７，７２７のｐＳＴＹ部位中の２９のリン酸化チロシン部位）、本研究で検出された６８２のリン酸化チロシン部位のほとんどは、チロシンリン酸化プロテオミクスの手法によってのみ同定された（図１ｅ）。これらの結果は、ｐＳＴＹとチロシンリン酸化リン酸化プロテオミクス解析の組み合わせが、セリン、スレオニンおよびチロシン残基を包括する、リン酸化状態高感度測定にとって効率的な手法であることを示している。 1.8 Results In order to clarify the kinase activated in each resistant cell line, highly sensitive phosphorylated proteomic analysis was performed using cetuximab-sensitive and resistant colon cancer cell lines. As shown in FIG. 1a, 4.0 and 16.0 mg protein lysates were used in pSTY and tyrosine phosphorylated proteomics analysis, respectively. In three experiments, pSTY proteomic analysis identified a total of 13,411 class 1 phosphosites and tyrosine phosphorylated proteomic analysis identified 1,308 class 1 phosphorylated tyrosine sites ( FIG. 1d). Of the phosphorylation sites identified in pSTY proteomics and tyrosine phosphorylation proteomics, only 5.2% (699 pSTY sites in 13,411 sites) and 13.1% (1,308 sites) were registered with PhosphositePlus, respectively. 172 phosphorylated tyrosine sites). This indicates that information corresponding to unknown phosphorylation signaling could be obtained by the phosphorylation proteomic analysis method of the present invention. For further statistical analysis, 7,727 pSTY sites and 682 phosphorylated tyrosine sites, identified as class 1 sites in all three experiments each, were used in subsequent analyses. As expected, the proportion of phosphorylated tyrosine sites identified from pSTY proteomics was low (<1%, 29 phosphorylated tyrosine sites in the 7,727 pSTY sites) and 682 phosphorylated tyrosine sites detected in this study. Most of these were only identified by tyrosine phosphorylated proteomics techniques (FIG. 1e). These results indicate that the combination of pSTY and tyrosine phosphorylated phosphorylation proteomics analysis is an efficient technique for phosphorylation state sensitive measurements involving serine, threonine and tyrosine residues.
実施例２
セツキシマブ耐性細胞で活性化するキナーゼの同定
２．１　セツキシマブ耐性細胞においてキナーゼ上で修飾されるリン酸化部位の特定
　キノームの活性プロファイリングは、薬剤感受性の予測に基づき抗がん剤治療を効率的に実施するために重要である。それゆえ、実施例１にて入手した高感度リン酸化プロテオミクスデータからセツキシマブ耐性細胞で活性化するキナーゼを同定するため、最初にセツキシマブ感受性群とセツキシマブ耐性群との間で有意な差を示すリン酸化部位を探索した。多くのキナーゼの活性は自身のリン酸化状態によって制御される（自己リン酸化）ことが広く知られている（１２）。従ってキノームの活性プロファイリングのため、まず、キナーゼ上で修飾されるリン酸化部位に注目した。 Example 2
Identification of kinases activated in cetuximab-resistant cells 2.1 Identification of phosphorylation sites that are modified on kinases in cetuximab-resistant cells Kinome activity profiling is effective for anticancer drug treatment based on prediction of drug sensitivity Is important to do. Therefore, in order to identify the kinase activated in cetuximab-resistant cells from the highly sensitive phosphorylated proteomics data obtained in Example 1, phosphorylation showing a significant difference between the cetuximab-sensitive group and the cetuximab-resistant group first. The site was searched. It is well known that the activity of many kinases is controlled by its own phosphorylation state (autophosphorylation) (12). Thus, for kinome activity profiling, we first focused on the phosphorylation sites modified on the kinase.
　有意な差を示すリン酸化部位の抽出のため、倍率変化（fold change）とt検定による統計的有意性に基づいたカットオフ値を定義した。倍率変化のカットオフの基準は、標準試料を用いて計算した実験誤差に基づいて定義した。三回のｐＳＴＹおよびチロシンリン酸化プロテオミクス解析における平均の二つのＳＤ値はそれぞれ、０．９８９および０．５５６であった。これらのデータに基づいて、倍率変化のカットオフを2SDにあたるｐＳＴＹプロテオミクスで１．９８５、チロシンリン酸化プロテオミクスで１．４７０に設定した。統計的有意性のカットオフは一律ｑ値（ｑ＜０．０５）に設定した。これら二つの閾値に基づいて、セツキシマブ感受性細胞群の平均値に対し、ＨＣＴ１１６およびＨＴ２９細胞において有意に増加するリン酸化部位を探索した（図２ａおよびｂ）。 In order to extract phosphorylation sites showing a significant difference, a cut-off value was defined based on statistical significance by fold change and t-test. The criteria for the magnification change cutoff was defined based on experimental errors calculated using standard samples. The average two SD values in triplicate pSTY and tyrosine phosphorylated proteomics analyzes were 0.989 and 0.556, respectively. Based on these data, the cutoff of the change in magnification was set to 1.985 for pSTY proteomics corresponding to 2SD, and 1.470 for tyrosine phosphorylated proteomics. The statistical significance cutoff was set at a uniform q value (q <0.05). Based on these two thresholds, we searched for a phosphorylation site that significantly increased in HCT116 and HT29 cells relative to the mean value of the cetuximab-sensitive cell population (FIGS. 2a and b).
　ＨＣＴ１１６細胞では、セツキシマブ処理または未処理において、それぞれキナーゼ上の３１および２９のリン酸化部位が有意に増加した。ＨＴ２９細胞の結果から、セツキシマブで処理または未処理において、それぞれキナーゼ上の１５および１９のリン酸化部位もまた増加した。 In HCT116 cells, phosphorylation sites 31 and 29 on the kinase were significantly increased either with or without cetuximab treatment. The results for HT29 cells also increased the 15 and 19 phosphorylation sites on the kinase, respectively, when treated or untreated with cetuximab.
２．２　活性化キナーゼ探索およびリン酸化ネットワークの構築
　有意差を伴うリン酸化部位の結果から、各耐性細胞株（ＨＣＴ１１６またはＨＴ２９）で活性なキナーゼ候補を同定し、それらのキナーゼのネットワークを再構築することを試みた。有望な活性化キナーゼの同定からキナーゼネットワークの再構築までの手順の概略を図３ａに示す。
　まず、活性化キナーゼを探索するため、二つの手法を用いた。
　Uniprotデータベースに記録されたキナーゼ上の活性制御リン酸化情報（１６）およびキナーゼ基質エンリッチメント解析（ＫＳＥＡ）の結果（１７）を用い、活性化キナーゼを選別した。有意に増加するリン酸化部位を特定した後、キナーゼ上の活性制御機能を持つリン酸化部位の数が増加しているキナーゼを選別した。ＫＳＥＡでの計算では、NetworKIN（４０）で予測したキナーゼ－基質関係（ＫＳＲ）を用いた。
　まず、我々は耐性細胞群にて存在量が増加していた(upregulated)リン酸化部位について、キナーゼの酵素活性の制御情報を付加した（図３ｂ）。各リン酸化部位の機能についての情報はUniprotデータベースから得た（１６）。 2.2 Search for activated kinase and construction of phosphorylation network From the results of phosphorylation sites with significant differences, identify active kinase candidates in each resistant cell line (HCT116 or HT29) and reconstruct the network of those kinases Tried to do. An outline of the procedure from the identification of a promising activated kinase to the reconstruction of the kinase network is shown in FIG. 3a.
First, two approaches were used to search for activated kinases.
Activated kinases were screened using activity-regulated phosphorylation information on kinases recorded in the Uniprot database (16) and results of kinase substrate enrichment analysis (KSEA) (17). After identifying a phosphorylation site that significantly increased, kinases with an increased number of phosphorylation sites having an activity control function on the kinase were selected. In the calculation with KSEA, the kinase-substrate relationship (KSR) predicted by NetworKIN (40) was used.
First, we added information on the regulation of kinase enzyme activity for phosphorylated sites that were upregulated in resistant cells (FIG. 3b). Information about the function of each phosphorylation site was obtained from the Uniprot database (16).
