Methods for determining responsiveness to anti-tumor necrosis factor therapy in the treatment of psoriasis

Abstract

The disclosure relates to the development of methods for predicting effectiveness of an anti-TNF agent in the treatment of psoriasis. More particularly, the disclosure provides new biomarkers and combinations of biomarkers for predicting effectiveness of an anti-TNF agent in the treatment of psoriasis and subsequently treating with an anti-TNF agent if the biomarker level is indicative of effectiveness in the anti-TNF treatment of the subject.

Description

(1) for USP18: an expression level at day 0 in uninvolved skin of at least about 86% greater than the mean expression level of USP18 in uninvolved skin of psoriatic patients at week 0; (2) for IL4R: an expression level at day 0 in uninvolved skin of at least about 36% greater than the mean expression level of IL4R in uninvolved skin of psoriatic patients at week 0; (3) for IFIH1: an expression level at day 0 in uninvolved skin of at least about 49% greater than the mean expression level of IFIH1 in uninvolved skin of psoriatic patients at week 0; (4) for SOX5: an expression level at day 0 in uninvolved skin of at least about 89% lesser than the mean expression level of SOX5 in uninvolved skin of psoriatic patients at week 0; and (5) for KRT2: an expression level at day 0 in uninvolved skin of at least about 99% lesser than the mean expression level of KRT2 in uninvolved skin of psoriatic patients at week 0. In other words, if a subject is determined to have a USP18 level at day 0 in uninvolved skin of at least about 86% greater than the control (i.e., the mean expression level of the biomarker in uninvolved skin in a population of psoriatic patients at week 0), or a IL4R level of at least about 36% greater than the control, or an IFIH1 level of at least about 49% greater than the control, or a SOX5 level of at least about 89% lesser than the control, or a KRT2 level of at least about 99% lesser than the control, the subject is predicted to have an average 10 point improvement in PASI score by week 12 of treatment with an anti-TNF agent.

[0089] In some aspects, it is predicted that the subject having a USP18 level at least about 20%, about 30%, about 40%, about 50%, about 60%, about 70%, or about 80% greater than the control level will have some improvement in PASI score by week 12 of treatment with an anti-TNF agent. In some aspects, it is predicted that the subject having an IL4R level at least about 10%, about 20%, or about 30% greater than the control level will have some improvement in PASI score by week 12 of treatment with an anti-TNF agent. In some aspects, it is predicted that the subject having an IFIH1 level at least about 10%, about 20%, about 30%, or about 40% greater than the control level will have some improvement in PASI score by week 12 of treatment with an anti-TNF agent. In some aspects, it is predicted that the subject having a SOX5 level at least about 20%, about 30%, about 40%, about 50%, about 60%, about 70%, or about 80% lesser than the control level will have some improvement in PASI score by week 12 of treatment with an anti-TNF agent. In some aspects, it is predicted that the subject having a KRT2 level at least about 20%, about 30%, about 40%, about 50%, about 60%, about 70%, about 80%, or about 90% lesser than the control level will have some improvement in PASI score by week 12 of treatment with an anti-TNF agent.

[0090] In some aspects, patients have a full clinical assessment at baseline (i.e., time 0), 2, 6 and 12 weeks by a dermatologist and BSA, PGA, and PASI scores are recorded. Methods of Treatment of Psoriasis

[0091] In various aspects, the disclosure includes methods of treating psoriasis.

[0092] In some aspects, the disclosure provides various anti-TNF agents in the treatment of psoriasis. In various aspects any anti-TNF agent is used in the methods or uses of the disclosure. In some aspects, the anti-TNF agent is an anti-TNF-alpha (anti-TNFoc) agent. In some aspects, the anti-TNF agent is etanercept, infliximab, adalimumab, certolizumab pegol, or golimumab, or a biosimilar thereof.

[0093] In some aspects, the anti-TNF agent is etanercept. Etanercept (e.g., ENBREL®) is available commercially and is an anti-TNF agent used to treat moderate-to-severe psoriasis, among other things. Etanercept treats autoimmune diseases by interfering with TNF, a soluble inflammatory cytokine, by acting as a TNF inhibitor. In some aspects, the anti-TNF agent is infliximab (e.g., REMICADE®). In some aspects, the anti-TNF agent is adalimumab (e.g., HUMIRA®). In some aspects, the anti-TNF agent is certolizumab pegol (e.g., CIMZIA®). In some aspects, the anti-TNF agent is golimumab (e.g., SIMPONI®).

[0094] In some aspects, the anti-TNF agent is a biosimilar to etanercept. In some aspects, the etanercept biosimilar is etanercept-ykro (Eticovo™) or etanercept-szzs (Erelzi™). In some aspects, the anti-TNF agent is a biosimilar to infliximab. In some aspects, the infliximab biosimilar is Remsima™ or infliximab-dyyb (Inflectra™). In some aspects, the anti-TNF agent is a biosimilar to adalimumab. In some aspects, the adalimumab biosimilar is adalimumab-atto (Amjevita™), adalimumab-bwwd (Hadlima™) or adalimumab-adaz (Hyrimoz™). In some aspects, the anti-TNF agent is a biosimilar to certolizumab pegol. In some aspects, the certolizumab pegol biosimilar is Xbrane™. In some aspects, the anti-TNF agent is a biosimilar to golimumab.

[0095] In other aspects, the anti-TNF agent is thalidomide, lenalidomide, pomalidomide, a xanthine derivative, or bupropion. In some aspects, it is possible that two or more anti-TNF agent is combined in a combination therapy. In some aspects, the anti-TNF agent is delivered with another drug or agent used in the treatment of psoriasis.

[0096] In some aspects, the disclosure includes additional treatments used in the treatment of psoriasis. In some aspects, such treatments are used in combination with treatment with an anti-TNF agent. These treatments can be used simultaneously or sequentially, either before or after treatment with an anti-TNF agent. Psoriasis treatments reduce inflammation and clear the skin. In some embodiments, treatments are divided into three main types: topical treatments, light therapy and systemic medications. Such topical treatments include, but are not limited to, corticosteroids, vitamin D analogues, anthralin, retinoids, calcineurin inhibitors, salicylic acid, coal tar, and moisturizers. Such light therapies include, but are not limited to, sunlight, UVB phototherapy, narrow band UVB phototherapy, Goeckerman therapy, psoralen plus ultraviolet A (PUVA) and exclimar laser. Such systemic medications include, but are not limited to, retinoids, methotrexate, cyclosporine, thioguanine, or hydroxyurea. Additionally, some psoriasis treatments include alternative medicines including, but not limited to, aloe vera, fish oil, and Oregon grape. Prognostic Methods and Methods of Treatment

[0097] In addition to the utilities described above, the biomarker or combination of biomarkers of the disclosure are useful in determining efficacy of a treatment for psoriasis. The phrase “treating psoriasis” includes ameliorating psoriasis and encompasses treating or ameliorating any of the symptoms associated with psoriasis.

