Method and kit for predicting effectiveness of dupilumab administration to atopic dermatitis patient

Abstract

This method for predicting the effectiveness of dupilumab administration to an atopic dermatitis patient comprises a step for measuring the concentration of at least one biomarker in a blood sample derived from the patient before dupilumab administration, wherein: the concentration of the biomarker is an indicator for predicting the effectiveness of the dupilumab administration; and the biomarker is selected from the group consisting of interleukin (IL)-22, C-C Motif Chemokine Ligand (CCL) 20, IL-18, IL-17, Tumor Necrosis Factor (TNF)-α, and C-X-C Motif Chemokine 9 (CXCL9).

Description

Method and kit for predicting efficacy of administration of dupilumab to patients with atopic dermatitis

[0001] The present invention relates to a method and a kit for predicting the efficacy of dupilumab administration to patients with atopic dermatitis. This application claims priority to Japanese Patent Application No. 2024-084052, filed May 23, 2024, the contents of which are incorporated herein by reference.

[0002] Atopic dermatitis is a disease involving a variety of inflammations, and there is a growing need for personalized medicine rather than one-size-fits-all treatment.

[0003] Dupilumab is a human anti-human IL-4 / 13 receptor monoclonal antibody that is used to treat moderate to severe atopic dermatitis (see, for example, Non-Patent Document 1). However, the effect of administering dupilumab to atopic dermatitis patients varies among individuals, and it has been reported that some atopic dermatitis patients do not achieve sufficient efficacy (see, for example, Non-Patent Document 2).

[0004] Agache I., et al., Efficacy and safety of dupilumab for moderate-to-severe atopic dermatitis: A systematic review for the EAACI biologicals guidelines, Allergy, 76, 45-58, 2021.Simpson EL., et al., Two Phase 3 Trials of Dupilumab versus Placebo in Atopic Dermatitis, N Engl J Med, 375 (24), 2335-2348, 2016.

[0005] Therefore, an object of the present invention is to provide a method and kit for predicting the effectiveness of administering dupilumab to patients with atopic dermatitis.

[0006] The present invention includes the following aspects: [1] A method for predicting the efficacy of administration of dupilumab to a patient with atopic dermatitis, comprising a step of measuring the concentration of at least one biomarker in a blood sample from the patient before administration of dupilumab, wherein the concentration of the biomarker is an index for predicting the efficacy of administration of dupilumab, and the biomarker is selected from the group consisting of interleukin (IL)-22, C-C motif chemokine ligand (CCL) 20, IL-18, IL-17, tumor necrosis factor (TNF)-α, and C-X-C motif chemokine 9 (CXCL9). [2] The method according to [1], comprising comparing the concentration of the biomarker with a predetermined threshold and predicting the efficacy of administration of dupilumab to the patient based on the comparison result. [3] The method of [1], wherein the concentrations of two or more biomarkers are compared with predetermined thresholds, and the effectiveness of administering dupilumab to the patient is predicted based on the comparison result. [4] The method of [1] or [2], wherein the biomarkers include IL-22 or IL-18. [5] A kit for predicting the effectiveness of administering dupilumab to a patient with atopic dermatitis, the kit comprising a substance that specifically binds to at least one biomarker selected from the group consisting of IL-22, CCL20, IL-18, IL-17, TNF-α, and CXCL9, and the kit is used to measure the concentration of the biomarker in a blood sample derived from the patient before administration of dupilumab, the concentration of the biomarker being an index for predicting the effectiveness of administering dupilumab to the patient. [6] The kit of [5], wherein the biomarkers include IL-22 or IL-18.

[0007] According to the present invention, a method and kit for predicting the effectiveness of administration of dupilumab to a patient with atopic dermatitis can be provided.

[0008] Fig. 1 is a graph showing the results of Experimental Example 1. Fig. 2 is an ROC curve showing the results of Experimental Example 2. Fig. 3 is a graph showing the results of Experimental Example 3. Fig. 4 is an ROC curve showing the results of Experimental Example 4.