　第二に、ｐＳＴＹおよびチロシンリン酸化プロテオミクスを含む全体のリン酸化プロテオミクスデータから、バイオインフォマティクスの方法を用いて、活性化キナーゼを予測した。感受性細胞株と比較して耐性細胞株で活性化しているキナーゼを選別するため、キナーゼ基質エンリッチメント解析(kinase-substrate enrichment analysis)（ＫＳＥＡ）を適用した（１７）。セツキシマブ未処理条件における比較では、ＨＣＴ１１６細胞における二つのキナーゼがセツキシマブ感受性細胞群に比べて高活性であることが予測された。加えて、セツキシマブ処理の２４時間後において、一つのキナーゼが高活性であると予測された（図３ｂ）。ウエスタンブロッティングを行うことでこれらのキナーゼの酵素活性に関連するリン酸化状態を検証したところ、ＳＲＣのタンパク質発現は同等であるにもかかわらず、ＳＲＣ上でリン酸化部位の１つ(Y418)が増加していることが明らかとなった（図３ｄ）。 Second, activated kinases were predicted from the entire phosphorylated proteomic data including pSTY and tyrosine phosphorylated proteomics using bioinformatics methods. Kinase-substrate enrichment analysis (KSEA) was applied to select kinases activated in resistant cell lines compared to sensitive cell lines (17). Comparison in cetuximab untreated conditions predicted that the two kinases in HCT116 cells were more active than the cetuximab sensitive cell population. In addition, one kinase was predicted to be highly active 24 hours after cetuximab treatment (FIG. 3b). When the phosphorylation state related to the enzyme activity of these kinases was verified by performing Western blotting, one of the phosphorylation sites (Y418) increased on the SRC even though the protein expression of the SRC was equivalent. (Fig. 3d).
２．３　結果
　全体として、ＨＣＴ１１６細胞およびＨＴ２９細胞から、１５および４の活性なキナーゼ候補が選別された。タンパク質機能情報データベース上におけるキナーゼ活性制御リン酸化部位の実測値によって選別されたキナーゼ（表内の「キナーゼ」）、そのリン酸化によってキナーゼ活性が制御されるキナーゼのリン酸化部位候補（表内の「キナーゼ上の活性制御リン酸化部位」）、キナーゼ基質関連情報を使用する計算科学的手法によって得られるキナーゼ活性予測値によって選別されたキナーゼ、すなわちＫＳＥＡアルゴリズムで予測された活性化キナーゼ（表内の「ＫＳＥＡ」）、ＫＳＲを介して活性化キナーゼと結び付けられる上流のキナーゼ（表内の「キナーゼ活性制御リン酸化部位の責任キナーゼ」）、およびＣＯＳＭＩＣデータベース内でアノテートされた同定されたキナーゼの点変異（表内の「変異」）を要約し、表１に示す。 2.3 Results Overall, 15 and 4 active kinase candidates were selected from HCT116 and HT29 cells. Kinases selected according to the measured values of kinase activity-regulated phosphorylation sites in the protein function information database ("kinase" in the table), and phosphorylation site candidates for kinases whose kinase activity is controlled by the phosphorylation ("table" in the table) Activity-regulated phosphorylation sites on kinases), kinases selected by kinase activity predictions obtained by computational science techniques using kinase substrate related information, ie activated kinases predicted by the KSEA algorithm (“ KSEA "), upstream kinases linked to activated kinases via KSR (" kinase responsible phosphorylation site kinases "in the table), and point mutations of identified kinases annotated in the COSMIC database ( The “mutations” in the table are summarized and shown in Table 1.
Figure JPOXMLDOC01-appb-T000001
Figure JPOXMLDOC01-appb-T000001
　注目すべきことに、キナーゼ上のリン酸化部位のほとんど（全条件における＞７０％）がチロシンリン酸化プロテオミクスデータのみから同定されており（図３ｃ）、これは、チロシンリン酸化プロテオミクスを用いる解析がキナーゼのリン酸化状態に基づく活性プロファイリングに役立つことを示す。 Of note, most of the phosphorylation sites on the kinase (> 70% under all conditions) have been identified from tyrosine phosphorylated proteomics data only (FIG. 3c), which indicates that the analysis using tyrosine phosphorylated proteomics It is useful for activity profiling based on the phosphorylation state of kinase.
　加えて、本研究で用いた細胞株での活性なキナーゼ候補、責任キナーゼにおけるゲノム上の変異の存在をＣＯＳＭＩＣデータベースで調査した（１８）。しかしながら、ＡＢＬ１およびＬＣＫを除くこれらのキナーゼ遺伝子のほとんどにおいて、ゲノム変異の情報が帰属されていなかった。この事実は、リン酸化プロテオミクスの手法を用いることによるキノームの活性プロファイリングが、ゲノムの手法によって特定できない新規のコンパニオンマーカー(companion marker)の発見に有用であり得ることを示す。 In addition, the existence of mutations on the genome of active kinase candidates and responsible kinases in the cell lines used in this study was investigated in the COSMIC database (18). However, genomic mutation information was not assigned to most of these kinase genes except ABL1 and LCK. This fact indicates that kinome activity profiling by using phosphorylated proteomics techniques may be useful in the discovery of new companion markers that cannot be identified by genomic techniques.
実施例３：ＫＳＲによるキナーゼネットワークの構築
　リン酸化シグナル伝達の再構築（rewiring）は抗がん治療における薬剤耐性の原因の一つであることが報告されている（４）。例えば、治療標的の下流のキナーゼの構成的な活性化や他のキナーゼの予期せぬ活性化によって生じるバイパスシグナル伝達は、薬剤耐性の原因となる（または、薬剤耐性に関与する）（４）。セツキシマブ耐性大腸がん細胞株において再構築されたシグナル伝達カスケードについてその機構を検討するため、リン酸化シグナル伝達ネットワークを構築した。キナーゼネットワークの構成因子として図３に示す活性なキナーゼ候補を用い、それらを、PhosphositePlusデータベース（１５）に登録されている実験的に検証済みのＫＳＲで結び付けた。図４ａおよびｂは、１３の活性化キナーゼとそれらの２１のＫＳＲを結び付けることによる、ＨＣＴ１１６細胞におけるリン酸化ネットワークを示す。このネットワークにおいて、ＳＲＣからＰＲＫＣＤへのリン酸化シグナル伝達は、セツキシマブ処理の有無にかかわらず恒常的に活性化されていた。ＨＴ２９細胞では、活性化キナーゼの数が不十分なため、活性化リン酸化ネットワーク構築が限定的であった（図４ｃ、ｄ）。 Example 3: Construction of a kinase network by KSR It has been reported that rewriting of phosphorylation signaling is one of the causes of drug resistance in anticancer therapy (4). For example, bypass signaling caused by constitutive activation of kinases downstream of therapeutic targets or unexpected activation of other kinases causes (or is involved in) drug resistance (4). In order to investigate the mechanism of the reconstituted signaling cascade in the cetuximab-resistant colorectal cancer cell line, a phosphorylated signaling network was constructed. The active kinase candidates shown in FIG. 3 were used as the constituent factors of the kinase network, and they were linked with the experimentally verified KSR registered in the PhosphositePlus database (15). Figures 4a and b show the phosphorylation network in HCT116 cells by linking 13 activated kinases and their 21 KSRs. In this network, phosphorylation signaling from SRC to PRKCD was constitutively activated with or without cetuximab treatment. In HT29 cells, activation phosphorylation network construction was limited due to insufficient number of activated kinases (FIGS. 4c, d).
　我々は、ＨＣＴ１１６細胞においてＳＲＣからＰＲＫＣＤへのシグナル伝達カスケードがセツキシマブ処理に依存せず恒常的に活性化していることを発見した（図４ｂ）。またＫＥＧＧ（２７）において、ＥＧＦＲからＳＲＣへの直接的な制御の関係性がすでに登録されていることから、この結果はＥＧＦＲの下流の経路であるＳＲＣ－ＰＲＫＣＤカスケードがＨＣＴ１１６細胞におけるセツキシマブ耐性に関与し得ることを示唆している。ＳＲＣに加えて、ＹＥＳ１、ＬＹＮ、ＨＣＫおよびＬＣＫなどのＳｒｃファミリーキナーゼの他のメンバーもまた、ＨＣＴ１１６細胞における有望な活性なキナーゼとして発見された。以前に、ＥＧＦＲとＳｒｃファミリーキナーゼとの関係は、セツキシマブに対して耐性のある非小細胞肺がんおよび結腸がんにおいて示されていた（２２，２８）。 We found that the signal transduction cascade from SRC to PRKCD is constantly activated in HCT116 cells independent of cetuximab treatment (FIG. 4b). In addition, in KEGG (27), since a direct regulatory relationship from EGFR to SRC has already been registered, this result suggests that the SRC-PRKCD cascade, a pathway downstream of EGFR, is involved in cetuximab resistance in HCT116 cells It suggests that you can. In addition to SRC, other members of Src family kinases such as YES1, LYN, HCK and LCK were also discovered as promising active kinases in HCT116 cells. Previously, a relationship between EGFR and Src family kinases has been shown in non-small cell lung and colon cancers that are resistant to cetuximab (22, 28).