[0098] In some aspects, it is useful to select subjects for treatment based on biomarker expression level. Also, in some aspects, it is useful to select subjects for treatment based on biomarker expression level along with the presence or absence of a variety of clinical parameters, such as PASI score, as discussed herein. Accordingly, the disclosure provides in one aspect a method of treating psoriasis in a subject suffering from psoriasis, wherein the method comprises the steps of measuring a level of a biomarker or a combination of biomarkers in a biological sample isolated from the subject, and wherein an increased or decreased level of the biomarker or combination of biomarkers present in the biological sample compared to a control level indicates a probability of successfully treating the subject with an anti-TNF agent, and administering an effective amount of a treatment comprising an anti-TNF agent.

[0099] In some embodiments, methods are provided for prognosing responsiveness to an anti-TNF agent in treatment of psoriasis in a subject and for treating psoriasis in a subject with an anti-TNF agent after it is determined or predicted that the subject will favorably respond to treatment with the anti-TNF agent.

[00100] The disclosure provides a method for prognosing responsiveness to an anti-TNF agent in treatment of psoriasis in a subject, the method comprising measuring a level of at least one biomarker in a biological sample of uninvolved skin isolated from the subject prior to treatment with the anti-TNF agent, wherein the at least one biomarker is ubiquitin specific protease 18 (USP18); keratin, type II cytoskeletal 2 epidermal (KRT2); interleukin 4 receptor (IL4R); sex-determining region Y-box transcription factor 5 (SOX5); interferon induced with helicase C domain 1 (IFIH1); or a combination of any two or more of the aforementioned biomarkers, and comparing the level with a control level, wherein the control level is the mean level of the biomarker in uninvolved skin in a population of subjects suffering from psoriasis prior to treatment with the anti-TNF agent, wherein when the level of USP18, ILR4, and / or IFIH1 in the subject is increased relative to the control level of the biomarker, the subject is predicted to be responsive to treatment with the anti-TNF agent, wherein when the level of KRT2 and / or SOX5 in the subject is decreased relative to the control level of the biomarker, the subject is predicted to be responsive to treatment with the anti-TNF agent, wherein when the level of USP18, ILR4, and / or IFIH1 in the subject is not increased relative to the control level of the biomarker, the subject is predicted to be non-responsive to treatment with the anti-TNF agent, and / or wherein when the level of KRT2 and / or SOX5 in the subject is not decreased relative to the control level of the biomarker, the subject is predicted to be non-responsive to treatment with the anti-TNF agent.

[00101] The disclosure provides a method for treating psoriasis in a subject, the method comprising measuring a level of at least one biomarker in a biological sample of uninvolved skin isolated from the subject prior to treatment with an anti-TNF agent, wherein the at least one biomarker is USP18 and the level of USP18 is increased relative to a control level; wherein the at least one biomarker is KRT2 and the level of KRT2 is decreased relative to a control level; wherein the at least one biomarker is IL4R and the level of IL4R is increased relative to a control level; wherein the at least one biomarker is SOX5 and the level of SOX5 is decreased relative to a control level; wherein the at least one biomarker is IFIH1 and the level of IFIH1 is increased relative to a control level; or wherein the at least one biomarker is a combination of any two or more of the aforementioned biomarkers; wherein the increased or decreased level of the biomarker in the subject relative to the control level predicts that the subject will be responsive to treatment with the anti-TNF agent, and wherein the control level is the mean level of the biomarker in uninvolved skin in a population of subjects suffering from psoriasis prior to treatment with the anti-TNF agent; and administering an effective amount of an anti-TNF agent to the subject predicted to be responsive to treatment.

[00102] In cases in which a method comprises combination of steps, each and every combination or sub-combination of the steps is encompassed within the scope of the disclosure, unless otherwise noted herein.

[00103] In regard to any of the methods provided, the steps of the method may occur simultaneously or sequentially. When the steps of the method occur sequentially, the steps may occur in any order, unless noted otherwise. Kits

[00104] As an additional aspect, the disclosure includes kits which comprise reagents packaged in a manner which facilitates their use for measuring a biomarker in a biological sample from a subject suffering from psoriasis. In some variations, such reagents are packaged together. In some variations, the kit further includes an analysis tool for evaluating the probability that the subject will favorably respond to an anti-TNF therapy after taking a measurement of at least one biomarker from a biological sample from the subject.

[00105] In one embodiment, the disclosure pertains to a kit for assaying a sample from a subject to determine the likelihood that the patient will positively respond to an anti-TNF therapy, wherein the kit comprises reagents necessary for selectively detecting the relative level of the biomarker or a combination of biomarkers in the subject and comparing them to a control. In certain embodiments, the biomarker is USP18, KRT2, IL4R, SOX5, or I Fl H1. In certain embodiments, the kit comprises one or more reagents for detecting and / or measuring the relative expression level of USP18, KRT2, IL4R, SOX5, or I Fl H1, or a combination of any one or more thereof in a sample from a subject suffering from psoriasis.

[00106] In a specific embodiment, the kits of the disclosure each contain an apparatus for collecting a biological sample from a subject and reagents for measuring the level of biomarker in a biological sample. In a further aspect, the kit comprises optional instructions included in the package that describes use of the reagents packaged in the kit for practicing the method.

[00107] In a further aspect of the present invention, a pharmaceutical pack (kit) is provided, the pack comprising an anti-TNF agent and a set of instructions for administration of the anti-TNF agent to a subject diagnostically tested and determined to be a subject who will favorably respond to treatment of their psoriasis with an anti-TNF agent. The anti-TNF agent can be any of the anti-TNF agents described herein. In exemplary aspects, the anti-TNF agent is etanercept.

[00108] In some embodiments, the kit further comprises a set of instructions for using the reagents comprising the kit. In certain embodiments, the kit further comprises a collection of data comprising correlation data between the biomarker level and the probability that the subject will favorably respond to treatment with the anti-TNF agent. In some aspects, therefore, the kit provides a means for measuring the relative level of the biomarker or biomarkers at day 0 and determining the relative increase or decrease in the level of the biomarker from a sample from the subject compared to the control level, i.e., the mean level of the biomarker at day 0 from the population of control subjects.

[00109] Each publication, patent application, patent, and other reference cited herein is incorporated by reference in its entirety to the extent that it is not inconsistent with the present disclosure.

[00110] Recitation of ranges of values herein are merely intended to serve as a shorthand method for referring individually to each separate value falling within the range and each endpoint, unless otherwise indicated herein, and each separate value and endpoint is incorporated into the specification as if it were individually recited herein.

[00111] All methods described herein are performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.

