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

Abstract

Provided is a method for predicting the efficacy of dupilumab administration to an atopic dermatitis patient, the method comprising a step for measuring the expression level of at least one biomarker in a skin tissue sample from the patient prior to dupilumab administration, wherein the expression level of the biomarker is an indicator for predicting the efficacy of dupilumab administration.

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. 2024-084406, 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 effectiveness of administration of dupilumab to a patient with atopic dermatitis, the method comprising a step of measuring the expression level of at least one biomarker in a skin tissue sample derived from the patient before administration of dupilumab, wherein the expression level of the biomarker is an index for predicting the effectiveness of administration of dupilumab, and the biomarker is selected from the group consisting of genes shown in Tables 1, 2, 3-1, and 3-2 below or proteins encoded by the genes. [2] The method of [1], wherein the skin tissue sample is a sample derived from a lesion and the biomarker is selected from the group consisting of the genes shown in Table 1 or Table 2 or proteins encoded by the genes, or the skin tissue sample is a sample derived from a non-lesion and the biomarker is selected from the group consisting of the genes shown in Table 3-1 or Table 3-2 or proteins encoded by the genes. [3] The method of [1] or [2], wherein the expression levels of the biomarkers are compared with predetermined thresholds and the efficacy of administering dupilumab to the patient is predicted based on the comparison results. [4] The method of any of [1] to [3], wherein the expression levels of two or more of the biomarkers are compared with predetermined thresholds and the efficacy of administering dupilumab to the patient is predicted based on the comparison results. [5] The biomarkers are OGN, RECK, PDGFRL, IGSF10, DCN, and OLFML1 shown in Table 1, FBLIM1, SPRR1A, UPP1, PRSS3, and EPGN shown in Table 2, and TOB2, EGR1, MCL1, CBX4, IER2, PLK2, CSRNP1, EGR3, PMAIP1, MIDN, SRF, TGIF1, F2RL1, FOSB, DUSP2, JUNB, and SIK shown in Table 3. The method according to any one of [1] to [4], wherein the gene is selected from the group consisting of the genes 1, NCOA7, BTG2, NR4A2, OVOL1, EGR4, PIM3, NR4A1, ERRFI1, PTGER4, PTP4A1, IRF2BP2, ARC, ATF3, RNF168, SLC25A25, CYR61, PPP1R15A, CD55, THBD, SMAD7, RAP2B, and ITPRIP, or proteins encoded by the genes. [6] The method according to any one of [1] to [4], wherein the biomarker is selected from the group consisting of the genes RECK shown in Table 1, SPRR1A, KRT6A, PRSS3, UPP1, KRT6C, SMOX, EPGN, JHDM1D-AS1, PI3, SERPINB4, IL1RN, and PHLDA2 shown in Table 2, and RNF168, IER2, MCL1, EPHA2, JUNB, PTGER4, TRIB1, CSRNP1, FOSB, and SLC25A25 shown in Table 3, or proteins encoded by the genes.[7] The method according to any one of [1] to [4], wherein the biomarker is selected from the group consisting of the genes RECK, PDGFRL, OLFML3, and OGN shown in Table 1, FBLIM1, KRT6A, KRT6C, LIPG, JHDM1D-AS1, SERPINB4, and SPRR1A shown in Table 2, and the genes RNF168, MCL1, NCOA7, IER2, CSRNP1, EGR4, SMAD7, PIM3, PLK2, FOSB, EGR1, and SLC25A25 shown in Table 3, or proteins encoded by the genes. [8] A kit for predicting the effectiveness of administration of dupilumab to a patient with atopic dermatitis, comprising: a primer set that specifically amplifies by RT-PCR the mRNA of any gene selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2 in [1]; a probe that specifically hybridizes to the mRNA of any gene selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2; or a substance that specifically binds to a protein encoded by any gene selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2; and the kit is used to measure the expression level of at least one biomarker in a skin tissue sample derived from the patient before administration of dupilumab, wherein the biomarker is selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2 or the proteins encoded by the genes, and the concentration of the biomarker is an index for predicting the effectiveness of administration of dupilumab to the patient.