　我々は、以下の試験例１に示すように、ＨＣＴ１１６細胞において、ＭＡＰＫ１３のノックダウンが細胞増殖を低下させることを示し、ＭＡＰＫ１３が細胞増殖阻害を示す良好な標的であることが分かった。しかし、現在利用できるＫＳＲの範囲が制限されているため、公開データベース内の精選されたＫＳＲを用いた場合、ＭＡＰＫ１３の制御ネットワークを構築できなかった。図Ｓ２に示すように、リン酸化部位の＞８０％が、PhosphositePlusに登録されておらず、ＫＳＲ情報を本研究で検出されたリン酸化部位に付加できなかった。この限界は、リン酸化プロテオミクスデータに基づいたシグナル伝達ネットワークの包括的な解釈について困難となった。それゆえ、がんにおけるリン酸化シグナル伝達全体の制御機能を理解するためには、より高感度なＫＳＲの蓄積が必要とされる。さらに、リン酸化プロテオミクスデータ（３１）またはトランスクリプトーム（３２）などの他のオミクスのデータの組み合わせのネットワーク解析のための統計的方法は、細胞リン酸化シグナル伝達のよりよい理解を導くはずである。 As shown in Test Example 1 below, we have shown that MAPK13 knockdown decreases cell proliferation in HCT116 cells, and that MAPK13 is a good target for cell proliferation inhibition. However, since the range of KSR that can be used at present is limited, when a KSR selected in the public database is used, a MAPK13 control network cannot be constructed. As shown in FIG. S2,> 80% of phosphorylation sites were not registered with PhosphositePlus, and KSR information could not be added to the phosphorylation sites detected in this study. This limitation made it difficult for a comprehensive interpretation of signaling networks based on phosphorylated proteomics data. Therefore, more sensitive KSR accumulation is required to understand the overall regulatory functions of phosphorylation signaling in cancer. Furthermore, statistical methods for network analysis of combinations of other omics data such as phosphorylated proteomic data (31) or transcriptome (32) should lead to a better understanding of cellular phosphorylation signaling. .
試験例１
活性化キナーゼの阻害における耐性細胞の細胞増殖への影響
　ＨＣＴ１１６細胞の細胞増殖における活性なキナーゼ候補の機能的な役割を確認した。siRNAはサーモサイエンティフィック社より購入した。購入したsiRNAリストを以下に記載した。 Test example 1
Effect on cell proliferation of resistant cells in inhibition of activated kinase The functional role of active kinase candidates in cell proliferation of HCT116 cells was confirmed. siRNA was purchased from Thermo Scientific. The list of purchased siRNAs is described below.
表２
Figure JPOXMLDOC01-appb-T000002
 Table 2
Figure JPOXMLDOC01-appb-T000002
Figure JPOXMLDOC01-appb-T000003
Figure JPOXMLDOC01-appb-T000003
Figure JPOXMLDOC01-appb-T000004
Figure JPOXMLDOC01-appb-T000004
　ＨＣＴ１１６細胞を各キナーゼ、ＭＡＰＫ１、ＭＡＰＫ３、ＭＡＰＫ１３に特異的な三つのｓｉＲＮＡで処理し、定量逆転写ポリメラーゼ連鎖反応（ｑＲＴ－ＰＣＲ）によって、ＨＣＴ１１６細胞の生存率を分析した。 HCT116 cells were treated with three siRNAs specific to each kinase, MAPK1, MAPK3, and MAPK13, and the viability of HCT116 cells was analyzed by quantitative reverse transcription polymerase chain reaction (qRT-PCR).
１．１　ｓｉＲＮＡ／化学物質処理、細胞増殖アッセイ、およびＩＣ５０の計算
　製造元の説明書に従って、ｓｉＲＮＡをリポフェクタミンRNAiMaxで遺伝子導入した。ｓｉＲＮＡ導入の２４時間前にＨＣＴ１１６細胞を播種し、その後培養液を２０ｎＭ ｓｉＲＮＡを含む新たな培養液に取り替えた。処理開始後ＨＣＴ１１６細胞を３７℃で７２時間培養し、細胞増殖能への影響を検討した。化学物質を使用する場合、アッセイを開始する２４時間前にＨＣＴ１１６細胞を播種し、培養液を各用量の化学物質を含む新たな培養液に取り替えた。 1.1 siRNA / Chemical Treatment, Cell Proliferation Assay, and IC50 Calculations siRNA was transfected with Lipofectamine RNAiMax according to manufacturer's instructions. HCT116 cells were seeded 24 hours before the introduction of siRNA, and then the culture medium was replaced with a new culture medium containing 20 nM siRNA. After the treatment was started, HCT116 cells were cultured at 37 ° C. for 72 hours, and the influence on cell proliferation ability was examined. If chemicals were used, HCT116 cells were seeded 24 hours prior to the start of the assay, and the media was replaced with fresh media containing each dose of chemical.
　次いで、製造元のプロトコルに従い、細胞増殖アッセイをCell Counting Kit-8を用いて行った。ｓｉＲＮＡスクリーニングの結果を表Ｓ７に要約する。ｓｉＲＮＡスクリーニングの統計的有意性を、対応のあるスチューデントのt検定（両側）を用いて計算し、Rのパッケージ「p. adjust」機能内のBenjamini－Hochberg法を用いてq値に調整した。カーブフィッティングおよびＩＣ５０の計算を、プリズム６を用いて行った。 Then, according to the manufacturer's protocol, a cell proliferation assay was performed using Cell® Counting Kit-8. The results of siRNA screening are summarized in Table S7. Statistical significance of siRNA screening was calculated using paired Student's t-test (two-sided) and adjusted to q value using Benjamini-Hochberg method in R package “p. adjust” function. Curve fitting and IC50 calculations were performed using prism 6.
１．２　定量逆転写ポリメラーゼ連鎖反応
　ｓｉＲＮＡノックダウンの効率をｑＲＴ－ＰＣＲを用いて確認した。製造元の説明書に従って、ｍＲＮＡをRNeasy Plus Mini Kit (Qiagen, Hilden, Germany)を用いて精製した。ｑＲＴ－ＰＣＲ実験を、RNA-direct SYBRグリーンリアルタイムＰＣＲマスターミックスを用いて行った。ｑＲＴ－ＰＣＲのデータを比較(comparative)コンピュータ断層撮影法を用いて分析し、表Ｓ６に要約する。ｑＲＴ－ＰＣＲにおけるプライマー配列を表Ｓ８に乗せる。 1.2 Quantitative Reverse Transcription Polymerase Chain Reaction The efficiency of siRNA knockdown was confirmed using qRT-PCR. MRNA was purified using RNeasy Plus Mini Kit (Qiagen, Hilden, Germany) according to manufacturer's instructions. qRT-PCR experiments were performed using RNA-direct SYBR green real-time PCR master mix. qRT-PCR data were analyzed using comparative computed tomography and summarized in Table S6. Primer sequences in qRT-PCR are put on Table S8.
１．３　結果
　三つのキナーゼ（ＭＡＰＫ１、ＭＡＰＫ３、ＭＡＰＫ１３）のノックダウンが、各キナーゼのｓｉＲＮＡ三つ全てにおいて、細胞増殖を有意に減少させることが観察された（図５ａ、表Ｓ７）。加えて、六つのキナーゼ（ＣＤＫ１２、ＭＡＰＫ１２、ＭＡＰＫ１４、ＰＲＫＣＤ、ＳＲＣ、ＹＥＳ１）を標的とする三つのｓｉＲＮＡの内二つが、ＨＣＴ１１６細胞の増殖を有意に阻害した（図５ａ、表Ｓ７）。
　ＭＡＰＫ１およびＭＡＰＫ３（それぞれＥＲＫ２、ＥＲＫ１）は、ＥＧＦＲシグナル伝達の下流の因子となるキナーゼである（１９）。したがって、これらのキナーゼのノックダウンによる細胞増殖の減少は、セツキシマブ処理の耐性機構の一つがＥＧＦＲシグナル伝達の下流のキナーゼの活性化であることを示唆する。ＨＣＴ１１６細胞内のＥＲＫ１／２を介する下流のシグナル伝達の活性化はまた、図１ｃに示すようにウエスタンブロッティングの結果によっても支持された。 1.3 Results It was observed that knockdown of three kinases (MAPK1, MAPK3, MAPK13) significantly reduced cell proliferation in all three siRNAs of each kinase (FIG. 5a, Table S7). In addition, two of the three siRNAs targeting six kinases (CDK12, MAPK12, MAPK14, PRKCD, SRC, YES1) significantly inhibited the proliferation of HCT116 cells (FIG. 5a, Table S7).
MAPK1 and MAPK3 (ERK2, ERK1 respectively) are kinases that are downstream factors of EGFR signaling (19). Thus, the decrease in cell proliferation due to knockdown of these kinases suggests that one of the resistance mechanisms of cetuximab treatment is activation of kinases downstream of EGFR signaling. Activation of downstream signaling via ERK1 / 2 in HCT116 cells was also supported by Western blotting results as shown in FIG. 1c.
　ドデシル硫酸ナトリウムポリアクリルアミドゲル電気泳動ゲル染色、ウエスタンブロッティングは、既報のように（１４，４１）、ＳＤＳ－ＰＡＧＥ実験を行った。ブロットしたタンパク質の化学発光測定を、ケミ－ルミスーパーを用いて行った。 For sodium dodecyl sulfate polyacrylamide gel electrophoresis gel staining and Western blotting, SDS-PAGE experiments were performed as previously described (14, 41). Chemiluminescence measurement of the blotted protein was performed using Chemilumi Super.