[00112] It is understood that the examples and embodiments described herein are for illustrative purposes only and that various modifications or changes in light thereof will be suggested to persons skilled in the art and are to be included within the spirit and purview of this application and scope of the appended claims. EXAMPLES

[00113] Additional aspects and details of the disclosure will be apparent from the following examples, which are intended to be illustrative rather than limiting. EXAMPLE 1 Materials and methods

[00114] Patient cohort

[00115] Patients with moderate-to-severe chronic plaque psoriasis for longer than 6 months were enrolled on an open-label 50mg biweekly etanercept treatment for three months. Study protocols were approved by the University of Michigan Institutional Review Board, and were carried out in accordance with Good Clinical Practice requirements and the Declaration of Helsinki. Informed consent was acquired from all participants. Patients were evaluated at baseline, and biopsy obtained under local anesthesia (lidocaine 1:10,000 epinephrine) from both uninvolved and lesional skin at baseline, and from lesional skin only at weeks 2, 6 and 12. Patients had full clinical assessment at 2, 6 and 12 weeks by a dermatologist and body-surface area, physician-global assessment and Psoriasis Area and Severity Index (PASI) were recorded. The study was registered on clinicaltrials.gov (NCT01971346).

[00116] RNA-seq processing

[00117] 50bp single-ended reads were generated from 210 RNA-seq samples from 46 patients. For each sequence file, trimmomatic was used to conduct adapter trimming (Bolger et al., Bioinformatics 2014; 30(15):2114-20), and STAR (Dobin et al., Bioinformatics. 2013; 29(1 ):15-21) was used for aligning the reads to human genome b37. HTSeq was employed for expression level quantification (Anders et al., Bioinformatics 2015; 31 (2):166-9), and only uniquely mapped reads were utilized. From 46 patients: one patient was removed due to drop out; two patients were removed because they did not have baseline (week 0) biopsy samples, leaving 43 patients and 206 RNA-seq samples for the subsequent analysis. One patient’s last visit was conducted on week 15, and the results were grouped to the week 12 data for all other patients when conducting the analysis. 28,182 genes were detected with on average >=1 read / sample, and we applied DEseq2 was applied for read normalization (Love et al., Genome Biol. 2014; 15(12):550). Principal component analysis was conducted using all genes after applying inverse normalization for the DESeq2 normalized data.

[00118] Associating RNA-seq expression with clinical response

[00119] Each gene expression profile, from baseline uninvolved or lesional skin samples, was correlated against change in psoriasis-area-and severity index (PASI), body surface area (BSA), and static Physician Global Assessment (sPGA) in each of the three follow-up visits. Age, gender, and baseline BMI of the patients were adjusted, and evaluated as both percent (%) as well as absolute (i.e. delta) disease improvement referencing the week 0 values. False Discovery Rate <10% was declared significant for association. Differential expression analyses (i.e. comparing uninvolved vs lesional skin at baseline; comparing lesional skin at baseline versus subsequent visit) were conducted using DESeq2 negative binomial distribution, and FDR<=10% and |log2Fold Change|>=1 were used as criteria to declare significant genes.

[00120] Comparison against cytokine signatures in keratinocytes

[00121] The procedures for identifying the cytokine signatures in keratinocytes were described previously [Tsoi et al., J. Invest. Dermatol. 2019 Jul; 139(7):1480-1489. doi: 10.1016 / j.jid.2O18.12.018. Epub 2019 Jan 11. PMID: 30641038], Briefly, 50 normal human keratinocyte samples from 50 different healthy adults were obtained. Keratinocytes were grown in a 12-well plate in 154 CF medium (Thermo Fisher #M154CF500) with human keratinocyte growth supplement (Thermo Fisher #S0015). Keratinocytes were grown to confluency at which time the complete medium (with supplements) was replaced by basal 154 CF medium (without supplements). Cells were then stimulated with cytokines (IL-4, IL-13, IFN-a, IFN-y, TNF-a, and IL-17A (R&D Systems)), each provided individually at 10 ng / ml concentration. After 8 hrs, cells were harvested and RNA was isolated using RNeasy Plus Mini kit (Qiagen # 74136). RNA was analyzed by RNA Nano Chips (Agilent Technologies) and sequenced (Sarkar et al., Ann Rheum Dis. 2018, 77:1653-1664). The top 1,000 genes were extracted with their baseline expression profiles showing the strongest correlations with future absolute PASI improvement in each of the three follow-up visits, and used in a hypergeometric test to compare against cytokine signatures to understand their molecular basis.

[00122] Predicting drug response

[00123] Each patient from the cohort was assigned a TNF or IFN score based on their baseline expression profiles in uninvolved skin: for each gene / induced by TNF / IFN in keratinocytes. The relative expression of that gene in patient pwas determined by referencing the median value across samples: rp'=gp7median(g'), where g is the normalized expression. The TNF or IFN score for patient p was then defined as the upper quartile of the r? value across all genes induced by TNF or IFN, respectively. To model the week 12 PASI response, baseline uninvolved skin expression profiles for the genes induced by TNF / Type I IFN by keratinocyte experiments (as described herein above) were utilized. Principal components were used to reduce the data dimension. Logistic regression was applied to model the drug responses at week 12 using the PASI 75 criteria, using leave-one-out to ensure the robustness upon model evaluation (i.e. principal component analysis and regression modeling were performed only on the training data). A 75% reduction in the PASI score (PASI 75) is the current benchmark of primary endpoints for most clinical trials of psoriasis. The area under the receiver operative characteristic (AUROC) was computed for PASI 75 using different numbers of principal components. Finally, to further assess the potential clinical implication, the precision (proportion of true positives among the predicted PASI75) and recall (proportion of actual PASI75 predicted), as functions of the proportion of top samples predicted from the model, was measured.

[00124] Immunohistochemistry

[00125] Formalin fixed, paraffin-embedded tissue slides obtained from patients with psoriasis and skin samples from healthy people not suffering from psoriasis, i.e., healthy or normal controls, were heated for 30 min at 60°C, rehydrated, and epitope retrieved with Tris-EDTA, pH 6. Slides were blocked, incubated with a USP18 primary antibody (1:100; LS-B1182-50; Lifespan Bioscience) overnight at 4°C. Slides were then washed with PBS and incubated with a biotinylated secondary antibody (biotinylated goat anti-rabbit IgG Antibody; BA1000; Vector Laboratories) for 30 min at room temperature, and then incubated with fluorochrome-conjugated streptavidin for 10 min at room temperature. Slides were prepared in mounting medium with 4',6-diamidino-2-phenylindole (DAPI) (VECTASHIELD Antifade Mounting Medium with DAPI, H-1200, VECTOR). Images were acquired using a Zeiss Axioskop 2 microscope and analyzed by SPOT software 5.1. Images presented were representative of at least three experiments.