[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 a graph showing the results of Experimental Example 1. FIG. 3 is a graph showing the results of Experimental Example 2. FIG. 4 is a graph showing the results of Experimental Example 2. FIG. 5 is a graph showing the results of Experimental Example 3. FIG. 6 is a graph showing the results of Experimental Example 3. FIG. 7 is an ROC curve showing the results of Experimental Example 4. FIG. 8 is an ROC curve showing the results of Experimental Example 4. FIG. 9 is an ROC curve showing the results of Experimental Example 4.

[0009] [Method for predicting the efficacy of administering dupilumab to a patient with atopic dermatitis] In one embodiment, the present invention provides a method for predicting the efficacy of administering dupilumab to a patient with atopic dermatitis, the method comprising the step of measuring the expression level of at least one biomarker in a skin tissue sample derived from the patient before administration of dupilumab, wherein the expression level of the biomarker is an index for predicting the efficacy of administration of dupilumab, and the biomarker is selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2 above or proteins encoded by the genes.

[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] The patient's skin tissue sample is collected from the patient before administration of dupilumab. The skin tissue sample can be a skin specimen obtained by skin biopsy, tape strip, or the like. The skin tissue sample can be a punch biopsy with a diameter of approximately 1 mm.

[0012] Skin tissue samples are collected from lesions or non-lesion areas. Lesion areas refer to areas with erythema, moist erythema, papules, serous papules, scales, crusts, lichenification, prurigo, etc., and non-lesion areas refer to areas other than lesions.

[0013] As described later in the Examples, the skin tissue sample may be a sample derived from a lesion, and the biomarker may be selected from the group consisting of the genes or proteins encoded by the genes shown in Table 1 or Table 2. Alternatively, as described later in the Examples, the skin tissue sample may be a sample derived from a non-lesion, and the biomarker may be selected from the group consisting of the genes or proteins encoded by the genes shown in Table 3-1 or Table 3-2.

[0014] The expression level of a gene may be measured at the mRNA level by RNA-Seq, reverse transcriptase (RT)-PCR, quantitative real-time RT-PCR, DNA microarray, etc. Alternatively, for genes that encode proteins, the expression level may be measured at the protein level by enzyme-linked immunosorbent assay (ELISA), antibody array, lateral flow immunoassay, tissue immunostaining, etc. Note that for genes that do not encode proteins, the expression level may be measured at the mRNA level.

[0015] In the method of this embodiment, the expression levels 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.

[0016] Here, the predetermined threshold value is not particularly limited, and can be set empirically, for example, by accumulating data on the expression levels of biomarkers in skin tissue samples from atopic dermatitis patients before administration of dupilumab and the evaluation results of the severity of atopic dermatitis after administration of dupilumab.

[0017] Alternatively, a predetermined threshold may be set as follows. First, the expression level of a biomarker in a skin tissue sample from an atopic dermatitis patient before administration of dupilumab is measured. Then, the severity of atopic dermatitis after administration of dupilumab (e.g., 5 to 6 months later) is evaluated. Here, a lower severity of atopic dermatitis after administration of dupilumab indicates that administration of dupilumab was effective. Next, a threshold is set between the expression level of a biomarker in a skin tissue sample from an atopic dermatitis patient for whom administration of dupilumab was effective and the expression level of a biomarker in a skin tissue 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.

[0018] As described later in the Examples, it can be determined that administration of dupilumab to a patient is effective in any of the following cases (1), (2), and (3): (1) When the expression level of any gene selected from the group consisting of genes shown in Table 1 above, in a skin tissue sample derived from a lesion of the patient, is higher than a predetermined threshold. (2) When the expression level of any gene selected from the group consisting of genes shown in Table 2 above, in a skin tissue sample derived from a lesion of the patient, is lower than a predetermined threshold. (3) When the expression level of any gene selected from the group consisting of genes shown in Tables 3-1 and 3-2 above, in a skin tissue sample derived from a non-lesion of the patient, is lower than a predetermined threshold.

