Molecular predictors and mechanisms of immune checkpoint inhibitor-induced myocarditis: A case-control study with translational correlates.
Bibliographic record
Abstract
12031 Background: Myocarditis from immune checkpoint inhibition (ICI) has been reported in 0.04-1.14% of patients on ICI, with mortality up to 50%. Self-antigens driving ICI-myocarditis are largely unknown. Shared T cell clones between heart and tumor have not yet been identified. We present the Montreal Immune-Related Adverse Events (MIRAE) myocarditis project, which seeks to elucidate cellular and molecular drivers of ICI-myocarditis. Methods: Our case-control study comprises 3 groups of patients on ICI: 1) ICI-myocarditis (per ASCO diagnostic criteria); 2) non-ICI troponemia (elevated troponins from non-immune etiology); and 3) controls matched by tumor type, sex, and age, with no troponemia. We analyzed blood from prior to ICI, at time of troponemia, or at 3-6 months after ICI initiation. Our multiomics pipeline spans cytokine profiling, immune cell subpopulation profiling of peripheral blood mononuclear cells (PBMCs) via single cell RNA and T/B cell receptor sequencing, spatial single-cell imaging proteomics, and spatial transcriptomics to localize sources of upregulated cytokines and to visualize cell-cell interactions. Results: Of 560 patients treated with ICI in our biobank, 4.3% had ICI-myocarditis. 19 myocarditis stored samples were included in our study. All 19 patients received steroids. Additional treatments were mycophenolate (32%), tofacitinib (21%), plasmapheresis (21%), IVIG (21%) and alemtuzumab (5%). 5 patients (26%) developed arrhythmias. 10 (47%) had concurrent irAE. There were no major cardiac adverse events nor deaths from myocarditis or other irAE. These encouraging results may reflect our hospital protocol of troponin screening during first 3 cycles of ICI, leading to earlier diagnosis and treatment. Elevations of blood neutrophil-to-lymphocyte ratio, alanine transaminase, and aspartate aminotransferase were associated with ICI-myocarditis. Plasma cytokine profiling of 13 ICI-myocarditis cases and controls revealed significant elevations of IP10, IL10, IL15 and IL13 at time of myocarditis. Subpopulation profiling of PBMCs is ongoing. Spatial phenotyping of an ICI-myocarditis biopsy demonstrated T cell and macrophage infiltration among cardiocytes and granulocyte accumulation within fibrotic tissue. Spatial transcriptomics analysis is ongoing for the ICI-myocarditis biopsy and 2 controls. Conclusions: This is one of the largest translational studies of ICI-myocarditis and controls. Our patients had improved clinical outcomes compared to those reported in the literature, which may be a result from our early screening. Our multiomics analyses of their biospecimens contributes novel data, such as spatial proteomics and transcriptomics analyses on heart tissue. Advancing our understanding of ICI-myocarditis will allow us to design screening strategies and more targeted treatments for ICI-myocarditis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".