　ＭＡＰＫ１３（ｐ３８デルタ）はｐ３８キナーゼファミリーのメンバーである（２０）。これまでに、ｐ３８キナーゼシグナル伝達は大腸がんの発生およびセツキシマブへの耐性に重要であることが報告されている（２１）。それゆえ、キノームの活性プロファイリングから得た我々の結果は、既報のデータと一致する。この事実は、我々のリン酸化プロテオミクスの手法が、がん細胞における薬剤耐性に関連する既知の機構を含む、リン酸化シグナル伝達を正確に捕捉できることを示唆する。 MAPK13 (p38 delta) is a member of the p38 kinase family (20). To date, p38 kinase signaling has been reported to be important for the development of colon cancer and resistance to cetuximab (21). Therefore, our results from kinome activity profiling are consistent with previously reported data. This fact suggests that our phosphorylated proteomic approach can accurately capture phosphorylated signaling, including known mechanisms associated with drug resistance in cancer cells.
　キナーゼネットワーク解析の結果から、ＨＣＴ１１６細胞でセツキシマブ処理に依存せず恒常的な活性化を示す新規の経路として、ＳＲＣ－ＰＲＫＣＤカスケードの存在が示唆された（図４ａおよびｂ）。興味深いことに、ＳＲＣおよびＰＲＫＣＤのノックダウンもまた、ＨＣＴ１１６細胞の細胞増殖を低下させた（図５ａ）。これは、ＳＲＣ－ＰＲＫＣＤカスケードがセツキシマブ耐性大腸がんの新規治療標的である事を示しているのと同時に、キナーゼ活性ネットワークの構築が薬剤耐性メカニズムを基盤として新規標的となるキナーゼスクリーニングに貢献できる事を示している。 The results of the kinase network analysis suggested the presence of the SRC-PRKCD cascade as a novel pathway showing constitutive activation independent of cetuximab treatment in HCT116 cells (FIGS. 4a and b). Interestingly, knockdown of SRC and PRKCD also reduced cell proliferation of HCT116 cells (FIG. 5a). This indicates that the SRC-PRKCD cascade is a novel therapeutic target for cetuximab-resistant colorectal cancer, and that the construction of a kinase activity network can contribute to the screening of new target kinases based on drug resistance mechanisms. Is shown.
試験例２
同定されたキナーゼが薬剤標的となることの確認
　本研究で同定したキナーゼが薬剤標的となり得るかを決定するため、キナーゼ阻害剤を用いて検証した。
　ＳＲＣおよびＹＥＳ１を標的とする二つのＴＫＩ（それぞれＫＸ２－３９１およびＳＵ６６５６）でＨＣＴ１１６細胞を処理したところ、これらのＴＫＩはＨＣＴ１１６の増殖だけでなく、ＨＴ２９、ＳＷ４８０およびＣｏｌｏ２０５といった他のセツキシマブ耐性細胞株の増殖も阻害することがわかった（図５ｂ）。ＳＲＣ阻害剤であるＫＸ２－３９１の５０％阻害濃度(ＩＣ５０)は、ＨＣＴ１１６（ＩＣ５０：１９ｎＭ）、ＨＴ２９（ＩＣ５０：３０ｎＭ）、ＳＷ４８０（ＩＣ５０：３６ｎＭ）、およびＣｏｌｏ２０５細胞（ＩＣ５０：２９ｎＭ）であった。ＹＥＳ１阻害剤であるＳＵ６６５６では、それぞれＨＣＴ１１６（ＩＣ５０：１０５６ｎＭ）、ＨＴ２９（ＩＣ５０：４６９ｎＭ）、ＳＷ４８０（ＩＣ５０：１４０８ｎＭ）、およびＣｏｌｏ２０５細胞（ＩＣ５０：５４０ｎＭ）のＩＣ５０を示した（図５ｂ）。したがって、これらの化合物、特にＳＲＣ阻害剤は、大腸がんのセツキシマブ耐性を克服するための有望な薬剤である事が示唆された。 Test example 2
Confirmation that the identified kinase is a drug target In order to determine whether the kinase identified in this study could be a drug target, it was tested using a kinase inhibitor.
Treatment of HCT116 cells with two TKIs targeting SRC and YES1 (KX2-391 and SU6656, respectively) revealed that these TKIs are not only proliferating in HCT116 but also in other cetuximab resistant cell lines such as HT29, SW480 and Colo205. It was found to also inhibit proliferation (FIG. 5b). The 50% inhibitory concentration (IC50) of the SRC inhibitor KX2-391 was HCT116 (IC50: 19 nM), HT29 (IC50: 30 nM), SW480 (IC50: 36 nM), and Colo205 cells (IC50: 29 nM). . SU6656, a YES1 inhibitor, showed IC50s of HCT116 (IC50: 1056 nM), HT29 (IC50: 469 nM), SW480 (IC50: 1408 nM), and Colo205 cells (IC50: 540 nM), respectively (FIG. 5b). Therefore, it was suggested that these compounds, particularly SRC inhibitors, are promising drugs for overcoming cetuximab resistance in colorectal cancer.
まとめ
　本研究では、高感度リン酸化プロテオミクス解析を行い、セツキシマブに対して耐性を示す大腸がん培養細胞における活性化キナーゼ候補を選別した。固定化金属イオンアフィニティクロマトグラフィーに基づくリン酸化プロテオミクスおよび高感度チロシンリン酸化プロテオミクス解析を行うことによって、高感度なリン酸化プロテオミクスデータを得た。感受性細胞株（ＬＩＭ１２１５およびＤＬＤ１）と耐性細胞株（ＨＣＴ１１６およびＨＴ２９）とを比較することで、耐性細胞株で高活性を示すキナーゼ候補が明らかになり、それらのほとんどはチロシンリン酸化プロテオミクス解析で同定された。驚くべきことに、これらのキナーゼのほとんどにおいて、ゲノム上の変異は認められなかった。活性化キナーゼ候補を用いた活性化キナーゼネットワーク解析は、ＨＣＴ１１６細胞おけるＳＲＣ－ＰＲＫＣＤカスケードの恒常的な活性を示唆したＳＲＣノックダウンおよびＳＲＣ阻害剤処理によって、ＨＣＴ１１６細胞の増殖が有意に阻害される事を確認した。 Summary In this study, high-sensitivity phosphorylated proteomics analysis was performed to select activated kinase candidates in cultured colon cancer cells that are resistant to cetuximab. Sensitive phosphorylated proteomics data were obtained by performing phosphorylated proteomics based on immobilized metal ion affinity chromatography and sensitive tyrosine phosphorylated proteomics analysis. Comparison of sensitive cell lines (LIM1215 and DLD1) and resistant cell lines (HCT116 and HT29) reveals kinase candidates that are highly active in resistant cell lines, most of which are identified by tyrosine phosphorylated proteomics analysis It was done. Surprisingly, no genomic variation was observed in most of these kinases. Activation kinase network analysis using activated kinase candidates indicated that the growth of HCT116 cells was significantly inhibited by SRC knockdown and treatment with SRC inhibitors, which suggested constitutive activity of the SRC-PRKCD cascade in HCT116 cells. It was confirmed.
実施例４
胃がん内視鏡検体からのキナーゼ活性プロファイリング
１．１　胃がんにおける内視鏡生検の収集
　すべての患者は、国立がんセンター病院（東京、日本）で治療された。内視鏡検査試料の採取と分析は、国立がんセンター病院および国立生物医学研究所健康栄養研究所（大阪、日本）の倫理委員会によって承認された。書面による同意がすべての患者から得られた。１人の患者から腫瘍生検3個および正常な胃生検3個を内視鏡的処置によって一度に収集した。収集後、各試料をスクリューキャップチューブに別々に入れ、すぐに液体窒素中で急速冷凍した。凍結した試料を、さらなる試料調製まで-80℃で保存した。 Example 4
Kinase activity profiling from gastric cancer endoscopic specimens 1.1 Collection of endoscopic biopsies in gastric cancer All patients were treated at National Cancer Center Hospital (Tokyo, Japan). The collection and analysis of endoscopy samples was approved by the Ethics Committee of the National Cancer Center Hospital and the National Institute of Biomedical Research (Osaka, Japan). Written consent was obtained from all patients. Three tumor biopsies and three normal gastric biopsies were collected from one patient at a time by endoscopic treatment. After collection, each sample was placed separately in a screw cap tube and immediately snap frozen in liquid nitrogen. Frozen samples were stored at −80 ° C. until further sample preparation.