[00126] RNAi depletion, RNA extraction, qRT-PCR

[00127] Upon reaching semi-confluence, the culture medium of keratinocytes was changed by Accell Delivery Media (B-005000, Dharmacon) with 1 pM Accell siRNA targeting USP18 (E-004236-00-0005, Dharmacon). After 48h, cells were stimulated with IFN-a (10ng / ml, I4276, R&D Systems), TNF-a (10ng / ml, 210-TA, R&D Systems), IL-17A (20ng / ml, 7955-IL, R&D Systems), or IFN-y (10ng / ml, 285-IF, R&D Systems) for another 24h. RNA was isolated from cells using RNeasy plus kit (74136, Qiagen). QRT-PCR was performed on a 7900HT Fast Real-time PCR system (Applied Biosystems) with TaqMan Universal PCR Master Mix (ThermoFisher 4304437). Primers (ThermoFisher Scientific) used in this study were: USP18, Hs00276441_m1; IL36G, Hs00219742_m1; DEFB4, Hs00175474_m1; MX1, Hs00895608_m1; OASL, Hs00984387_m1; IRF7, Hs01014809_g1; IFNK, Hs00737883_m1 (ThermoFisher Scientific). EXAMPLE 2 RNA-seq to profile the trajectory of transcriptome for patients initiated on etanercept therapy

[00128] 46 psoriatic patients were enrolled for this study (Figure 1 A). Each patient was treated with etanercept (trade name Enbrel or Benepali), twice weekly with 50 mg. Prior to initiation (baseline / week 0), demographic information (age, sex) and other clinical information, including PASI score, body surface area (BSA), and sPGA were collected. Skin punch biopsies were performed at baseline on uninvolved and lesional skin for transcriptome profiling using RNA-seq, and additional lesional samples were obtained at the time of follow-up on week 2, week 6, and week 12, along with clinical assessment. Follow-up data on 42 patients was obtained (i.e. with transcriptomic data from both baseline and at least one of the follow-up visits), and a total of 36 patients completed the study with RNA-seq and clinical data available at both baseline and at the week 12 visit.

[00129] A total of 210 RNA-seq experiments were performed on the 46 patients in the cohort. By using principal component analysis (PCA), changes of the transcriptomes were tracked over the treatment course (Fig. 1B). As expected, PCA separated uninvolved and lesional skin at baseline, but during the treatment period, the largest principal component (i.e., PC1) of lesional skin changed overtime such that by week 12 it overlapped, in a proportion of the cohort, with that of uninvolved skin at baseline. However, some patients still had PC1 values that remained at baseline level by week 12, despite improvement in PASI. Notably, the former group tended to have a lower PASI score than the latter group at week 12 (lower panel in Fig. 1B). Changes over time were further investigated at the gene expression level to determine how the expression profiles changed during the 12-week treatment period (Fig. 1C): Similar to the PCA results , there was a sharp contrast between uninvolved and lesional skin at baseline, but the contrast decreased (or became less apparent) as treatment with etanercept proceeded. Indeed, when comparing gene expression levels in baseline lesional skin with that from follow-up visits, a gradual increase in the number of differentially expressed transcripts was observed (see Table 2 below), and restoration towards gene expression levels in uninvolved skin at baseline (Figure 6) was observed. Nevertheless, heterogeneity was observed among patients’ transcriptomic responses at week 12, concordant with the clinical variations (Leonardi et al., N Engl J Med. 2003; 349(21 ):2014-22; Zaba et al., J Allergy Clin Immunol. 2009; 124(5):1022-10 e1 -395.)). Table 2. Number of differentially expressed genes when comparing the lesional skin (PP) from baseline versus that from follow-up visits. PP week 0 versus: Up-regulated genes Down-regulated genes Total Differential expressed genes Week 2 47 132 179 Week 6 547 532 1,079 Week 12 1,004 796 1,800 EXAMPLE 3 Expression profiles at baseline uninvolved skin are associated with PASI improvement

[00130] The associations between baseline expression profiles and clinical presentation were examined. The expression level (from uninvolved or lesional skin) of each gene at week 0 was correlated with the change in PASI, BSA, and / or sPGA in each of the three follow-up visits. Both percent (%) as well as absolute (i.e., delta) disease improvement were evaluated, referencing the week 0 values.

[00131] Surprisingly, significant associations between gene profiles could be identified only in baseline uninvolved skin, rather than lesional skin, versus PASI improvement from at least one of the follow-up visits. When using percent change as measure, there were 198 genes with their week 0 expression profiles significantly (FDR<=10%) associated with week 12 PASI improvement. When using absolute change as measure, there were 192 genes at week 6 and 391 genes at week 12 with their baseline expression profiles significantly associated with week PASI improvement. No significant results for associations against BSA and sPGA change were detectable.

[00132] Among the significant genes with their baseline expressions associating with PASI improvement at week 12, 105 of them overlapped between the percent and absolute measures. USP18, an ubiquitin specific peptidase, and KRT2, a type I cytokeratin, are two prominent examples with expression in uninvolved skin at baseline showing significant association with PASI improvement in follow-up visit (Figure 2A-F):

[00133] USP18 was significantly up-regulated in lesional skin at baseline (fold change, FC=2.5; p=1x10'26), and its expression in uninvolved skin at baseline was positively correlated with absolute PASI improvement at week 12 (p=9.8x10'4; 20% increase from mean expression level has on average 2.3 PASI improvement after adjusting for age, gender, and BMI); KRT2 was significantly down-regulated in lesional skin at baseline (FC=0.32; p=1.3x10'6) and its expression in uninvolved skin at week 0 was inversely correlated with both the absolute (p=1.4x1 O'5; 20% decrease from mean expression level has on average 0.99 PASI improvement after adjusting forage, gender, and BMI) and percent (p=5.4x10'4) PASI improvement at week 12. Although their associations with PASI improvement at week 2 and week 6 were not significant, the direction of correlations is consistent (Fig. 2A and 2D). Interestingly, these associations were not observed when using baseline expression levels in lesional skin (Fig. 2B and 2D). Furthermore, the expression levels of these two genes in lesional skin gradually “restored” towards expression levels in uninvolved skin over time (Fig. 2C and 2F). These results indicate that both USP18 and KRT2 are dysregulated in psoriatic skin but can be “restored” to uninvolved skin levels by etanercept treatment, and their expression level in uninvolved skin prior to treatment are associated with future PASI improvement.