[0009] [Method for predicting the efficacy of administration of dupilumab to a patient with atopic dermatitis] In one embodiment, the present invention provides a method for predicting the efficacy of administration of dupilumab to a patient with atopic dermatitis, the method comprising a step of measuring the concentration of at least one biomarker in a blood sample from the patient before administration of dupilumab, wherein the concentration of the biomarker is an index for predicting the efficacy of administration of dupilumab, and the biomarker is selected from the group consisting of IL-22, CCL20, IL-18, IL-17, TNF-α, and CXCL9.

[0010] As will be described later in the Examples, the method of this embodiment makes it possible to predict the effectiveness of dupilumab administration to atopic dermatitis patients before dupilumab administration. This serves as an indicator for selecting an appropriate treatment for the patient, and can prevent the administration of dupilumab to atopic dermatitis patients for whom dupilumab administration does not provide sufficient therapeutic effect, which is preferable from a medical economic perspective. Furthermore, it can prevent the administration of treatments with poor therapeutic effect to patients, thereby reducing the burden on patients.

[0011] Examples of patient-derived blood include serum, plasma, etc. collected from the patient before administration of dupilumab. The concentrations of IL-22, CCL20, IL-18, IL-17, TNF-α, and CXCL9 in the patient-derived blood can be measured by a commonly used method, for example, enzyme-linked immunosorbent assay (ELISA).

[0012] The NCBI accession number for human IL-22 protein is NP_065386.1, etc. The NCBI accession numbers for human CCL20 protein are NP_001123518.1, NP_004582.1, etc. The NCBI accession numbers for human IL-18 protein are NP_001230140.1, NP_001373349.1, NP_001553.1, etc. The NCBI accession number for human IL-17 protein is NP_002181.1. The NCBI accession number for human TNF-α protein is NP_000585.2. The NCBI accession number for human CXCL9 protein is NP_002407.1.

[0013] In the method of this embodiment, the concentrations of the above biomarkers are compared with predetermined thresholds, and the effectiveness of administering dupilumab to the patient can be predicted based on the comparison results.

[0014] Here, the predetermined threshold value is not particularly limited and can be set empirically, for example, by accumulating data on the concentration of biomarkers in blood samples from atopic dermatitis patients before administration of dupilumab and the results of evaluation of the severity of atopic dermatitis after administration of dupilumab.

[0015] Alternatively, a predetermined threshold may be set as follows. First, the concentration of the biomarker in a blood sample from an atopic dermatitis patient before administration of dupilumab is measured. Then, the severity of atopic dermatitis after administration of dupilumab (e.g., 4 to 6 months later) is evaluated. Here, a low level of severity of atopic dermatitis after administration of dupilumab indicates that administration of dupilumab was effective. Next, a threshold is set within a range higher than the concentration of the biomarker in a blood sample from an atopic dermatitis patient for whom administration of dupilumab was effective and lower than the concentration of the biomarker in a blood sample from an atopic dermatitis patient for whom administration of dupilumab was ineffective. It is preferable to set the threshold at a value that can accurately distinguish the effectiveness of administration of dupilumab to atopic dermatitis patients. Here, a discriminant equation may be created using a statistical analysis method known in the art, and the threshold may be calculated from these accumulated measured values ​​using this equation. Alternatively, the effectiveness of administration of dupilumab to atopic dermatitis patients may be automatically determined based on the accumulated measured values ​​using a machine learning method or the like.

[0016] As used herein, the term "about" refers to a value that includes ±10%. For example, about 5 pg / mL means 4.5 pg / mL to 5.5 pg / mL. As will be described later in the Examples, for example, when the serum IL-22 concentration in a patient before administration of dupilumab is about 5 pg / mL or less, e.g., 5.34 pg / mL or less, the CCL20 concentration is about 4 pg / mL or less, e.g., 3.85 pg / mL or less, the IL-18 concentration is about 330 pg / mL or less, e.g., 332.62 pg / mL or less, the IL-17 concentration is about 0.04 pg / mL or less, the TNF-α concentration is about 7 pg / mL or less, e.g., 7.03 pg / mL or less, or the CXCL9 concentration is about 30 pg / mL or less, e.g., 27.49 pg / mL or less, it can be said that administration of dupilumab to a patient is effective.

[0017] In the method of this embodiment, the concentrations of the combination of two or more of the biomarkers may be compared with a predetermined threshold, and the effectiveness of administering dupilumab to the patient may be predicted based on the comparison result. As described below in the Examples, by combining two or more of the biomarkers, the effectiveness of administering dupilumab to patients with atopic dermatitis can be predicted with higher sensitivity and specificity.