１．２　内視鏡生検の均質化と可溶化
　凍結した生検をPowerMasher 2（Nippi、Tokyo、Japan）の1.5mlチューブに移し、PTS緩衝液[34]と混合した。各生検を30秒間ホモジナイズし、95℃で5分間煮沸工程に付した。タンパク質溶解産物をさらにBioruptor超音波処理器（Cosmo Bio、Tokyo、Japan）で3回（1セットにつき15分）超音波処理した。超音波処理後、タンパク質濃度をDetergent Compatible（DC）タンパク質アッセイキット（Bio-Rad、Hercules、CA、USA）で測定した。 1.2 Homogenization and solubilization of endoscopic biopsy The frozen biopsy was transferred to a 1.5 ml tube of PowerMasher 2 (Nippi, Tokyo, Japan) and mixed with PTS buffer [34]. Each biopsy was homogenized for 30 seconds and subjected to a boiling step at 95 ° C. for 5 minutes. The protein lysate was further sonicated three times (15 minutes per set) with a Bioruptor sonicator (Cosmo Bio, Tokyo, Japan). After sonication, protein concentration was measured with a Detergent Compatible (DC) protein assay kit (Bio-Rad, Hercules, CA, USA).
１．２－２　タンパク質沈殿、タンパク質消化の消化、および界面活性剤の除去
　混入物を除去するために、細胞溶解物中のタンパク質500μgをメタノール/クロロホルム沈殿により沈殿させた。ペレットをPTS緩衝液に再懸濁した。再懸濁した溶液中のタンパク質量をDCタンパク質アッセイキットで測定し、320μgのタンパク質溶解物を還元およびアルキル化工程に供した。DTTおよびIAAをそれぞれ還元およびアルキル化工程に用いた。次に、サンプルをABC緩衝液で4倍に希釈し、トリプシン（タンパク質重量1/50）とLys-C（タンパク質重量1/50）を混合した。 1.2-2 Protein Precipitation, Protein Digestion, and Surfactant Removal To remove contaminants, 500 μg of protein in the cell lysate was precipitated by methanol / chloroform precipitation. The pellet was resuspended in PTS buffer. The amount of protein in the resuspended solution was measured with a DC protein assay kit and 320 μg of protein lysate was subjected to reduction and alkylation steps. DTT and IAA were used for the reduction and alkylation steps, respectively. Next, the sample was diluted 4 times with ABC buffer, and trypsin (protein weight 1/50) and Lys-C (protein weight 1/50) were mixed.
１．３　リン酸化ペプチドの脱塩、濃縮
　製造元のプロトコルに従ってOASIS HLBを用いたペプチドの脱離を行った。 Fe3 + IMAC樹脂によるリン酸化ペプチドの濃縮は、基本的に以前に記載されているように行った[35]。この実施例では、Fe-IMAC / C18ステージチップ上のリン酸化ペプチドを濃縮した。手短に言えば、C18ディスクを200μlの使い捨てチップにセットし、Fe-IMAC樹脂をC18ディスクにセットした。脱塩したペプチドをIMAC / C18ステージチップに通した。リン酸化ペプチドを1％H 3 PO 4で溶出し、下部C18ディスク上で精製した。濃縮されたリン酸化ペプチドを、TMT標識の次の工程に供した。 1.3 Desalting and Concentration of Phosphorylated Peptide Peptide was desorbed using OASIS HLB according to the manufacturer's protocol. Concentration of phosphorylated peptides with Fe3 + IMAC resin was basically performed as previously described [35]. In this example, the phosphorylated peptide on the Fe-IMAC / C18 stage chip was concentrated. In short, the C18 disk was set on a 200 μl disposable chip, and Fe-IMAC resin was set on the C18 disk. The desalted peptide was passed through an IMAC / C18 stage chip. The phosphorylated peptide was eluted with 1% H 3 PO 4 and purified on the lower C18 disk. The concentrated phosphopeptide was subjected to the next step of TMT labeling.
１．４　TMT標識およびC18 / SCXステガチップにおけるリン酸化ペプチドの分画
　各生検でリン酸化部位を定量するために、TMT標識を行った。TMT標識の手順は、製造業者のプロトコールに対応していた。標識されたリン酸化ペプチドは、以前報告された手法に従ってC18 / SCXステージチップによる7つの画分に分画された（Adachi et al., Anal Chem, 2016, Improved Proteome and Phosphoproteome Analysis on a Cation Exchanger by a Combined Acid and Salt Gradient）。 1.4 TMT labeling and fractionation of phosphorylated peptides on C18 / SCX stega chips TMT labeling was performed to quantify phosphorylation sites in each biopsy. The TMT labeling procedure corresponded to the manufacturer's protocol. Labeled phosphopeptides were fractionated into 7 fractions on a C18 / SCX stage chip according to previously reported techniques (Adachi et al., Anal Chem, 2016, Improved Proteome and Phosphoproteome Analysis on a Cation Exchanger by a Combined Acid and Salt Gradient).
１．５　LC-MS / MS分析
　Ultimate 3000（Thermo Fisher Scientific）およびHTC-PAL（CTC Analytics、Zwingen、Switzerland）と結合したQ Exactive Plus（Thermo Fisher Scientific、Waltham、MA、USA）を用いて、この研究におけるリン酸化プロテオミクスを行った。バッファーA（0.1％ギ酸、2％アセトニトリル）およびバッファーB（0.1％ギ酸、90％アセトニトリル）を用いて勾配を行った。135分で5～30％Q Exactive Plusの典型的なパラメーターは、以前のリンプロテオーム研究[13]の条件と一致した。 1.5 LC-MS / MS analysis Using Ultimate Exact 3000 (Thermo Fisher Scientific) and Q Exactive Plus (Thermo Fisher Scientific, Waltham, MA, USA) coupled with HTC-PAL (CTC Analytics, Zwingen, Switzerland) Phosphorylated proteomics in the study was performed. A gradient was performed using buffer A (0.1% formic acid, 2% acetonitrile) and buffer B (0.1% formic acid, 90% acetonitrile). Typical parameters of 5-30% Q Exactive Plus at 135 minutes were consistent with the conditions of previous linproteome studies [13].
１．６　結果
　内視鏡生検のリン酸化プロテオミクス解析から、11,840個のリン酸化ペプチド、14,687個のリン酸化部位、10,162個のクラス1リン酸化部位を同定した（図７Ａ）。すべてのクラス1リン酸化部位の中で、TMT 10プレックス標識の少なくとも1つのラベルにおいて定量されたリン酸化部位は8,340個であった（図７Ａ）。14,687個のリン酸化部位は、12,062個のリン酸化セリン部位（82.1％）、2,531個のリン酸化トレオニン部位（17.2％）、および94個のリン酸化チロシン部位（0.7％）から構成された（図７Ｂ）。次に、我々の結果の中で、これまでに報告されていないリン酸化部位の数を調査した。PhosphositePlusデータベースには、同定された14,687個のリン酸化部位のうち1,346個（9.2％）が割り当てられていないことが判明した（図７Ｃ）。この結果は、我々の実験手法が多くの未知のリン酸化部位の測定を可能にすることを示している。さらに、胃がんの手術組織を用いて以前に報告されたリン酸化プロテオーム研究とのデータを比較した[Park, J. M., Park, J. H., Mun, D. G., Bae, J., Jung, J. H., Back, S., Lee, H., Kim, H., Jung, H. J., Kim, H. K., Kim, K. P., Hwang, D., and Lee, S. W. (2015) Integrated analysis of global proteome, phosphoproteome, and glycoproteome enables complementary interpretation of disease-related protein networks. Scientific reports 5, 18189]。Jong-Moon,P. et alは、胃がんにおける手術組織からの20,391個のリン酸化ペプチドの同定を報告した。以前のデータと本発明者らの結果との間の同定されたリン酸化ペプチドの比較は、57.9％（本発明者らのデータセット中の11,840個のリン酸化ペプチドのうち6.851個）のみが共通に同定されたことを明らかにした（図７Ｄ）。この結果は、手術検体と内視鏡検体との間の試料回収時における虚血状態などのバイアスの差異を示している可能性がある。要約すると、我々はわずか2mm 立方のサンプルである内視鏡的生検を用いて1万個以上のクラス1リン酸化部位の同定に成功した。 1.6 Results From the phosphorylated proteomic analysis of the endoscopic biopsy, 11,840 phosphorylated peptides, 14,687 phosphorylated sites, and 10,162 class 1 phosphorylated sites were identified (FIG. 7A). Among all class 1 phosphorylation sites, there were 8,340 phosphorylation sites quantified in at least one label of the TMT 10 plex label (FIG. 7A). The 14,687 phosphorylation sites consisted of 12,062 phosphorylated serine sites (82.1%), 2,531 phosphorylated threonine sites (17.2%), and 94 phosphorylated tyrosine sites (0.7%) (Fig. 7B). Next, we investigated the number of phosphorylation sites not previously reported in our results. It was found that 1,346 (9.2%) of the 14,687 phosphorylation sites identified were not assigned to the PhosphositePlus database (FIG. 7C). This result shows that our experimental method allows measurement of many unknown phosphorylation sites. In addition, we compared data with previously reported phosphoproteomic studies using surgical tissues for gastric cancer [Park, JM, Park, JH, Mun, DG, Bae, J., Jung, JH, Back, S. , Lee, H., Kim, H., Jung, HJ, Kim, HK, Kim, KP, Hwang, D., and Lee, SW (2015) Integrated analysis of global proteome, phosphoproteome, and glycoproteome enables complementary interpretation of disease -related protein networks. Scientific reports 5, 18189]. Jong-Moon, P. et al reported the identification of 20,391 phosphorylated peptides from surgical tissue in gastric cancer. Comparison of identified phosphopeptides between previous data and our results is common only for 57.9% (6.851 of 11,840 phosphopeptides in our data set) (Fig. 7D). This result may indicate a difference in bias such as an ischemic state at the time of sample collection between the surgical specimen and the endoscopic specimen. In summary, we have successfully identified more than 10,000 class 1 phosphorylation sites using endoscopic biopsy, a sample of only 2 mm cube.