[00134] Several functional assays were carried out to better understand the potential role of USP18 in TNF responses. First, an independent transcriptomic cohort recently conducted was used to validate the up-regulation of USP18 in lesional skin (Figure 7). Interestingly, the expression level of USP18 was found to be marginally up-regulated in uninvolved skin when compared with normal skin (FC=1.5; p=1.2x1 O'2). USP18 is also positively correlated with other psoriasis cytokines (IL23A and IL36G) in lesional skin (p=6.3x10 5 and p=8.3x10 7, respectively). By using immunostaining (Fig. 3A), the distribution of USP18 proteins in both uninvolved and lesional psoriatic skin was observed, confirming its expression in the epidermal layer. Small inhibitory RNA (siRNA) was used to knockdown the expression of USP18 in keratinocytes and evaluate the impact on TNF / interferon (IFN) responses. Significantly, the effective knock-down of USP18 had an effect on both TNF and IFN stimulations (Fig. 3B-D). Upon TNF stimulation, USP18 knock-down tended to suppress IL36G mRNA expression but tended to induce DEFB4 mRNA expression (during TNF+IL17 stimulation). Upon IFN stimulation, USP18 knock-down promoted greater expression of IFN-response genes, including MX1, IFNK, OASL, and IRF7. Conversely, USP18 overexpression (Fig. 3E-G) decreased type I and type II IFN responses (Fig. 3E-G) but enhanced IL-17A induced effect on IL36G and TNF-induced effect on DEFB4 (Fig. 3E). These results suggest that USP18 has an inhibitory effect on IFN response, while facilitating some TNF responses (i.e., IL36G mRNA expression).

[00135] Because IFN and TNF have been thought to have counter-regulatory roles in psoriasis (Conrad et al., Nat Commun. 2018; 9(1):25), a lower USP18 expression level, in some aspects, may be helpful in promoting a greater IFN response and, thus, lower dependence on TNF, in agreement with the observation that USP18 has a positive correlation with PASI improvement during the course of etanercept treatment. EXAMPLE 4 Integrative approach to provide biological and clinical implications using uninvolved skin

[00136] An integrative approach was used to understand how RNA-seq results could be used to provide biological and clinical implications for etanercept treatment in psoriasis. Results with in vitro experiments studying the effect of different cytokine stimulations in keratinocytes were first analyzed. Among the genes showing the strongest differential expression (upregulation and downregulation) in lesional skin between baseline and subsequent follow-up visits, significant (FDR (or log fold change) <10%) enrichment of IFN, TNF, and IL17 signatures (Fig. 4A) were observed, concordant with the etanercept’s TNF inhibitory effect and its associated negative regulation on Th17 response (Krueger et al., J. Amer. Acad. Derm. 2006;54(3 Suppl 2) :S 112-9; Zaba et al., J Allergy Clin Immunol. 2009; 124(5):1022-10 e1-395).

[00137] Next, the top 1,000 genes with their baseline expression profiles showing the strongest correlations with future absolute PASI improvement in each of the three follow-up visits were extracted, and compared against type I IFN, TNF and IL-17A keratinocytes cytokine signatures to understand their molecular basis. Strikingly, it was found that significant enrichment for TNF and Type I IFN signatures for week 0 uninvolved skin gene expression profiles have the strongest correlations with week 6 and week 12 absolute PASI improvement (Fig. 4B). Notably, there was no significant enrichment when using week 0 gene expression profiles in lesional skin. When using percentage PASI improvement as a measure, the same Type I IFN signature enrichment was observed (e.g., week 6 for IFN-a and week 12 for IFN-y), and enrichment for IL-17A responses was observed at week 12. It is notable that both USP18 and KRT2 were significantly differentially expressed upon TNF stimulation in keratinocytes, and USP18 was up-regulated by IFNs (Fig. 8).

[00138] Each patient from the cohort was assigned a TNF or IFN score (see Example 1), summarizing the respective cytokine signature loading for the uninvolved skin of that patient at baseline (Fig. 5A-B). Among the patients showing higher IFN or TNF scores, a higher proportion of PASI improvement was observed in terms of both absolute or percentage measures. It therefore was hypothesized that by using cytokine signatures from keratinocytes as prior information, drug response assessment could be provided. To provide the most robust drug response assessment, a genomic approach was used. Greater than 2,900 genes were identified as being dysregulated upon cytokine stimulation in independent experiments. For each psoriatic patient in the cohort, the principal components of the baseline uninvolved skin expression levels for >2,900 genes that were induced in response to treatment with TNF-a, IFN-a or IFN-y were obtained.

[00139] Logistic regression was applied to these components to model the drug responses at week 12 using the PASI 75 criteria, using the leave-one-out validation to ensure robustness upon model evaluation, up to 0.75 in area under the receiver operating characteristic (AUROC) (Fig. 5C) was able to be obtained. To further assess the potential clinical implications, precision (proportion of true positives among the predicted PASI 75) and recall (proportion of actual PASI 75 predicted) were measured as functions of the proportion of top samples predicted from the model (Fig. 5D). Among the top 20% of samples exhibiting the top PASI 75 predicted score, up to 80% accuracy was achieved, representing the ability to use uninvolved skin transcriptome at baseline to identify patients that will most likely benefit from etanercept treatment. EXAMPLE 5 Integrative approach to identify additional genes important in assessing drug response of etanercept

[00140] To identify predictors of treatment outcome with etanercept, a longitudinal study with 210 RNA-seq samples from 46 patients with chronic plaque psoriasis treated with etanercept was conducted.

[00141] An integrative approach was taken to identify the most informative biological features that can assess the drug response of etanercept at week 12, combining longitudinal tissue molecular profiling (RNA-seq), and cross compared against RNA-seq data from in vitro independent cytokine-stimulated keratinocytes in conjunction with statistical modeling. The associations between baseline gene expression profiles and clinical presentation were examined. The expression level (from uninvolved skin) of each gene was measured using RNA-seq at week 0, and was correlated with the change in PASI score in each of the three follow-up visits (at weeks 2, 6, and 12). Both percent (%) change as well as absolute (i.e. delta) change in disease improvement, referencing the week 0 values, were evaluated.

[00142] Significant associations between gene profiles in baseline uninvolved skin versus PASI improvement from at least one of the follow-up visits were identified only when using percent change as measure. There were 198 genes with their week 0 expression profiles significantly (false discovery rate (FDR)<=10%) associated with week 12 PASI improvement; when using absolute change as measure. There were 192 genes with their baseline expression profiles significantly associated with week 6 12 PASI improvement. There were 391 genes with their baseline expression profiles significantly associated with week 12 PASI improvement.

