| Literature DB >> 34803999 |
Garth E Ringheim1, Matthew Wampole2, Kinsi Oberoi2.
Abstract
Clinical development of BTK kinase inhibitors for treating autoimmune diseases has lagged behind development of these drugs for treating cancers, due in part from concerns over the lack of selectivity and associated toxicity profiles of first generation drug candidates when used in the long term treatment of immune mediated diseases. Second generation BTK inhibitors have made great strides in limiting off-target activities for distantly related kinases, though they have had variable success at limiting cross-reactivity within the more closely related TEC family of kinases. We investigated the BTK specificity and toxicity profiles, drug properties, disease associated signaling pathways, clinical indications, and trial successes and failures for the 13 BTK inhibitor drug candidates tested in phase 2 or higher clinical trials representing 7 autoimmune and 2 inflammatory immune-mediated diseases. We focused on rheumatoid arthritis (RA), multiple sclerosis (MS), and systemic lupus erythematosus (SLE) where the majority of BTK nonclinical and clinical studies have been reported, with additional information for pemphigus vulgaris (PV), Sjogren's disease (SJ), chronic spontaneous urticaria (CSU), graft versus host disease (GVHD), and asthma included where available. While improved BTK selectivity versus kinases outside the TEC family improved clinical toxicity profiles, less profile distinction was evident within the TEC family. Analysis of genetic associations of RA, MS, and SLE biomarkers with TEC family members revealed that BTK and TEC family members may not be drivers of disease. They are, however, mediators of signaling pathways associated with the pathophysiology of autoimmune diseases. BTK in particular may be associated with B cell and myeloid differentiation as well as autoantibody development implicated in immune mediated diseases. Successes in the clinic for treating RA, MS, PV, ITP, and GVHD, but not for SLE and SJ support the concept that BTK plays an important role in mediating pathogenic processes amenable to therapeutic intervention, depending on the disease. Based on the data collected in this study, we propose that current compound characteristics of BTK inhibitor drug candidates for the treatment of autoimmune diseases have achieved the selectivity, safety, and coverage requirements necessary to deliver therapeutic benefit.Entities:
Keywords: B cell; Bruton’s tyrosine kinase (BTK); Sjogren’s syndrome; autoimmune disease; multiple sclerosis; pemphigus vulgaris; rheumatoid arthritis; systemic lupus erythematosus
Mesh:
Substances:
Year: 2021 PMID: 34803999 PMCID: PMC8595937 DOI: 10.3389/fimmu.2021.662223
Source DB: PubMed Journal: Front Immunol ISSN: 1664-3224 Impact factor: 7.561
Clinical BTK inhibitors in phase 2 or higher clinical trials. BTK inhibitors are listed by registered names if available.
| Drug | Covalent | RA | SLE | MS | SJ | PV | CSU | ITP | GVHD | Asthma | Trial No./Indication/Status/Trial length |
|---|---|---|---|---|---|---|---|---|---|---|---|
| BMS-986142 | N | 2(-) | NCT02638948/RA/completed/12 wks | ||||||||
| 2 | NCT02843659/SJ/terminated/12 wks | ||||||||||
| Branebrutinib | Y | 2 | NCT04186871/RA/ongoing/12 wks | ||||||||
| 2 | NCT04186871/SLE/ongoing/24 wks | ||||||||||
| 2(-) | NCT04186871/SJ/ongoing/24 wks | ||||||||||
| Acalabrutinib | Y | 2 | NCT02387762/RA/completed/4 wks | ||||||||
| Elsubrutinib | Y | 2 | NCT03682705/RA/completed/12 wks | ||||||||
| 2 | NCT03978520/SLE/recruiting/24 wks | ||||||||||
