4C3 Human Monoclonal Antibody: A Proof of Concept for Non-pathogenic Proteinase 3 Anti-neutrophil Cytoplasmic Antibodies in Granulomatosis With Polyangiitis

Granel, Jérôme; Lemoine, Robert; Morello, Eric; Gallais, Yann; Mariot, J.; Drapeau, Marion; Musnier, Astrid; Poupon, Anne; Pugnière, Martine; Seren, Seda; Nouar, D.; Gouilleux-Gruart, Valérie; Watier, Hervé; Korkmaz, Brice; Hoarau, C.

doi:10.3389/fimmu.2020.573040

Cited by 6 publications

(5 citation statements)

References 70 publications

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“…It allows identifying a correct epitope region in more than 80% of cases. This method has been successfully applied to many examples (Kizlik-Masson et al, 2017;Ashraf et al, 2019;Neiveyans et al, 2019;Granel et al, 2020;Trilleaud et al, 2021;Vayne et al, 2021;Ugamraj et al, 2022), including when the crystal structure of the target is unknown, and a 3D homology model has to be built.…”

Section: Epitope Mappingmentioning

confidence: 99%

Applying artificial intelligence to accelerate and de-risk antibody discovery

Musnier,

Dumet,

Mitra

et al. 2024

Front. Drug Discov.

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As in all sectors of science and industry, artificial intelligence (AI) is meant to have a high impact in the discovery of antibodies in the coming years. Antibody discovery was traditionally conducted through a succession of experimental steps: animal immunization, screening of relevant clones, in vitro testing, affinity maturation, in vivo testing in animal models, then different steps of humanization and maturation generating the candidate that will be tested in clinical trials. This scheme suffers from different flaws, rendering the whole process very risky, with an attrition rate over 95%. The rise of in silico methods, among which AI, has been gradually proven to reliably guide different experimental steps with more robust processes. They are now capable of covering the whole discovery process. Amongst the players in this new field, the company MAbSilico proposes an in silico pipeline allowing to design antibody sequences in a few days, already humanized and optimized for affinity and developability, considerably de-risking and accelerating the discovery process.

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Section: Epitope Mappingmentioning

confidence: 99%

Applying artificial intelligence to accelerate and de-risk antibody discovery

Musnier,

Dumet,

Mitra

et al. 2024

Front. Drug Discov.

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“…pathogenesis is therefore critical to relate these models to human studies. More recently, Granel et al (2020) developed a nonactivating human monoclonal antibody after testing various membrane proteins (CD 11b,CD 18,and CD 63) as well as the metabolic product ROS from neutrophils, which offers promising results in understanding the PR3-ANCA pathogenicity and possible future therapeutic application.…”

Section: Anca-associated Vasculitis In Animal Studiesmentioning

confidence: 99%

Proteinase 3 associated with Wegener's granulomatosis

Goldmann

2022

Cell Biology International

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Wegener's granulomatosis (WG) is a form of systemic vasculitis characterized by granulomatous inflammation of the upper and lower airways, vasculitis, and necrotizing glomerulonephritis. It is strongly associated with anti-neutrophil cytoplasmic antibodies against proteinase 3 (PR3-ANCAs). Various in vitro observations provided strong evidence that autoimmune PR3-ANCAs are directly involved in glomerular and vascular inflammation. However, little is known about the pathogenic significance of PR3-ANCAs in vivo. Therefore, the generation of animal models helped to validate the suggested autoimmune origin and pathophysiology in WG. To characterize and improve the models, numerous studies were carried out to elucidate the effect of mouse/rat PR3-ANCAs on neutrophil function as well as the role of CD4/CD8 in T and B cells and antibodies in the pathogenesis of the disease.Understanding the pathogenesis is therefore critical to relate these models to human studies hoping that they will be useful for better insight of WG and the development of specific therapies for the disease.

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“…Furthermore, due to the absence of any functional defect in its Fc fragment, we hypothesize that its non-pathogenic character is related to the epitope recognized on PR3. Indeed, mAb 4C3 binds mbPR3 on a newly described epitope close to the hydrophobic patch ( 154 ). Epitopes associated with non-pathogenicity of PR3-ANCA could be a relevant biomarker.…”

Section: Applying Knowledge On Proteinase 3-anti-neutrophil Cytoplasmmentioning

confidence: 99%

“…As described above, we have produced the mAb 4C3, a non-pathogenic human anti-PR3 mAb which was shown to be unable to activate neutrophils in vitro. Moreover, this mAb is able to neutralize auto-immune activation of neutrophils induced by pathogenic PR3-ANCA from GPA patients at diagnosis ( 154 ). This promising result offers perspectives to develop new therapies in GPA but must be confirmed by further studies.…”

Section: Applying Knowledge On Proteinase 3-anti-neutrophil Cytoplasmmentioning

confidence: 99%

Pathogenicity of Proteinase 3-Anti-Neutrophil Cytoplasmic Antibody in Granulomatosis With Polyangiitis: Implications as Biomarker and Future Therapies

et al. 2021

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Granulomatosis with polyangiitis (GPA) is a rare but serious necrotizing auto-immune vasculitis. GPA is mostly associated with the presence of Anti-Neutrophil Cytoplasmic Antibody (ANCA) targeting proteinase 3 (PR3-ANCA), a serine protease contained in neutrophil granules but also exposed at the membrane. PR3-ANCAs have a proven fundamental role in GPA: they bind neutrophils allowing their auto-immune activation responsible for vasculitis lesions. PR3-ANCAs bind neutrophil surface on the one hand by their Fab binding PR3 and on the other by their Fc binding Fc gamma receptors. Despite current therapies, GPA is still a serious disease with an important mortality and a high risk of relapse. Furthermore, although PR3-ANCAs are a consistent biomarker for GPA diagnosis, relapse management currently based on their level is inconsistent. Indeed, PR3-ANCA level is not correlated with disease activity in 25% of patients suggesting that not all PR3-ANCAs are pathogenic. Therefore, the development of new biomarkers to evaluate disease activity and predict relapse and new therapies is necessary. Understanding factors influencing PR3-ANCA pathogenicity, i.e. their potential to induce auto-immune activation of neutrophils, offers interesting perspectives in order to improve GPA management. Most relevant factors influencing PR3-ANCA pathogenicity are involved in their interaction with neutrophils: level of PR3 autoantigen at neutrophil surface, epitope of PR3 recognized by PR3-ANCA, isotype and glycosylation of PR3-ANCA. We detailed in this review the advances in understanding these factors influencing PR3-ANCA pathogenicity in order to use them as biomarkers and develop new therapies in GPA as part of a personalized approach.

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4C3 Human Monoclonal Antibody: A Proof of Concept for Non-pathogenic Proteinase 3 Anti-neutrophil Cytoplasmic Antibodies in Granulomatosis With Polyangiitis

Cited by 6 publications

References 70 publications

Applying artificial intelligence to accelerate and de-risk antibody discovery

Applying artificial intelligence to accelerate and de-risk antibody discovery

Proteinase 3 associated with Wegener's granulomatosis

Pathogenicity of Proteinase 3-Anti-Neutrophil Cytoplasmic Antibody in Granulomatosis With Polyangiitis: Implications as Biomarker and Future Therapies

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