RORγt inverse agonists demonstrating a margin between inhibition of IL-17A and thymocyte apoptosis

Mia Collins; Rikard Pehrson; Hanna Grindebacke; Agnes Leffler; Marie Ramnegård; Helena Rannikmäe; Nina Krutrök; Linda Yrlid; Charlotte Pollard; Ian Dainty; Frank Narjes; Stefan von Berg; Antonio Llinas; Anna Malmberg; Jane McPheat; Eva Hansson; Elisabeth Bäck; Jenny Bernström; Thomas G Hansson; David Keeling; Johan Jirholt

doi:10.1371/journal.pone.0317090

. 2025 Jan 16;20(1):e0317090. doi: 10.1371/journal.pone.0317090

RORγt inverse agonists demonstrating a margin between inhibition of IL-17A and thymocyte apoptosis

Mia Collins ^1,^*, Rikard Pehrson ², Hanna Grindebacke ¹, Agnes Leffler ¹, Marie Ramnegård ¹, Helena Rannikmäe ¹, Nina Krutrök ¹, Linda Yrlid ¹, Charlotte Pollard ¹, Ian Dainty ¹, Frank Narjes ³, Stefan von Berg ³, Antonio Llinas ², Anna Malmberg ², Jane McPheat ⁴, Eva Hansson ⁴, Elisabeth Bäck ¹, Jenny Bernström ⁴, Thomas G Hansson ⁵, David Keeling ⁵, Johan Jirholt ¹

Editor: Subhasis Barik⁶

¹Bioscience COPD/IPF, Research and Early Development, Respiratory & Immunology, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

²Drug Metabolism and Pharmacokinetics, Research and Early Development, Respiratory & Immunology, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

³Medicinal Chemistry, Research and Early Development, Respiratory & Immunology, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

⁴Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

⁵Projects, Research and Early Development, Respiratory & Immunology, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

⁶Chittaranjan National Cancer Institute, INDIA

Competing Interests: All authors are or have been employees of AstraZeneca. Several of the authors are or have been shareholders of AstraZeneca. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

^✉

* E-mail: Mia.collins@astrazeneca.com

Roles

Mia Collins: Conceptualization, Data curation, Formal analysis, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing

Rikard Pehrson: Conceptualization, Data curation, Formal analysis, Methodology, Visualization, Writing – original draft, Writing – review & editing

Hanna Grindebacke: Conceptualization, Data curation, Formal analysis, Investigation, Writing – original draft, Writing – review & editing

Agnes Leffler: Conceptualization, Data curation, Formal analysis, Methodology, Visualization, Writing – original draft, Writing – review & editing

Marie Ramnegård: Data curation, Formal analysis, Methodology, Visualization, Writing – original draft, Writing – review & editing

Helena Rannikmäe: Data curation, Formal analysis, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing

Nina Krutrök: Data curation, Formal analysis, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing

Linda Yrlid: Conceptualization, Data curation, Formal analysis, Methodology, Validation, Writing – original draft, Writing – review & editing

Charlotte Pollard: Data curation, Formal analysis, Methodology, Validation, Writing – original draft, Writing – review & editing

Ian Dainty: Data curation, Formal analysis, Investigation, Visualization, Writing – original draft, Writing – review & editing

Frank Narjes: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing

Stefan von Berg: Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing

Antonio Llinas: Conceptualization, Data curation, Formal analysis, Investigation, Validation, Visualization, Writing – original draft, Writing – review & editing

Anna Malmberg: Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – original draft, Writing – review & editing

Jane McPheat: Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – original draft, Writing – review & editing

Eva Hansson: Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

Elisabeth Bäck: Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – original draft, Writing – review & editing

Jenny Bernström: Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

Thomas G Hansson: Conceptualization, Investigation, Project administration, Supervision, Writing – original draft, Writing – review & editing

David Keeling: Conceptualization, Investigation, Project administration, Supervision, Writing – original draft, Writing – review & editing

Johan Jirholt: Conceptualization, Formal analysis, Investigation, Methodology, Supervision, Visualization, Writing – original draft, Writing – review & editing

Subhasis Barik: Editor

PMCID: PMC11737796 PMID: 39820614

Abstract

Multiple genetic associations suggest a causative relationship between Th17-related genes coding for proteins, such as IL-17A, IL-23 and STAT3, and psoriasis. Further support for this link comes from the findings that neutralizing antibodies directed against IL-17A, IL-17RA and IL-23 are efficacious in diseases like psoriasis, psoriatic arthritis and ankylosing spondylitis. RORγt is a centrally positioned transcription factor driving Th17 polarization and cytokine secretion and modulation of RORγt may thus provide additional benefit to patients. However, RORγt also plays a role in the normal development of T cells in the thymus and genetic disruption of RORγt in the mouse leads to the development of lymphoma originating in the thymus. Whilst it is not established that down-regulation of RORγt activity would lead to the same consequence in humans, further understanding of the thymus effects is desirable to support progress of this target as a potential treatment of Th17-driven disease. Herein we present the characterisation of recently disclosed RORγt inverse agonists demonstrating target engagement and efficacy in vitro and in vivo against Th17 endpoints but requiring higher concentrations in vitro to affect thymocyte apoptosis.

Introduction

Th17 cells were discovered some 20 years ago [1,2] and rapidly became the focus of intense study. These cells play an important role in host defense against extracellular bacteria and fungal infections caused by pathogens such as mycobacteria and candida [3]. Such actions are mediated, in part, through the production of pro-inflammatory cytokines such as IL-17. The differentiation and maturation of Th17 cells is also aided by the cytokine IL-23 which also helps to maintain their pro-inflammatory phenotype [4]. However, when dysregulated, Th17 cells can be important drivers of pathological processes leading to autoimmune diseases [5]. In psoriasis, clinical studies with neutralizing antibodies towards IL-17A and IL-23 have demonstrated efficacy [6–8]. These therapies have also been reported to be efficacious in the treatment of other diseases such as ankylosing spondylitis, psoriatic arthritis [9] and Crohn’s disease [10].

Th17 cells are dependent on the transcription factor retinoic acid related-orphan nuclear receptor γt (RORγt) for their polarization and the production of IL-17A [11]. RORγt has in addition been shown to down regulate the expression of FoxP3 and enhance transcription of genes coding for IL-17F, IL-22, IL-21, and IL-23R [12,13].

However, in the mouse thymus, αβ T cell precursors require the expression of RORγt during positive selection and maturation. Upon TCRβ selection, the thymic precursor cell enters a rapid proliferative burst phase. This is followed by the upregulation of RORγt leading to a quiescent state where recombination of the TCRα locus ensues [14,15]. After successful TCRα recombination a fully functional T cell receptor is upregulated on the cell surface, together with both CD4 and CD8, constituting double positive thymocytes. About 85% of thymocytes are double positive and remain dependent on RORγt for their survival at this developmental stage [16–18]. We use this dependency later in this study to evaluate in vivo effects of our compounds on thymocytes. In the mouse, thymocytes deficient in RORγt remain hyperproliferative but they also rapidly apoptose through the lack of RORγt-dependent Bcl-xL induced quiescence [17,19]. RORγt is encoded by the RORC gene and disruption of the Rorc gene in mice has been shown to lead to development of thymic lymphoblastic lymphomas. It is not yet known if this observation is relevant for other species such as humans, as some data suggest species differences in thymus biology [20,21]. However, when considering the development of drugs inhibiting RORγt, it would be important to establish a margin between any thymocyte effects and the desired inhibition of peripheral cytokine production in Th17 cells [22].

The RORC gene produces two isoforms of RORγ, γ and γt, which differ slightly in the N-terminus but share the exons encoding the ligand binding domain. Thus, pharmaceutical intervention directed towards this domain is likely to inhibit both isoforms similarly. The isoforms also differ in their tissue distribution where RORγt is restricted to immune cells while RORγ is expressed in many tissues such as liver and muscle [23]. Interestingly, both RORγ and RORγt are present in Th17 cells whereas only RORγt is present in thymocytes [24]. For simplicity we will refer to both isoforms as RORγt since we do not expect the compounds described here to differentiate between them.

RORγt is also important in other cell types where it drives cytokine expression and polarization [25]. Amongst these are γδ T cells, which are rapid innate-like producers of IL-17A and have been shown to be of importance in human psoriatic skin [26]. Preclinical in vivo models of psoriasis and skin inflammation in rodents often use imiquimod (IMQ, a TLR7/8 agonist) which, after application on the skin, gives rise to local inflammation characterised by erythema, swelling, scaling and thickening of the skin similar to psoriasis in the human [27]. IMQ drives a mixed inflammation but it is described to be mediated by the IL-23/IL-17 axis [27] and γδ T cells have been suggested to be the main producers of IL-17A in this model [28].

Whilst antibodies against Th17-related cytokines have proved efficacious against psoriasis and a number of related diseases, small molecule inhibition of this nuclear hormone receptor may be an attractive route for intervention and provide additional benefit to the patient compared with single cytokine neutralization through antibodies and several papers describe efforts towards this end [29,30].

In this paper we describe further pharmacological characterisation of six compounds from our chemical campaign, previously disclosed by us, that are inverse agonists of RORγt [31–33]. The compounds exhibited a robust inhibition of IL-17A release from human primary Th17 cells and show high affinity to the RORγt receptor. Compounds 1–4 belong to the acetamide series, from which the clinical candidate AZD0284 (5) was eventually derived [33]. Compound 6 is a more potent analogue of 5. Compound 3 was obtained by separation of the racemic mixture, as has been described for compound 2. In this study we characterised additional RORγt inverse agonists and investigated their effect on thymocyte apoptosis and inhibition of cytokine release.

Material and methods

Screening assays

Human RORγt radioligand competition binding assay

This assay was used to test whether compounds could inhibit the binding of tritiated 2-(4-(ethylsulfonyl)phenyl)-N-(4-(2-(methoxymethyl)phenyl)thiophen-2-yl)acetamide to recombinant human RORγt LBD (pIC₅₀ = 7.32, n = 6).

The assay was run in white polystyrene flat-bottom 384-well plates (Greiner, cat. No. 781075). Assays were carried out in 40 μl reaction volumes. A concentration range of test ligands in 0.4 μl of DMSO were added to assay plates using an acoustic liquid dispenser. 4 nM purified N-(HN)6-GST-TCS-hRORγ (258–518) was mixed with 1 mgml^-1 yttrium oxide (YOx) glutathione SPA imaging beads in assay buffer (20 mM Tris, 150 mM NaCl,10% glycerol, 0.25% CHAPS, 1 mM TCEP) prior to adding to 30 μl to test ligands. Assay plates were incubated for 1 hour at room temperature before adding 10 μl tritiated 2-(4-(ethylsulfonyl)phenyl)-N-(4-(2-(methoxymethyl)phenyl)thiophen-2-yl)acetamide to test plates in assay buffer (final concentration, 25 nM). Test plates were incubated for 16 hours and read using a LEADseeker (GE Healthcare, USA) Multimodality imaging instrument. K_i was calculated from the IC₅₀ value using the equation K_i = IC₅₀/(1+[L]/Kd) where [L] = 25 nmol/l and K_d = 17 nmol/l.

Murine RORγt radioligand competition binding assay

This assay was used to test whether compounds could inhibit the binding of the same tritiated ligand used in the human binding assay described above to recombinant murine RORγt LBD (pIC₅₀ = 6.91, n = 3). The assay was run in white/clear polystyrene flat-bottom 384-well plates (Greiner, cat. No. 781095). Assays were carried out in 40 μl reaction volumes. 0.125 μl of a fixed concentration range of test ligands dissolved in DMSO were added to assay plates using an acoustic liquid dispenser. 10nM purified HN-AVI-GST-TCS-mRORγ(aa256-516) was mixed with 0.75 mgml^- yttrium silicate (Ysi) glutathione coated beads in assay buffer (20 mM Tris pH7.5, 150 mM NaCl,10% glycerol, 0.25% CHAPS, 1mM DTT) prior to adding 30 μl to test ligands. Assay plates were incubated for 30 minutes at room temperature before adding 10 μl tritiated 2-(4-(ethylsulfonyl)phenyl)-N-(4-(2-(methoxymethyl)phenyl)thiophen-2-yl)acetamide to test plates in assay buffer (final concentration, 15 nM). Test plates were incubated for 8–20 hours and read using a 1450 MicroBeta TriLux Liquid Scintillation Counter (Perkin Elmer, MA, USA). K_i was calculated from the IC₅₀ value using the equation Ki = IC₅₀/1+[L]/Kd) where [L] = 15 nmol/l and K_d = 45 nmol/l.

Human RORβ radioligand competition binding assay

This assay was used to estimate compound potency for inhibition of radioligand binding (³H- all-trans retinoic acid) to the human retinoic acid receptor-related orphan receptor beta (RORB).

The assay (SPA) was run in white/clear polystyrene flat-bottom 384-well plates (Greiner, cat. No. 781095). Assays were carried out in 50 μl reaction volumes. A 0.5 μl volume of a fixed concentration range of test ligands dissolved in DMSO were added to assay plates using an acoustic liquid dispenser. Assay buffer (50 mM Tris pH 7.5, 150 mM NaCl, 10% Glycerol, 0.1% Triton X-100, 1 mM TCEP) containing 150 nM 6H-AVI-GST-TEV-hRORβT221-K470) and 0.8 mgml^-1 Yttrium silicate (YSi) copper SPA beads in was prepared and 40 μl was added to test ligands. Assay plates were incubated for 30 minutes at room temperature before adding 10 μl tritiated all-trans retinoic acid to test plates in assay buffer (final concentration, 30 nM). Test plates were incubated for 18–23 hours and read using a 1450 MicroBeta TriLux Liquid Scintillation Counter (Perkin Elmer, MA, USA).

RORγt co-factor recruitment assay

A co-activator recruitment assay was used to test whether compounds could inhibit the recruitment of steroid receptor coactivator peptide 1 (NCOA1-677-700) to the human retinoic acid receptor-related orphan receptor gamma (RORC) LBD.

The assay was run in black 384 well plates (Greiner cat no: 784900). Various concentrations of test ligands in 0.1 μl DMSO were dispensed to assay plates using an Echo acoustic dispenser (Beckman Coulter, UK). Two pre-mixes were prepared and incubated for 1 hour at room temp in the dark. Pre-mix 1 comprised 100 nM protein (biotinylated HN-Avi-MBP-TCS-hRORγ 258–518)) and 60 nM streptavidin APC in assay buffer, 50 mM MOPS pH7.4, 50 mM KF, 0.003% (w/v) CHAPS, 10 mM DTT and 0.01% (w/v) BSA and pre-mix 2 comprised 160 nM biotinylated SRC-1 peptide (NCOA1-677-700) and 20 nM europium-W8044 labelled Streptavidin in assay buffer. Five μl of pre-mix 2 was dispensed to assay plates containing test compound and incubated for 15 minutes prior to adding 5 μl of pre-mix 1. Plates were incubated at room temperature for 1 hour in the dark, prior to reading in a Pherastar multi-mode plate reader (BMG LABTECH, Ortenberg, Germany) using HTRF filter set (ex 320 nm, em 612 and 665 nm). The FRET signal at 665 nm was divided by the signal at 612 nm and multiplied by 10,000 to generate a signal ratio value for each well.

RORα co-factor recruitment assay

The aim of this assay was to show whether compounds could inhibit or stimulate the recruitment of peroxisome proliferator-activated receptor γ coactivator 1-α (PGC1alpha 130–154) peptide to the human RORα LBD in a co-activator recruitment assay. The hypothesis was that if compounds could bind to the receptor they would either inhibit or stimulate recruitment of the PGC1alpha 130–154 coactivator peptide.

The assay was run in black 384 well plates (Greiner: 784900). A 0.2 μl volume of a fixed concentration range of test ligands dissolved in DMSO were added to assay plates using an acoustic liquid dispenser. Two pre-mixes were prepared in falcon tubes. Pre-mix 1 comprised 180 nM Protein (His6-tcs-hRORαLBD) and 8 nM Lance Eu-W1024-anti 6xHis in assay buffer, 50 mM Hepes pH7.4, 100 mM NaCl, 0.1% (w/v) BSA, 1 mM TCEP which was incubated for 30 minutes at room temperature before dispensing 10 μl to assay plates. Then, pre-mix 2 comprising 200 nM biotinylated PGC1alpha peptide and 50 nM streptavidin APC in assay buffer, was prepared and incubated for 30 minutes at room temperature before adding 10 μl to assay plates containing test compound and premix 1. Plates were incubated at room temperature for 1 hour in the dark, prior to reading in a Pherastar multi-mode plate reader (BMG LABTECH) using HTRF filter set (ex 320 nm, em 612 and 665 nm). The FRET signal at 665 nm was divided by the signal at 612 nm and multiplied by 10,000 to generate a signal ratio value for each well.