| Evobrutinib | Y | 2(-) | NCT02784106/RA/completed/12 wks | ||||||||
| 2(-) | NCT02975336/SLE/completed/52 wks | ||||||||||
| 2(+) 3 | NCT02975349/MS/ongoing/48 wks | ||||||||||
| Fenebrutinib | N | 2(+) | NCT03233230/RA/completed/12 wks | ||||||||
| 2(-) | NCT02908100/SLE/completed/48 wks | ||||||||||
| 2 | NCT04586023/MS/ongoing/96 wks | ||||||||||
| 2(-) | NCT03693625/CSU/terminated/24 wks | ||||||||||
| Ibrutinib | Y | (+) | Approved. Multiple ongoing expansion trials | ||||||||
| Poseltinib | Y | 2(-) | NCT02628028/RA/terminated/4 wks (part A) | ||||||||
| Remibrutinib | Y | 2 | NCT04035668: SJ/ongoing/24 wks | ||||||||
| 2 | NCT03926611/CSU/ongoing/16 wks | ||||||||||
| 2(-) | NCT03944707/Asthma/terminated/12 wks | ||||||||||
| Rilzabrutinib | Y | 2(+) 3(-) | NCT02704429/PV/completed/24 wks | ||||||||
| 2(+) 3 | NCT04562766/ITP/ongoing/24 wks | ||||||||||
| Spebrutinib | Y | 2(-) | NCT01975610/RA/completed/4 wks | ||||||||
| Tirabrutinib | Y | 1 | NCT02626026/RA/completed/4 wks | ||||||||
| 2(-) | NCT03100942/Sj/completed/24 wks | ||||||||||
| Tolebrutinib | Y | 2(+) | NCT03889639/MS/completed/16 wks | ||||||||
| 3 | NCT04410978/MS/ongoing/36 months |
Indications being tested for each BTK inhibitor have the associated phase status number and positive (+) or negative (-) results indicated if reported. The assigned clinical trial number/indication/trial status/and length of trial is referenced for each indication. If more than one trial exists for a specific BTK inhibitor in an indication, only the clinical trial supporting the main efficacy of the BTK inhibitor is listed. N, no; Y, yes; Covalent, BTK inhibitor forms a covalent bond with BTK; RA, rheumatoid arthritis; SLE, systemic lupus erythematosus; MS, multiple sclerosis; SJ, Sjogren’s disease; PV, pemphigus vulgaris; CSU, chronic spontaneous urticaria; ITP, idiopathic thrombocytopenic purpura; GVHD, graft versus host disease.
BTK inhibitors tested in preclinical animal disease models. BTK inhibitors tested in animal models of disease are listed if they have been reported.
| BTK Inhibitor | Other Names | RA Models | SLE Models | MS Model | ITP Model | References |
|---|---|---|---|---|---|---|
| BMS-986142 | BMS-986142 | CIA mouse CAIA mouse | NZB/W | ( | ||
| Branebrutinib | BMS-986195 | CIA mouse CAIA mouse | NZB/W | ( | ||
| Acalabrutinib | calquence ACP-196 | CIA mouse | MRL/lpr | ( | ||
| Elsubrutinib | ABBV-105 | CIA rat | NZB/W MRL/lpr | ( | ||
| Evobrutinib | M2951 | CIA mouse CIA rat | IFN-alpha NZB/W | MOG EAE | ( | |
| MSC-2364447 | ||||||
| Fenebrutinib | GDC-0853 RG7845 | CIA rat | PLP EAE | ( | ||
| Ibrutinib | imbruvica, PCI-32765 | CIA mouse CIA rat | MRL/lpr B6.Sle1 B6.Sle1.Sle3 | ( | ||
| Poseltinib | LLY-333764 | CIA mouse | NZB/W MRL/lpr | ( | ||
| HM-71224 | ||||||
| Remibrutinib | LOU064 | CIA rat | ( | |||
| Rilzabrutinib | PRN1008 | CIA mouse CIA rat | Mouse anti-CD41 | ( | ||
| Spebrutinib | CC-292 | CIA mouse | NZB/W MRL/lpr | ( | ||
| AVL-292 | ||||||
| Tirabrutinib | GSK-4059 ONO-4059 | CIA mouse CIA rat sRANKL | NZBWF1 | ( | ||
| Tolebrutinib | SAR442168 PRN2246 | MOG EAE | ( |
If more than one type of model was performed it was listed only if a different animal strain, species, or major mechanism of action was employed. CIA, collagen induced arthritis; CAIA, collagen antibody induced arthritis; sRANKL, soluble receptor activator for nuclear factor κB ligand; MOG EAE, myelin oligodendrocyte glycoprotein experimental autoimmune encephalomyelitis; PLP EAE, proteolipoprotein experimental autoimmune encephalomyelitis; IFN-alpha, interferon-alpha. Remaining abbreviations refer to animal strains used.