[0018] The combination of biomarkers is not particularly limited as long as it is a combination of two or more cytokines selected from IL-22, CCL20, IL-18, IL-17, TNF-α, and CXCL9, and examples include a combination of IL-18, CCL20, IL-17, IL-22, TNF-α, and CXCL9, a combination of IL-17 and CXCL9, a combination of IL-22, CCL20, and TNF-α, and a combination of CCL20, IL-17, IL-22, and TNF-α.

[0019] As described below in the Examples, for example, if the total concentration of IL-18, CCL20, IL-17, IL-22, TNF-α, and CXCL9 in the patient's serum before administration of dupilumab is about 0.5 pg / mL or less, the total concentration of IL-17 and CXCL9 is about 0.29 pg / mL or less, the total concentration of IL-22, CCL20, and TNF-α is about 0.22 pg / mL or less, or the total concentration of CCL20, IL-17, IL-22, and TNF-α is about 0.5 pg / mL or less, it can be said that administration of dupilumab to a patient is effective.

[0020] In the method of this embodiment, the biomarker may be IL-22 or IL-18. As described later in the Examples, the inventors have demonstrated that the concentrations of IL-18 and IL-22 in the serum of patients before administration of dupilumab correlate with the mean severity of atopic dermatitis 5 and 6 months after the start of dupilumab administration. Here, the mean severity of atopic dermatitis 5 and 6 months later refers to the mean severity of atopic dermatitis 5 months later and 6 months later.

[0021] [Kit for Predicting the Efficacy of Dupilumab Administration to Patients with Atopic Dermatitis] In one embodiment, the present invention provides a kit for predicting the efficacy of dupilumab administration to patients with atopic dermatitis, the kit comprising a substance that specifically binds to at least one biomarker selected from the group consisting of IL-22, CCL20, IL-18, IL-17, TNF-α, and CXCL9, the kit being used to measure the concentration of the biomarker in a blood sample derived from the patient prior to administration of dupilumab, the concentration of the biomarker being an index for predicting the efficacy of dupilumab administration to the patient. The kit of this embodiment can be used to preferably carry out the above-described method for predicting the efficacy of dupilumab administration to patients with atopic dermatitis. As will be described later in the Examples, the kit of this embodiment allows the efficacy of dupilumab administration to be predicted to patients with atopic dermatitis prior to administration of dupilumab.

[0022] IL-22, CCL20, IL-18, IL-17, TNF-α, CXCL9, and their concentrations are the same as those described above. Substances that specifically bind to IL-22, CCL20, IL-18, IL-17, TNF-α, and CXCL9 include antibodies, antibody fragments, aptamers, and the like. Antibody fragments include F(ab') ２ , Fab', Fab, Fv, scFv and the like.

[0023] In the kit of this embodiment, the specific binding substance is preferably configured to enable measurement of the concentration of IL-22, CCL20, IL-18, IL-17, TNF-α, or CXCL9 in a patient-derived blood sample. The method for measuring the concentration of IL-22, CCL20, IL-18, IL-17, TNF-α, or CXCL9 in a patient-derived blood sample is the same as that described above, and can be performed by, for example, ELISA.

[0024] The kit of this embodiment may compare the concentrations of the biomarkers with a predetermined threshold and predict the effectiveness of administering dupilumab to the patient based on the comparison result, where the predetermined threshold is the same as described above.

[0025] The kit of this embodiment may compare the concentrations of the combination of two or more of the biomarkers with a predetermined threshold and predict the efficacy of administering dupilumab to the patient based on the comparison result, where the combination of two or more of the biomarkers is the same as described above.

[0026] In the kit of this embodiment, the biomarker may be IL-22 or IL-18. As will be described later in the Examples, the inventors have demonstrated that the concentrations of IL-18 and IL-22 in the serum of patients before administration of dupilumab correlate with the mean severity of atopic dermatitis 5 and 6 months after the start of dupilumab administration.