[00143] Among the genes identified to have their baseline expression levels associating with PASI improvement at week 12, 105 of them overlapped between the percent and absolute measures. USP18, an ubiquitin specific peptidase, and KRT2, a type I cytokeratin, are two prominent examples with expression in uninvolved skin at baseline showing significant association with PASI improvement in follow-up visit (Figure 1). USP18 was significantly up-regulated in lesional skin at baseline (Fold Change (FC)=2.5; p=1x10'26), and its expression in uninvolved skin at baseline was positively correlated with absolute PASI improvement at week 12 (p=9.8x10'4). KRT2 was significantly down-regulated in lesional skin at baseline (FC=0.32; p=1.3x1 O'6) and its expression in uninvolved skin at week 0 was inversely correlated with both the absolute (p=1.4x1 O'5) and percent (p=5.4x10'4) PASI improvement at week 12. Although their associations with PASI improvement at weeks 2 and 6 were not significant statistically, the direction of correlations is consistent (Fig. 1A and 1D). Interestingly, these associations were not observed when using baseline expression levels in lesional skin (Fig. 1B and 1D). Furthermore, the expression levels of these two genes in lesional skin gradually “restored” toward expression levels in uninvolved skin over time (Fig. 1C and 1F). These results indicate that both USP18 and KRT2 are dysregulated in psoriatic skin but can be “restored” to uninvolved skin levels by etanercept treatment, and their expression levels in uninvolved skin prior to treatment with etanercept are associated with future PASI improvement.

[00144] To model the week 12 PASI response, baseline (week zero) uninvolved skin gene expression profiles for the >2,900 genes induced by cytokine stimulation, e.g., TNF / Type I IFN (as identified by previous keratinocytes experiments), were utilized as described herein above. For each psoriatic patient in the cohort, the principal components of the baseline uninvolved skin expression levels for >2,900 genes that were induced in response to treatment with TNF-oc, IFN- oc or IFN-y were obtained.

[00145] Logistic regression was applied to model the drug responses at week 12 using the PASI 75 criteria, using leave-one-out to ensure the robustness upon model evaluation (i.e., principal component analysis and regression modeling were performed only on the training data). Area under the receiver operative characteristic (AUROC) for PASI 75 was computed using different number of principal components. To further assess the potential clinical implication, precision (proportion of true positives among the predicted PASI 75) and recall (proportion of actual PASI 75 predicted) were measured as functions of the proportion of top samples predicted from the model. Up to 0.75 in AUROC was obtained (Fig. 2). Among the top 20% of samples exhibiting the top PASI 75 prediction, up to 80% accuracy in predictive response was achieved, representing the ability to use the uninvolved skin transcriptome at baseline to identify patients that will most likely benefit from etanercept treatment.

[00146] Regression analysis was applied to identify genes whose expression levels correlated with drug responses in psoriatic patients who will most likely benefit from etanercept treatment. USP18, KRT2, IL4R, SOX5, and IFIH1 were identified as the top protein-coding gene candidates to be used biomarkers for indicating whether a psoriatic patient will favorably respond to treatment with an anti-TNF agent. To evaluate the robustness of this approach, the feature selection process was repeated 36 times, leaving out a different sample each time, and assessing the performance of the left-out samples, achieving AUROC>0.75.

[00147] This study showed that by modeling with in vitro genomic data on cytokine responses, significant associations between gene profiles from uninvolved skin at baseline and improvement in psoriasis severity index (PASI) at follow-up visits were identified. Notably, gene profiles in uninvolved, but not inflamed skin, at baseline were the best predictors of treatment response at week 12. These results demonstrate feasibility of assessing drug response in psoriasis utilizing uninvolved skin and implicate involvement of IFN / TNF regulators in anti-TNF responses. EXAMPLE 6 Assessing PASI improvement in response to treatment with etanercept

[00148] Each gene expression profile from baseline uninvolved or lesional skin samples was correlated against change in PASI, body surface area (BSA), and static Physician Global Assessment (sPGA) in each of the three follow-up visits. Each sample was adjusted for age, gender, and baseline BMI of the patients, and evaluated both percent (%) as well as absolute (i.e., delta) disease improvement referencing the week 0 (i.e. day 0) values. False Discovery Rate <10% was declared significant for association. Specifically, regression analysis was applied to identify genes whose expression levels correlated with drug responses in psoriatic patients who will most likely benefit from anti-TNF (e.g. etanercept) treatment. USP18, KRT2, IL4R, SOX5, and IFIH1 were identified as the top protein-coding gene candidates to be used also biomarkers for indicating whether a psoriatic patient will favorably respond to treatment with an anti-TNF agent. Age, gender, and BMI were used as covariate in the regression analysis. The p-values for these genes in the association analysis were as follows: USP18: 9.81x1 O'4; KRT2: 1.45x1 O'5; IFIH1: 2.12x1 O'3; SOX5: 1.85x1 O'3; and IL4R: 1.6x1 O'5.

[00149] Using USP18 as a biomarker for predicting responsiveness to etanercept, a 20% increased level from the baseline or mean level of USP18 in the control (i.e., mean level in uninvolved skin from psoriatic patients prior to treatment) showed an average 2.3 point improvement in PASI in a subject at week 12 of treatment with etanercept. Using KRT2 as a biomarker for predicting responsiveness to etanercept, a 20% increased level from the baseline mean level of KRT2 in the control (i.e., uninvolved skin from psoriatic patients) showed an average 0.99 point improvement in PASI in a subject at week 12 of treatment with etanercept. Using IL4R as a biomarker for predicting responsiveness to etanercept, a 20% increased level from the mean level of IL4R in the control (i.e., uninvolved skin from psoriatic patients) showed an average 5.5 point improvement in PASI in a subject at week 12 of treatment with etanercept. Using SOX5 as a biomarker for predicting responsiveness to etanercept, a 20% increased level from the mean level of SOX5 in the control (i.e., uninvolved skin from psoriatic patients) showed an average 2.3 point improvement in PASI in a subject at week 12 of treatment with etanercept. Using I Fl H1 as a biomarker for predicting responsiveness to etanercept, a 20% increased level from the mean level of IFIH1 in the control (i.e., uninvolved skin from psoriatic patients) showed an average 4.1 point improvement in PASI in a subject at week 12 of treatment with etanercept.

[00150] The disclosure has been described in terms of particular embodiments found or proposed to comprise specific modes for the practice of the disclosure. Various modifications and variations of the described invention will be apparent to those skilled in the art without departing from the scope and spirit of the invention. Although the invention has been described in connection with specific embodiments, it should be understood that the invention as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes for carrying out the invention that are obvious to those skilled in the relevant fields are intended to be within the scope of the following claims.