[0019] Tables 1, 2, 3-1, and 3-2 show the name of each gene, and for genes that encode proteins, the UniProt ID of the protein encoded by the gene is shown. The JHDM1D-AS1 gene in Table 2 is a gene that does not encode a protein, so the expression level can be measured at the mRNA level.

[0020] In the method of this embodiment, the expression levels of a combination of two or more of the above biomarkers may be compared with a predetermined threshold, and the effectiveness of administering dupilumab to the patient may be predicted based on the comparison results. As described below in the Examples, by combining two or more of the above biomarkers, the effectiveness of administering dupilumab to patients with atopic dermatitis can be predicted with higher sensitivity and specificity.

[0021] Examples of combinations of biomarkers include a combination of RECK, SPRR1A, and RNF168; a combination of RECK, KRT6A, and IER2; a combination of RECK, PRSS3, and MCL1; a combination of RECK, UPP1, and EPHA2; and a combination of RECK, KRT6C, and JUNB.

[0022] In the method of this embodiment, the biomarkers are OGN, RECK, PDGFRL, IGSF10, DCN, and OLFML1 shown in Table 1 above, FBLIM1, SPRR1A, UPP1, PRSS3, and EPGN shown in Table 2 above, and TOB2, EGR1, MCL1, CBX4, IER2, PLK2, CSRNP1, EGR3, PMAIP1, MIDN, SRF, TGIF1, F2RL1, FOSB, and DUSP shown in Table 3 above. 2, JUNB, SIK1, NCOA7, BTG2, NR4A2, OVOL1, EGR4, PIM3, NR4A1, ERRFI1, PTGER4, PTP4A1, IRF2BP2, ARC, ATF3, RNF168, SLC25A25, CYR61, PPP1R15A, CD55, THBD, SMAD7, RAP2B, and ITPRIP, or proteins encoded by the genes. As described below in Experimental Example 1 of the Examples, significant differences were observed in the expression levels of these genes between patients with atopic dermatitis who responded to administration of dupilumab and those who did not.

[0023] In the method of this embodiment, the biomarker may be selected from the group consisting of the genes or proteins encoded by the genes: RECK shown in Table 1; SPRR1A, KRT6A, PRSS3, UPP1, KRT6C, SMOX, EPGN, JHDM1D-AS1, PI3, SERPINB4, IL1RN, PHLDA2 shown in Table 2; and RNF168, IER2, MCL1, EPHA2, JUNB, PTGER4, TRIB1, CSRNP1, FOSB, SLC25A25 shown in Table 3. As will be described later in Experimental Example 2 of the Examples, significant differences were observed in the expression levels of these genes between atopic dermatitis patients for whom administration of dupilumab was effective and those for whom it was not effective.

[0024] In the method of this embodiment, the biomarker may be selected from the group consisting of the genes or proteins encoded by the genes: RECK, PDGFRL, OLFML3, and OGN shown in Table 1 above; FBLIM1, KRT6A, KRT6C, LIPG, JHDM1D-AS1, SERPINB4, and SPRR1A shown in Table 2 above; and RNF168, MCL1, NCOA7, IER2, CSRNP1, EGR4, SMAD7, PIM3, PLK2, FOSB, EGR1, and SLC25A25 shown in Table 3 above. As described below in Experimental Example 3 of the Examples, a significant correlation was observed between the expression levels of these genes and the average severity of atopic dermatitis 5 and 6 months after the start of dupilumab administration. Here, the average severity of atopic dermatitis after 5 and 6 months is the average of the severity of atopic dermatitis after 5 months and the severity of atopic dermatitis after 6 months.

[0025] [Kit for predicting the efficacy of administration of dupilumab to patients with atopic dermatitis] In one embodiment, the present invention provides a kit for predicting the efficacy of administration of dupilumab to patients with atopic dermatitis, the kit comprising: a primer set that specifically amplifies by RT-PCR the mRNA of any gene selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2 above; a probe that specifically hybridizes to the mRNA of any gene selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2 above; or a substance that specifically binds to a protein encoded by any gene selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2 above; the kit is used to measure the expression level of at least one biomarker in a skin tissue sample derived from the patient before administration of dupilumab, the biomarker being selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2 above or the proteins encoded by the genes; and the concentration of the biomarker is an index for predicting the efficacy of administration of dupilumab to the patient.