Biological assays

Primary human Th17 cell assay

Peripheral blood mononuclear cells were isolated from heparin treated human whole blood from healthy donors by density gradient centrifugation. Th17 cells (CD4⁺CXCR3^-CCR6⁺) were enriched using a human Th17 Cell Enrichment Kit (cat #18162, STEMCELL Technologies, Cambridge, UK) according to the manufacturer’s protocol. The isolated Th17 cells were activated with anti-CD3, anti-CD28, and anti-CD2 beads (Miltenyi Biotech, Bergisch Gladbach, Germany) and cultured in X-Vivo15 medium (Lonza, Basel, Switzerland) supplemented with L-glutamine, β-mercaptoethanol (Gibco/Invitrogen, Thermo Fisher Scientific, MA, USA) and a cytokine cocktail consisting of; 10 ng/ml IL-2 (Gibco/Invitrogen), 20 ng/ml IL-6 (PeproTech Nordic, Stockholm, Sweden), 100 ng/ml IL-23, 20 ng/ml IL-1β, and 2 ng/ml TGF-β (R&D Systems Inc, MN, USA). Cells were seeded at 8000 cells/well in a 384-plate (cat #3707, Corning, MA, USA) in the presence of compounds or DMSO and cultured for 4 days (37°C, 5% CO₂). On day 4, supernatants were collected and IL-17A was measured using a Human IL-17A HTRF Assay kit (Cisbio/PerkinElmer, MA, USA) according to the manufacturer’s protocol.

In addition, the cytotoxic effect of compounds was evaluated on the cell plates (after removal of cell media supernatants for IL-17A analysis) using CellTiter-Glo® Luminescent Cell Viability assay (Promega Biotech AB, Nacka, Sweden) that measures adenosine triphosphate (ATP) levels which reflects the number of metabolically active cells.

Mouse thymocyte apoptosis assay ex vivo

The thymus from a female C57BL/6NCrl (Charles River) mouse aged around 7 weeks was dissected out after giving the mouse a lethal i.p. injection of penthobarbital. Single cell suspension of thymocytes was prepared by disrupting the thymus through a 70 μm cell strainer with the top of a sterile 5 ml syringe plunger in DPBS (without Ca/Mg). Cells were filtered through a 40 μm cell strainer and washed in serum-free media before being resuspended in complete media (RPMI1640 with L-glutamine supplemented with 10% heat inactivated foetal bovine serum (FBS) (Gibco/Invitrogen) and 50 μM 2-mercaptoethanol (Gibco/Invitrogen).

Cells were seeded at 500 000 cells/well in 96-well plates (U-bottom, cat #3799, Corning, MA, USA) in the presence of compounds or DMSO and cultured for 26 hours (37°C, 5% CO₂). The thymocytes were then washed twice in cold DPBS (without Ca/Mg) and stained with APC AnnexinV (#550475, BD Pharmingen, BD Biosciences, CA, USA) and 7AAD (#559925, BD Pharmingen) in AnnexinV Binding buffer (#556454, BD Pharmingen) for 15 minutes at RT (dark) in order to separate live cells from dead, early apoptotic and late apoptotic cells when analysed on the BD Accuri C6 (BD Biosciences, CA, USA).

The compound effect on the percentage of surviving cells relative to the DMSO control were calculated using the following formula;

% Relative survival = (% viable cells / mean % viable cells of DMSO controls) x 100 and plotted as dose-response curves.

Thymus involution in vivo

Female C57BL/6NCrl mice (Charles River, MA, USA) arrived at AstraZeneca at an age of 5 weeks +/- 2 days and were organized into groups and acclimatized for one week in order to reduce stress and variability of thymus weight. The mice in the experiment were intentionally young to reduce the impact of the normal process of thymic involution that starts at 4 weeks as this introduces further variability with regards to thymus size and cellularity. Additionally, age-related thymic involution is at its largest post puberty and less pronounced in females [34]. Prior to start of the experiment, the mice were weighed, and tail marked for identification. Two separate studies were conducted. For compound 4, three doses were selected (15, 50 and 150mg/kg) with a control group dosed with the vehicle (0.5% w/w HPMC and 0.5% w/w F127) (n = 10 in each group). For compound 3, 50mg/kg (n = 8) and 150mg/kg (n = 4) were selected, with a control group dosed with an inactive compound from the same series (5 mg/ml HPMC, 1 mg/ml Tween). Animals were dosed twice daily perorally at 7.30 and 15.30 except for the 150mg/kg group for compound 3 which got only one dose at 7.30 the final day (in total 3 doses during the treatment period).

Mice were terminated 48 hours post first dose via anesthetization with isoflourane followed by carbon dioxide asphyxiation. Thymi were dissected, weighed and stored on ice in PBS until all tissues were harvested and could proceed immediately to further analysis.

IMQ induced skin inflammation in vivo

Male C57BL/6NCrl mice (Charles River, MA, USA) arrived at an age of 7 weeks +/- 2 days and were randomly organized into cages marked with an identifier. Prior to start of the experiment the mice were weighed to facilitate assessment of general health post disease induction and during treatment. After disease induction mice were weighed at day 1, 5 and 8. The study included 2 groups: Control group (n = 12), dosed with a non-active compound from the same series and a group dosed with compound 3 at 50 mg/kg (n = 8). Animals were dosed perorally at 07:30 and 15:30 for 7 days. Both experimental groups were treated on the inner and outer side of both ear pinnas with Aldara (IMQ) (Meda, Solna, Sweden) cream daily for 7 days and terminated 24 hours later. The application of Aldara cream took place in the morning after oral compound dosing. The level of ear inflammation (redness, swelling and thickness of the ear) was assessed at day 0 and day 4–7. A micrometer screw with a 4 mm diameter piston tensioned at 2 N was used to measure the ear thickness and a total of 2 measurements per ear were taken and the average was logged. At the day of termination, animals were terminated by cervical dislocation under isoflourane anesthesia, death was confirmed through cardiac laceration. The ear thickness was measured where after ears were cut off and the inner and outer skin were separated and put in PBS (without Ca/Mg) until the preparation for flow cytometric analysis.

Cell preparations from tissues

For the thymus involution model, thymi were disrupted and run through a cell strainer. Red blood cells were lysed using Pharmlyse (555899) (BD) and cells were filtered and washed after which they were resuspended in 1 ml of PBS with 2% FBS (Gibco/Invitrogen, Thermo Fisher Scientific, MA, USA). A small aliquot was taken from each sample for cell counting (Sysmex, Kobe Japan).

For the IMQ model, ears were digested for 1.5 hours using Liberase TL research grade (5401020001) (Roche, Basel, Switzerland) and processed using the OctaMACS (Miltenyi) program C. Ear cells were filtered and washed, after which they were resuspended in 1 mL of PBS containing 5% FBS (Gibco/Invitrogen). An aliquot (100 μl) was taken off from the ear cell suspension for CD45 cell counting using the count bright beads (C36950) (Life Technologies, CA, USA). 450 μl were used for phenotypic analysis of cell populations in the ear and the rest was stimulated for 3.5 hours with Leukocyte activation cocktail (550583) (BD) and then stained for flow cytometric analysis.

Preparation for flow cytometric analysis

For the thymus involution model, approximately 2 million cells were used for flow cytometric staining. Cells were washed and stained with a viability dye (L34975) (Live/Dead aqua, Life Technologies) and non-specific binding was blocked by using FC-block (553141) (BD) after which extracellular staining for flow cytometric analysis was performed using antibodies directed against surface antigens CD4 V450 (RM4-5) (560468) (BD) and CD8 PE-Cy7 (53–6.7) (561097) (BD Pharmingen) incubating for 30 minutes at 4°C. Cells were washed and analysed on the BD FACS Fortessa (BD).

For the IMQ model, cells were washed and stained with a viability dye (Live/Dead aqua, Life Technologies) and non-specific binding was blocked by using FC-block (BD) after which extracellular staining for flow cytometric analysis was performed using antibodies directed against surface antigens CD45 FITC (30-F11) (553080) (BD), CD4 APC (RM4-5) (553051) (BD), TCRγδ PE-Cy7 (GL3) (25-5711-80) (eBioscience, CA, USA), CD3 Alexa Fluor 700 (500A2) (557984) (BD) and TCRβ APC-Cy7 (H57-597) (560656) (BD Pharmingen). Cells were incubated for 30 minutes at 4°C and then washed and fixed for 1 hour in room temperature using the FoxP3 transcription factor staining buffer set (cat# 00-5523-00) (eBioscience). Cells were washed with permeabilization buffer and FC blocked in room temperature for 15 minutes where after intracellular staining was performed using antibodies directed against IL-17A BV421 (TC11-18H10) (563354) (BD), INFg PE (XMG1.2) (554412) (BD). Cells were incubated at 4°C for 45 minutes and then washed with permeabilization buffer and analysed on the BD FACS Fortessa (BD).

Analysis parameters

Thymocytes were gated on their forward and side scatter (FSC/SSC) properties and single cells were selected. The parameter “Time” was used to detect any variances in the flow. Live cells were selected after which CD4 and CD8 were plotted against each other. Double positive thymocytes (expressing both CD4 and CD8 on their surface) were gated. The absolute number of double positive thymocytes were calculated from the flow cytometry data for live double positive thymocytes and the white blood cell count from the Sysmex and presented as absolute number of double positive thymocytes.

Ear cells were gated on their FCS/SSC properties and single cells were selected. The parameter “Time” was used to detect any variances in the flow. Live cells were selected after which the leukocyte marker CD45 was gated. TCRγδ intermediate expressing cells that were negative for the TCRβ marker were gated and IL-17A was selected (flow cytometric gating presented in S1 Fig). IL-17A producing γδ T cells in the ear at day 8 was the primary readout and was evaluated using GraphPad Prism, US v5.0 (GraphPad, CA, USA). All flow cytometric analysis was performed using FlowJo software (FlowJo, OR, USA).

Statistical evaluation

The raw data from the radio-ligand and co-factor recruitment assays were transformed to % effect using the equation:

Compound % effect = 100*[(X-min)/(max-min)]

where X represents the effect in the presence of test compound and max and min are the effects in presence of the maximum and minimum controls respectively.

The data was plotted to generate concentration response profiles and the concentration-response curves were fitted to the data using the non-linear regression analysis; 4 parameter logistic smart fit method in the Analyser application of the Genedata^® Screener software (Genedata, Inc., Basel, Switzerland). The pIC₅₀ and pEC₅₀ values were calculated as the negative logarithm of the molar concentration of compound required for 50% inhibition or stimulation in measured effect. K_i was calculated from the IC₅₀ value using the equation Ki = IC₅₀/1+[L]/Kd)

Genedata Screener® software (Genedata, Inc., Basel, Switzerland) was used for data normalization, curve fitting and calculation of IC₅₀ for IL-17A inhibition as well as for cell viability. Raw data from the Human IL-17A HTRF Assay and CellTiter-Glo® Luminescent Cell Viability assay was transformed to % effect according to the formula:

Compound % effect = 100*[(X-min)/(max-min)],

where X represents the effect in the presence of test compound. For IL-17A calculations, DMSO was used as minimum (min) inhibition control and RORγt inverse agonist 3-(1,3-benzodioxol-5-yl)-1-(3,5-dimethylpiperidin-1-yl)-3-(2-hydroxy-4,6-dimethoxyphenyl)propan-1-one) at 10 μM was used as the maximum (max) inhibition control [35,36]. For the cell viability calculations, 2-(2,2-dicyclohexylethyl)piperidine at 10 μM was used as maximal toxicity control while DMSO was used as minimal toxicity control. A four-parameter logistic smart fit method in the Analyser application of the Genedata^® Screener software was used for curve fitting of the % effect data and IC₅₀ calculation. If a compound reduced the cell viability more than 30% in the CellTiter-Glo 2.0 viability assay at a certain concentration, the corresponding data point for IL-17A production was excluded from the curve fitting.

The IC₅₀ values for the tested compounds in the thymocyte apoptosis assay ex vivo were determined in GraphPad Prism by fitting the % relative survival data in a four-parameter logistic curve model.

Flow cytometric data for double positive thymocytes was analysed using one-way ANOVA followed by Sidak’s post-test for multiple comparisons. Cell populations in the ear of IMQ treated mice were analysed using unpaired t-test. Ear thickness data was analysed using two-way ANOVA with Bonferroni post-test, error bars indicate SEM. Box and whiskers graphs are shown with error bars indicating min-max. Significance levels are used as follows: * (p ≤ 0.05), ** (p ≤ 0.01), *** (p ≤ 0.001).

Dose-response curves for the different comparisons were generated with non-linear regression analysis with log agonist vs response, four parameters, variable slope model.

Pharmacokinetics and pharmacodynamics

In vitro. For the comparisons of effect size across assays, the normalized effect size was plotted for the corresponding concentrations. Where the exact concentration did not correspond between the assays an effect size was extrapolated for that concentration for one of the assays based on the IC₅₀ curve fit.

In vivo

Test compound concentrations were analysed in blood obtained from the vena saphena by means of capillary tubes and analysed by LC-MS/MS. The terminal concentrations obtained were merged with pharmacokinetic data from satellite animals (animals dosed with compound but not used for other readouts) using the same formulation and dose route. By means of a one compartment model using a population approach (Phoenix®WinNonLin® Certara L.P. Build 6.4.0.768, Princeton, NJ, USA), the individual exposure (AUC) up to termination was estimated. The average concentration was calculated by dividing with the treatment length (48 hours).

Ethics statement

Whole blood was supplied from healthy AstraZeneca blood donors under written consent approved by the Ethics committee in Gothenburg, Sweden, approval Dnr T705-14 Ad 033–10 during the period 2014-08-25 until 2017-01-16.

All animal experiments were approved by the Gothenburg Ethics Committee for Experimental Animals in Sweden and conform to ethical license No. 47–2013 and No. 142–2015. The approved site number is 31-5373/11 for the animal facilities and all efforts were made to minimize suffering.

Results

During the development of RORγt inhibitors, we set out to perform a more extensive evaluation of the pharmacological properties of selected compounds. The chemical evolution and characterisation as RORγt inhibitors, has been published recently [31–33]. Compound structures can be found in S2 Fig.

Binding assays

Firstly, the propensity of the compounds to compete with a known RORγt ligand for binding to the RORγt LBD was evaluated. All compounds were able to inhibit the binding of the tritiated RORγt ligand to the human RORγt LBD in competition binding studies with sub micro-molar potency (Table 1). The compounds were then tested for their ability to displace a RORγt ligand from the mouse RORγt LBD. The potencies were similar between the human and mouse binding assays with the largest difference being fourfold (Table 1).

Table 1. Overview of compound potencies in multiple assays.

	1	2	3	4	5	6
Binding Human RORγt	8.1±0.1 (5)	6.6 ± 0.1 (4)	6.7 ± 0.1 (3)	6.5 ± 0.0 (3)	7.1 ± 0.1 (11)	8.1 (1)
Binding Murine RORγt	7.5 ±0.1 (2)	6.5 (1)	6.4 ± 0.1 (2)	6.3 ± 0.1 (3)	7.1 ± 0.1 (3)	7.7 (1)
Binding RORβ	n.d.	<5.0 (3)	<5.0 (3)	<5.0 (4)	<5.0 (6)	<5 (2)
Inverse agonism RORα	4.7 (1)	<4.5 (1)	<4.5 (2)	<4.5 (2)	<4.5 (1)	<4.5 (1)
Agonism RORα	<4.5 (1)	5.6 (1)	5.3 ± 0.1 (2)	<4.5 (2)	6.4 (1)	6.5 (1)
Inverse agonism RORγt	7.2 (1)	7.4 ± 0.1 (2)	7.3 ± 0.2 (2)	7.3 ± 0.1 (2)	7.4 ± 0.1 (11)	7.5 (1)
Thymocyte apoptosis	6.2 ±0.1 (3)	5.8 ± 0.1 (3)	5.6 ± 0.1 (3)	5.6 ± 0.1 (2)	6.6 ± 0.1 (4)	7.5 (2)
Human IL-17A in Th17 cells	7.2 ± 0.2 (5)	7.3 ± 0.1 (9)	7.3 ± 0.3 (6)	7.5 ± 0.3 (6)	7.8 ± 0.2 (45)	8.2 ±0.2 (6)
Mouse PPB (% unbound)	0.5 (1)	10.9 (1)	6.2 (1)	17.9 (1)	18.6 (1)	5.1 (1)

Open in a new tab

^aThe arithmetic mean of pIC₅₀ / pEC₅₀ values is shown ± standard deviation, where appropriate; in brackets: The number of independent test occasions. N.d.: Not determined. PPB: Plasma protein binding.