Claims

1. A method for treating psoriasis in a subject, the method comprising:measuring a level of each biomarker in a combination of two or more biomarkers in a biological sample of uninvolved, non-inflamed skin isolated from a subject having psoriasis prior to treatment with an anti-tumor necrosis factor (anti-TNF) agent, wherein the combination of two or more biomarkers comprises:ubiquitin specific protease 18 (USP18), and the level of USP18 is increased relative to a control level; andat least one further biomarker selected from(a) keratin, type II cytoskeletal 2 epidermal (KRT2) and the level of KRT2 is decreased relative to a control level;(b) interleukin 4 receptor (IL4R) and the level of IL4R is increased relative to a control level;(c) sex-determining region Y-box transcription factor 5 (SOX5), and the level of SOX5 is decreased relative to a control level; and(d) interferon induced with helicase C domain 1 (IFIH1), and the level of IFIH1 is increased relative to a control level; andcomparing the level of each biomarker in the sample with a control level for each biomarker, wherein the control level for each biomarker is the mean level of the biomarker in uninvolved, non-inflamed skin in a population of subjects suffering from psoriasis prior to treatment with the anti-TNF agent, andwherein when the level of USP18, IL4R, and / or IFIH1 in the sample is increased relative to the control level of the biomarker, the subject is predicted to be responsive to treatment with the anti-TNF agent; and / orwherein when the level of KRT2 and / or SOX5 in the sample is decreased relative to the control level of the biomarker, the subject is predicted to be responsive to treatment with the anti-TNF agent;wherein when the level of USP18, IL4R, and / or IFIH1 in the sample is not increased relative to the control level of the biomarker, the subject is predicted to be non-responsive to treatment with the anti-TNF agent; and / orwherein when the level of KRT2 and / or SOX5 in the sample is not decreased relative to the control level of the biomarker, the subject is predicted to be non-responsive to treatment with the anti-TNF agent; andadministering an effective amount of an anti-TNF agent to the subject predicted to be responsive to treatment.

2. The method of claim 1, wherein the combination of two or more biomarkerscomprises:USP18 and KRT2;2020357978   11 Sep 2026USP18 and IL4R;USP18 and SOX5;USP18 and IFIH1;USP18, KRT2, and IL4R;USP18, KRT2, and SOX5;USP18, KRT2, and IFIH1;USP18, KRT2, IL4R, and SOX5;USP18, KRT2, SOX5, and IFIH1; orUSP18, KRT2, IL4R, SOX5, and IFIH1.

3. The method of claim 1 or 2, wherein the level of USP18 is increased by at least about86% or more relative to the control level.

4. The method of claim 1 or 2, wherein the level of KRT2 is decreased by at least about99% or more relative to the control level.

5. The method of claim 1 or 2, wherein the level of IL4R is increased by at least about36% or more relative to the control level.

6. The method of claim 1 or 2, wherein the level of SOX5 is decreased by at least about89% or more relative to the control level.

7. The method of claim 1 or 2, wherein the level of IFIH1 is increased by at least about49% or more relative to the control level.

8. The method of any one of claims 1-7, wherein the level is a measure of the level of anucleic acid or protein present in the biological sample.

9. The method of claim 8, wherein the nucleic acid is deoxyribonucleic acid.

10. The method of claim 8, wherein the nucleic acid is ribonucleic acid.

11. The method of any one of claims 1-10, wherein the anti-TNF agent is etanercept,infliximab, adalimumab, certolizumab pegot, or golimumab.

12. The method of any one of claims 1-10, wherein the anti-TNF agent is thalidomide, lenalidomide, pomalidomide, a xanthine derivative, or bupropion.

13. The method of any one of claims 1-12, wherein the psoriasis is plaque psoriasis, guttate psoriasis, inverse psoriasis, intertriginous psoriasis, pustular psoriasis, erythrodermic psoriasis, or psoriatic arthritis.

14. The method of any one of claims 1-13, further comprising administering to the subject at least one additional treatment or medication for psoriasis.

15. The method of any one of claims 1-14, wherein the subject is a human subject.2020357978   11 Sep 202616. The method of any one of claims 1-15, wherein the level of the biomarker is measured with an immunoassay, Northern blot analysis, reverse transcription quantitative polymerase chain reaction, RNA sequencing, or high-throughput sequencing.

17. The method of any one of claims 1-16, wherein the subject treated with the anti-TNF agent shows PASI improvement by about 12 weeks of treatment.

18. The method of claim 17, wherein the PASI improvement is at least about 10% of PASI improvement.

19. A method for prognosing responsiveness to an anti-TNF agent in treatment of psoriasis in a subject, the method comprising:measuring a level of each biomarker in a combination of two or more biomarkers in a biological sample of uninvolved, non-inflamed skin isolated from a subject having psoriasis prior to treatment with an anti-tumor necrosis factor (anti-TNF) agent, wherein the combination of two or more biomarkers comprises:ubiquitin specific protease 18 (USP18); andat least one further biomarker selected from(a) keratin, type II cytoskeletal 2 epidermal (KRT2);(b) interleukin 4 receptor (IL4R);(c) sex-determining region Y-box transcription factor 5 (SOX5); and(d) interferon induced with helicase C domain 1 (IFIH1); andcomparing the level of each biomarker in the sample with a control level for each biomarker, wherein the control level for each biomarker is the mean level of the biomarker in uninvolved, non-inflamed skin in a population of subjects suffering from psoriasis prior to treatment with the anti-TNF agent,wherein when the level of USP18, IL4R, and / or IFIH1 in the sample is increased relative to the control level of the biomarker, the subject is predicted to be responsive to treatment with the anti-TNF agent;wherein when the level of KRT2 and / or SOX5 in the sample is decreased relative to the control level of the biomarker, the subject is predicted to be responsive to treatment with the anti-TNF agent;wherein when the level of USP18, IL4R, and / or IFIH1 in the sample is not increased relative to the control level of the biomarker, the subject is predicted to be non-responsive to treatment with the anti-TNF agent; and / orwherein when the level of KRT2 and / or SOX5 in the sample is not decreased relative to the control level of the biomarker, the subject is predicted to be non-responsive to treatment with the anti-TNF agent.

20. The method of claim 19, further comprising administering an effective amount of the anti-TNF agent to treat the subject predicted to be responsive to treatment with the anti-TNF agent.2020357978   11 Sep 202621. The method of claim 19 or 20, wherein the combination of two or more biomarkers comprises:USP18 and KRT2;USP18 and IL4R;USP18 and SOX5;USP18 and IFIH1;USP18, KRT2, and IL4R;USP18, KRT2, and SOX5;USP18, KRT2, and IFIH1;USP18, KRT2, IL4R, and SOX5;USP18, KRT2, SOX5, and IFIH1; orUSP18, KRT2, IL4R, SOX5, and IFIH1.

22. The method of any one of claims 19-21, wherein the level of USP18 is increased by at least about 86% or more relative to the control level.

23. The method of any one of claims 19-21, wherein the level of KRT2 is decreased by at least about 99% or more relative to the control level.

24. The method of any one of claims 19-21, wherein the level of IL4R is increased by at least about 36% or more relative to the control level.

25. The method of any one of claims 19-21, wherein the level of SOX5 is decreased by at least about 89% or more relative to the control level.

26. The method of any one of claims 19-21, wherein the level of IFIH1 is increased by at least about 49% or more relative to the control level.