[0026] The kit of this embodiment can be used to suitably carry out the above-described method for predicting the effectiveness of dupilumab administration to atopic dermatitis patients. As will be described later in the Examples, the kit of this embodiment can predict the effectiveness of dupilumab administration to atopic dermatitis patients before dupilumab administration.

[0027] The kit of this embodiment may include an RNA-Seq reagent, which can be used to measure the mRNA expression level of any gene selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2 above by RNA-Seq using a next-generation sequencer.

[0028] A primer set that specifically amplifies by RT-PCR the mRNA of any gene selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2 above can be used to measure the expression level of the gene by the above-mentioned RT-PCR, quantitative real-time RT-PCR, etc. When quantitative real-time RT-PCR is performed, the kit of this embodiment may further include a TaqMan (registered trademark) probe specific to the gene to be measured.

[0029] A probe that specifically hybridizes to the mRNA of any gene selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2 above may, for example, constitute the above-mentioned DNA microarray and can be used to measure the expression level of the gene.

[0030] A substance that specifically binds to a protein encoded by any gene selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2 above can be used to measure the expression level of the gene at the protein level by the above-mentioned ELISA method, antibody array, lateral flow immunoassay, etc. Examples of specific binding substances include antibodies, antibody fragments, aptamers, etc. Examples of antibody fragments include F(ab') ２ , Fab', Fab, Fv, scFv and the like.

[0031] The kit of this embodiment may compare the expression levels of the biomarkers with a predetermined threshold and predict the efficacy of administering dupilumab to a patient based on the comparison results, where the predetermined threshold is the same as that described above.

[0032] The kit of this embodiment may compare the expression levels of a combination of two or more of the biomarkers with a predetermined threshold and predict the efficacy of administering dupilumab to a patient based on the comparison results, where the combination of two or more of the biomarkers is the same as that described above.

[0033] Other Embodiments In one embodiment, the present invention provides a method for treating atopic dermatitis, comprising the steps of measuring the expression level of at least one biomarker in a skin tissue sample derived from a lesion of the patient before administration of dupilumab, comparing the expression level with a predetermined threshold, and administering dupilumab to the patient if the effectiveness of administering dupilumab to the patient is indicated based on the comparison result, wherein the biomarker is selected from the group consisting of genes listed in Tables 1, 2, 3-1, and 3-2 above or proteins encoded by the genes. 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.

[0034] In the treatment method of this embodiment, the expression levels of the biomarkers and the predetermined thresholds are the same as those described above. In addition, the expression levels of a combination of two or more of the above biomarkers may be compared with a predetermined threshold, and the effectiveness of administering dupilumab to a patient may be predicted based on the comparison results.

[0035] The method for measuring gene expression levels is the same as described above. Dupilumab is typically administered to atopic dermatitis patients subcutaneously at 600 mg for adults initially, followed by 300 mg every two weeks. For children aged 6 months or older, dupilumab should be administered subcutaneously according to the following protocol based on body weight: 5 kg or more but less than 15 kg: 200 mg every four weeks; 15 kg or more but less than 30 kg: 300 mg every four weeks; 30 kg or more but 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.

[0036] 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.

[0037] [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).

[0038] (Collection of Skin Tissue Samples) Skin tissue samples were collected from lesions and non-lesion areas of atopic dermatitis patients before administration of dupilumab using Skin Biopsy Punch (product name, diameter 1 mm, Kai Corporation).