　内視鏡生検がん部位で、がん特有のリン酸化シグナル経路が反映されているかどうかを確認するため、リン酸化プロテオミクスの定量分析を行った。定量解析に使用したリン酸化部位は、質量分析計による解析を行った10サンプルのうち少なくとも1つのサンプルで定量値のついたものを選抜した。それら8,340個のリン酸化部位の定量データを、パスウェイ解析およびキノームプロファイリングを含む以下の定量分析に使用した。 Quantitative analysis of phosphorylated proteomics was performed in order to confirm whether the cancer-specific phosphorylation signal pathway was reflected at the endoscopic biopsy cancer site. As the phosphorylation site used for the quantitative analysis, at least one sample out of the 10 samples analyzed by the mass spectrometer was selected with a quantitative value. Quantitative data of these 8,340 phosphorylation sites was used for the following quantitative analysis including pathway analysis and kinome profiling.
　まず、各内視鏡生検でリン酸化プロテオミクスの定量的特徴を調べた。主成分分析（PCA）では、正常群（図８Ａ：正常１－５）およびがん群（図８Ａ：がん２－５）のリン酸化プロテオームの結果ははっきりと分類された。一方、がん患者No.1のがんデータは、他の患者のがん検体のデータとは異なるリン酸化修飾状態をとっている事が明らかになった。また相関分析によると、患者No.1がん検体のピアソン相関係数は、他の組み合わせ（図８Ｂ、８Ｃ）よりも有意に低かった（0.68～0.77、p値= 3.9e-6）。これらのデータは、患者No.1がん検体の性質が他のデータと全く異なることを示している（図８Ｂ）。患者No.1がん検体データの異常の理由は不明であるが、不必要な偏りを避けるために、患者No.1のデータを以下の分析では除外した。 First, the quantitative characteristics of phosphorylated proteomics were examined with each endoscopic biopsy. In the principal component analysis (PCA), the results of phosphorylated proteome in the normal group (FIG. 8A: normal 1-5) and the cancer group (FIG. 8A: cancer 2-5) were clearly classified. On the other hand, it became clear that the cancer data of cancer patient No. 1 has a phosphorylation modification state different from the data of cancer samples of other patients. Further, according to the correlation analysis, the Pearson correlation coefficient of the patient No. 1 cancer specimen was significantly lower (0.68 to 0.77, p value = 3.9e-6) than the other combinations (FIGS. 8B and 8C). These data indicate that the properties of patient No. 1 cancer specimen are completely different from other data (FIG. 8B). The reason for the abnormalities in patient No. 1 cancer specimen data is unknown, but in order to avoid unnecessary bias, patient No. 1 data was excluded from the following analysis.
　次に、がん生検と正常胃生検との間に有意差を示したリン酸化部位を選択した。ウェルチt検定を用いて、382および345のリン酸化部位を、それぞれがんにおける増加（右翼）および減少リン酸化部位（左翼）として選択した（図９Ａ）。ボルケーノプロットは、ウェルチt検定および置換試験を行うことによって、各リン酸化部位のLog2倍変化およびq値で表される。次に、これらのリン酸化部位をWebGestaltのパスウェイ解析のワークフローに供した[21]。KEGG [22]とWikiPathway [23]の2種類のデータベースを用いてパスウェイ解析を行った。2つのグラフのすべてのパスウェは、q値が0.01未満である。右側に示すがん増加の棒グラフは、がん生検で増加したリン酸化部位にパスウェイが豊富であることを示している。左側に示すがん減少の棒グラフは、正常組織と比較してがん生検で減少しているリン酸化部位にパスウェイが豊富であることを示している。2つのタイプの分析から得られた結果を比較すると、よく知られている「Cancer Hallmarks」[2]に関連する共通の変動が見出された。がんにおける活性化したパスウェイの中で「ゲノム不安定性および突然変異」がKEGGおよびWikipathway（図９Ｂ、右翼）の両方で示唆された。さらにATRキナーゼの活性化制御リン酸化部位も、がん検体で増加していることが確認された（図９Ｃ）[24]。さらに、ATRの基質であるNBNの343番セリン残基も、がん検体において有意な増加が認められた（図９Ｃ）。図９Ｃにおいて、同じ患者のがん/正常生検の対は、黒い線で結んでいる。対照的に、細胞接着に関与するいくつかのパスウェイは、がん組織で不活性化していることがパスウェイ解析から示唆された（図９ｂ）。まとめると、これらの結果は、内視鏡生検におけるリン酸化プロテオームデータは、リンシグナル化の観点から胃がんにおけるがん特性を反映することを示している。 Next, phosphorylation sites that showed a significant difference between cancer biopsy and normal gastric biopsy were selected. Using Welch's t-test, 382 and 345 phosphorylation sites were selected as increased (right wing) and decreased phosphorylation sites (left wing) in cancer, respectively (FIG. 9A). The Volcano plot is expressed by Log2 fold change and q value of each phosphorylation site by performing Welch t-test and substitution test. Next, these phosphorylation sites were subjected to WebGestalt pathway analysis workflow [21]. Pathway analysis was performed using two types of databases, KEGG [22] and WikiPathway [23]. All pathways in the two graphs have q values less than 0.01. The cancer growth bar graph on the right shows that pathways rich in phosphorylation sites increased by cancer biopsy are abundant. The cancer reduction bar graph on the left shows that the pathway is rich in phosphorylation sites that are reduced in cancer biopsies compared to normal tissues. Comparing the results obtained from the two types of analyses, we found common variations associated with the well-known “Cancer Hallmarks” [2]. Among the activated pathways in cancer, “genomic instability and mutation” were suggested in both KEGG and Wikipathway (FIG. 9B, right wing). Furthermore, it was confirmed that the activation-regulated phosphorylation site of ATR kinase was also increased in cancer specimens (FIG. 9C) [24]. Furthermore, a significant increase was also observed in the cancer sample for the 343 serine residue of NBN which is a substrate of ATR (FIG. 9C). In FIG. 9C, cancer / normal biopsy pairs from the same patient are connected by a black line. In contrast, pathway analysis suggested that some pathways involved in cell adhesion are inactivated in cancer tissue (FIG. 9b). Taken together, these results indicate that phosphorylated proteome data in endoscopic biopsies reflect cancer characteristics in gastric cancer from the perspective of phosphorous signaling.
　内視鏡生検のリン酸化プロテオームデータから、キナーゼの活性プロファイリングを得るために、以前の研究[15]で報告された方法でキノームプロファイリングを行った。最初に、我々は、428のセリン/スレオニンキナーゼのうち187個と90個のチロシンキナーゼのうち30個にリン酸化部位が検出されたことを見出した（図１０Ａ）。このデータは、本研究におけるリン酸化プロテオームプロトコルが、リン酸化修飾の状態の観点から、多くのキナーゼの活性をモニターすることを可能にすることを実証している。次に、キナーゼ－基質との関係を用いてキナーゼの活性を推測するKSEAを実施した[17]。KSEAアルゴリズムは、68種のキナーゼの間での酵素活性化の変動を示した。KSEAアルゴリズムからの有意差（q値<0.05）を有する全てのキナーゼを棒グラフでプロットした。KSEAの結果は、14のキナーゼの活性が胃がんと正常領域との間で有意に活性変動されることを示した（図１０Ｂ）。 In order to obtain kinase activity profiling from endoscopic biopsy phosphorylated proteome data, kinome profiling was performed as reported in previous studies [15]. Initially, we found that phosphorylation sites were detected in 187 of 428 serine / threonine kinases and 30 of 90 tyrosine kinases (FIG. 10A). This data demonstrates that the phosphorylated proteome protocol in this study makes it possible to monitor the activity of many kinases in terms of the state of phosphorylation modification. Next, KSEA was performed to infer kinase activity using the kinase-substrate relationship [17]. The KSEA algorithm showed a variation in enzyme activation among 68 kinases. All kinases with significant difference from the KSEA algorithm (q value <0.05) were plotted as a bar graph. KSEA results showed that the activity of 14 kinases was significantly altered between gastric cancer and normal regions (FIG. 10B).