[0027] Other Embodiments In one embodiment, the present invention provides a method for treating atopic dermatitis, comprising the steps of measuring the concentration of IL-22, CCL20, IL-18, IL-17, TNF-α, or CXCL9 in a blood sample from a patient with atopic dermatitis before administration of dupilumab, comparing the concentration with a predetermined threshold, and administering dupilumab to the patient if the comparison result indicates that administration of dupilumab to the patient is effective. According to the treatment method of this embodiment, dupilumab can be administered to patients for whom administration of dupilumab is expected to be effective, and a sufficient therapeutic effect can be expected.

[0028] In the treatment method of this embodiment, IL-22, CCL20, IL-18, IL-17, TNF-α, CXCL9, their concentrations, and the predetermined threshold are the same as those described above. Furthermore, the concentrations of a combination of two or more of the above biomarkers may be compared with a predetermined threshold, and the efficacy of administering dupilumab to a patient may be predicted based on the comparison results. Furthermore, the biomarker may be IL-22 or IL-18.

[0029] Dupilumab is typically administered subcutaneously to adults with atopic dermatitis at an initial dose of 600 mg, followed by 300 mg every two weeks. Children aged 6 months or older should receive the following subcutaneous doses based on their weight: 5 kg to less than 15 kg: 200 mg every four weeks; 15 kg to less than 30 kg: 300 mg every four weeks; 30 kg to less than 60 kg: 400 mg initially, followed by 200 mg every two weeks; and 60 kg or more: 600 mg initially, followed by 300 mg every two weeks.

[0030] The present invention will now be described in more detail with reference to examples, but the present invention is not limited to the following examples.

[0031] [Materials and Methods] (Evaluation of Severity of Atopic Dermatitis) The severity of atopic dermatitis was evaluated using a modified method of the eczema area and severity index (EASI, Hanifin JM, et al., "The eczema area and severity index (EASI): assessment of reliability in atopic dermatitis." EASI Evaluator Group, Exp Dermatol, 10 (1), 11-18, 2001). Specifically, the severity of atopic dermatitis was evaluated using the modified EASI (mEASI), calculated by subtracting the severity of the head and neck from the EASI (Nakagawa, H. et al., Phase 2 clinical study of delgocitinib ointment in pediatric patients with atopic dermatitis, The Journal of Allergy and Clinical Immunology, 144 (6), 1575-1583, 2019).

[0032] (Measurement of serum cytokine concentrations) Cytokine concentrations in serum collected from patients were measured. The cytokine concentrations measured included CCL27, IL-4, IL-5, eosinophil-derived neurotoxin (EDN), C-C motif chemokine ligand (CCL) 17, CCL20, IL-17, IL-22, C-X-C motif chemokine 9 (CXCL9), IL-16, IL-18, CCL5, matrix metalloproteinase-9 (MMP9), IL-6, tumor necrosis factor (TNF)-α, thymic stromal lymphopoietin (TSLP), and IL-10. Cytokines other than IL-17 and CCL17 were measured using the Sysmex Corporation fully automated immunoassay system HISCL, which was independently constructed at the Sysmex R&D Center Europe GmbH. （Ｒ）The following reagents R1 to R5 were used for measuring IL-22. The remaining markers were measured in the same manner as for measuring IL-22, except that the capture and detection antibodies were changed.

[0033] R1 Reagent: Biotin-labeled anti-IL-22 monoclonal antibody (Thermo Fisher Scientific) was dissolved in a buffer containing 100 mM triethanolamine (pH 7.4) containing 150 mM NaCl, 1% bovine serum albumin (BSA), and 0.5% casein to prepare R1 Reagent.

[0034] <<R2 Reagent>> Magnetic particles with streptavidin immobilized on the surface (hereinafter also referred to as "STA-bound magnetic particles"; average particle diameter 2 μm; amount of streptavidin per 1 g of magnetic particles 2.9 to 3.5 mg) were washed three times with 10 mM HEPES (pH 7.5). The washed STA-bound magnetic particles were added to 10 mM HEPES (pH 7.5) so that the streptavidin concentration was 18 to 22 μg / mL (STA-bound magnetic particle concentration 0.48 to 0.52 mg / mL), thereby preparing the R2 reagent.