[0039] (RNA-Seq) Samples for RNA transcriptome analysis were prepared using RNAlater ＴＭThe samples were stored immersed in a solution (Thermo Fisher Scientific) at 4°C and then frozen at -80°C. RNA was extracted from the samples using Trizol (Thermo Fisher Scientific) and the Direct-Zol RNA Kit MiniPrep Kit (ZYMO RESEARCH) according to the manufacturer's protocol. Libraries were prepared using the NEBNext Ultra RNA Library Prep Kit for Illumina (New England Biolabs). A total of 10 ng of RNA (1 ng for small samples) was used for library preparation. The number of PCR cycles was adjusted to 18 or 21 depending on the amount of extracted RNA. Sequencing was performed using Illumina Hiseq 1500 or 2500 (Illumina).

[0040] Experimental Example 1 (Search for Markers Capable of Predicting the Efficacy of Dupilumab Administration to Atopic Dermatitis Patients 1) Before the start of treatment, skin tissue samples from lesions and non-lesion areas of 19 atopic dermatitis patients were analyzed by RNA-Seq. Subsequently, continuous administration of dupilumab was initiated to the patients. Dupilumab was administered subcutaneously at an initial dose of 600 mg, 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.

[0041] Based on the results of the evaluation of the severity of atopic dermatitis over 6 months of treatment, atopic dermatitis patients were divided into three groups: excellent responders, good responders, and poor responders. Patients in the excellent responder group were highly effective in receiving dupilumab. Patients in the good responder group were effective in receiving dupilumab. Patients in the poor responder group were poorly effective in receiving dupilumab.

[0042] 1 and 2 are graphs showing the expression levels of genes expressed in skin tissue for each of the good responder group, the favorable responder group, and the unfavorable responder group. The upper end of the whiskers in the box-and-whisker plots on the graphs indicates the third quartile + 1.5 x IQR (interquartile range), the lower end of the whiskers indicates the first quartile - 1.5 x IQR, the upper end of the box indicates the third quartile, and the lower end of the box indicates the first quartile. The box-and-whisker plots also show the median.

[0043] Figure 1 shows the results for skin tissue samples derived from lesions, and Figure 2 shows the results for skin tissue samples derived from non-lesion areas. Figure 1 shows the results for n = 19. Figure 2 shows the results for n = 15 because skin tissue samples derived from non-lesion areas could not be obtained in four cases. In Figures 1 and 2, "vst normalized value" means the gene expression level subjected to variance stabilizing transformation.

[0044] In Figures 1 and 2, "KC / FB / MD2," "KC / FB1," and "KC3" are the names of the gene groups given by the inventors. The gene group consisting of the genes shown in Table 1 above is "KC / FB / MD2." The gene group consisting of the genes shown in Table 2 above is "KC / FB1." The gene group consisting of the genes shown in Tables 3-1 and 3-2 above is "KC3."

[0045] 1 and 2 show genes that were found to be significantly correlated with the three groups of poor responders, good responders, and favorable responders by Spearman correlation analysis.

[0046] As a result, the results in Figure 1 show that administration of dupilumab to patients is effective when the expression levels of OGN, RECK, PDGFRL, IGSF10, DCN, and OLFML1, which are included in the gene group "KC / FB / MD2," are high in skin tissue samples derived from lesions of atopic dermatitis patients before administration of dupilumab.

[0047] Furthermore, it was shown that administering dupilumab to patients is effective when the expression levels of FBLIM1, SPRR1A, UPP1, PRSS3, and EPGN, which are included in the gene group "KC / FB1," are low in skin tissue samples derived from lesions of atopic dermatitis patients before dupilumab administration.

[0048] Furthermore, the results in Figure 2 show that in skin tissue samples from non-lesional areas of atopic dermatitis patients before dupilumab administration, TOB2, EGR1, MCL1, CBX4, IER2, PLK2, CSRNP1, EGR3, PMAIP1, MIDN, SRF, TGIF1, F2RL1, FOSB, DUSP2, JUNB, SIK1, NCOA7, BTG, and other genes included in the gene group "KC3" were detected. It has been shown that administration of dupilumab to patients with low expression levels of 2, NR4A2, OVOL1, EGR4, PIM3, NR4A1, ERRFI1, PTGER4, PTP4A1, IRF2BP2, ARC, ATF3, RNF168, SLC25A25, CYR61, PPP1R15A, CD55, THBD, SMAD7, RAP2B, and ITPRIP is effective.