Pathway map enrichment with disease biomarkers.
| Pathway Map Name | BTK | TEC | ITK | BMX | TXK | JAK3 | EGFR | SLE | RA | MS | SJ |
|---|---|---|---|---|---|---|---|---|---|---|---|
| p-value | p-value | p-value | p-value | ||||||||
| Chemotaxis_CXCL12/CXCR4-induced chemotaxis of immune cells | 8.28E-08 | 2.44E-05 | 3.01E-03 | 2.41E-03 | |||||||
| Role of tumor-infiltrating B cells in anti-tumor immunity | 3.33E-25 | 4.25E-21 | 1.55E-16 | 7.66E-29 | |||||||
| Immune response_NF-AT in immune response | 5.40E-12 | 3.25E-07 | 1.34E-03 | 3.95E-03 | |||||||
| Immune response_IL-6 signaling pathway | 2.24E-08 | 1.16E-07 | 5.01E-04 | 3.42E-04 | |||||||
| Immune response_PIP3 signaling in B lymphocytes | 1.42E-02 | 3.68E-02 | NA | NA | |||||||
| Role of B cells in SLE | 1.39E-28 | 9.93E-30 | 2.17E-18 | 2.97E-26 | |||||||
| SLE genetic marker-specific pathways in B cells | 2.51E-24 | 2.66E-14 | 4.12E-11 | 6.54E-10 | |||||||
| B cell signaling in hematological malignancies | 1.55E-18 | 1.64E-13 | 8.03E-07 | 1.15E-08 | |||||||
| Immune response_Fc epsilon RI pathway: Lyn-mediated cytokine production | 4.65E-18 | 2.04E-09 | 5.00E-05 | 3.77E-08 | |||||||
| IgE- and MGF-induced Lyn-mediated production of cytokines and arachidonic acid metabolites in lung mast cells in asthma | 1.47E-17 | 5.94E-09 | 8.95E-06 | 1.05E-04 | |||||||
| Immune response_IL-5 signaling | 5.41E-12 | 9.14E-12 | 1.71E-04 | 4.18E-04 | |||||||
| Immune response_B cell antigen receptor (BCR) pathway | 1.37E-10 | 6.13E-06 | NA | 1.06E-04 | |||||||
| Immune response_BAFF-induced canonical NF-κB signaling | 3.88E-07 | 1.46E-08 | 1.73E-03 | 3.98E-07 | |||||||
| Cell adhesion_Integrin inside-out signaling in neutrophils | 1.83E-05 | 5.68E-05 | 2.45E-03 | 4.61E-04 | |||||||
| Immune response_TLR3 and TLR4 induced TICAM1-specific signaling pathway | 2.31E-05 | 4.89E-07 | 2.92E-02 | 4.38E-05 | |||||||
| Proinflammatory mediators release and arachidonic acid metabolites production in basophils in asthma | 1.21E-03 | 4.03E-05 | 1.02E-02 | 2.72E-02 | |||||||
| Blood coagulation_GPVI-dependent platelet activation | 2.53E-03 | 3.35E-03 | NA | NA | |||||||
| G-protein signaling_G-Protein alpha-q signaling cascades | 3.78E-03 | 3.38E-02 | NA | NA | |||||||
| Production of reactive oxygen species and arachidonic acid metabolites by neutrophils in asthma | 1.50E-02 | 1.19E-03 | 9.73E-03 | 1.58E-02 |
Enrichment results generated using pathway map enrichment analysis in MetaCore. Left side shows the presence of the target/off-target on the map and the right corner shows the p-value for the biomarker list colored as: Highly significant in red, mid value in yellow and low significance in green.