27. The method of any one of claims 19-26, wherein the level is a measure of the level of a nucleic acid or protein present in the biological sample.

28. The method of claim 27, wherein the nucleic acid is deoxyribonucleic acid.

29. The method of claim 27, wherein the nucleic acid is ribonucleic acid.

30. The method of any one of claims 19-29, wherein the anti-TNF agent is etanercept,infliximab, adalimumab, certolizumab pegot, or golimumab.

31. The method of any one of claims 19-29, wherein the anti-TNF agent is thalidomide, lenalidomide, pomalidomide, a xanthine derivative, or bupropion.

32. The method of any one of claims 19-31, wherein the psoriasis is plaque psoriasis, guttate psoriasis, inverse psoriasis, intertriginous psoriasis, pustular psoriasis, erythrodermic psoriasis, or psoriatic arthritis.

33. The method of any one of claims 19-32, further comprising administering to the subject at least one additional treatment or medication for psoriasis.2020357978   11 Sep 202634.    The method of any one of claims 19-33, wherein the subject is a human subject.

35. The method of any one of claims 19-34, wherein the level of the biomarker ismeasured with an immunoassay, Northern blot analysis, reverse transcription quantitative polymerase chain reaction, RNA sequencing, or high-throughput sequencing.

36. The method of any one of claims 19-35, wherein the subject predicted to be responsive to treatment with the anti-TNF agent is expected to show PASI improvement by about 12 weeks of treatment.

37. The method of claim 36, wherein the PASI improvement is expected to be at least about 10% of PASI improvement.

38. A kit comprising reagents, when used for measuring a level of each biomarker in a combination of two or more biomarkers in a biological sample of uninvolved, non-inflamed skin isolated from a subject having psoriasis prior to treatment with an anti-tumor necrosis factor (anti-TNF) agent, wherein the combination of two or more biomarkers comprises ubiquitin specific protease 18 (USP18) and at least one further biomarker selected from(a) keratin, type II cytoskeletal 2 epidermal (KRT2);(b) interleukin 4 receptor (IL4R);(c) sex-determining region Y-box transcription factor 5 (SOX5); and(d) interferon induced with helicase C domain 1 (IFIH1), andwherein the level is the level of nucleic acid or protein of the biomarker in the biological sample.

39. The kit of claim 38, further comprising a means for comparing the level of the nucleic acid or protein of the biomarker in the biological sample with a control level, wherein the control level is the mean level of the biomarker in uninvolved, non-inflamed skin in a population of subjects suffering from psoriasis prior to treatment with the anti-TNF agent.

40. The kit of claim 38 or 39, wherein the biological sample is obtained from a biopsy of uninvolved skin from a subject suffering from psoriasis.

41. Use of measurement of an increased or decreased level of each biomarker in a combination of two or more biomarkers in a biological sample of uninvolved, non-inflamed skin from a subject having psoriasis in comparison to measurement of a control level, wherein the control level for each biomarker is the mean level of the biomarker in uninvolved, non-inflamed skin in a population of subjects having psoriasis prior to treatment with an anti-tumor necrosis factor (anti-TNF), for prognosing responsiveness of the subject to treatment with the anti-TNF agent, wherein the combination of two or more biomarkers comprises:ubiquitin specific protease 18 (USP18), and at least one further biomarker selected from(a) keratin, type II cytoskeletal 2 epidermal (KRT2);(b) interleukin 4 receptor (IL4R);(c) sex-determining region Y-box transcription factor 5 (SOX5); and2020357978   11 Sep 2026(d) interferon induced with helicase C domain 1 (IFIH1),wherein when the level of USP18, IL4R, and / or IFIH1 in the sample is increased relative to the control level of the biomarker, the subject is predicted to be responsive to treatment with the anti-TNF agent;wherein when the level of KRT2 and / or SOX5 in the sample is decreased relative to the control level of the biomarker, the subject is predicted to be responsive to treatment with the anti-TNF agent;wherein when the level of USP18, IL4R, and / or IFIH1 in the sample is not increased relative to the control level of the biomarker, the subject is predicted to be non-responsive to treatment with the anti-TNF agent; and / orwherein when the level of KRT2 and / or SOX5 in the sample is not decreased relative to the control level of the biomarker, the subject is predicted to be non-responsive to treatment with the anti-TNF agent.

42. The use of claim 41, wherein the combination of two or more biomarkers comprises a combination as set out in any one of the following combinations:USP18 and KRT2;USP18 and IL4R;USP18 and SOX5;USP18 and IFIH1;USP18, KRT2, and IL4R;USP18, KRT2, and SOX5;USP18, KRT2, and IFIH1;USP18, KRT2, IL4R, and SOX5;USP18, KRT2, SOX5, and IFIH1; orUSP18, KRT2, IL4R, SOX5, and IFIH1.

43. The use of claim 41 or 42, wherein the level of USP18 is increased by at least about 86% or more relative to the control level.

44. The use of claim 41 or 42, wherein the level of KRT2 is decreased by at least about 99% or more relative to the control level.

45. The use of claim 41 or 42, wherein the level of IL4R is increased by at least about 36% or more relative to the control level.

46. The use of claim 41 or 42, wherein the level of SOX5 is decreased by at least about 89% or more relative to the control level.

47. The use of claim 41 or 42, wherein the level of IFIH1 is increased by at least about 49% or more relative to the control level.2020357978   11 Sep 202648. The use of any one of claims 41-47, wherein the level is a measure of the level of a nucleic acid or protein present in the biological sample.

49. The use of claim 48, wherein the nucleic acid is deoxyribonucleic acid.

50. The use of claim 48, wherein the nucleic acid is ribonucleic acid.

51. The use of any one of claims 41-50, wherein the anti-TNF agent is etanercept,infliximab, adalimumab, certolizumab pegot, or golimumab.

52. The use of any one of claims 41-50, wherein the anti-TNF agent is thalidomide, lenalidomide, pomalidomide, a xanthine derivative, or bupropion.

53. The use of any one of claims 41-52, wherein the psoriasis is plaque psoriasis, guttate psoriasis, inverse psoriasis, intertriginous psoriasis, pustular psoriasis, erythrodermic psoriasis, or psoriatic arthritis.

54. The use of any one of claims 41-53, wherein the subject is a human subject.

55. The use of any one of claims 41-54, wherein the level of the biomarker is measuredwith an immunoassay, Northern blot analysis, reverse transcription quantitative polymerase chain reaction, RNA sequencing, or high-throughput sequencing.

56. The use of any one of claims 41-55, wherein the subject predicted to be responsive to treatment with the anti-TNF agent is expected to show PASI improvement by about 12 weeks of treatment.

57. The use of claim 56, wherein the PASI improvement is expected to be at least about 10% of PASI improvement.

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