[0049] Experimental Example 2 (Search for Markers Capable of Predicting the Effectiveness of Dupilumab Administration to Atopic Dermatitis Patients 2) The same 19 atopic dermatitis patients as in Experimental Example 1 were divided into two groups, excellent responders and moderate responders, based on the evaluation results of the average severity of atopic dermatitis 5 and 6 months after the start of dupilumab administration. Patients with an mEASI<3 were classified as excellent responders.

[0050] Figures 3 and 4 are graphs showing the expression levels of genes expressed in skin tissue for the good responder group and the moderate responder group. The upper end of the whiskers in the box-and-whisker plots on the graphs indicates the third quartile + 1.5 x IQR (interquartile range), the lower end of the whiskers indicates the first quartile - 1.5 x IQR, the upper end of the box indicates the third quartile, and the lower end of the box indicates the first quartile. The box-and-whisker plots also show the median.

[0051] 3 and 4 show genes for which a significant difference in expression level was observed between the good responder group and the moderate responder group by Wilcoxon test.

[0052] Figure 3 shows the results for skin tissue samples derived from lesions, and Figure 4 shows the results for skin tissue samples derived from non-lesion areas. Figure 3 shows the results for n = 19. Figure 4 shows the results for n = 15 because non-lesion skin tissue samples could not be obtained in four cases. In Figures 3 and 4, "vst normalized value" means the gene expression level subjected to variance stabilizing transformation.

[0053] As a result, the results in Figure 3 showed that administration of dupilumab to patients is effective when the expression level of RECK, which is included in the gene group "KC / FB / MD2," is high in skin tissue samples derived from lesions of atopic dermatitis patients before administration of dupilumab.

[0054] Furthermore, it was shown that administration of dupilumab to patients is effective when the expression levels of SPRR1A, KRT6A, PRSS3, UPP1, KRT6C, SMOX, EPGN, JHDM1D-AS1, PI3, SERPINB4, IL1RN, and PHLDA2, which are included in the gene group "KC / FB1," are low in skin tissue samples derived from lesions of atopic dermatitis patients before administration of dupilumab.

[0055] Furthermore, the results in Figure 4 show that administration of dupilumab to patients is effective when the expression levels of RNF168, IER2, MCL1, EPHA2, JUNB, PTGER4, TRIB1, CSRNP1, FOSB, and SLC25A25, which are included in the gene group "KC3," are low in skin tissue samples derived from non-lesional areas of atopic dermatitis patients before dupilumab administration.

[0056] Next, for these genes, a multiple logistic model was created in which the objective variable was treatment response and the explanatory variable was the expression level of the gene expressed in the patient's skin tissue before dupilumab administration, and the AIC (Akaike information criterion) was calculated. Furthermore, the expression level of each gene was substituted to obtain a predicted value of treatment response, and ROC analysis was performed based on the calculated predicted value, and a cutoff value was calculated using the Youden method.

[0057] 5 and 6 show the ROC curves. Table 4 below shows the AUC, the 95% confidence interval of the AUC (AUC 95% CI), the cutoff value, the specificity, the sensitivity, and the AIC. In Table 4, next to the gene name, it is indicated whether the skin tissue sample whose expression level was measured was derived from a lesion or a non-lesion.

[0058]

[0059] As a result, it was shown that administration of dupilumab to a patient is effective when the expression level of RECK in skin tissue samples derived from lesions of atopic dermatitis patients before administration of dupilumab is 8.38 or higher.