Co-factor modulation assay

Having established that the compounds bind to RORγt we set out to assess the mode of action through a co-activator recruitment assay. This assay can discriminate agonist, partial agonist and inverse agonist activities of the tested compounds. A clear concentration dependent displacement of the SRC-1 co-activator peptide was achieved for all compounds (Table 1), demonstrating robust inverse agonism with a maximal inhibition of 100%.

Compound selectivity

RORγt is related to two other proteins, RORα and RORβ, that together constitute the RAR-related orphan receptor family. To evaluate selectivity towards the different ROR isoforms, the compounds were tested in a RORα cofactor modulation assay assessing both inhibitory and agonistic compound effects. If the compounds could bind to the receptor, they would either inhibit or stimulate recruitment of the PGC1alpha 130–154 coactivator peptide.

No inhibitory effect could be detected for any of the compounds up to the highest tested concentration (≤33μM). However, agonism with an EC50 activity <10μM was observed for compounds 2–3 and 5–6 at various maximal PGC1alpha recruitment levels. This agonist activity did not correlate with either potencies or effects in RORγt dependent assays (Table 1). The compounds were further analysed using a radio-ligand binding assay assessing the ability of the compounds to compete for binding with 3H-all-trans retinoic acid to the LBD of the RORβ protein. In this assay no binding could be detected at any concentration tested (≤10μM). These data are summarized in Table 1.

Biological effects

Inhibition of IL-17A release from human Th17 cells

To evaluate if these compounds were efficacious in a human system, we set out to determine the inhibitory effect on IL-17A production in primary human T cells. Briefly, Th17 cells were enriched from blood of healthy donors, activated, and stimulated in a Th17 cytokine milieu with or without test compounds. The cumulative production of IL-17A was measured in the supernatants after 4 days and dose response curves were generated (all dose curves are presented in Fig 1). The compounds demonstrated a dose-dependent near complete inhibition of IL-17A production (93–99% vs control) with pIC₅₀ values in the range 7.2–8.2 (Table 1).

Fig 1 — Response vs concentration profile for compound 1–6 in the ligand binding assays (human = red, mouse = blue), the primary human Th17 cell assay (purple) and in the thymocyte apoptosis assay (orange). Error bars indicate standard deviation.

While the supernatants from the primary human Th17 cell assay were analysed for IL-17A protein levels, the cells in the corresponding wells were lysed and analysed for ATP content as an indicative measure of toxicity. This was done to increase confidence that the observed inhibition of IL-17A was neither due to a reduction in cell viability, nor proliferation. No reduction in ATP levels was observed for any of the compounds (S3 Fig).

Evaluation of thymocyte apoptosis

Since double positive thymocytes in the mouse require RORγt for their survival, we used this dependency to study the effect of RORγt inhibitors on thymocyte apoptosis. Mouse thymocytes were isolated, plated and incubated with compounds for 26 hours followed by AnnexinV and 7AAD staining to quantify apoptosis. The compounds all increased the basal rate of apoptosis and demonstrated a range of activities (pEC₅₀ 5.6–7.5) in the thymocyte apoptosis assay. Interestingly, the effect on murine thymocyte apoptosis required a significantly higher compound concentration than inhibition of IL-17A in human cells (Fig 1). Since binding potency is similar between the species, these data indicate a potential margin between the two effects.

Target engagement through thymus involution in vivo

After establishing an in vitro potency for the compounds on thymocyte apoptosis we set out to test this effect in a corresponding in vivo model. Compounds 3 and 4 were selected based on their favourable pharmacokinetic profiles. The in vivo profile of compound 5 has previously been published by our group [33].

Briefly, C57Bl/6NCrl mice were dosed with compounds twice daily for 2 days after which a single-cell suspension was prepared from each thymus. The cells were counted, stained and analysed by flow cytometry for CD4⁺CD8⁺ cell numbers and frequencies. We were able to demonstrate that the absolute number of double positive thymocytes was reduced in a dose dependent manner for compounds 3 and 4 (Fig 2A and 2B). This is in accordance with what was observed in the in vitro thymocyte apoptosis assay.

Evaluation of systemic anti-inflammatory effects on psoriasis like skin inflammation in vivo

Compound 3 was selected for further in vivo evaluation based on the stable predicted exposure levels over time (see Fig 2C and 2D).

The anti-inflammatory effects of this compound were investigated in a psoriasis-like model of skin inflammation. In short, skin inflammation was induced by daily applications of IMQ cream for 7 days in the presence or absence of a RORγt inhibitor. Animals were dosed orally at 50mg/kg twice daily with compound 3, which due to accumulation, led to an exposure at steady state similar to the high dose group (150 mg/kg) in the thymus involution study (S4 Fig). Animals were terminated on the morning of day 8, cells were harvested from the ears and cell populations were investigated by flow cytometry.

To assess the overall inflammation, cells were analysed for their capacity to produce IL-17A after restimulation ex vivo and frequencies of total IL-17A positive immune cells were shown to be reduced (p = 0.0002) (Fig 3A). Similarly, γδ T cells were found to produce significantly less IL-17A after compound treatment (p = 0.002) (Fig 3B) and their frequency was decreased (p = 0.006) (Fig 3C) indicating reduced recruitment and/or expansion of γδ T cells to the ear. Mean fluorescence intensity of IL-17A was also reduced for total IL-17A producing cells (p = 0.0004) as well as within the γδ T cell population (p = 0.02) in the compound treated group (S5 Fig). Taken together, compound treatment reduced the number of IL-17A positive cells and cells remaining positive for IL-17A expressed the protein at lower levels. Ear thickness was significantly decreased towards the end of the study (Fig 3D) indicating an anti-inflammatory effect of compound treatment (0.33 mm) as compared to vehicle (0.37 mm, p = 0.04) despite the continuous application of IMQ. A representative histogram of γδ T cells and individual data points for ear thickness are shown in S5 Fig.

Fig 3 — Cell populations in the ear of IMQ treated animals after treatment with compound 3. A) Percentage of total IL-17A producing cells among CD45+ cells B) Percentage IL-17A producing cells among γδ T cells C) Percentage of γδ T cells among CD45⁺ cells D) Ear thickness measured over the course of the IMQ induces skin inflammation model *in vivo*. Significance levels: * (p ≤ 0.05), ** (p ≤ 0.01), *** (p ≤ 0.001).

Inter-assay comparison

To aid in the interpretation of these data we have evaluated the cross-species potencies and protein binding of the tested compounds.

Among the six compounds, human and mouse inhibition constants (Ki) are generally similar (Fig 4A) with a trend towards higher potency in the human assay. This allows us to compare assay effects across species.

The desired effect is to inhibit IL-17A production in human Th17 cells. In this cell assay, for each concentration of compound, the effect on human IL-17A production was greater than the effect on human RORγt binding, except for Compound 1 (Fig 4B). However, this compound has a significantly higher protein bound fraction compared to the other five compounds (see Table 1), resulting in a reduction in the free compound concentration in assays with a higher protein content, such as the human IL-17A assay, potentially explaining the discrepancy.

In contrast, for each concentration of compound, the effect in the thymocyte apoptosis assay is consistently lower than the effect in the mouse ligand binding assay (Fig 4C).

For all compounds the effect is significantly lower in the thymocyte apoptosis assay compared to the human IL-17A production assay. Consequently, it is only when the inhibition of IL-17A production in the human cell is above 75% that the effect on mouse thymocyte apoptosis becomes significant (Fig 4D). The one compound that deviates somewhat from this behaviour (Compound 1) shows high protein binding which we predict will lead to a greater loss of activity in the IL-17A assay than in the mouse thymocyte assay. We therefore conclude that these two effects require different levels of inhibition of RORγt with a greater degree of inhibition needed to affect thymocyte apoptosis.

Discussion

Monoclonal antibodies directed against either IL-17A or IL-23 [37] have been demonstrated to be efficacious in both psoriasis patients and in spondyloarthropathies [38]. Due to the central role of RORγt in directing the cell-state and the production of multiple pro-inflammatory cytokines in several cell types, such as Th17, γδ T cells, ILC3 cells etc [39], inhibition may lead to additional clinical efficacy. Whilst clinical experience with anti-IL-17A and anti-IL-23 antibodies has not revealed significant safety concerns [40], the shorter half-life of a small molecule may allow for rapid treatment discontinuation, for example during clearance of a serious mycobacterial infection.

However, as we and others have published previously, an obstacle to clinical progression for the RORγt inhibitory mechanism may be the additional role played by RORγt during the maturation of thymocytes. In mice where the RORγt gene has been removed, either from conception [17] or when animals have reached adulthood [41], thymic lymphoma has been shown to develop in a large fraction of the animals [19]. Furthermore, scientists at Bristol Myers Squibb have reported thymic lymphomas in both rats and mice, but not cynomolgus monkey, following dosing with the RORγt inverse agonist, BMS-986251 [42]. The translation of this effect to humans is not clear as indicated by the fact that no lymphomas were reported in three kindreds bearing loss-of-function mutations in the RORC gene in children up to the age of 9 years [20] while mice develop thymic lymphomas within 4–5 months of losing Rorc [19,41]. Nevertheless, the identification of compounds with a preferential effect on cytokine production over thymocyte maturation would be desirable. However, in a subset of acute lymphoblastic leukemia originating in the early T precursor cell (ETP-ALL), enrichment in the IL-17 pathway has been described [43]. Furthermore, during early thymocyte maturation, in the DN1 stage, a subset of thymocytes upregulate the expression of Rorc [44] and these cells can, if dysregulated, also develop into ETP-ALL. In this situation it may be valuable to evaluate if inhibition of RORγt reduces the proliferation and expansion of such cells.

In this paper we present in vitro data arguing that a lower level of inhibition is required to reduce production of Th17 cytokines than is required to induce apoptosis in murine thymocytes.

We have evaluated six compounds with similar potencies in the mouse and the human ligand binding assays allowing comparison across species. We demonstrate an enhanced potency on inhibition of IL-17A production in primary human Th17-cells compared to the ligand binding assay. Also, the potency of cofactor displacement is close to the potency in the human Th17 cell assay suggesting that these two assays better represent the functional potency of the compounds than does the ligand-domain binding assay. This observation has been seen previously for other series of compounds in similar cell assay systems [45–48].

Contrasting with this finding, there is a consistent drop in potency between the ligand binding assay and the thymus apoptosis assay. Taken together this provides potential evidence that a greater inhibition of RORγt is required to affect thymocyte apoptosis than to reduce cytokine production in vitro.

Through the IMQ model we were able to demonstrate anti-inflammatory effects of RORγt inhibition in the ear skin of mice. It is worth to note that this is one of many animal models used to mimic part of the complex pathophysiology of psoriasis [49]. The model only weakly resembles human psoriasis but allows the evaluation of systemic anti-inflammatory effects targeting RORγt biology [50]. Upon oral treatment, the frequency of IL-17A producing cells was significantly reduced in IMQ treated ear skin and the remaining IL-17A+ cells had reduced protein levels after stimulation, consistent with an overall reduction of inflammation. In fact, a statistically significant reduction in ear thickness could be identified towards the end of the experiment compared to vehicle treated animals, despite the tissue edema. The anti-inflammatory effect of RORγt inhibition has been demonstrated previously on IMQ induced skin inflammation [47,48,51]. One paper describes that an effective reduction of IL-17A protein in IMQ treated ears [48] could be achieved at compound exposures corresponding to the in vitro IC₅₀ in a murine IL-17A inhibition cell assay (compound 66, free C_min). However, a higher concentration corresponding to IC₈₀ (free C_min) was needed for a statistically significant decrease of IMQ induced swelling [48]. There are similarities with our results, where high concentrations of compound 3 led to a clear reduction in IL-17A positive cells in IMQ treated ears, but a partial response on ear thickness day 8. Additionally, in our previous paper ([33] Compound 5) we observed a larger effect from repeated daily dosing of 15 mg/kg in the IMQ model whereas bi-daily administration of 10 mg/kg did not have a significant effect on thymocyte numbers after two days. These two administration regimes gave very similar exposure profiles but also indicated a differential effect between IL-17A effector cell function and thymocyte apoptosis. Also in this study, the ear thickness was significantly but partially reduced [33]. One possible explanation for the partial effect is that continuous application of a TLR7 agonist (IMQ) is likely to drive a broader inflammatory response than just the IL-17 arm and hence appear more resistant to RORγt inhibition [52].

Nevertheless, RORγt inhibitors in clinical development have been terminated due to the potential safety risks. Even though the full outcome from these studies remains to be published, it is likely that this is due to the challenge of establishing a large enough safety margin to thymic changes (reviewed in [53]). To date, both mice and rats have been exposed to RORγt inverse agonists and at higher doses this has resulted in the development of thymic lymphomas [42,54]. Furthermore, at lower doses, changes to the thymic cellular organization have been detected in both mouse and rat, as well as cynomolgus monkey [42].

Today there are no established means to differentiate between tolerable compound-induced thymic changes, and pre-neoplastic changes that may lead to the development of thymic lymphoma and ultimately T-cell acute lymphoblastic leukemia (T-ALL) during chronic treatment. This has been discussed by Haggerty et al based on the partly disclosed findings using BMS-986251 in cynomolgus monkey [42]. An additional complication of inhibition of RORgt has been suggested by Guo et al [55] where they have demonstrated a skewing of the TCRa gene rearrangement and hence limitations to the diversity of the T cell repertoire in mice. While skewing of the T cell repertoire is noteworthy, due to the potentially enhanced risk of developing autoimmune disorders and infection, the T cell leukopenia observed in humans carrying RORC biallelic loss of function mutations, is less pronounced than that observed in mice [20].

Hence, today, clinical progression of this class of inhibitor seems to be an unsurmountable hurdle due to the lack of means to predict and evaluate the safety profile with regards to development of thymic lymphoma and T-ALL, which is a clear limitation. However, our observation of the requirement for higher levels of inhibition of RORγt to induce thymus apoptosis may open an avenue towards the development of further novel compounds with increased differentiation between Th-17 cells and thymocytes. This might be achieved by a partial inhibitor of the nuclear receptor such that the level of inhibition needed to affect thymocytes is never reached. Other approaches may be through engaging tissue specific cofactors and one publication suggests a differential dependency between Th17 cells and thymocyte differentiation upon Src family kinases for the transcriptional activity of RORγt [56].

Additionally, mutations in the DNA-binding domain of RORγt have been suggested to impart a similar separation of effect between the thymus and effector cells [57], although currently there has been no publication of compounds raised against this part of the protein.

Other possibilities to separate the thymus apoptosis from effector cells have been suggested through the different conformations adapted by RORγt upon binding to its two different RORγt response elements. This conformational difference has been suggested to affect the co-factor recruitment and hence it might be possible to harness these findings in compound design [58]. To our knowledge, only one clinically tested compound has been suggested to inhibit effector cells but spare the thymus, IMU-935 [59], however this compound has been withdrawn from further clinical development [60]. This recently developed compound would have been valuable to evaluate in our experiments with the hope that it would separate the thymic effects from the inhibition of Th17 cells.