[0035] <<R3 Reagent>> An anti-IL-22 monoclonal antibody (Thermo Fisher Scientific) derived from a clone different from the antibody used in the R1 Reagent was labeled with alkaline phosphatase (ALP) by a conventional method. The resulting ALP-labeled anti-IL-22 antibody was dissolved in 100 mM triethanolamine (pH 7.4) (containing 150 mM NaCl and 1% BSA) to prepare the R3 Reagent.

[0036] <<R4 Reagent and R5 Reagent>> The R4 reagent is a measurement buffer, HISCL. （Ｒ） R4 reagent (Sysmex Corporation) was used. R5 reagent was HISCL containing CDP-Star (registered trademark) (Applied Biosystems), a chemiluminescent substrate for ALP. （Ｒ） R5 reagent (Sysmex Corporation) was used.

[0037] Sysmex Corporation Fully Automated Immunoassay Device HISCL （Ｒ）The measurement procedure was as follows: After mixing the sample (20-30 μL) with the R1 reagent (50-100 μL), the R2 reagent (30 μL) was added. The magnetic particles in the resulting mixture were collected by magnetic collection, and the supernatant was removed. （Ｒ） A washing solution (300 μL) was added to wash the magnetic particles. The supernatant was removed, and R3 reagent (100 μL) was added to the magnetic particles and mixed. The magnetic particles in the resulting mixture were collected by magnetic collection, and the supernatant was removed. （Ｒ） The magnetic particles were washed by adding a wash solution (300 μL). The supernatant was removed, and R4 reagent (50 μL) and R5 reagent (100 μL) were added to the magnetic particles, and the chemiluminescence intensity was measured. The obtained chemiluminescence intensity was applied to a calibration curve to determine the concentration of the biomarker. The calibration curve was created using a calibrator for each biomarker. The calibrator was prepared from the recombinant protein of each biomarker.

[0038] IL-17 was measured using reagents for the Sysmex Corporation high-sensitivity automated immunoassay system HI-1000, which were independently constructed at Sysmex R&D Center Europe GmbH. IL-17 was measured using the following r1, r4 to r7 reagents and the above-mentioned R4 and R5 reagents.

[0039] <<r1 Reagent>> The r1 reagent was prepared by dissolving ALP-labeled anti-IL-17 monoclonal antibody (Thermo Fisher Scientific) in a buffer containing 100 mM triethanolamine (pH 7.4) (containing 150 mM NaCl, 1% BSA, and 0.5% casein).

[0040] <<r4 Reagent>> An anti-IL-17 monoclonal antibody (Thermo Fisher Scientific) derived from a clone different from the antibody used in the r1 reagent was labeled with biotin-dinitrophenol (DNP) and dissolved in a buffer containing 100 mM triethanolamine (pH 7.4) (containing 150 mM NaCl, 1% BSA, and 0.5% casein) to prepare the r4 reagent.

[0041] <<r5 Reagent>> Magnetic particles with anti-DNP antibodies immobilized on their surfaces (also referred to as anti-DNP magnetic particles) were washed with 100 mM MES (pH 6.5). The washed anti-DNP magnetic particles were added to 100 mM MES (pH 7.5) so that the concentration of the anti-DNP magnetic particles was 1%, to prepare the r5 reagent.

[0042] <<r6 Reagent>> Nε-DNP-L-lysine hydrochloride was added to 100 mM Tris (pH 7.5) to give a concentration of 2.5 mM to prepare r6 reagent.

[0043] <<r7 Reagent>> Magnetic particles with streptavidin immobilized on the surface (hereinafter also referred to as "STA-bound magnetic particles"; average particle diameter 2 μm; amount of streptavidin per 1 g of magnetic particles 2.9 to 3.5 mg) were washed three times with 10 mM HEPES (pH 7.5). The STA-bound magnetic particles after washing were added to 10 mM HEPES (pH 7.5) so that the streptavidin concentration was 18 to 22 μg / mL (STA-bound magnetic particle concentration 0.48 to 0.52 mg / mL), thereby preparing the r7 reagent.