Figure 1“Chemotaxis_CXCL12/CXCR4-induced chemotaxis of immune cells”. Illustration generated with MetaCore pathway analysis tool indicating the involvement of BTK and disease biomarkers to induce chemotactic response in immune cells leading to cell adhesion and cell migration. Data overlaid onto the pathway map are represented as thermometers which typically would indicate the level of over/under expression of a gene. Thermometer 1 represents SJ biomarkers, thermometer 2 represents MS biomarkers, thermometer 3 represents SLE biomarkers, and thermometer 4 represents RA biomarkers. For demonstration purposes, each of these biomarkers was given a value of 1.
IC50 values were collected from data provided in Cortellis Drug Discovery Intelligence.
| Name (synonyms) | BTK | TEC | ITK | BMX | TXK | JAK3 | EGFR |
|---|---|---|---|---|---|---|---|
| Branebrutinib (BMS-986195) | 0.1 * | 0.9 | 100.0 | 1.5 | 5.0 | No data | 2,000.0 |
| BMS-986142 | 0.7 * | 21.2 * | 507.5 * | 85.0 * | 87.5 * | 1,000.0 | 1,000.0 |
| Tolebrutinib (SAR-442168, PRN2246) | 0.9 * | 1.0 | 365.0 | 1.1 | 1.7 | 1425.0 * | 4.1 |
| Poseltinib (LY-3337641, HM-71224) | 2.3 * | 4.5 | 103.0 | 0.6 | 4.6 | 18.8 * | 26.0 * |
| Ibrutinib (imbruvica, PCI-32765) | 2.4 * | 37.2 * | 91.9 * | 1.2 * | 4.5 * | 51.8 * | 30.2 * |
| Fenebrutinib (GDC-0853) | 5.3 * | >1000 | >1000 | 351.0 | >1000 | >1000 | >1000 |
| Remibrutinib (LOU064) | 5.5 * | No data | No data | No data | No data | No data | No data |
| Tirabrutinib (GSK-4059, ONO-4059) | 7.8 * | 29.0 * | >1000 | 21.7 * | 203.5 * | >1000 | >1000 |
| Acalabrutinib (calaquence, ACP-196) | 10.4 * | 142.1 * | >1000 | 91.6 * | 427.8 * | >1000 | >1000 |
| Spebrutinib (CC-292) | 15.4 * | 10.2 * | 674.7 * | 6.4 * | 93.7 * | 75.3 * | 436.0 * |
| Rilzabrutinib (PRN1008) | 33.4 * | 0.8 * | 440.0 | 1.0 * | 1.2 * | >5000 | 520.0 |
| Evobrutinib (M2951) | 47.7 * | ≤ 100 | ≤ 10000 | > 10 | >100 | 10,000.0 | 10,000.0 |
| Elsubrutinib (ABBV-105) | 175.0 * | 23,400.0 | 32,400.0 | No data | 9,180.0 | 8,640.0 | 14,400.0 |
Instances where multiple values were averaged together and noted with a *. For analysis, these values were binned together based on the strength of their nanomolar IC50s and colored as follows: low nanomolar (<10 nM) in red, low-mid nanomolar (10-100 nM) in orange, high-mid nanomolar (100-1000 nM) in yellow, and high nanomolar (>1000 nM) in green.
OFF-X Comparative Drug Safety Evidence showing safety findings for BTK inhibitor.