This study has a number of limitations. The lack of experimental data on human thymocytes prevents a direct comparison with Th-17 cells with the need to bridge potencies across species. However, the anatomical location of the thymus close to the heart and natural involution in adults significantly hampers access to fresh tissue which generally is only available from young children undergoing open heart surgery. A further limitation is the lack of establishing an in vivo margin between the positive effect of RORγt inhibition (reduction of IL-17A) and the unwanted effect of thymocyte apoptosis in the same animal experiment. This was not achievable due to the stress-sensitive nature of the thymus which undergoes rapid involution upon handling (e.g. application of IMQ cream and dosing of compounds) of the animals. Furthermore, the already occurring natural thymic involution would introduce further variability in thymus size in the adult animals needed in the IMQ experiment, both for the immune system to be fully matured and to minimize variability from growth related differences in size and thickness of ear pinnas and cell numbers. This limitation did not apply to the experiments studying thymus effects as the animals were intentionally young to minimize effects from early thymic involution. A potential complication in measuring thymus cellularity of double positive thymocytes is premature thymic escape. This process has not been investigated in this work, however most of the literature has investigated premature thymic double positive escape in the context of infection or inflammation [61,62]. However, it is established by us and others that loss of [16,17] or inhibition of [54] RORγt has a direct and rapid effect on apoptosis. Since these animals are healthy and in a clean environment, we attribute the majority of the rapid loss of double positive thymocytes to apoptosis. An additional limitation is the artificiality of the thymocyte apoptosis assay where the thymic organization is disrupted thereby limiting the normal cytokine milieu and cellular cross talk (TCR stimulation). To circumvent this the thymocytes could have been stimulated in different ways. However, the enhanced apoptosis is supported in the thymus involution in vivo study where signaling and cross talk are intact.

Another limitation is the unknown level of inhibition of RORγt needed to achieve a clinically relevant effect on disease remission in human patients which would require longer clinical studies.

In this paper we present enhanced pharmaceutical insight for RORγt specific compounds with drug like properties. Furthermore, we were able to establish their anti-inflammatory effects as measured by cytokine production in vitro and measured through overall tissue inflammation in vivo. In addition, a margin between the in vitro inhibitory effect on IL-17A and enhanced thymocyte apoptosis was defined. Nevertheless, the translation of an in vitro margin to the separation of clinical efficacy from lymphoma risk in the clinic is unclear. Without the demonstration of compounds with a safe efficacy profile in vivo, or clear evidence that the mechanism by which lymphomas are induced in rodents is not relevant to humans, further development of RORγt inverse agonists for the treatment of Th17 related disease remains problematic.

Supporting information

S1 Fig. Flow cytometric gating strategy from ear tissue.

Single cells were selected followed by CD45+ live cells, TCRγδ intermediate TCRβ negative cells, further selected on CD3 and IL-17A using a histogram.

(TIF)

pone.0317090.s001.tif^{(186.3KB, tif)}

S2 Fig. Compound structures.

(TIF)

pone.0317090.s002.tif^{(358.3KB, tif)}

S3 Fig. Representative data of cell toxicity as measured by terminal ATP levels in the primary human Th17 cell assay.

(TIF)

pone.0317090.s003.tif^{(224.6KB, tif)}

S4 Fig. Exposure prediction and terminal concentrations in the IMQ model.

Exposure prediction (line) and terminal concentrations (dots) in eight mice treated with compound 3 following 7 days twice-daily oral dosing with 50 mg/kg in the IMQ-induced skin inflammation model.

(TIF)

pone.0317090.s004.tif^{(50.7KB, tif)}

S5 Fig. Flowcytometric parameters and ear thickness from the IMQ model.

A) Mean fluorescence intensity of IL-17A in CD45+ cells B) Mean fluorescence intensity of IL-17A in γδ T cells C) Histogram of IL-17A in γδ T cells, grey: Vehicle, in red: Compound 3 D) Ear thickness over time with individual data points visualised.

(TIF)

pone.0317090.s005.tif^{(275.9KB, tif)}

S1 File. Raw data.

(XLSX)

pone.0317090.s006.xlsx^{(88.9KB, xlsx)}

Acknowledgments

We wish to thank the AstraZeneca laboratory animal science unit for their excellent help in animal husbandry and care taking. We also would like to thank Pharmaceutical Sciences for their help in preparing compound formulations for the animal work. We thank Roine Olsson and Sarah Lever for help in compound design and synthesis.

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

The author(s) received no specific funding for this work.

References

1.Cua DJ, Sherlock J, Chen Y, Murphy CA, Joyce B, Seymour B, et al. Interleukin-23 rather than interleukin-12 is the critical cytokine for autoimmune inflammation of the brain. Nature. 2003;421(6924):744–8. doi: 10.1038/nature01355 . [DOI] [PubMed] [Google Scholar]
2.Langrish CL, Chen Y, Blumenschein WM, Mattson J, Basham B, Sedgwick JD, et al. IL-23 drives a pathogenic T cell population that induces autoimmune inflammation. J Exp Med. 2005;201(2):233–40. doi: 10.1084/jem.20041257 ; PubMed Central PMCID: PMC2212798. [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Rosain J, Kong XF, Martinez-Barricarte R, Oleaga-Quintas C, Ramirez-Alejo N, Markle J, et al. Mendelian susceptibility to mycobacterial disease: 2014–2018 update. Immunol Cell Biol. 2018. doi: 10.1111/imcb.12210 ; PubMed Central PMCID: PMC6438774. [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Veldhoen M, Hocking RJ, Atkins CJ, Locksley RM, Stockinger B. TGFbeta in the context of an inflammatory cytokine milieu supports de novo differentiation of IL-17-producing T cells. Immunity. 2006;24(2):179–89. doi: 10.1016/j.immuni.2006.01.001 . [DOI] [PubMed] [Google Scholar]
5.Gaffen SL, Jain R, Garg AV, Cua DJ. The IL-23-IL-17 immune axis: from mechanisms to therapeutic testing. Nat Rev Immunol. 2014;14(9):585–600. doi: 10.1038/nri3707 ; PubMed Central PMCID: PMC4281037. [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Shelton SK, Bai SR, Jordan JK, Sheehan AH. Ixekizumab: A Review of Its Use for the Management of Moderate to Severe Plaque Psoriasis. Ann Pharmacother. 2018:1060028018799982. doi: 10.1177/1060028018799982 . [DOI] [PubMed] [Google Scholar]
7.Yiu ZZ, Warren RB. Guselkumab for psoriasis: a critical appraisal of Phase III studies. Immunotherapy. 2018;10(1):67–75. Epub 20171018. doi: 10.2217/imt-2017-0106 . [DOI] [PubMed] [Google Scholar]
8.Rendon A, Schakel K. Psoriasis Pathogenesis and Treatment. Int J Mol Sci. 2019;20(6). Epub 20190323. doi: 10.3390/ijms20061475 ; PubMed Central PMCID: PMC6471628. [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Naik GS, Ming WK, Magodoro IM, Akinwunmi B, Dar S, Poulsen HE, et al. Th17 Inhibitors in Active Psoriatic Arthritis: A Systematic Review and Meta-Analysis of Randomized Controlled Clinical Trials. Dermatology. 2017;233(5):366–77. Epub 20171220. doi: 10.1159/000484520 . [DOI] [PubMed] [Google Scholar]
10.Frieder J, Kivelevitch D, Haugh I, Watson I, Menter A. Anti-IL-23 and Anti-IL-17 Biologic Agents for the Treatment of Immune-Mediated Inflammatory Conditions. Clin Pharmacol Ther. 2018;103(1):88–101. Epub 20171019. doi: 10.1002/cpt.893 . [DOI] [PubMed] [Google Scholar]
11.Ivanov II, McKenzie BS, Zhou L, Tadokoro CE, Lepelley A, Lafaille JJ, et al. The orphan nuclear receptor RORgammat directs the differentiation program of proinflammatory IL-17+ T helper cells. Cell. 2006;126(6):1121–33. doi: 10.1016/j.cell.2006.07.035 . [DOI] [PubMed] [Google Scholar]
12.Zuniga LA, Jain R, Haines C, Cua DJ. Th17 cell development: from the cradle to the grave. Immunol Rev. 2013;252(1):78–88. doi: 10.1111/imr.12036 . [DOI] [PubMed] [Google Scholar]
13.Burgler S, Mantel PY, Bassin C, Ouaked N, Akdis CA, Schmidt-Weber CB. RORC2 is involved in T cell polarization through interaction with the FOXP3 promoter. J Immunol. 2010;184(11):6161–9. Epub 20100428. doi: 10.4049/jimmunol.0903243 . [DOI] [PubMed] [Google Scholar]
14.Xi H, Schwartz R, Engel I, Murre C, Kersh GJ. Interplay between RORgammat, Egr3, and E proteins controls proliferation in response to pre-TCR signals. Immunity. 2006;24(6):813–26. Epub 2006/06/20. doi: 10.1016/j.immuni.2006.03.023 . [DOI] [PubMed] [Google Scholar]
15.Naik AK, Dauphars DJ, Corbett E, Simpson L, Schatz DG, Krangel MS. RORγt up-regulates RAG gene expression in DP thymocytes to expand the Tcra repertoire. Sci Immunol. 2024;9(93):eadh5318. Epub 20240315. doi: 10.1126/sciimmunol.adh5318 ; PubMed Central PMCID: PMC11005092. [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Kurebayashi S, Ueda E, Sakaue M, Patel DD, Medvedev A, Zhang F, et al. Retinoid-related orphan receptor gamma (RORgamma) is essential for lymphoid organogenesis and controls apoptosis during thymopoiesis. Proc Natl Acad Sci U S A. 2000;97(18):10132–7. doi: 10.1073/pnas.97.18.10132 ; PubMed Central PMCID: PMC27750. [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Sun Z, Unutmaz D, Zou YR, Sunshine MJ, Pierani A, Brenner-Morton S, et al. Requirement for RORgamma in thymocyte survival and lymphoid organ development. Science. 2000;288(5475):2369–73. doi: 10.1126/science.288.5475.2369 . [DOI] [PubMed] [Google Scholar]
18.Ashby KM, Hogquist KA. A guide to thymic selection of T cells. Nature Reviews Immunology. 2023;24(2):103–17. doi: 10.1038/s41577-023-00911-8 [DOI] [PubMed] [Google Scholar]
19.Ueda E, Kurebayashi S, Sakaue M, Backlund M, Koller B, Jetten AM. High incidence of T-cell lymphomas in mice deficient in the retinoid-related orphan receptor RORgamma. Cancer Res. 2002;62(3):901–9. . [PubMed] [Google Scholar]
20.Okada S, Markle JG, Deenick EK, Mele F, Averbuch D, Lagos M, et al. IMMUNODEFICIENCIES. Impairment of immunity to Candida and Mycobacterium in humans with bi-allelic RORC mutations. Science. 2015;349(6248):606–13. Epub 2015/07/15. doi: 10.1126/science.aaa4282 ; PubMed Central PMCID: PMC4668938. [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Taghon T, Van de Walle I, De Smet G, De Smedt M, Leclercq G, Vandekerckhove B, et al. Notch signaling is required for proliferation but not for differentiation at a well-defined beta-selection checkpoint during human T-cell development. Blood. 2009;113(14):3254–63. Epub 20081023. doi: 10.1182/blood-2008-07-168906 . [DOI] [PubMed] [Google Scholar]
22.Zhong X, Wu H, Zhang W, Gwack Y, Shang W, Lee KO, et al. Decoupling the role of RORgammat in the differentiation and effector function of T(H)17 cells. Sci Adv. 2022;8(42):eadc9221. Epub 20221021. doi: 10.1126/sciadv.adc9221 ; PubMed Central PMCID: PMC9586477. [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Jetten AM. Retinoid-related orphan receptors (RORs): critical roles in development, immunity, circadian rhythm, and cellular metabolism. Nucl Recept Signal. 2009;7:e003. Epub 20090403. doi: 10.1621/nrs.07003 ; PubMed Central PMCID: PMC2670432. [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Ruan Q, Kameswaran V, Zhang Y, Zheng S, Sun J, Wang J, et al. The Th17 immune response is controlled by the Rel-RORgamma-RORgamma T transcriptional axis. J Exp Med. 2011;208(11):2321–33. Epub 20111017. doi: 10.1084/jem.20110462 ; PubMed Central PMCID: PMC3201209. [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Ruiz de Morales JMG, Puig L, Dauden E, Canete JD, Pablos JL, Martin AO, et al. Critical role of interleukin (IL)-17 in inflammatory and immune disorders: An updated review of the evidence focusing in controversies. Autoimmun Rev. 2020;19(1):102429. Epub 20191115. doi: 10.1016/j.autrev.2019.102429 . [DOI] [PubMed] [Google Scholar]
26.Cai Y, Shen X, Ding C, Qi C, Li K, Li X, et al. Pivotal role of dermal IL-17-producing gammadelta T cells in skin inflammation. Immunity. 2011;35(4):596–610. Epub 20111006. doi: 10.1016/j.immuni.2011.08.001 ; PubMed Central PMCID: PMC3205267. [DOI] [PMC free article] [PubMed] [Google Scholar]
27.van der Fits L, Mourits S, Voerman JS, Kant M, Boon L, Laman JD, et al. Imiquimod-induced psoriasis-like skin inflammation in mice is mediated via the IL-23/IL-17 axis. J Immunol. 2009;182(9):5836–45. Epub 2009/04/22. doi: 10.4049/jimmunol.0802999 . [DOI] [PubMed] [Google Scholar]
28.Pantelyushin S, Haak S, Ingold B, Kulig P, Heppner FL, Navarini AA, et al. Rorgammat+ innate lymphocytes and gammadelta T cells initiate psoriasiform plaque formation in mice. J Clin Invest. 2012;122(6):2252–6. Epub 20120501. doi: 10.1172/JCI61862 ; PubMed Central PMCID: PMC3366412. [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Zeng J, Li M, Zhao Q, Chen M, Zhao L, Wei S, et al. Small molecule inhibitors of RORγt for Th17 regulation in inflammatory and autoimmune diseases. Journal of Pharmaceutical Analysis. 2023;13(6):545–62. doi: 10.1016/j.jpha.2023.05.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Gege C. Retinoic acid-related orphan receptor gamma t (RORγt) inverse agonists/antagonists for the treatment of inflammatory diseases—where are we presently? Expert Opin Drug Discov. 2021;16(12):1517–35. Epub 20210707. doi: 10.1080/17460441.2021.1948833 . [DOI] [PubMed] [Google Scholar]
31.Narjes F, Xue Y, von Berg S, Malmberg J, Llinas A, Olsson RI, et al. Potent and Orally Bioavailable Inverse Agonists of RORgammat Resulting from Structure-Based Design. J Med Chem. 2018;61(17):7796–813. Epub 20180827. doi: 10.1021/acs.jmedchem.8b00783 . [DOI] [PubMed] [Google Scholar]
32.von Berg S, Xue Y, Collins M, Llinas A, Olsson RI, Halvarsson T, et al. Discovery of Potent and Orally Bioavailable Inverse Agonists of the Retinoic Acid Receptor-Related Orphan Receptor C2. ACS Med Chem Lett. 2019;10(6):972–7. Epub 20190529. doi: 10.1021/acsmedchemlett.9b00158 ; PubMed Central PMCID: PMC6580541. [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Narjes F, Llinas A, von Berg S, Jirholt J, Lever S, Pehrson R, et al. AZD0284, a Potent, Selective, and Orally Bioavailable Inverse Agonist of Retinoic Acid Receptor-Related Orphan Receptor C2. J Med Chem. 2021;64(18):13807–29. Epub 20210831. doi: 10.1021/acs.jmedchem.1c01197 . [DOI] [PubMed] [Google Scholar]
34.Liang Z, Dong X, Zhang Z, Zhang Q, Zhao Y. Age-related thymic involution: Mechanisms and functional impact. Aging Cell. 2022;21(8):e13671. Epub 20220712. doi: 10.1111/acel.13671 ; PubMed Central PMCID: PMC9381902. [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Huh JR, Englund EE, Wang H, Huang R, Huang P, Rastinejad F, et al. Identification of Potent and Selective Diphenylpropanamide RORgamma Inhibitors. ACS Med Chem Lett. 2013;4(1):79–84. doi: 10.1021/ml300286h ; PubMed Central PMCID: PMC3770298. [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Littman D. JRH, Huang R., Huang W., Englund E.E., inventorAMIDO COMPOUNDS AS RORyt MODULATORS AND USES THEREOF2011. [Google Scholar]
37.Erichsen CY, Jensen P, Kofoed K. Biologic therapies targeting the interleukin (IL)-23/IL-17 immune axis for the treatment of moderate-to-severe plaque psoriasis: a systematic review and meta-analysis. J Eur Acad Dermatol Venereol. 2020;34(1):30–8. Epub 20190904. doi: 10.1111/jdv.15879 . [DOI] [PubMed] [Google Scholar]
38.Sieper J, Poddubnyy D, Miossec P. The IL-23-IL-17 pathway as a therapeutic target in axial spondyloarthritis. Nat Rev Rheumatol. 2019;15(12):747–57. Epub 20190924. doi: 10.1038/s41584-019-0294-7 . [DOI] [PubMed] [Google Scholar]
39.Mills KHG. IL-17 and IL-17-producing cells in protection versus pathology. Nature Reviews Immunology. 2023;23(1):38–54. doi: 10.1038/s41577-022-00746-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Loft ND, Vaengebjerg S, Halling AS, Skov L, Egeberg A. Adverse events with IL-17 and IL-23 inhibitors for psoriasis and psoriatic arthritis: a systematic review and meta-analysis of phase III studies. J Eur Acad Dermatol Venereol. 2019. Epub 2019/11/14. doi: 10.1111/jdv.16073 . [DOI] [PubMed] [Google Scholar]
41.Liljevald M, Rehnberg M, Soderberg M, Ramnegard M, Borjesson J, Luciani D, et al. Retinoid-related orphan receptor gamma (RORgamma) adult induced knockout mice develop lymphoblastic lymphoma. Autoimmun Rev. 2016;15(11):1062–70. Epub 20160802. doi: 10.1016/j.autrev.2016.07.036 . [DOI] [PubMed] [Google Scholar]
42.Haggerty HG, Sathish JG, Gleason CR, Al-Haddawi M, Brodie TA, Bonnette KL, et al. Thymic Lymphomas in a 6-Month rasH2-Tg Mouse Carcinogenicity Study With the RORγt Inverse Agonist, BMS-986251. Toxicol Sci. 2021;183(1):93–104. doi: 10.1093/toxsci/kfab086 . [DOI] [PubMed] [Google Scholar]
43.Mukherjee S, Kar A, Paul P, Dey S, Biswas A, Barik S. In Silico Integration of Transcriptome and Interactome Predicts an ETP-ALL-Specific Transcriptional Footprint that Decodes its Developmental Propensity. Front Cell Dev Biol. 2022;10:899752. Epub 20220513. doi: 10.3389/fcell.2022.899752 ; PubMed Central PMCID: PMC9138408. [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Spidale NA, Sylvia K, Narayan K, Miu B, Frascoli M, Melichar HJ, et al. Interleukin-17-Producing gammadelta T Cells Originate from SOX13(+) Progenitors that Are Independent of gammadeltaTCR Signaling. Immunity. 2018;49(5):857–72 e5. Epub 20181106. doi: 10.1016/j.immuni.2018.09.010 ; PubMed Central PMCID: PMC6249057. [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Guendisch U, Weiss J, Ecoeur F, Riker JC, Kaupmann K, Kallen J, et al. Pharmacological inhibition of RORgammat suppresses the Th17 pathway and alleviates arthritis in vivo. PLoS One. 2017;12(11):e0188391. Epub 2017/11/21. doi: 10.1371/journal.pone.0188391 ; PubMed Central PMCID: PMC5695821. [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Xue X, Soroosh P, De Leon-Tabaldo A, Luna-Roman R, Sablad M, Rozenkrants N, et al. Pharmacologic modulation of RORgammat translates to efficacy in preclinical and translational models of psoriasis and inflammatory arthritis. Sci Rep. 2016;6:37977. Epub 2016/12/03. doi: 10.1038/srep37977 ; PubMed Central PMCID: PMC5131364. [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Skepner J, Ramesh R, Trocha M, Schmidt D, Baloglu E, Lobera M, et al. Pharmacologic inhibition of RORgammat regulates Th17 signature gene expression and suppresses cutaneous inflammation in vivo. J Immunol. 2014;192(6):2564–75. Epub 2014/02/12. doi: 10.4049/jimmunol.1302190 . [DOI] [PubMed] [Google Scholar]
48.Schnute ME, Wennerstal M, Alley J, Bengtsson M, Blinn JR, Bolten CW, et al. Discovery of 3-Cyano- N-(3-(1-isobutyrylpiperidin-4-yl)-1-methyl-4-(trifluoromethyl)-1 H-pyrrolo[2,3- b]pyridin-5-yl)benzamide: A Potent, Selective, and Orally Bioavailable Retinoic Acid Receptor-Related Orphan Receptor C2 Inverse Agonist. J Med Chem. 2018;61(23):10415–39. Epub 2018/08/22. doi: 10.1021/acs.jmedchem.8b00392 . [DOI] [PubMed] [Google Scholar]
49.Gangwar RS, Gudjonsson JE, Ward NL. Mouse Models of Psoriasis: A Comprehensive Review. J Invest Dermatol. 2022;142(3 Pt B):884–97. Epub 20211223. doi: 10.1016/j.jid.2021.06.019 ; PubMed Central PMCID: PMC10190156. [DOI] [PMC free article] [PubMed] [Google Scholar]
50.Hawkes JE, Chan TC, Krueger JG. Psoriasis pathogenesis and the development of novel targeted immune therapies. J Allergy Clin Immunol. 2017;140(3):645–53. doi: 10.1016/j.jaci.2017.07.004 ; PubMed Central PMCID: PMC5600287. [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Banerjee D, Zhao L, Wu L, Palanichamy A, Ergun A, Peng L, et al. Small molecule mediated inhibition of RORgamma-dependent gene expression and autoimmune disease pathology in vivo. Immunology. 2016;147(4):399–413. Epub 20160126. doi: 10.1111/imm.12570 ; PubMed Central PMCID: PMC4799885. [DOI] [PMC free article] [PubMed] [Google Scholar]
52.Shimizu T, Kamata M, Fukaya S, Hayashi K, Fukuyasu A, Tanaka T, et al. Anti-IL-17A and IL-23p19 antibodies but not anti-TNFalpha antibody induce expansion of regulatory T cells and restoration of their suppressive function in imiquimod-induced psoriasiform dermatitis. J Dermatol Sci. 2019;95(3):90–8. Epub 20190723. doi: 10.1016/j.jdermsci.2019.07.006 . [DOI] [PubMed] [Google Scholar]
53.Zeng J, Li M, Zhao Q, Chen M, Zhao L, Wei S, et al. Small molecule inhibitors of RORgammat for Th17 regulation in inflammatory and autoimmune diseases. J Pharm Anal. 2023;13(6):545–62. Epub 20230520. doi: 10.1016/j.jpha.2023.05.009 ; PubMed Central PMCID: PMC10334362. [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Guntermann C, Piaia A, Hamel ML, Theil D, Rubic-Schneider T, Del Rio-Espinola A, et al. Retinoic-acid-orphan-receptor-C inhibition suppresses Th17 cells and induces thymic aberrations. JCI Insight. 2017;2(5):e91127. Epub 20170309. doi: 10.1172/jci.insight.91127 ; PubMed Central PMCID: PMC5333964. [DOI] [PMC free article] [PubMed] [Google Scholar]
55.Guo Y, MacIsaac KD, Chen Y, Miller RJ, Jain R, Joyce-Shaikh B, et al. Inhibition of RORgammaT Skews TCRalpha Gene Rearrangement and Limits T Cell Repertoire Diversity. Cell Rep. 2016;17(12):3206–18. doi: 10.1016/j.celrep.2016.11.073 . [DOI] [PubMed] [Google Scholar]
56.He Z, Zhang J, Du Q, Xu J, Gwack Y, Sun Z. SRC3 Is a Cofactor for RORgammat in Th17 Differentiation but Not Thymocyte Development. J Immunol. 2019;202(3):760–9. Epub 20181219. doi: 10.4049/jimmunol.1801187 ; PubMed Central PMCID: PMC6344289. [DOI] [PMC free article] [PubMed] [Google Scholar]
57.He Z, Ma J, Wang R, Zhang J, Huang Z, Wang F, et al. A two-amino-acid substitution in the transcription factor RORgammat disrupts its function in T(H)17 differentiation but not in thymocyte development. Nat Immunol. 2017;18(10):1128–38. Epub 20170828. doi: 10.1038/ni.3832 ; PubMed Central PMCID: PMC5678981. [DOI] [PMC free article] [PubMed] [Google Scholar]
58.Strutzenberg TS, Zhu Y, Novick SJ, Garcia-Ordonez RD, Doebelin C, He Y, et al. Conformational Changes of RORγ During Response Element Recognition and Coregulator Engagement. Journal of Molecular Biology. 2021;433(22):167258. 10.1016/j.jmb.2021.167258. [DOI] [PMC free article] [PubMed] [Google Scholar]
59.Polasek TM, Leelasena I, Betscheider I, Marolt M, Kohlhof H, Vitt D, et al. Safety, Tolerability, and Pharmacokinetics of IMU-935, a Novel Inverse Agonist of Retinoic Acid Receptor-Related Orphan Nuclear Receptor gammat: Results From a Double-Blind, Placebo-Controlled, First-in-Human Phase 1 Study. Clin Pharmacol Drug Dev. 2023;12(5):525–34. Epub 20230320. doi: 10.1002/cpdd.1243 . [DOI] [PubMed] [Google Scholar]
60.Therapeutics I. Maintenance Phase of Phase 2 CALDOSE-1 Trial of Vidofludimus Calcium in Moderate-to-Severe Ulcerative Colitis 2023. Available from: https://ir.imux.com/2023-04-05-Immunic-Reports-Positive-Data-from-Maintenance-Phase-of-Phase-2-CALDOSE-1-Trial-of-Vidofludimus-Calcium-in-Moderate-to-Severe-Ulcerative-Colitis. [Google Scholar]
61.de Meis J, Aurelio Farias-de-Oliveira D, Nunes Panzenhagen PH, Maran N, Villa-Verde DM, Morrot A, et al. Thymus atrophy and double-positive escape are common features in infectious diseases. J Parasitol Res. 2012;2012:574020. Epub 20120201. doi: 10.1155/2012/574020 ; PubMed Central PMCID: PMC3307005. [DOI] [PMC free article] [PubMed] [Google Scholar]
62.Demoulins T, Abdallah A, Kettaf N, Baron ML, Gerarduzzi C, Gauchat D, et al. Reversible blockade of thymic output: an inherent part of TLR ligand-mediated immune response. J Immunol. 2008;181(10):6757–69. doi: 10.4049/jimmunol.181.10.6757 . [DOI] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0317090.r001