[0044] The measurement procedure using the Sysmex Corporation High Sensitivity Automated Immunoassay System HI-1000 was as follows: After mixing the sample (30 μL) with r1 reagent (60 μL), r4 reagent (60 μL) was added. 20 μL of r5 was then added, and the magnetic particles in the resulting mixture were collected by magnetic collection, the supernatant was removed, and the resultant was analyzed by HISCL. （Ｒ） A washing solution (300 μL) was added to wash the magnetic particles. The supernatant was removed, and 110 μL of r6 reagent was added to the magnetic particles. The antigen-antibody complex contained in 80 μL of the supernatant was mixed with r7 reagent (30 μL). The magnetic particles in the resulting mixture were collected by magnetic collection, and the supernatant was removed. （Ｒ） The magnetic particles were washed by adding a wash solution (300 μL). The supernatant was removed, and R4 reagent (50 μL) and R5 reagent (100 μL) were added to the magnetic particles, and the chemiluminescence intensity was measured. The obtained chemiluminescence intensity was applied to a calibration curve to determine the concentration of the biomarker. The calibration curve was created using a calibrator for each biomarker. The calibrator was prepared from the recombinant protein of each biomarker.

[0045] HISCL is used to measure CCL17. （Ｒ） TARC reagent (Shionogi Pharmaceutical Co., Ltd.) was used.

[0046] Experimental Example 1 (Search for a Marker Capable of Predicting the Efficacy of Dupilumab Administration to Atopic Dermatitis Patients) Serum samples were collected from 19 atopic dermatitis patients before dupilumab administration, and the concentrations of the various cytokines described above were measured. Subsequently, continuous administration of dupilumab was initiated to the patients. Dupilumab was administered subcutaneously at 600 mg initially, followed by subcutaneous administration of 300 mg every two weeks. After the start of dupilumab administration, the severity of the patients' atopic dermatitis was evaluated every month for six months.

[0047] Based on the mean severity of atopic dermatitis after 5 and 6 months, patients were divided into two groups: excellent responders and moderate responders. Patients with an mEASI < 3 were classified as excellent responders.

[0048] Figure 1 is a graph showing the concentrations of various cytokines in the serum of patients in each group before administration of dupilumab. The upper end of the whiskers in the box-and-whisker plot represents the third quartile + 1.5 x IQR (interquartile range), the lower end of the whiskers represents the first quartile - 1.5 x IQR, the upper end of the box represents the third quartile, and the lower end of the box represents the first quartile. The box-and-whisker plot also shows the median.

[0049] As a result, it was revealed that there were significant differences in the concentrations of IL-22, CCL20, IL-18, IL-17, TNF-α, and CXCL9 in the serum of patients before administration of dupilumab between the good responder group and the moderate responder group.

[0050] Experimental Example 2 (Analysis of ROC curve, AUC, cutoff value, specificity, sensitivity, and AIC) Based on the results of Experimental Example 1, ROC curves (Receiver Operating Characteristic curves) were created for IL-22, CCL20, IL-18, IL-17, TNF-α, and CXCL9 when the patients were divided into a good responder group and a moderate responder group. The area under curve (AUC) was calculated from the ROC curve. The cutoff value was calculated using the Youden method. A logistic regression analysis was performed using treatment response as the objective variable and the cytokine concentration in the patient's serum before dupilumab administration as the explanatory variable, and the Akaike information criterion (AIC) was calculated.

[0051] The ROC curve is shown in Figure 2. Table 1 below shows the AUC, the 95% confidence interval of the AUC (AUC 95% CI), the cutoff value, the specificity, the sensitivity, and the AIC.

[0052]

[0053] The results showed that administration of dupilumab to patients was effective if the patient's serum IL-22 concentration before dupilumab administration was 5.34 pg / mL or less, CCL20 concentration was 3.85 pg / mL or less, IL-18 concentration was 332.62 pg / mL or less, IL-17 concentration was 0.04 pg / mL or less, TNF-α concentration was 7.03 pg / mL or less, or CXCL9 concentration was 27.49 pg / mL or less.

[0054] The above results demonstrate that the efficacy of administering dupilumab to patients with atopic dermatitis can be predicted based on the concentration of IL-22, CCL20, IL-18, IL-17, TNF-α, or CXCL9 in the patient's serum before administration of dupilumab.