[0060] Furthermore, it was shown that administration of dupilumab to patients is effective when the expression level of SPRR1A in skin tissue samples derived from lesions of atopic dermatitis patients before administration of dupilumab is 10.54 or less, the expression level of KRT6A is 12.75 or less, the expression level of PRSS3 is 9.5 or less, the expression level of UPP1 is 7.44 or less, the expression level of KRT6C is 8.62 or less, the expression level of SMOX is 8.95 or less, the expression level of EPGN is 6.81 or less, the expression level of JHDM1D-AS1 is 7.69 or less, the expression level of PI3 is 7.89 or less, the expression level of SERPINB4 is 9.27 or less, the expression level of IL1RN is 10.1 or less, or the expression level of PHLDA2 is 8.24 or less.

[0061] Experimental Example 3 (Search for markers capable of predicting the effectiveness of dupilumab administration to atopic dermatitis patients 3) For the same 19 atopic dermatitis patients as in Experimental Example 1, without dividing them into groups based on the evaluation results of the severity of atopic dermatitis, a Spearman correlation analysis was performed between the expression levels of genes expressed in the skin tissue of the patients before dupilumab administration and the average severity of atopic dermatitis 5 and 6 months after the start of dupilumab administration.

[0062] Figures 7 and 8 are graphs showing the relationship between the expression levels of genes expressed in the skin tissue of patients before dupilumab administration and the average severity of atopic dermatitis 5 and 6 months after the start of dupilumab administration. The severity of atopic dermatitis is shown as the average mEASI score. Figures 7 and 8 show genes for which significant differences were observed as a result of Spearman correlation analysis.

[0063] Figure 7 shows the results for skin tissue samples derived from lesions, and Figure 8 shows the results for skin tissue samples derived from non-lesion areas. Figure 5 shows the results for n = 19. Figure 8 shows the results for n = 15 because non-lesion skin tissue samples could not be obtained in four cases. In Figures 7 and 8, "vst normalized value" means the gene expression level subjected to variance stabilizing transformation.

[0064] As a result, the results in Figure 7 showed that administration of dupilumab to patients is effective when the expression levels of RECK, PDGFRL, OLFML3, and OGN, which are included in the gene group "KC / FB / MD2," are high in skin tissue samples derived from lesions of atopic dermatitis patients before administration of dupilumab.

[0065] Furthermore, it was shown that administration of dupilumab to patients is effective when the expression levels of FBLIM1, KRT6A, KRT6C, LIPG, JHDM1D-AS1, SERPINB4, and SPRR1A, which are included in the gene group "KC / FB1," are low in skin tissue samples derived from lesions of atopic dermatitis patients before administration of dupilumab.

[0066] Furthermore, the results in Figure 8 showed that administration of dupilumab to patients is effective when the expression levels of RNF168, MCL1, NCOA7, IER2, CSRNP1, EGR4, SMAD7, PIM3, PLK2, FOSB, EGR1, and SLC25A25, which are included in the gene group "KC3," are low in skin tissue samples derived from non-lesional areas of atopic dermatitis patients before administration of dupilumab.

[0067] [Experimental Example 4] (Analysis of Gene Combinations) Based on the results of Experimental Example 1, a multiple logistic model was created for a combination of multiple genes, with the objective variable being treatment response and the explanatory variable being the expression level of the genes expressed in the patient's skin tissue before dupilumab administration, and the Akaike information criterion (AIC) was calculated. Furthermore, the expression level of each gene was substituted to obtain a predicted value of treatment response, and ROC analysis was performed based on the calculated predicted value, and a cutoff value was calculated using the Youden method.

[0068] Figure 9 shows an ROC curve based on the expression levels of a combination of multiple genes. Table 5 below shows the AUC, 95% confidence interval of the AUC (AUC 95% CI), cutoff value, specificity, sensitivity, and AIC. In Table 5, next to the gene name, it is indicated whether the skin tissue sample for which the expression level was measured was derived from a lesion or a non-lesion.

[0069]

[0070] As a result, it was shown that administration of dupilumab to patients is effective when the predicted value calculated from the expression levels of RECK, SPRR1A, and RNF168 in skin tissue samples derived from lesions of atopic dermatitis patients before dupilumab administration is 0.5 or greater, the predicted value calculated from the expression levels of RECK, KRT6A, and IER2 is 0.5 or greater, the predicted value calculated from the expression levels of RECK, PRSS3, and MCL1 is 0.5 or greater, the predicted value calculated from the expression levels of RECK, UPP1, and EPHA2 is 0.5 or greater, or the predicted value calculated from the expression levels of RECK, KRT6C, and JUNB is 0.34 or greater.