Decision Letter 0

Subhasis Barik

28 May 2024

PONE-D-24-01191RORγt inverse agonists demonstrating a margin between inhibition of IL-17A and thymocyte apoptosisPLOS ONE

Dear Dr. Collins,

==============================

Both the reviewers raised several pertinent issues that need to be addressed in a proper way.

==============================

Please submit your revised manuscript by Jul 12 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Subhasis Barik

Academic Editor

PLOS ONE

Journal Requirements:

1. When submitting your revision, we need you to address these additional requirements.

Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf.

2. Please note that PLOS ONE has specific guidelines on code sharing for submissions in which author-generated code underpins the findings in the manuscript. In these cases, all author-generated code must be made available without restrictions upon publication of the work. Please review our guidelines at https://journals.plos.org/plosone/s/materials-and-software-sharing#loc-sharing-code and ensure that your code is shared in a way that follows best practice and facilitates reproducibility and reuse.

3. Thank you for stating the following in the Competing Interests section:

[I have read the journal's policy and the authors of this manuscript have the following competing interests: All authors are or have been employees of AstraZeneca. Several of the authors are or have been shareholders of AstraZeneca.].

Please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials, by including the following statement: ""This does not alter our adherence to PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests). If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.

Please include your updated Competing Interests statement in your cover letter; we will change the online submission form on your behalf.

Additional Editor Comments:

Both the reviewers raised several pertinent issues that need to be addressed in a proper way.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript "RORγt inverse agonists demonstrating a margin between inhibition of IL-17A and thymocyte apoptosis" investigates a fundamental duality in T cell functions; where targeting the key transcription factor that promotes Th17 cell functions in autoimmune diseases, may also lead to a defect in thymic T cell development. The work looks into the problem from a clinical perspective and finds a difference in dose for RORγt inverse agonists to exert these two opposite effects, which might be of therapeutic significance. Overall, the work has merit, but also has certain technical pitfalls. I have a few points for suggestions, as listed below.

a. The primary aim of this work is to uncouple CD4+CD8+ thymocyte apoptosis from Th17 cell activity modulation by the RORγt-targeted compounds. Since RORγt expression is thymus-specific, while RORγ is not expressed in the thymus to a considerable extent, the authors might have chosen a compound that selectively targets RORγ and not RORγt. This could have completely abolished any thymus-specific effect. The authors need to justify this.

b. IL-17 and other proinflammatory cytokine signalling pathways are highly active in early T cell progenitors and are associated with their leukemic potential (reference doi: 10.3389/fcell.2022.899752). Even though the authors have mentioned the implications of RORγt inhibition on thymic lymphoma in mice, they have not mentioned the potential effects of such therapies on the development of thymic T cell leukemia, which should be separately addressed as a limitation of the study. Similarly, the authors have also not mentioned the importance of RORγt on the selection of diverse TCRs in the thymus, which is a major hindrance to autoimmunity (reference doi: 10.1016/j.celrep.2016.11.073). The potential risks of developing T cells with autoimmune features by RORγt inhibition should also be discussed.

c. The ex vivo mouse thymocyte apoptosis assay in presence or absence of the compounds of interest has been performed without stimulating the thymocytes. However, apoptosis of thymocytes in the thymus during the selection checkpoints is dependent on a T cell receptor-mediated activation signal. The authors need to point out this fact and mention the need for assessing thymocyte apoptosis by these compounds upon ex vivo stimulation.

d. Even though the authors show significant success of compound 3 in reducing the levels of IL-17A as well as γδ T cells in the ear after imiquimod-induced skin inflammation, they might have also shown their levels in the systemic circulation (for example, in blood or spleen), to establish its role in moderating the systemic inflammation.

e. The authors have stated their inability to test their compound's efficacy in mediating thymocyte apoptosis during imiquimod-mediated skin inflammation. This could have been overcome by changing the dose of imiquimod which would have induced skin inflammation but with minimal damage to the thymus. Alternatively, IL-17A-dependent established inflammatory models which do not cause significant damage to the thymus (reference doi: 10.1111/j.1365-3083.2007.01923.x), might have been used. The authors need to discuss this issue.

f. Please replace "unspecific" with "non-specific" (Materials and methods).

Reviewer #2: Psoriasis and associated autoimmune manifestations are a set of chronic immunopathologies without plenty of available treatment options. Against such a backdrop, the authors have explored a unique side of anti-psoriatic medication, where a certain dose of an RORgammaT inverse agonist ameliorates psoriatic symptoms at the periphery without affecting T cell development. This is definitely of immense clinical importance, since defective thymopoiesis is often associated with several immunosuppressive therapies, such as corticosteroid therapy; unavoidably producing numerous side effects. While I do not find any major drawbacks in the rationale and design of the study, I have a few questions and suggestions towards the authors, as follows.

In figure 2, where the authors estimate the effects of their compounds on thymic DP cells in vivo, they have only measured the cell numbers and have shown a steady decrease in it with increasing concentration of their compound. How do they attribute this to be caused by apoptosis and not premature thymic escape of the DP thymocytes (de Meis et al, Journal of Parasitology Research, 2012) without specific assays conducted in vivo which indicate apoptosis (Annexin V binding, TUNEL, cleaved Caspase-3 measurement etc)? The correlation with their in vitro findings does not suffice for such an explanation.

The authors only look at the DP thymocyte number upon treatment with their compounds, and conclude that they are not affecting thymopoiesis to a great extent. However, several recent studies highlight the presence of crucial developmental events which, if perturbed, affect the functionality of the ensuing T cells upon maturation (Gamble et al, Nature Immunology, 2024; Bovolenta et al, PNAS, 2022) without taking a toll on their survival. Since RORgt has an important role in thymopoiesis, how do the authors ensure that their compounds are not affecting the epigenetic circuitry inside the developing thymocytes in any such way?

