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Enregistrement W3048464089 · doi:10.1093/rheumatology/keaa412

Immune-checkpoint kinetics for T cells in anti-MDA5 positive interstitial lung disease

2020· article· en· W3048464089 sur OpenAlexaff
Kunihiro Suzuki, Toyoshi Yanagihara, Koichiro Matsumoto, Sy Giin Chong, Hiroyuki Ando, Maako Ide, Masako Arimura‐Omori, Kentaro Hata, Naoki Hamada

Notice bibliographique

RevueLara D. Veeken · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Établissements canadiensMcMaster UniversitySt. Joseph’s Healthcare Hamilton
Organismes subventionnairesnon disponible
Mots-clésMedicineInterstitial lung diseaseImmune checkpointImmune systemMDA5KineticsLungImmunologyCancer researchImmunotherapyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Immune checkpoint kinetics can be monitored in anti-MDA5 positive interstitial lung disease. DEAR EDITOR, The anti-melanoma differentiation associated gene 5 (anti-MDA5) antibody is associated with rapidly progressive interstitial lung disease in patients with dermatomyositis. Although adaptive immunity is considered to be involved in pathogenesis, precise molecular pathways remain largely unknown. We report the case of a 71-year-old Japanese man who was referred to our department due to deterioration of his dyspnea and abnormal findings on his chest radiograph. A surgery for his pharyngeal and esophagus cancer was planned. Physical examination revealed Gottron papules, heliotrope rash and bilateral fine crackles on his lung bases, but no myalgia nor muscle weakness. High-resolution computed tomography of the chest showed a patchy distribution of consolidation predominantly in the lower lung (Fig. 1). Pulmonary function test showed a restrictive pattern with moderate DLco impairment. Examination of bronchoalveolar lavage fluid (BALF) showed lymphocytosis with decreased CD4/CD8 ratio (0.08). Immune checkpoint expression in T cells in a patient with anti-MDA5 positive interstitial lung disease (A) High-resolution computed tomography of the chest of the patient showed a patchy distribution of consolidation predominantly in the lower lung, suggestive of organizing pneumonia pattern. (B) A clinical course of the patient. The proportion of immune-checkpoint expression on CD3+CD4+ or CD3+CD8+ T cells in peripheral blood before and after immunosuppressive treatment. (C) Flow cytometric analysis of CD3+CD4+ or CD3+CD8+ T cells in BALF or peripheral blood at the initiation of treatment and during follow-up. BALF: bronchoalveolar lavage fluid; mPSL: methylprednisolone; PBMC: peripheral blood mononuclear cell; PSL: prednisolone; TAC: tacrolimus; Tx: therapy. Immune checkpoint expression in T cells in a patient with anti-MDA5 positive interstitial lung disease (A) High-resolution computed tomography of the chest of the patient showed a patchy distribution of consolidation predominantly in the lower lung, suggestive of organizing pneumonia pattern. (B) A clinical course of the patient. The proportion of immune-checkpoint expression on CD3+CD4+ or CD3+CD8+ T cells in peripheral blood before and after immunosuppressive treatment. (C) Flow cytometric analysis of CD3+CD4+ or CD3+CD8+ T cells in BALF or peripheral blood at the initiation of treatment and during follow-up. BALF: bronchoalveolar lavage fluid; mPSL: methylprednisolone; PBMC: peripheral blood mononuclear cell; PSL: prednisolone; TAC: tacrolimus; Tx: therapy. Based on the positivity of the anti-MDA5 antibody on admission along with the clinical information, he was diagnosed as clinically amyopathic dermatomyositis-associated interstitial lung disease (CADM-ILD). The patient was subsequently treated with methylprednisolone pulse therapy, followed by treatment with oral prednisolone and tacrolimus. Troughs of tacrolimus during treatment were around 8–10 ng/ml. Clinical remission was maintained during the tapering of steroid therapy. Because little is known about the role of immune-checkpoints in the pathogenesis of CADM-ILD, we analysed the expression of immune-checkpoints—PD-1, TIM-3, TIGIT and PD-L1—on T cells in BALF and peripheral blood. We detected PD-1, TIM-3, TIGIT and PD-L1 expression on T cells in BALF, while scant PD-1 expression was in peripheral blood (Fig. 1). Please see the methods in the previous study [1]. We were able to detect the kinetic changes of immune-checkpoint expression, especially TIM-3 and TIGIT, on T cells in peripheral blood during treatment. Specifically, TIM-3 expression on both CD4+ and CD8+ T cells substantially decreased immediately after methylprednisolone pulse, peaked transiently on day 19 but remained at a low level afterwards. In contrast, TIGIT expression on CD8+ T cells decreased to its bottom level on day 19 but gradually increased thereafter. As the expression levels of immune-checkpoints can be one of the markers of T-cell activation [2], we showed evidence of the effects of immunosuppressive treatment in T cells from a patient with CADM-ILD. The titer of anti-MDA5 antibody is reported to be a useful tool to monitor the disease activity in CADM-ILD [3]. Considering the central role of T cells in immunity, we predicted that the measurement of the T-cell activation could be a much faster and more sensitive predictor of the clinical course rather than the other markers. Future study is warranted to confirm our hypothesis. We previously reported that the proportion of PD-1+PD-L1+ cells among CD8+ T cells was correlated with the severity of immune-checkpoint inhibitor-related ILD (ICI-ILD) [1]. Given the recent findings on cis-PD-L1/CD80 or cis-PD-L1/PD-1 interactions for optimal T-cell responses [4, 5], we are of the opinion that augmented PD-1 and PD-L1 expressions on CD8+ T cells might act as one of the inhibitory mechanisms of the auto-reactivity and then interruption of this cis-PD-L1/PD-1 interaction by ICI (anti-PD-1 or anti-PD-L1 antibodies) for treatment of cancers might cause the progression of CADM-ILD. Interestingly, the expression pattern of PD-1, TIM-3 and TIGIT in this case was quite similar with the expression pattern found in ICI-ILD but different from other ILDs such as sarcoidosis, rheumatoid arthritis-related or Sjögren’s syndrome-related ILD [1]. Our patient has cancers, and the association between dermatomyositis and malignancies has been reported in several studies. We previously showed that the identical T-cell clones were found in BALF from ICI-ILD and peritumoral pleural effusion by sequencing of the complementarity-determining region of the T-cell receptor [6]. We speculate that the immune-checkpoint positive T cells in BALF from the patient could be related to tumor-infiltrating lymphocytes. The other possibility of these immune-checkpoint positive T cells could be follicular helper T cells (TFH, CXCR5+ PD-1+) [7] or peripheral helper T cells (TPH, CXCR5– PD-1+ CXCL13+) [8], which may help B cells generating autoantibodies including anti-MDA5 antibodies. Thus, our report illustrates a ‘bench to bedside’ approach and would provide a mechanistic insight into this life-threatening disease. Experimental conception and design: T.Y. and K.S. Performed experiments: K.S. Clinical data collection and patient follow-up: H.A., M. I. and K.S. Interpreted results and provided critical support: T.Y., K.S., K. M., S.G.C., M.A-O., K.H. and N.H. Prepared manuscript: T.Y. and S.G.C. Reviewed or edited, and approved manuscript: all authors. Funding: No specific funding was received from any funding bodies in the public, commercial or not-for-profit sectors to carry out the work described in this manuscript. Disclosure statement: the authors have declared no conflicts of interest.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,256
Écart entre enseignants0,244 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2020
Routes d'admission1
Résumé présentoui

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