　がんにおける酵素活性を増加させることが期待されるキナーゼのうちには、その阻害剤がすでに臨床で使用されているERBB2 [27]が含まれていた（図１０Ｂ）。生検の免疫染色からのKSEAとHer2（ERBBの同義語）強度とのERBB2活性の関係を個人別に評価するために、KSEAの計算で使用されたERBB2基質リン酸化部位の変動を分析した。ERBB2 Y877、Y1248、およびCDK1 Y15（CDK2およびCDK3のY15を含む）の変化を図１０Ｃにプロットした。Her2陽性患者（No.2）の試料では、本実施例で分析した4人の患者の中で、3つの基質すべてが最も高い増加を示した（図１０Ｃ、最左棒）。図１０Ｃにおけるそれぞれの最左の棒は、胃がんがHer2陽性であった患者No.2の倍数変化を示す。 Among the kinases that are expected to increase the enzyme activity in cancer, ERBB2 [27] whose inhibitor has already been used in clinical practice was included (FIG. 10B). To assess the individual relationship of ERBB2 activity to KSEA and Her2 (ERBB synonyms) intensity from biopsy immunostaining, we analyzed the variation of ERBB2 substrate phosphorylation sites used in KSEA calculations. Changes in ERBB2 Y877, Y1248, and CDK1 Y15 (including Y15 of CDK2 and CDK3) are plotted in FIG. 10C. In the Her2 positive patient (No. 2) sample, among the four patients analyzed in this example, all three substrates showed the highest increase (FIG. 10C, leftmost bar). Each leftmost bar in FIG. 10C shows the fold change of patient No. 2 in which gastric cancer was Her2 positive.
　KSEAから予測された他の活性キナーゼも、胃がんに関与することが報告されている。例えば、一本鎖DNA切断に対する損傷応答の調節因子であるATRの活性化がKSEAから予測された（図１０Ｂ）。これらのATR活性の結果は、DNA損傷応答（図９Ｂ）パスウェイ解析における濃縮、およびATR活性制御リン酸化部位（T1989）の増加と一致する（図９Ｃ）。さらに、DNA損傷応答における別のカスケードの調節因子であるCHEK2の活性化も予測された。CHEK2は、二本鎖DNA切断に対する損傷応答の重要な要素であるATMキナーゼの基質である[29]。以前に報告されたように、キノームプロファイリングにおけるこれらの結果は、胃がんにおける全DNA損傷応答の活性化を支持している[30]。
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　本発明の責任キナーゼをスクリーニングする方法は、ゲノム解析では見つけられない新たな治療標的または薬効予測標的を見出すことができ、ひいては個別化医療に資することができる。今後、患者がん由来実験モデルへの適用に加え、血中より精製した血中循環腫瘍細胞の責任キナーゼスクリーニングを視野に入れた非侵襲的な治療標的・薬効予測標的の診断方法の開発へ繋がるものと期待される。 The method for screening a responsible kinase of the present invention can find a new therapeutic target or a drug effect prediction target that cannot be found by genome analysis, and can contribute to personalized medicine. In the future, in addition to the application to patient cancer-derived experimental models, it will lead to the development of diagnostic methods for noninvasive therapeutic targets and drug efficacy prediction targets with a view to responsible kinase screening of circulating tumor cells purified from blood Expected.

Claims (25)

  1. 　リン酸化プロテオミクスから得られたデータに基づき、リン酸化修飾活性が有意に増加しているリン酸化部位を特定し、タンパク質機能情報データベース上におけるキナーゼ活性制御リン酸化部位の実測値、および／またはキナーゼ基質関連情報を使用する計算科学的手法によって得られるキナーゼ活性予測値によって、リン酸化修飾活性が有意に増加しているキナーゼを選別する、治療標的または薬効予測標的となり得る責任キナーゼをスクリーニングする方法。 Based on the data obtained from phosphorylation proteomics, the phosphorylation site where phosphorylation modification activity is significantly increased is identified, the actual value of the kinase activity control phosphorylation site in the protein function information database, and / or the kinase substrate A method for screening a responsible kinase that can be a therapeutic target or a target for predicting drug efficacy, wherein a kinase having a significantly increased phosphorylation-modifying activity is selected based on a predicted kinase activity obtained by a computational scientific method using related information.
  2. 　対照を含む対照試料および標的を含む標的試料、または標的を含む標的試料に対し、リン酸化プロテオミクスを行う、請求項１記載の方法。 The method according to claim 1, wherein phosphorylation proteomics is performed on a control sample containing a control and a target sample containing a target, or a target sample containing a target.
  3. 　標的試料が生検である、請求項２記載の方法。 3. The method according to claim 2, wherein the target sample is a biopsy.
  4. 　標的試料が内視鏡検体である、請求項３記載の方法。 4. The method according to claim 3, wherein the target sample is an endoscopic specimen.
  5. 　１）対照試料として対照細胞および標的試料として治療対象細胞の細胞溶解物から濃縮したリン酸化セリン、リン酸化スレオニンおよび／またはリン酸化チロシンペプチドについてリン酸化プロテオミクスデータを取得し、
    　２）得られたデータに基づき、統計学的手法により、対照細胞と比較して治療対象細胞において有意に増加しているリン酸化部位を特定し、
    　３）タンパク質機能情報データベース上におけるキナーゼ活性制御リン酸化部位の実測値、および／またはキナーゼ基質関連情報を使用する計算科学的手法によって得られるキナーゼ活性予測値によって、対照細胞と比較して治療対象細胞において有意にリン酸化修飾活性が増加しているキナーゼを選別し、それを責任キナーゼとする、請求項２から４いずれか記載の方法。     1) Obtain phosphorylated proteomics data for phosphorylated serine, phosphorylated threonine and / or phosphorylated tyrosine peptide concentrated from cell lysates of control cells as control samples and treated cells as target samples;
    2) Based on the obtained data, a statistical method is used to identify phosphorylation sites that are significantly increased in the cells to be treated compared to the control cells,
    3) Treatment target cells compared to control cells based on actual values of kinase activity-regulated phosphorylation sites on the protein function information database and / or kinase activity prediction values obtained by computational scientific methods using kinase substrate related information The method according to any one of claims 2 to 4, wherein a kinase having significantly increased phosphorylation-modifying activity is selected as a responsible kinase.
  6. 　１）内視鏡検体の細胞溶解物から濃縮したリン酸化セリン、リン酸化スレオニンおよび／またはリン酸化チロシンペプチドについてリン酸化プロテオミクスデータを取得し、
    　２）得られたデータに基づき、統計学的手法により、がん患者母集団平均と比較して有意に増加しているリン酸化部位を特定し
    　３）タンパク質機能情報データベース上におけるキナーゼ活性制御リン酸化部位の実測値、および／またはキナーゼ基質関連情報を使用する計算科学的手法によって得られるキナーゼ活性予測値によって、内視鏡検体において有意にリン酸化修飾活性が増加しているキナーゼを選別し、それを責任キナーゼとする、請求項１記載の方法。     1) Obtain phosphorylated proteomics data for phosphorylated serine, phosphorylated threonine and / or phosphorylated tyrosine peptide concentrated from cell lysates of endoscopic specimens,
    2) Based on the data obtained, statistical methods were used to identify phosphorylation sites that were significantly increased compared to the mean population of cancer patients. 3) Kinase activity-regulated phosphorylation on the protein function information database Based on the actual measurement of the site and / or the predicted kinase activity obtained by the computational science method using the kinase substrate-related information, the kinase having a significantly increased phosphorylation-modifying activity in the endoscopic specimen is selected, The method according to claim 1, wherein is a responsible kinase.
  7. 　工程２）における統計学的手法が、２群で有意な変動を示すリン酸化部位、または多群の中で有意さを示すリン酸化部位を抽出するための手法である、請求項５または６記載の方法。 7. The statistical method in step 2) is a method for extracting a phosphorylation site exhibiting significant variation in two groups, or a phosphorylation site exhibiting significance among multiple groups. the method of.
  8. 　工程１）におけるリン酸化チロシンの濃縮を、金属アフィニティクロマトグラフィーを用いるリン酸化ペプチド濃縮、次いで抗リン酸化チロシン抗体を用いた免疫沈降法によって行う、請求項５から７のいずれか記載の方法。 The method according to any one of claims 5 to 7, wherein the concentration of phosphorylated tyrosine in step 1) is performed by concentration of phosphorylated peptide using metal affinity chromatography and then immunoprecipitation using an anti-phosphotyrosine antibody.
  9. 　金属アフィニティクロマトグラフィーを用いたリン酸化セリン、リン酸化スレオニン、およびリン酸化チロシンを包括的に解析し、高感度リン酸化プロテオミクスデータを取得する、請求項５から８のいずれか記載の方法。 The method according to claim 5, wherein phosphorylated serine, phosphorylated threonine, and phosphorylated tyrosine are comprehensively analyzed using metal affinity chromatography to obtain highly sensitive phosphorylated proteomics data.