The methods are described in a slightly haphazard way. While there are plenty of details regarding how the authors validate the screened compounds in terms of their binding capacity, there is insufficient information about which compounds (or library) were deemed qualified for screening, and based on what criteria. The methodology related to the imiquimod-induced skin inflammation model is also written in a wayward manner. When is the compound applied, before or after imiquimod application?

The connection between RORgammaT manipulation and thymic lymphoma is very interesting. The authors should mention the risks of thymic T cell progenitor leukemia as well, since dysregulated IL-17 signaling and RORgammaT-dependent pathways are critically involved in the emergence of early T cell progenitor leukemia (Mukherjee et al, Frontiers in Cell & Developmental Biology, 2022).

In the discussion, the authors mention the variability in thymus size of 6-8 weeks old mice as a limitation of this study. Again, they mention the age of mice used in the thymic involution experiments as 5 weeks. They need to explain this discrepancy.

The authors test the efficacy of their compounds in an imiquimod-induced dermatitis model, which very weakly resembles psoriasis (Hawkes et al, Journal of investigative dermatology, 2017). This needs to be clearly mentioned in the discussion section.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2025 Jan 16;20(1):e0317090. doi: 10.1371/journal.pone.0317090.r002

Author response to Decision Letter 0

26 Aug 2024

Editor’s summary and main concerns:

Dear Editor

Thank you for the possibility to revise this manuscript. It is clear to us that the reviewers have spent substantial time and effort in reviewing our work in order to help us make improvements.

We have formulated responses to each of the questions below and updated the manuscript accordingly.

We believe that the paper is improved from the feedback we have received and that the text is clearer and easier to read and understand.

Yours sincerely,

Dr Mia Collins

Review Comments to the Author

Reviewer 1:

Thank you for this comment, it is indeed a great suggestion and it would have been optimal to include such a compound. However, except for the compound referenced in the discussion of the manuscript (Reference 54 Polasek et al), we are not aware of any compound that distinguishes between the 2 isoforms and the referenced compound was not available at the time of the study. The protein sequence of the ligand binding domain is identical between the RORγ and RORγt isoforms, and isoform specificity is likely to be very hard to achieve. Furthermore, since both isoforms are expressed in Th17 cells, it is likely that it will be necessary to inhibit both RORγ and RORγt to achieve efficacy in peripheral T-cells. This data is stated in the introduction, rows 77-84, and we have added an additional clarification to accommodate the reviewers feedback rows 667-669.

This is an important point, and we share these thoughts and concerns. We have now made it even more clear than before that this might be a problem in humans and we added to this discussion at rows 646-649. The following section now reads:

“Hence, today, clinical progression of this class of inhibitor seems to be an unsurmountable hurdle due to the lack of means to predict and evaluate the safety profile with regards to development of thymic lymphoma and T-ALL, which is a clear limitation.”

Similarly, the authors have also not mentioned the importance of RORγt on the selection of diverse TCRs in the thymus, which is a major hindrance to autoimmunity (reference doi: 10.1016/j.celrep.2016.11.073). The potential risks of developing T cells with autoimmune features by RORγt inhibition should also be discussed.

We would like to thank the reviewer for this important point. We have updated the manuscript to reflect this data and its potential consequences. Rows 638-644 which now reads:

“An additional complication of inhibition of RORgt has been suggested by Guo et al [51] where they have demonstrated a skewing of the TCRa gene rearrangement and hence limitations to the diversity of the T cell repertoire in mice. While skewing of the T cell repertoire is noteworthy, due to the potentially enhanced risk of developing autoimmune disorders and infection, the T cell leukopenia observed in humans carrying RORC biallelic loss of function mutations, is less pronounced than that observed in mice [19].”

Thank you for this comment, it is important to bring up several aspects of this complicated biology. Thymocytes apoptose naturally in the thymus both due to an overly strong TCR engagement and a too week, or lack of engagement aka “death by neglect”. We have updated the text to reflect this and to make it more clear. Rows 67-69 now reads:

“In the mouse, thymocytes deficient in RORγt remain hyperproliferative but they also rapidly apoptose through the lack of RORγt-dependent Bcl-xL induced quiescence [16, 18].”

This is a great suggestion and in hindsight we might have included this. The IMQ model mainly induces a local inflammation in the ear during the 8-day treatment period. The point we would like to make with this experiment is to demonstrate that through peroral drug administration we achieve systemic exposure at sufficient levels to block inflammation even in the periphery such as the ear pinnas. As we have demonstrated exposure in the blood, we have no doubt that we will also affect inflammation throughout the body.

Alternatively, IL-17A-dependent established inflammatory models which do not cause significant damage to the thymus (reference doi: 10.1111/j.1365-3083.2007.01923.x), might have been used. The authors need to discuss this issue.

Thank you for these comments. While several processes affect thymocyte survival, we have not been able to find any data indicating that IMQ causes thymic damage. Ageing, however, comes with the involution of the thymus where the organ reduces in size with age, as well as its output of naïve T-cells. This process is variable in individuals and across the sexes. This variability hampers the possibility to use the thymic readouts in such models where ethical considerations dictate the usable age span of the experimental animals. Thymus involution sets in approximately at sexual maturation in mice-(6-8 weeks). Additionally, the daily application of IMQ creme and per oral compound administration induces some stress to the animals that affects the cellularity and weight of the animals’ thymae. In line with this reasoning, the suggested use of the dextran sulphate sodium-induced intestinal inflammation model is unlikely to aid in circumventing the stress, malaise and age dependent variability of the thymus size and cellularity. We have updated the section that highlights that this separation between thymic effects and effect on IMQ induced inflammation is important and subject to stress and age dependent variability. Rows 675-685 now read:

“A further limitation is the lack of establishing an in vivo margin between the positive effect of RORγt inhibition (reduction of IL-17A) and the unwanted effect of thymocyte apoptosis in the same animal experiment. This was not achievable due to the stress-sensitive nature of the thymus which undergoes rapid involution upon handling (e.g application of IMQ cream and dosing of compounds) of the animals. Furthermore, the early onset of natural thymic involution in mice around sexual maturity (6-8 weeks) would introduce further variability in thymus size in the adult animals needed in the IMQ experiment, both for the immune system to be fully matured and to minimize variability from growth related differences in size and thickness of ear pinnas and cell numbers. This limitation did not apply to the experiments studying thymus effects as the animals were intentionally young to ensure thymic involution had not yet started.”

f. Please replace "unspecific" with "non-specific" (Materials and methods).

Thank you, this has been corrected.

Reviewer 2:

a. In figure 2, where the authors estimate the effects of their compounds on thymic DP cells in vivo, they have only measured the cell numbers and have shown a steady decrease in it with increasing concentration of their compound. How do they attribute this to be caused by apoptosis and not premature thymic escape of the DP thymocytes (de Meis et al, Journal of Parasitology Research, 2012) without specific assays conducted in vivo which indicate apoptosis (Annexin V binding, TUNEL, cleaved Caspase-3 measurement etc)? The correlation with their in vitro findings does not suffice for such an explanation.

Thank you for this comment. We show in this paper that we induce apoptosis in freshly isolated primary thymocytes ex vivo through AnnexinV staining. While this does not constitute evidence for the same process taking place in vivo, it demonstrates that high levels of inhibition of RORgt leads to apoptosis in the same way as loss of function of RORgt does. That loss of RORgt induces apoptosis in vivo has been established previously, both through AnnexinV staining of thymocytes and TUNEL staining in thymic sections (reference 18, Ueda 2002). Based on these established findings we believe that we can conclude that we lose thymocytes primarily through apoptosis. We have added this reference to row 69 to make this clearer to the reader. Reviewer 1 had a similar comment and hence we have also made changes to the text to reflect this at rows 67-69.

“In the mouse, thymocytes deficient in RORγt remain hyperproliferative but they also rapidly apoptose through the lack of RORγt-dependent Bcl-xL induced quiescence [16, 18].”

b. The authors only look at the DP thymocyte number upon treatment with their compounds, and conclude that they are not affecting thymopoiesis to a great extent. However, several recent studies highlight the presence of crucial developmental events which, if perturbed, affect the functionality of the ensuing T cells upon maturation (Gamble et al, Nature Immunology, 2024; Bovolenta et al, PNAS, 2022) without taking a toll on their survival.

Since RORgt has an important role in thymopoiesis, how do the authors ensure that their compounds are not affecting the epigenetic circuitry inside the developing thymocytes in any such way?

This is a good point; however, the paper aims to suggest a potential for a window between the effect on mature effector T-cells and thymus apoptosis. It is likely that with a substantial inhibition of RORγ in the thymus of mice many perturbations to the normal T-cell development can be expected, including epigenetic effects and effects on TCRα splicing and recombination. These can be inferred from the observed sustained proliferation followed by rapid apoptosis vs a proliferative burst followed by quiescence and then more limited apoptosis. Additionally, a skewing of the TCR repertoire has been observed both in mice and man. Some of the underlying causes have been described, like the mentioned lack of Bcl-xL upregulation. If we can circumvent the induced apoptosis, then these other issues can be studied. This has not been accomplished in this work, but we have enhanced the discussion on potential consequences of inhibiting RORγ. There was a similar comment from Reviewer 1 and this was addressed in rows 638-644.

Thank you for this comment. In this paper we have focused on describing biological effects of RORγt inhibition in developing thymocytes and peripheral mature T cells that are of general interest to the field. The chemical development of this series of RORγt inverse agonists have been described in three publications by us (see references 30-32) where a detailed account of the chemical evolution as well as the desired properties are presented. We have updated the introduction rows 100-101 to emphasize that information regarding the chemistry campaign is described in the three papers referenced.

The methodology related to the imiquimod-induced skin inflammation model is also written in a wayward manner. When is the compound applied, before or after imiquimod application?

Thank you for pointing this out. This is an omission on our part and the text has been updated to clarify timing and order of manipulations. Rows 270-271 now reading:

“The application of Aldara cream took place in the morning after oral compound dosing.”

Thanks for raising these points, it is indeed a very interesting paper and it is supported by other papers. Tarantini et al. Biomarker Research (2021) 9:89 https://doi.org/10.1186/s40364-021-00347-z

However, there is no mention of neither IL-17 nor RORγt in either of these papers as being active in ETP as stated by the reviewer. The current data supports that loss of RORγ or RORγt function in the mouse can lead

Attachment

Submitted filename: Response to reviewers.docx

pone.0317090.s007.docx^{(47.6KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0317090.r003

Decision Letter 1

Subhasis Barik

17 Oct 2024

PONE-D-24-01191R1RORγt inverse agonists demonstrating a margin between inhibition of IL-17A and thymocyte apoptosisPLOS ONE

Dear Dr. Collins,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised by both the reviewers. Please submit your revised manuscript by Dec 01 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Subhasis Barik

Academic Editor

PLOS ONE

Additional Editor Comments:

Authors are requested to clarify the raised issues by both the reviewers

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: The authors have addressed most of my concerns. I have a minor issue with their response to my comment no. c in the previous round of review. In their response as well as the modification in the manuscript, they do not mention the need for assessing thymocyte apoptosis in the presence of ex vivo stimulation. What they tried to convey through the modified text in the manuscript was not clear to me in this context. Indeed, thymocytes die in the thymus both due to excessively strong TCR stimulation or no stimulation at all. While they have analysed the effects of their compounds on the thymocytes in absence of any stimulation, it would be of greater value if they could assess the same in the presence of ex vivo stimuli.The authors need to give a more to-the-point explanation for this.

Reviewer #2: Collins et al have demonstrated formidable sincerity in addressing my comments. However, some of their responses could not directly address the particular queries raised by me.

Apoptosis and thymic escape of DP thymocytes are not mutually exclusive events [de Meis, Juliana et al. “Thymus atrophy and double-positive escape are common features in infectious diseases.” Journal of parasitology research vol. 2012 (2012): 574020. doi:10.1155/2012/574020; Démoulins, Thomas et al. “Reversible blockade of thymic output: an inherent part of TLR ligand-mediated immune response.” Journal of immunology (Baltimore, Md. : 1950) vol. 181,10 (2008): 6757-69. doi:10.4049/jimmunol.181.10.6757]. How do the authors, then, conclude that the loss of DP thymocytes does not involve premature DP escape as a potential reason? Simply referring to the fact that DP apoptosis is predominant during thymic involution does not suffice for this statement.

The authors state that the reference mentioned by me [Mukherjee, Soumyadeep et al. “In Silico Integration of Transcriptome and Interactome Predicts an ETP-ALL-Specific Transcriptional Footprint that Decodes its Developmental Propensity.” Frontiers in cell and developmental biology vol. 10 899752. 13 May. 2022, doi:10.3389/fcell.2022.899752] does not explicitly mention that ETP-ALL has high IL-17 activity. However, figure 2F in that article clearly shows a strong enrichment of IL-17 signaling in ETP-ALL. Furthermore, defined subsets of DN1 thymocytes (which also contribute to ETP-ALL) express a handsome amount of RORC transcript [Spidale, Nicholas A et al. “Interleukin-17-Producing γδ T Cells Originate from SOX13+ Progenitors that Are Independent of γδTCR Signaling.” Immunity vol. 49,5 (2018): 857-872.e5. doi:10.1016/j.immuni.2018.09.010], whereby it cannot be ruled out that RORgammaT inhibition might have some impact on ETP-ALL. I think the authors underestimated the implications of my comment in this context and it would be great if they highlight this aspect with due care.

6-8 weeks old mice are barely susceptible to age-induced thymic involution. However, natural age-associated thymic involution starts from approx. 4 weeks. Therefore, the authors’ claim regarding the optimality of their use of 5 weeks old mice for thymic involution experiments does not make much sense. In that case, they need to substantiate their claim by treating 0-2 weeks old pups with IMQ and check its effects on thymic involution. Nevertheless, I believe simply rephrasing their claim might be enough to avoid the confusion.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

PLoS One. 2025 Jan 16;20(1):e0317090. doi: 10.1371/journal.pone.0317090.r004

Author response to Decision Letter 1

25 Nov 2024

Editor’s summary and main concerns:

Dear Editor

Thank you for the possibility to revise this manuscript again. We appreciate the reviewers’ time and effort with this, and we can see that the manuscript is now improved and that limitations with the study are now highlighted even more.

We have formulated responses to each of the questions below and updated the manuscript accordingly. We hope that our responses will be satisfactory.

Yours sincerely,

Dr Mia Collins

Review Comments to the Author

Reviewer 1:

Reviewer #1: The authors have addressed most of my concerns. I have a minor issue with their response to my comment no. c in the previous round of review. In their response as well as the modification in the manuscript, they do not mention the need for assessing thymocyte apoptosis in the presence of ex vivo stimulation. What they tried to convey through the modified text in the manuscript was not clear to me in this context. Indeed, thymocytes die in the thymus both due to excessively strong TCR stimulation or no stimulation at all. While they have analysed the effects of their compounds on the thymocytes in absence of any stimulation, it would be of greater value if they could assess the same in the presence of ex vivo stimuli. The authors need to give a more to-the-point explanation for this.

Thank you for following up on this comment.

In the normal situation DP thymocytes increase their expression of a fully formed TCRab receptor and begin to sample self peptides presented to them. However, DP thymocytes are dependent on Bcl-xL for their survival, the expression of which is governed by RORgt. Hence, blocking RORgt causes the loss of quiescence and cells begin to apoptose, effectively reducing the number of thymocytes expressing a fully formed TCRab receptor. This is an upstream event before thymocytes commit to becoming CD8+ Tc or CD4+ Th cells and leave the thymus as mature naive T-cells. It is therefore unlikely that exogenous CD3/CD28 stimulation or similar will affect this relatively short assay. In both mouse and human the number of mature peripheral T-cells is reduced in subjects where the RORgt protein function has been lost, but fully mature peripheral T-cells still exist. Apparently, a fraction of T-cells escape the thymus although RORgt has been lost, potentially depending on the timing or the strength of the positive selection signal (i.e. TCR stimulation) and this is an effect that we would suggest warrants further investigation. In this situation the reviewer’s suggestion is important to consider but not entirely straightforward to accomplish in this short assay. The assay is run as separated whole thymus cells, but the critical cellular organization and cytokine milieu is of course severely disrupted and quite difficult to mimic. As a follow up experiment to this assay, we do the in vivo experiment where similar effects are seen in an intact thymus with endogenous physiological TCR stimulation and selection.

