1250 Molecular predictors and mechanisms of immune checkpoint inhibitor-induced myocarditis: a case-control study with translational correlates
Notice bibliographique
Résumé
Background Myocarditis from immune checkpoint inhibition (ICI) has been reported in 0.04–1.14% of patients on ICI, with mortality up to 50%.1 Murine models reveal cardiac-myosin-specific T cells contribute to ICI-myocarditis; genetic/phenotypic differences may predispose to their activity.2 We present the Montreal Immune-Related Adverse Events (MIRAE) ICI-myocarditis project, conducted by an interdisciplinary team of physicians and scientists to understand molecular drivers of ICI-myocarditis. Methods This case-control study comprises three groups of patients treated with ICI: 1) ICI-myocarditis; 2) non-ICI troponemia (elevated troponins from non-immune etiology); and 3) controls matched by tumour type, with no IRAEs nor troponemia. We analyzed blood samples from prior to ICI, at time of troponemia, or at 3–6 months after ICI initiation if no troponemia. We developed a multi-omics pipeline to understand mechanisms of ICI-myocarditis (figure 1), with immune cell subpopulation profiling of peripheral blood mononuclear cells (PBMCs) using single cell RNA and T/B cell receptor sequencing. This is validated with genomic DNA methylation, cytokine analyses, and PhenoCycler spatial single-cell imaging proteomics to localize cellular sources of upregulated cytokines and to visualize cell-cell interactions underpinning cardiac pathology. Results Of 473 patients treated with ICI in the MIRAE biobank, 3.59% had ICI-myocarditis. Of these, 19 had stored samples and were included in this study (see table 1 for baseline characteristics). 5 patients (26%) developed arrhythmias. 10 (53%) had concurrent IRAE. 1 (5%) died from concurrent IRAE. There were no deaths from myocarditis. Elevations of blood neutrophil-to-lymphocyte ratio, alanine transaminase, and aspartate aminotransferase were associated with ICI-myocarditis, compared to non-myocarditis patients at 3–6 months on ICI (figure 2). Plasma cytokine profiling of 13 ICI-myocarditis cases and matching controls demonstrated no significant differences in baseline cytokines prior to ICI. Significant elevations of chemokine IP10 and anti-inflammatory cytokine IL10 were detected at time of myocarditis, implicating various immune cells, including T lymphocytes and monocytes (figure 3). Immune cell subpopulation profiling of PBMCs is ongoing (figure 4). Spatial profiling of the first ICI-myocarditis biopsy demonstrated T cell and macrophage infiltration between myocardiocytes and granulocyte accumulation within fibrotic tissue. This suggests a role of innate immunity in myocardial damage, in addition to lymphocyte activation (figure 5). Conclusions This is one of the largest translational studies of ICI-myocarditis patients and matched controls. The preliminary data highlight the role of innate immunity, in addition to the previously known role of T lymphocytes. Advancing molecular understandings of ICI-myocarditis will allow us to design more targeted, effective immunosuppressive treatments for ICI-myocarditis. Acknowledgements Laboratories of Dr Wilson Miller, Dr Sonia Del Rincón, Dr Réjean Lapointe, Dr Jun Ding, and Dr Lucas Salas. Funding from Canadian Institutes of Health Research and a generous donation to the Jewish General Hospital Clinical Research Unit by Cathy Monticciolo-Cianci in memory of her mother Maria Monticciolo. References Mahmood SS, Fradley MG, Cohen JV, Nohria A, Reynolds KL, Heinzerling LM, et al. Myocarditis in Patients Treated With Immune Checkpoint Inhibitors. J Am Coll Cardiol. 2018;71(16):1755–64. Axelrod ML, Meijers WC, Screever EM, Qin J, Carroll MG, Sun X, et al. T cells specific for α-myosin drive immunotherapy-related myocarditis. Nature. 2022;611(7937):818–26. Ethics Approval This study was approved by the CIUSS West-Central Montreal Ethics Board; approval number 2022–3081. All patient participants gave informed consent to be enrolled in the Montreal Immune-Related Adverse Events project.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».