| ADVERSE EVENT | ALERT TYPE | ACALABRUTINIB | BMS-986142 | BRANEBRUTINIB | EVOBRUTINIB | FENEBRUTINIB | IBRUTINIB | POSELTINIB | REMIBRUTINIB | RILZABRUTINIB | SPEBRUTINIB | TIRABRUTINIB | TOLEBRUTINIB | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CLASS ALERT | DRUG ALERT | |||||||||||||||
| # of alerts | # of drugs | # of alerts | # of drugs | # of alerts | ||||||||||||
| All Adverse Events (853) | 26 | 4 | 5096 | 12 | 1383 | 10 | 11 | 123 | 52 | 3136 | 23 | 3 | 18 | 14 | 493 | 6 |
| Atrial fibrillation | 2 | 1 | 211 | 3 | 50 | 0 | 0 | 0 | 0 | 163 | 0 | 0 | 0 | 0 | 2 | 0 |
| Diarrhoea | 2 | 1 | 171 | 8 | 58 | 1 | 0 | 2 | 2 | 111 | 0 | 0 | 4 | 1 | 11 | 0 |
| Haemorrhage | 2 | 1 | 159 | 3 | 55 | 0 | 0 | 0 | 0 | 110 | 0 | 0 | 0 | 0 | 4 | 0 |
| Neutropenia | 1 | 1 | 153 | 5 | 49 | 0 | 0 | 1 | 0 | 99 | 0 | 0 | 0 | 1 | 12 | 0 |
| Hypertension | 1 | 1 | 135 | 4 | 32 | 0 | 0 | 1 | 0 | 104 | 0 | 0 | 0 | 0 | 1 | 0 |
| Pneumonia | 0 | 129 | 7 | 45 | 0 | 0 | 1 | 1 | 78 | 1 | 0 | 0 | 1 | 4 | 0 | |
| Anaemia | 0 | 126 | 6 | 47 | 0 | 0 | 0 | 3 | 73 | 1 | 0 | 0 | 1 | 9 | 0 | |
| Infection | 1 | 1 | 110 | 6 | 29 | 0 | 0 | 3 | 1 | 79 | 1 | 0 | 0 | 0 | 2 | 0 |
| Thrombocytopenia | 0 | 108 | 5 | 27 | 0 | 0 | 0 | 2 | 77 | 0 | 0 | 0 | 1 | 9 | 0 | |
| Fatigue | 0 | 107 | 6 | 36 | 0 | 0 | 1 | 3 | 70 | 0 | 0 | 3 | 0 | 2 | 0 | |
| Nausea | 0 | 99 | 9 | 33 | 1 | 1 | 6 | 4 | 49 | 0 | 0 | 4 | 1 | 7 | 0 | |
| Headache | 0 | 95 | 10 | 58 | 1 | 1 | 3 | 3 | 28 | 1 | 0 | 1 | 0 | 1 | 1 | |
| Contusion | 0 | 94 | 4 | 36 | 0 | 0 | 0 | 1 | 55 | 0 | 0 | 0 | 0 | 7 | 0 | |
| Arthralgia | 0 | 85 | 6 | 21 | 0 | 0 | 2 | 1 | 62 | 1 | 0 | 0 | 0 | 3 | 0 | |
| Rash | 0 | 79 | 6 | 14 | 0 | 1 | 0 | 1 | 58 | 1 | 0 | 0 | 0 | 9 | 0 | |
| Upper respiratory tract infection | 0 | 69 | 8 | 22 | 1 | 1 | 4 | 2 | 36 | 0 | 0 | 0 | 0 | 3 | 1 | |
| Death | 0 | 59 | 4 | 18 | 0 | 0 | 0 | 1 | 35 | 0 | 0 | 0 | 0 | 6 | 0 | |
| Pyrexia | 0 | 57 | 4 | 14 | 0 | 0 | 0 | 1 | 39 | 0 | 0 | 0 | 0 | 5 | 0 | |
| Cough | 0 | 56 | 6 | 22 | 1 | 0 | 0 | 2 | 27 | 0 | 0 | 0 | 1 | 4 | 0 | |
| Myalgia | 0 | 49 | 4 | 18 | 0 | 1 | 0 | 0 | 32 | 0 | 0 | 0 | 0 | 1 | 0 | |
The number on the table is the count of alerts for each drug associated with that adverse event. The background color represents the drug score linking the strength of evidence between each adverse event and the drug: red is very high evidence, orange is high evidence, lighter orange color is Medium Evidence, yellow is low evidence, grey is target/class evidence only, and white indicates no evidence is available.