Nonetheless, the limitations part of the discussion has been updated to reflect the reviewer’s important point. See rows: 701-706

“An additional limitation is the artificiality of the thymocyte apoptosis assay where the thymic organization is disrupted thereby limiting the normal cytokine milieu and cellular cross talk (TCR stimulation). To circumvent this the thymocytes could have been stimulated in different ways. However, the enhanced apoptosis is supported in the thymus involution in vivo study where signaling and cross talk are intact.”

Reviewer 2:

Reviewer #2: Collins et al have demonstrated formidable sincerity in addressing my comments. However, some of their responses could not directly address the particular queries raised by me.

1. Apoptosis and thymic escape of DP thymocytes are not mutually exclusive events [de Meis, Juliana et al. “Thymus atrophy and double-positive escape are common features in infectious diseases.” Journal of parasitology research vol. 2012 (2012): 574020. doi:10.1155/2012/574020; Démoulins, Thomas et al. “Reversible blockade of thymic output: an inherent part of TLR ligand-mediated immune response.” Journal of immunology (Baltimore, Md. : 1950) vol. 181,10 (2008): 6757-69. doi:10.4049/jimmunol.181.10.6757]. How do the authors, then, conclude that the loss of DP thymocytes does not involve premature DP escape as a potential reason? Simply referring to the fact that DP apoptosis is predominant during thymic involution does not suffice for this statement.

Thank you for pointing out this important phenomenon. The reviewer correctly points out the lack of evidence to rule out premature thymic escape in our work. Having read the suggested papers and others, the published literature is limited in describing this in non-infectious or non-inflammatory situations, while being clear in establishing that loss of- or inhibition of- RORgt induces a direct and rapid DP thymocyte apoptosis. Given that our experimental animals are healthy and reside in a relatively clean environment, our conclusion is that the majority of the DP loss can be attributed to apoptosis. To highlight that the manuscript does not address this, we have updated the limitations part of the discussion to illuminate this shortcoming, see rows: 695-701

“A potential complication in measuring thymus cellularity of double positive thymocytes is premature thymic escape. This process has not been investigated in this work, however most of the literature has investigated premature thymic double positive escape in the context of infection or inflammation [61,62]. However, it is established by us and others that loss [16,17] or inhibition of [54] RORγt has a direct and rapid effect on apoptosis. Since these animals are healthy and in a clean environment, we attribute the majority of the rapid loss of double positive thymocytes to apoptosis.”

2. The authors state that the reference mentioned by me [Mukherjee, Soumyadeep et al. “In Silico Integration of Transcriptome and Interactome Predicts an ETP-ALL-Specific Transcriptional Footprint that Decodes its Developmental Propensity.” Frontiers in cell and developmental biology vol. 10 899752. 13 May. 2022, doi:10.3389/fcell.2022.899752] does not explicitly mention that ETP-ALL has high IL-17 activity. However, figure 2F in that article clearly shows a strong enrichment of IL-17 signaling in ETP-ALL. Furthermore, defined subsets of DN1 thymocytes (which also contribute to ETP-ALL) express a handsome amount of RORC transcript [Spidale, Nicholas A et al. “Interleukin-17-Producing γδ T Cells Originate from SOX13+ Progenitors that Are Independent of γδTCR Signaling.” Immunity vol. 49,5 (2018): 857-872.e5. doi:10.1016/j.immuni.2018.09.010], whereby it cannot be ruled out that RORgammaT inhibition might have some impact on ETP-ALL. I think the authors underestimated the implications of my comment in this context and it would be great if they highlight this aspect with due care.

We clearly underestimated the implications of the reviewer’s comments regarding ETP-ALL and IL-17 and ROR gamma and for this we are sorry. The reviewer is correct in highlighting that ETP-ALL are differentiated from non-ETP-ALL by an IL-17 signal and that DN1 cells can express ROR gamma. We have updated the text to reflect the involvement of this pathway in ETP-ALL, see rows: 590-596

“However, in a subset of acute lymphoblastic leukemia originating in the early T precursor cell (ETP-ALL), enrichment in the IL-17 pathway has been described [43]. Furthermore, during early thymocyte maturation, in the DN1 stage, a subset of thymocytes upregulate the expression of Rorc [44] and these cells can, if dysregulated, also develop into ETP-ALL. In this situation it may be valuable to evaluate if inhibition of RORyt reduces the proliferation and expansion of such cells.”

3. 6-8 weeks old mice are barely susceptible to age-induced thymic involution. However, natural age-associated thymic involution starts from approx. 4 weeks. Therefore, the authors’ claim regarding the optimality of their use of 5 weeks old mice for thymic involution experiments does not make much sense. In that case, they need to substantiate their claim by treating 0-2 weeks old pups with IMQ and check its effects on thymic involution. Nevertheless, I believe simply rephrasing their claim might be enough to avoid the confusion.

This is an important point that we apologize for overlooking.

The mouse thymus involution indeed starts at 4 weeks of age. The most rapid decline in the mouse thymus starts after puberty and has a more rapid onset in males than females. In an experimental setting, stress has a far bigger impact on the thymus size at this time why precautions were taken to minimize stressors in the animal facility. We have reworked the text according to the reviewer’s suggestion, please see rows 246-251 which now reads:

“Female C57BL/6NCrl mice (Charles River, MA, USA) arrived at AstraZeneca at an age of 5 weeks +/- 2 days and were organized into groups and acclimatized for one week in order to reduce stress and variability of thymus weight. The mice in the experiment were intentionally young to reduce the impact of the normal process of thymic involution that starts at 4 weeks as this introduces further variability with regards to thymus size and cellularity. Additionally, age-related thymic involution is at its largest post puberty and less pronounced in females [34].”

And rows 689-695

“Furthermore, the already occurring natural thymic involution would introduce further variability in thymus size in the adult animals needed in the IMQ experiment, both for the immune system to be fully matured and to minimize variability from growth related differences in size and thickness of ear pinnas and cell numbers. This limitation did not apply to the experiments studying thymus effects as the animals were intentionally young to minimize effects from early thymic involution.”

Attachment

Submitted filename: Response to reviewers.docx

pone.0317090.s008.docx^{(45.6KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0317090.r005

Decision Letter 2

Subhasis Barik

22 Dec 2024

RORγt inverse agonists demonstrating a margin between inhibition of IL-17A and thymocyte apoptosis

PONE-D-24-01191R2

Dear Dr. Collins,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Subhasis Barik

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: (No Response)

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: The authors have incorporated all the suggestions in the manuscript and have satisfactorily addressed all the comments.

Reviewer #2: My comments have been addressed. I do not have any more queries or comments regarding this manuscript.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

PLoS One. doi: 10.1371/journal.pone.0317090.r006

Acceptance letter

Subhasis Barik

6 Jan 2025

PONE-D-24-01191R2

PLOS ONE

Dear Dr. Collins,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Subhasis Barik

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. Flow cytometric gating strategy from ear tissue.

Single cells were selected followed by CD45+ live cells, TCRγδ intermediate TCRβ negative cells, further selected on CD3 and IL-17A using a histogram.

(TIF)

pone.0317090.s001.tif^{(186.3KB, tif)}

S2 Fig. Compound structures.

(TIF)

pone.0317090.s002.tif^{(358.3KB, tif)}

S3 Fig. Representative data of cell toxicity as measured by terminal ATP levels in the primary human Th17 cell assay.

(TIF)

pone.0317090.s003.tif^{(224.6KB, tif)}

S4 Fig. Exposure prediction and terminal concentrations in the IMQ model.

Exposure prediction (line) and terminal concentrations (dots) in eight mice treated with compound 3 following 7 days twice-daily oral dosing with 50 mg/kg in the IMQ-induced skin inflammation model.

(TIF)

pone.0317090.s004.tif^{(50.7KB, tif)}

S5 Fig. Flowcytometric parameters and ear thickness from the IMQ model.

(TIF)

pone.0317090.s005.tif^{(275.9KB, tif)}

S1 File. Raw data.

(XLSX)

pone.0317090.s006.xlsx^{(88.9KB, xlsx)}

Attachment

Submitted filename: Response to reviewers.docx

pone.0317090.s007.docx^{(47.6KB, docx)}

Attachment

Submitted filename: Response to reviewers.docx

pone.0317090.s008.docx^{(45.6KB, docx)}

Data Availability Statement

All relevant data are within the manuscript and its Supporting Information files.

[pone.0317090.ref001] 1.Cua DJ, Sherlock J, Chen Y, Murphy CA, Joyce B, Seymour B, et al. Interleukin-23 rather than interleukin-12 is the critical cytokine for autoimmune inflammation of the brain. Nature. 2003;421(6924):744–8. doi: 10.1038/nature01355 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref002] 2.Langrish CL, Chen Y, Blumenschein WM, Mattson J, Basham B, Sedgwick JD, et al. IL-23 drives a pathogenic T cell population that induces autoimmune inflammation. J Exp Med. 2005;201(2):233–40. doi: 10.1084/jem.20041257 ; PubMed Central PMCID: PMC2212798. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref003] 3.Rosain J, Kong XF, Martinez-Barricarte R, Oleaga-Quintas C, Ramirez-Alejo N, Markle J, et al. Mendelian susceptibility to mycobacterial disease: 2014–2018 update. Immunol Cell Biol. 2018. doi: 10.1111/imcb.12210 ; PubMed Central PMCID: PMC6438774. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref004] 4.Veldhoen M, Hocking RJ, Atkins CJ, Locksley RM, Stockinger B. TGFbeta in the context of an inflammatory cytokine milieu supports de novo differentiation of IL-17-producing T cells. Immunity. 2006;24(2):179–89. doi: 10.1016/j.immuni.2006.01.001 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref005] 5.Gaffen SL, Jain R, Garg AV, Cua DJ. The IL-23-IL-17 immune axis: from mechanisms to therapeutic testing. Nat Rev Immunol. 2014;14(9):585–600. doi: 10.1038/nri3707 ; PubMed Central PMCID: PMC4281037. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref006] 6.Shelton SK, Bai SR, Jordan JK, Sheehan AH. Ixekizumab: A Review of Its Use for the Management of Moderate to Severe Plaque Psoriasis. Ann Pharmacother. 2018:1060028018799982. doi: 10.1177/1060028018799982 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref007] 7.Yiu ZZ, Warren RB. Guselkumab for psoriasis: a critical appraisal of Phase III studies. Immunotherapy. 2018;10(1):67–75. Epub 20171018. doi: 10.2217/imt-2017-0106 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref008] 8.Rendon A, Schakel K. Psoriasis Pathogenesis and Treatment. Int J Mol Sci. 2019;20(6). Epub 20190323. doi: 10.3390/ijms20061475 ; PubMed Central PMCID: PMC6471628. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref009] 9.Naik GS, Ming WK, Magodoro IM, Akinwunmi B, Dar S, Poulsen HE, et al. Th17 Inhibitors in Active Psoriatic Arthritis: A Systematic Review and Meta-Analysis of Randomized Controlled Clinical Trials. Dermatology. 2017;233(5):366–77. Epub 20171220. doi: 10.1159/000484520 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref010] 10.Frieder J, Kivelevitch D, Haugh I, Watson I, Menter A. Anti-IL-23 and Anti-IL-17 Biologic Agents for the Treatment of Immune-Mediated Inflammatory Conditions. Clin Pharmacol Ther. 2018;103(1):88–101. Epub 20171019. doi: 10.1002/cpt.893 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref011] 11.Ivanov II, McKenzie BS, Zhou L, Tadokoro CE, Lepelley A, Lafaille JJ, et al. The orphan nuclear receptor RORgammat directs the differentiation program of proinflammatory IL-17+ T helper cells. Cell. 2006;126(6):1121–33. doi: 10.1016/j.cell.2006.07.035 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref012] 12.Zuniga LA, Jain R, Haines C, Cua DJ. Th17 cell development: from the cradle to the grave. Immunol Rev. 2013;252(1):78–88. doi: 10.1111/imr.12036 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref013] 13.Burgler S, Mantel PY, Bassin C, Ouaked N, Akdis CA, Schmidt-Weber CB. RORC2 is involved in T cell polarization through interaction with the FOXP3 promoter. J Immunol. 2010;184(11):6161–9. Epub 20100428. doi: 10.4049/jimmunol.0903243 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref014] 14.Xi H, Schwartz R, Engel I, Murre C, Kersh GJ. Interplay between RORgammat, Egr3, and E proteins controls proliferation in response to pre-TCR signals. Immunity. 2006;24(6):813–26. Epub 2006/06/20. doi: 10.1016/j.immuni.2006.03.023 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref015] 15.Naik AK, Dauphars DJ, Corbett E, Simpson L, Schatz DG, Krangel MS. RORγt up-regulates RAG gene expression in DP thymocytes to expand the Tcra repertoire. Sci Immunol. 2024;9(93):eadh5318. Epub 20240315. doi: 10.1126/sciimmunol.adh5318 ; PubMed Central PMCID: PMC11005092. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref016] 16.Kurebayashi S, Ueda E, Sakaue M, Patel DD, Medvedev A, Zhang F, et al. Retinoid-related orphan receptor gamma (RORgamma) is essential for lymphoid organogenesis and controls apoptosis during thymopoiesis. Proc Natl Acad Sci U S A. 2000;97(18):10132–7. doi: 10.1073/pnas.97.18.10132 ; PubMed Central PMCID: PMC27750. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref017] 17.Sun Z, Unutmaz D, Zou YR, Sunshine MJ, Pierani A, Brenner-Morton S, et al. Requirement for RORgamma in thymocyte survival and lymphoid organ development. Science. 2000;288(5475):2369–73. doi: 10.1126/science.288.5475.2369 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref018] 18.Ashby KM, Hogquist KA. A guide to thymic selection of T cells. Nature Reviews Immunology. 2023;24(2):103–17. doi: 10.1038/s41577-023-00911-8 [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref019] 19.Ueda E, Kurebayashi S, Sakaue M, Backlund M, Koller B, Jetten AM. High incidence of T-cell lymphomas in mice deficient in the retinoid-related orphan receptor RORgamma. Cancer Res. 2002;62(3):901–9. . [PubMed] [Google Scholar]