[0055] Experimental Example 3 (IL-18 and IL-22 concentrations in patient serum before dupilumab administration correlated with the mean severity of atopic dermatitis 5 and 6 months after the start of dupilumab administration) Based on the results of Experimental Example 1, a Spearman correlation analysis was performed between the concentration of each cytokine in patient serum before dupilumab administration and the mean severity of atopic dermatitis 5 and 6 months after the start of dupilumab administration, without using the grouping of Experimental Example 1. Figure 3 is a graph showing the relationship between the concentration of each cytokine in patient serum before dupilumab administration and the mean severity of atopic dermatitis 5 and 6 months after the start of dupilumab administration. The severity of atopic dermatitis was expressed as the mean mEASI score.

[0056] The results showed that the concentrations of IL-18 and IL-22 in the serum of patients before dupilumab administration were significantly correlated with the average severity of atopic dermatitis 5 and 6 months after the start of dupilumab administration.

[0057] These results further support the idea that the effectiveness of dupilumab administration to patients with atopic dermatitis can be predicted based on the concentrations of IL-22 and IL-18 in the patient's serum before dupilumab administration.

[0058] Experimental Example 4 (Analysis of Combinations of Cytokines) Based on the results of Experimental Example 1, a multiple logistic model was created for combinations of two or more cytokines selected from IL-22, CCL20, IL-18, IL-17, TNF-α, and CXCL9, with treatment response as the objective variable and cytokine concentrations in the patient's serum before dupilumab administration as the explanatory variable, and the AIC was calculated. Furthermore, predicted values ​​for treatment response were obtained by substituting the concentrations of each cytokine, and ROC analysis was performed based on the calculated predicted values, and a cutoff value was calculated using the Youden method.

[0059] The ROC curve is shown in Figure 4. Table 2 below shows the AUC, the 95% confidence interval of the AUC (AUC 95% CI), the cutoff value, the specificity, the sensitivity, and the AIC.

[0060]

[0061] As a result, it was shown that administration of dupilumab to patients is effective if the predicted value calculated from the concentrations of IL-18, CCL20, IL-17, IL-22, TNF-α, and CXCL9 in the patient's serum before administration of dupilumab is 0.5 or greater, the predicted value calculated from the concentrations of IL-17 and CXCL9 is 0.29 or greater, the predicted value calculated from the concentrations of IL-22, CCL20, and TNF-α is 0.22 or greater, or the predicted value calculated from the concentrations of CCL20, IL-17, IL-22, and TNF-α is 0.5 or greater.

[0062] The above results demonstrate that the AUC is higher when based on the concentration of a combination of multiple cytokines than when based on the concentration of a single cytokine from among IL-22, CCL20, IL-18, IL-17, TNF-α, and CXCL9 in the serum of patients before dupilumab administration, and that the effectiveness of administering dupilumab to patients with atopic dermatitis can be predicted with higher accuracy.

[0063] According to the present invention, a method and kit for predicting the effectiveness of administration of dupilumab to a patient with atopic dermatitis can be provided.

Claims

1. A method for predicting the effectiveness of administration of dupilumab to a patient with atopic dermatitis, comprising a step of measuring the concentration of at least one biomarker in a blood sample from the patient prior to administration of dupilumab, wherein the concentration of the biomarker is an indicator for predicting the effectiveness of administration of dupilumab, and the biomarker is selected from the group consisting of interleukin (IL)-22, C-C Motif Chemokine Ligand (CCL) 20, IL-18, IL-17, Tumor Necrosis Factor (TNF)-α, and C-X-C Motif Chemokine 9 (CXCL9).

2. The method of claim 1, wherein the concentration of the biomarker is compared with a predetermined threshold, and the effectiveness of administering dupilumab to the patient is predicted based on the comparison result.

3. The method of claim 1, wherein the concentrations of two or more of the biomarkers are compared with predetermined thresholds, and the effectiveness of administering dupilumab to the patient is predicted based on the comparison result.

4. The method of claim 1 or 2, wherein the biomarker comprises IL-22 or IL-18.

5. A kit for predicting the effectiveness of administration of dupilumab to a patient with atopic dermatitis, comprising a substance that specifically binds to at least one biomarker selected from the group consisting of IL-22, CCL20, IL-18, IL-17, TNF-α, and CXCL9, the kit being used to measure the concentration of the biomarker in a blood sample derived from the patient prior to administration of dupilumab, and the concentration of the biomarker being an index for predicting the effectiveness of administration of dupilumab to the patient.

6. The kit of claim 5, wherein the biomarker comprises IL-22 or IL-18.

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