  10. 　治療標的が、有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患の原因である責任キナーゼであり、そして対照試料が正常細胞、標的試料が当該疾患細胞である、請求項１から９のいずれか記載の方法。 The therapeutic target is a responsible kinase responsible for the disease selected from among diseases for which there is no effective therapeutic agent, advanced malignant cancer, and cancer with characteristic cancer characteristics, and controls The method according to any one of claims 1 to 9, wherein the sample is a normal cell and the target sample is the diseased cell.
  11. 　有効な治療薬がない疾患が薬剤耐性疾患または、責任キナーゼが関与する難治性疾患である、請求項１０記載の方法。 The method according to claim 10, wherein the disease for which there is no effective therapeutic agent is a drug resistant disease or an intractable disease involving responsible kinase.
  12. 　薬剤耐性疾患が、有効な分子標的治療薬はあるが、その治療薬に耐性になった患者における疾患である、請求項１１記載の方法。 The method according to claim 11, wherein the drug resistant disease is a disease in a patient who has an effective molecular targeted therapeutic agent but has become resistant to the therapeutic agent.
  13. 　分子標的治療薬がキナーゼ阻害剤である、請求項１２記載の方法。 The method according to claim 12, wherein the molecular targeted therapeutic agent is a kinase inhibitor.
  14. 　薬効予測標的が、有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患に罹患している被験者において、当該疾患を処置または予防する治療薬の有効性を予測するために使用される責任キナーゼであり、そして対照試料が当該治療薬に感受性の細胞または不存在、標的試料が、被験者由来の組織、血中循環細胞および細胞外小胞の中から選ばれる、請求項１から９のいずれか記載の方法。 In a subject whose drug efficacy prediction target is a disease selected from among diseases for which there is no effective therapeutic drug, advanced malignant cancer, and cancer having characteristic cancer characteristics, Is a responsible kinase used to predict the effectiveness of a therapeutic agent to treat or prevent, and the control sample is cells or absence sensitive to the therapeutic agent, the target sample is tissue from the subject, blood circulation The method according to any one of claims 1 to 9, which is selected from cells and extracellular vesicles.
  15. 　有効な治療薬がない疾患が薬剤耐性疾患または、責任キナーゼが関与する難治性疾患である、請求項１４記載の方法。 The method according to claim 14, wherein the disease for which there is no effective therapeutic drug is a drug resistant disease or an intractable disease involving responsible kinase.
  16. 　薬剤耐性疾患が、有効な分子標的治療薬はあるが、その治療薬に耐性になった患者における疾患である、請求項１５記載の方法。 The method according to claim 15, wherein the drug resistant disease is a disease in a patient who has an effective molecular targeted therapeutic agent but has become resistant to the therapeutic agent.
  17. 　分子標的治療薬がキナーゼ阻害剤である、請求項１６記載の方法。 The method according to claim 16, wherein the molecular targeted therapeutic agent is a kinase inhibitor.
  18. 　対照試料が治療薬に感受性の細胞の場合、感受性細胞および標的試料に対し、リン酸化プロテオミクスを行い、感受性細胞と比較し標的試料において有意にリン酸化修飾活性が増加しているキナーゼを選別し、それを責任キナーゼとする、請求項１４から１７いずれか記載の方法。 When the control sample is a cell sensitive to a therapeutic agent, phosphorylation proteomics is performed on the sensitive cell and the target sample, and a kinase whose phosphorylation modifying activity is significantly increased in the target sample as compared with the sensitive cell is selected. The method according to any one of claims 14 to 17, wherein it is a responsible kinase.
  19. 　対照試料が不存在の場合、標的試料に対し、リン酸化プロテオミクスを行い、キナーゼ活性レベルのPan-cancer Analysisによって、がん母集団のキナーゼ活性平均値を対照とし、リン酸化修飾活性値の有意な増加を示すキナーゼを選別し、それを責任キナーゼとする、請求項１４から１７いずれか記載の方法。 In the absence of the control sample, phosphorylation proteomics is performed on the target sample, and the average kinase activity of the cancer population is controlled by Pan-cancer Analysis of the kinase activity level. The method according to any one of claims 14 to 17, wherein a kinase exhibiting an increase is selected and used as a responsible kinase.
  20. 　当該被験者において、当該疾患を処置または予防する治療薬の有効性を予測するために使用される責任キナーゼが不存在の場合、当該被験者は当該治療薬が有効であると判定する、請求項１４から１９いずれか記載の方法。 The subject determines that the therapeutic is effective if the responsible kinase used to predict the effectiveness of the therapeutic to treat or prevent the disease in the subject is absent. 19. The method according to any one of 19.
  21. 　請求項１から２０記載の方法によってスクリーニングされた責任キナーゼのリン酸化修飾活性を阻害する物質をスクリーニングするための方法であって、
    　１）責任キナーゼを有する標的試料の培地中に責任キナーゼのリン酸化修飾活性を阻害し得る候補物質を添加し、
    　２）責任キナーゼを有する標的試料における候補物質処理群と未処理群との細胞増殖活性における比較を行い、
    　３）候補物質処理群の細胞増殖活性が未処理群よりも低ければ、その候補物質を責任キナーゼのリン酸化修飾活性を阻害する物質であると評価する、方法。     A method for screening a substance that inhibits the phosphorylation-modifying activity of a responsible kinase screened by the method according to claim 1,
    1) A candidate substance capable of inhibiting the phosphorylation-modifying activity of the responsible kinase is added to the medium of the target sample having the responsible kinase,
    2) Compare the cell proliferation activity of the candidate substance-treated group and the untreated group in the target sample having the responsible kinase,
    3) A method for evaluating a candidate substance as a substance that inhibits the phosphorylation-modifying activity of a responsible kinase if the cell proliferation activity of the candidate substance-treated group is lower than that of the untreated group.
  22. 　責任キナーゼのリン酸化修飾活性を阻害する物質が分子標的薬である、請求項２１記載の方法。 The method according to claim 21, wherein the substance that inhibits the phosphorylation-modifying activity of the responsible kinase is a molecular target drug.
  23. 　大腸がん細胞におけるABL1、CDK12、HCK、JAK2、LCK、LYN、MAP2K6、MAPK12、MAPK14、PRKCD、YES1、およびDYRK4の中から選ばれる少なくとも１つの責任キナーゼのリン酸化修飾活性を阻害する物質をスクリーニングするための方法である、請求項２２記載の方法。 Screening for substances that inhibit the phosphorylation-modifying activity of at least one responsible kinase selected from ABL1, CDK12, HCK, JAK2, LCK, LYN, MAP2K6, MAPK12, MAPK14, PRKCD, YES1, and DYRK4 in colorectal cancer cells 23. The method of claim 22, wherein the method is a method for doing so.
  24. 　胃がん細胞におけるCDK1、ERBB2、PRKACA、MAPK13、CKD2、CHEK2、MAPKAPK2、ATR、CAMK2A、PRKAA1、MAP2K1、GSK3B、RET、およびMTORの中から選ばれる少なくとも１つの責任キナーゼのリン酸化修飾活性を阻害する物質をスクリーニングするための方法である、請求項２２記載の方法。 Substance that inhibits the phosphorylation-modifying activity of at least one responsible kinase selected from CDK1, ERBB2, PRKACA, MAPK13, CKD2, CHEK2, MAPKAPK2, ATR, CAMK2A, PRKAA1, MAP2K1, GSK3B, RET, and MTOR in gastric cancer cells 23. The method of claim 22, wherein the method is for screening.
  25. 　有効な治療薬がない疾患、悪性度が高い進行がん、および個人に特徴的ながん特性を有するがんの中から選ばれる疾患に罹患している被験者において、当該疾患を処置または予防する治療薬が有効か、有効でないかを判定することによって、被験者を層別化する方法であって、
    　１）請求項１４から２０いずれか記載の方法によって薬効予測標的である責任キナーゼをスクリーニングし、
    　２）当該被験者において、当該疾患を処置または予防する治療薬の有効性を予測するために使用される責任キナーゼが不存在の場合、当該被験者は当該治療薬が有効である群に割り付け、責任キナーゼが存在する場合、当該被験者は当該治療薬が有効でない群に割り付け、被験者を層別化する方法。     Treat or prevent the disease in a subject who has a disease selected from among diseases for which there is no effective therapeutic agent, advanced cancer with high malignancy, and cancer with characteristic cancer characteristics. A method of stratifying subjects by determining whether a therapeutic is effective or not,
    1) Screening a responsible kinase which is a drug efficacy prediction target by the method according to any one of claims 14 to 20,
    2) If the responsible kinase used to predict the effectiveness of a therapeutic agent to treat or prevent the disease in the subject is absent, the subject is assigned to the group for which the therapeutic agent is effective, and the responsible kinase If the subject is present, the subject is assigned to a group where the therapeutic agent is not effective, and the subject is stratified.
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