[pone.0317090.ref020] 20.Okada S, Markle JG, Deenick EK, Mele F, Averbuch D, Lagos M, et al. IMMUNODEFICIENCIES. Impairment of immunity to Candida and Mycobacterium in humans with bi-allelic RORC mutations. Science. 2015;349(6248):606–13. Epub 2015/07/15. doi: 10.1126/science.aaa4282 ; PubMed Central PMCID: PMC4668938. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref021] 21.Taghon T, Van de Walle I, De Smet G, De Smedt M, Leclercq G, Vandekerckhove B, et al. Notch signaling is required for proliferation but not for differentiation at a well-defined beta-selection checkpoint during human T-cell development. Blood. 2009;113(14):3254–63. Epub 20081023. doi: 10.1182/blood-2008-07-168906 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref022] 22.Zhong X, Wu H, Zhang W, Gwack Y, Shang W, Lee KO, et al. Decoupling the role of RORgammat in the differentiation and effector function of T(H)17 cells. Sci Adv. 2022;8(42):eadc9221. Epub 20221021. doi: 10.1126/sciadv.adc9221 ; PubMed Central PMCID: PMC9586477. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref023] 23.Jetten AM. Retinoid-related orphan receptors (RORs): critical roles in development, immunity, circadian rhythm, and cellular metabolism. Nucl Recept Signal. 2009;7:e003. Epub 20090403. doi: 10.1621/nrs.07003 ; PubMed Central PMCID: PMC2670432. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref024] 24.Ruan Q, Kameswaran V, Zhang Y, Zheng S, Sun J, Wang J, et al. The Th17 immune response is controlled by the Rel-RORgamma-RORgamma T transcriptional axis. J Exp Med. 2011;208(11):2321–33. Epub 20111017. doi: 10.1084/jem.20110462 ; PubMed Central PMCID: PMC3201209. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref025] 25.Ruiz de Morales JMG, Puig L, Dauden E, Canete JD, Pablos JL, Martin AO, et al. Critical role of interleukin (IL)-17 in inflammatory and immune disorders: An updated review of the evidence focusing in controversies. Autoimmun Rev. 2020;19(1):102429. Epub 20191115. doi: 10.1016/j.autrev.2019.102429 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref026] 26.Cai Y, Shen X, Ding C, Qi C, Li K, Li X, et al. Pivotal role of dermal IL-17-producing gammadelta T cells in skin inflammation. Immunity. 2011;35(4):596–610. Epub 20111006. doi: 10.1016/j.immuni.2011.08.001 ; PubMed Central PMCID: PMC3205267. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref027] 27.van der Fits L, Mourits S, Voerman JS, Kant M, Boon L, Laman JD, et al. Imiquimod-induced psoriasis-like skin inflammation in mice is mediated via the IL-23/IL-17 axis. J Immunol. 2009;182(9):5836–45. Epub 2009/04/22. doi: 10.4049/jimmunol.0802999 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref028] 28.Pantelyushin S, Haak S, Ingold B, Kulig P, Heppner FL, Navarini AA, et al. Rorgammat+ innate lymphocytes and gammadelta T cells initiate psoriasiform plaque formation in mice. J Clin Invest. 2012;122(6):2252–6. Epub 20120501. doi: 10.1172/JCI61862 ; PubMed Central PMCID: PMC3366412. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref029] 29.Zeng J, Li M, Zhao Q, Chen M, Zhao L, Wei S, et al. Small molecule inhibitors of RORγt for Th17 regulation in inflammatory and autoimmune diseases. Journal of Pharmaceutical Analysis. 2023;13(6):545–62. doi: 10.1016/j.jpha.2023.05.009 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref030] 30.Gege C. Retinoic acid-related orphan receptor gamma t (RORγt) inverse agonists/antagonists for the treatment of inflammatory diseases—where are we presently? Expert Opin Drug Discov. 2021;16(12):1517–35. Epub 20210707. doi: 10.1080/17460441.2021.1948833 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref031] 31.Narjes F, Xue Y, von Berg S, Malmberg J, Llinas A, Olsson RI, et al. Potent and Orally Bioavailable Inverse Agonists of RORgammat Resulting from Structure-Based Design. J Med Chem. 2018;61(17):7796–813. Epub 20180827. doi: 10.1021/acs.jmedchem.8b00783 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref032] 32.von Berg S, Xue Y, Collins M, Llinas A, Olsson RI, Halvarsson T, et al. Discovery of Potent and Orally Bioavailable Inverse Agonists of the Retinoic Acid Receptor-Related Orphan Receptor C2. ACS Med Chem Lett. 2019;10(6):972–7. Epub 20190529. doi: 10.1021/acsmedchemlett.9b00158 ; PubMed Central PMCID: PMC6580541. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref033] 33.Narjes F, Llinas A, von Berg S, Jirholt J, Lever S, Pehrson R, et al. AZD0284, a Potent, Selective, and Orally Bioavailable Inverse Agonist of Retinoic Acid Receptor-Related Orphan Receptor C2. J Med Chem. 2021;64(18):13807–29. Epub 20210831. doi: 10.1021/acs.jmedchem.1c01197 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref034] 34.Liang Z, Dong X, Zhang Z, Zhang Q, Zhao Y. Age-related thymic involution: Mechanisms and functional impact. Aging Cell. 2022;21(8):e13671. Epub 20220712. doi: 10.1111/acel.13671 ; PubMed Central PMCID: PMC9381902. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref035] 35.Huh JR, Englund EE, Wang H, Huang R, Huang P, Rastinejad F, et al. Identification of Potent and Selective Diphenylpropanamide RORgamma Inhibitors. ACS Med Chem Lett. 2013;4(1):79–84. doi: 10.1021/ml300286h ; PubMed Central PMCID: PMC3770298. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref036] 36.Littman D. JRH, Huang R., Huang W., Englund E.E., inventorAMIDO COMPOUNDS AS RORyt MODULATORS AND USES THEREOF2011. [Google Scholar]

[pone.0317090.ref037] 37.Erichsen CY, Jensen P, Kofoed K. Biologic therapies targeting the interleukin (IL)-23/IL-17 immune axis for the treatment of moderate-to-severe plaque psoriasis: a systematic review and meta-analysis. J Eur Acad Dermatol Venereol. 2020;34(1):30–8. Epub 20190904. doi: 10.1111/jdv.15879 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref038] 38.Sieper J, Poddubnyy D, Miossec P. The IL-23-IL-17 pathway as a therapeutic target in axial spondyloarthritis. Nat Rev Rheumatol. 2019;15(12):747–57. Epub 20190924. doi: 10.1038/s41584-019-0294-7 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref039] 39.Mills KHG. IL-17 and IL-17-producing cells in protection versus pathology. Nature Reviews Immunology. 2023;23(1):38–54. doi: 10.1038/s41577-022-00746-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref040] 40.Loft ND, Vaengebjerg S, Halling AS, Skov L, Egeberg A. Adverse events with IL-17 and IL-23 inhibitors for psoriasis and psoriatic arthritis: a systematic review and meta-analysis of phase III studies. J Eur Acad Dermatol Venereol. 2019. Epub 2019/11/14. doi: 10.1111/jdv.16073 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref041] 41.Liljevald M, Rehnberg M, Soderberg M, Ramnegard M, Borjesson J, Luciani D, et al. Retinoid-related orphan receptor gamma (RORgamma) adult induced knockout mice develop lymphoblastic lymphoma. Autoimmun Rev. 2016;15(11):1062–70. Epub 20160802. doi: 10.1016/j.autrev.2016.07.036 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref042] 42.Haggerty HG, Sathish JG, Gleason CR, Al-Haddawi M, Brodie TA, Bonnette KL, et al. Thymic Lymphomas in a 6-Month rasH2-Tg Mouse Carcinogenicity Study With the RORγt Inverse Agonist, BMS-986251. Toxicol Sci. 2021;183(1):93–104. doi: 10.1093/toxsci/kfab086 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref043] 43.Mukherjee S, Kar A, Paul P, Dey S, Biswas A, Barik S. In Silico Integration of Transcriptome and Interactome Predicts an ETP-ALL-Specific Transcriptional Footprint that Decodes its Developmental Propensity. Front Cell Dev Biol. 2022;10:899752. Epub 20220513. doi: 10.3389/fcell.2022.899752 ; PubMed Central PMCID: PMC9138408. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref044] 44.Spidale NA, Sylvia K, Narayan K, Miu B, Frascoli M, Melichar HJ, et al. Interleukin-17-Producing gammadelta T Cells Originate from SOX13(+) Progenitors that Are Independent of gammadeltaTCR Signaling. Immunity. 2018;49(5):857–72 e5. Epub 20181106. doi: 10.1016/j.immuni.2018.09.010 ; PubMed Central PMCID: PMC6249057. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref045] 45.Guendisch U, Weiss J, Ecoeur F, Riker JC, Kaupmann K, Kallen J, et al. Pharmacological inhibition of RORgammat suppresses the Th17 pathway and alleviates arthritis in vivo. PLoS One. 2017;12(11):e0188391. Epub 2017/11/21. doi: 10.1371/journal.pone.0188391 ; PubMed Central PMCID: PMC5695821. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref046] 46.Xue X, Soroosh P, De Leon-Tabaldo A, Luna-Roman R, Sablad M, Rozenkrants N, et al. Pharmacologic modulation of RORgammat translates to efficacy in preclinical and translational models of psoriasis and inflammatory arthritis. Sci Rep. 2016;6:37977. Epub 2016/12/03. doi: 10.1038/srep37977 ; PubMed Central PMCID: PMC5131364. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref047] 47.Skepner J, Ramesh R, Trocha M, Schmidt D, Baloglu E, Lobera M, et al. Pharmacologic inhibition of RORgammat regulates Th17 signature gene expression and suppresses cutaneous inflammation in vivo. J Immunol. 2014;192(6):2564–75. Epub 2014/02/12. doi: 10.4049/jimmunol.1302190 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref048] 48.Schnute ME, Wennerstal M, Alley J, Bengtsson M, Blinn JR, Bolten CW, et al. Discovery of 3-Cyano- N-(3-(1-isobutyrylpiperidin-4-yl)-1-methyl-4-(trifluoromethyl)-1 H-pyrrolo[2,3- b]pyridin-5-yl)benzamide: A Potent, Selective, and Orally Bioavailable Retinoic Acid Receptor-Related Orphan Receptor C2 Inverse Agonist. J Med Chem. 2018;61(23):10415–39. Epub 2018/08/22. doi: 10.1021/acs.jmedchem.8b00392 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref049] 49.Gangwar RS, Gudjonsson JE, Ward NL. Mouse Models of Psoriasis: A Comprehensive Review. J Invest Dermatol. 2022;142(3 Pt B):884–97. Epub 20211223. doi: 10.1016/j.jid.2021.06.019 ; PubMed Central PMCID: PMC10190156. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref050] 50.Hawkes JE, Chan TC, Krueger JG. Psoriasis pathogenesis and the development of novel targeted immune therapies. J Allergy Clin Immunol. 2017;140(3):645–53. doi: 10.1016/j.jaci.2017.07.004 ; PubMed Central PMCID: PMC5600287. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref051] 51.Banerjee D, Zhao L, Wu L, Palanichamy A, Ergun A, Peng L, et al. Small molecule mediated inhibition of RORgamma-dependent gene expression and autoimmune disease pathology in vivo. Immunology. 2016;147(4):399–413. Epub 20160126. doi: 10.1111/imm.12570 ; PubMed Central PMCID: PMC4799885. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref052] 52.Shimizu T, Kamata M, Fukaya S, Hayashi K, Fukuyasu A, Tanaka T, et al. Anti-IL-17A and IL-23p19 antibodies but not anti-TNFalpha antibody induce expansion of regulatory T cells and restoration of their suppressive function in imiquimod-induced psoriasiform dermatitis. J Dermatol Sci. 2019;95(3):90–8. Epub 20190723. doi: 10.1016/j.jdermsci.2019.07.006 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref053] 53.Zeng J, Li M, Zhao Q, Chen M, Zhao L, Wei S, et al. Small molecule inhibitors of RORgammat for Th17 regulation in inflammatory and autoimmune diseases. J Pharm Anal. 2023;13(6):545–62. Epub 20230520. doi: 10.1016/j.jpha.2023.05.009 ; PubMed Central PMCID: PMC10334362. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref054] 54.Guntermann C, Piaia A, Hamel ML, Theil D, Rubic-Schneider T, Del Rio-Espinola A, et al. Retinoic-acid-orphan-receptor-C inhibition suppresses Th17 cells and induces thymic aberrations. JCI Insight. 2017;2(5):e91127. Epub 20170309. doi: 10.1172/jci.insight.91127 ; PubMed Central PMCID: PMC5333964. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref055] 55.Guo Y, MacIsaac KD, Chen Y, Miller RJ, Jain R, Joyce-Shaikh B, et al. Inhibition of RORgammaT Skews TCRalpha Gene Rearrangement and Limits T Cell Repertoire Diversity. Cell Rep. 2016;17(12):3206–18. doi: 10.1016/j.celrep.2016.11.073 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref056] 56.He Z, Zhang J, Du Q, Xu J, Gwack Y, Sun Z. SRC3 Is a Cofactor for RORgammat in Th17 Differentiation but Not Thymocyte Development. J Immunol. 2019;202(3):760–9. Epub 20181219. doi: 10.4049/jimmunol.1801187 ; PubMed Central PMCID: PMC6344289. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref057] 57.He Z, Ma J, Wang R, Zhang J, Huang Z, Wang F, et al. A two-amino-acid substitution in the transcription factor RORgammat disrupts its function in T(H)17 differentiation but not in thymocyte development. Nat Immunol. 2017;18(10):1128–38. Epub 20170828. doi: 10.1038/ni.3832 ; PubMed Central PMCID: PMC5678981. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref058] 58.Strutzenberg TS, Zhu Y, Novick SJ, Garcia-Ordonez RD, Doebelin C, He Y, et al. Conformational Changes of RORγ During Response Element Recognition and Coregulator Engagement. Journal of Molecular Biology. 2021;433(22):167258. 10.1016/j.jmb.2021.167258. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref059] 59.Polasek TM, Leelasena I, Betscheider I, Marolt M, Kohlhof H, Vitt D, et al. Safety, Tolerability, and Pharmacokinetics of IMU-935, a Novel Inverse Agonist of Retinoic Acid Receptor-Related Orphan Nuclear Receptor gammat: Results From a Double-Blind, Placebo-Controlled, First-in-Human Phase 1 Study. Clin Pharmacol Drug Dev. 2023;12(5):525–34. Epub 20230320. doi: 10.1002/cpdd.1243 . [DOI] [PubMed] [Google Scholar]

[pone.0317090.ref060] 60.Therapeutics I. Maintenance Phase of Phase 2 CALDOSE-1 Trial of Vidofludimus Calcium in Moderate-to-Severe Ulcerative Colitis 2023. Available from: https://ir.imux.com/2023-04-05-Immunic-Reports-Positive-Data-from-Maintenance-Phase-of-Phase-2-CALDOSE-1-Trial-of-Vidofludimus-Calcium-in-Moderate-to-Severe-Ulcerative-Colitis. [Google Scholar]

[pone.0317090.ref061] 61.de Meis J, Aurelio Farias-de-Oliveira D, Nunes Panzenhagen PH, Maran N, Villa-Verde DM, Morrot A, et al. Thymus atrophy and double-positive escape are common features in infectious diseases. J Parasitol Res. 2012;2012:574020. Epub 20120201. doi: 10.1155/2012/574020 ; PubMed Central PMCID: PMC3307005. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0317090.ref062] 62.Demoulins T, Abdallah A, Kettaf N, Baron ML, Gerarduzzi C, Gauchat D, et al. Reversible blockade of thymic output: an inherent part of TLR ligand-mediated immune response. J Immunol. 2008;181(10):6757–69. doi: 10.4049/jimmunol.181.10.6757 . [DOI] [PubMed] [Google Scholar]

PERMALINK

RORγt inverse agonists demonstrating a margin between inhibition of IL-17A and thymocyte apoptosis

Mia Collins

Rikard Pehrson

Hanna Grindebacke

Agnes Leffler

Marie Ramnegård

Helena Rannikmäe

Nina Krutrök

Linda Yrlid

Charlotte Pollard

Ian Dainty

Frank Narjes

Stefan von Berg

Antonio Llinas

Anna Malmberg

Jane McPheat

Eva Hansson

Elisabeth Bäck

Jenny Bernström

Thomas G Hansson

David Keeling

Johan Jirholt

Roles

Abstract

Introduction

Material and methods

Screening assays

Human RORγt radioligand competition binding assay

Murine RORγt radioligand competition binding assay

Human RORβ radioligand competition binding assay

RORγt co-factor recruitment assay

RORα co-factor recruitment assay

Biological assays

Primary human Th17 cell assay

Mouse thymocyte apoptosis assay ex vivo

Thymus involution in vivo

IMQ induced skin inflammation in vivo

Cell preparations from tissues

Preparation for flow cytometric analysis

Analysis parameters

Statistical evaluation

Pharmacokinetics and pharmacodynamics

In vivo

Ethics statement

Results

Binding assays

Table 1. Overview of compound potencies in multiple assays.

Co-factor modulation assay

Compound selectivity

Biological effects

Inhibition of IL-17A release from human Th17 cells

Fig 1. Dose response curves for human and mouse ligand binding and functional assays.

Evaluation of thymocyte apoptosis

Target engagement through thymus involution in vivo

Fig 2. Thymocyte numbers and exposure predictions and measurements after compound treatment in the thymus involution model.

Evaluation of systemic anti-inflammatory effects on psoriasis like skin inflammation in vivo

Fig 3. Reduction of IL-17A and inflammatory readouts in the ear of IMQ treated mice after treatment with compound 3.

Inter-assay comparison

Fig 4. Correlation of screening assays with functional readouts show separation of IL-17A and thymocyte apoptosis effects.

Discussion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Subhasis Barik

Roles

Author response to Decision Letter 0

Decision Letter 1

Subhasis Barik

Roles

Author response to Decision Letter 1

Decision Letter 2

Subhasis Barik

Roles

Acceptance letter

Subhasis Barik

Roles