[0071] Furthermore, the results in Tables 4 and 5 indicate that the AUC is higher when based on the expression levels of a combination of multiple genes than when based on the expression levels of a single gene, and that the effectiveness of administering dupilumab to patients with atopic dermatitis can be determined with higher accuracy.

[0072] 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 expression level of at least one biomarker in a skin tissue sample derived from the patient before administration of dupilumab, wherein the expression level of the biomarker is an indicator for predicting the effectiveness of administration of dupilumab, and the biomarker is selected from the group consisting of genes or proteins encoded by the genes shown in Tables 1, 2, 3-1 and 3-2 below.

2. The method of claim 1, wherein the skin tissue sample is derived from a lesion and the biomarker is selected from the group consisting of the genes shown in Table 1 or Table 2 or proteins encoded by the genes, or the skin tissue sample is derived from a non-lesion and the biomarker is selected from the group consisting of the genes shown in Table 3-1 or Table 3-2 or proteins encoded by the genes.

3. The method according to claim 1 or 2, wherein the expression level 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.

4. The method according to claim 1 or 2, wherein the expression levels 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.

5. The biomarkers are: OGN, RECK, PDGFRL, IGSF10, DCN, and OLFML1 shown in Table 1; FBLIM1, SPRR1A, UPP1, PRSS3, and EPGN shown in Table 2; 3. The method of claim 1 or 2, wherein the gene is selected from the group consisting of TOB2, EGR1, MCL1, CBX4, IER2, PLK2, CSRNP1, EGR3, PMAIP1, MIDN, SRF, TGIF1, F2RL1, FOSB, DUSP2, JUNB, SIK1, NCOA7, BTG2, NR4A2, OVOL1, EGR4, PIM3, NR4A1, ERRFI1, PTGER4, PTP4A1, IRF2BP2, ARC, ATF3, RNF168, SLC25A25, CYR61, PPP1R15A, CD55, THBD, SMAD7, RAP2B, and ITPRIP genes shown in Table 3, or proteins encoded by the genes.

6. The method of claim 1 or 2, wherein the biomarker is selected from the group consisting of the genes RECK shown in Table 1, SPRR1A, KRT6A, PRSS3, UPP1, KRT6C, SMOX, EPGN, JHDM1D-AS1, PI3, SERPINB4, IL1RN, and PHLDA2 shown in Table 2, and RNF168, IER2, MCL1, EPHA2, JUNB, PTGER4, TRIB1, CSRNP1, FOSB, and SLC25A25 shown in Table 3, or proteins encoded by the genes.

7. The method of claim 1 or 2, wherein the biomarker is selected from the group consisting of the genes RECK, PDGFRL, OLFML3, and OGN shown in Table 1, FBLIM1, KRT6A, KRT6C, LIPG, JHDM1D-AS1, SERPINB4, and SPRR1A shown in Table 2, and RNF168, MCL1, NCOA7, IER2, CSRNP1, EGR4, SMAD7, PIM3, PLK2, FOSB, EGR1, and SLC25A25 shown in Table 3, or proteins encoded by the genes.

8. A kit for predicting the effectiveness of administration of dupilumab to a patient with atopic dermatitis, comprising: a primer set that specifically amplifies by RT-PCR the mRNA of any gene selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2 of claim 1; a probe that specifically hybridizes to the mRNA of any gene selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2; or a substance that specifically binds to a protein encoded by any gene selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2; the kit is used to measure the expression level of at least one biomarker in a skin tissue sample derived from the patient before administration of dupilumab, the biomarker being selected from the group consisting of the genes shown in Tables 1, 2, 3-1, and 3-2 or the proteins encoded by the genes; and the concentration of the biomarker is an index for predicting the effectiveness of administration of dupilumab to the patient.

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