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. 2024 Jun 10:11:1408586.
doi: 10.3389/fcvm.2024.1408586. eCollection 2024.

Stringent monitoring can decrease mortality of immune checkpoint inhibitor induced cardiotoxicity

Ying Wang #  1 , Carolin Ertl #  1   2 , Christina Schmitt  1 , Linda Hammann  3 , Rafaela Kramer  4 , Ulrich Grabmaier  5 , Florian Schöberl  6   7 , David Anz  3   8 , Ignazio Piseddu  3   8 , Giulia Pesch  1 , Julio Vera  4 , Waltraud Froehlich  3 , Ludwig Weckbach  5 , Dirk Tomsitz  1 , Carmen Loquai  9 , Lisa Zimmer  10 , Johanna Mangana  11 , Reinhard Dummer  11 , Ralf Gutzmer  12 , Kai-Christian Klespe  13 , Henner Stege  14 , Frank Meiss  15 , Kai-Martin Thoms  16 , Patrick Terheyden  17 , Paul J Bröckelmann  18 , Douglas B Johnson  19 , Lars E French  1   20 , Lucie Heinzerling  1   2   4
Affiliations

Stringent monitoring can decrease mortality of immune checkpoint inhibitor induced cardiotoxicity

Ying Wang et al. Front Cardiovasc Med. .

Abstract

Background: Immune checkpoint inhibitor (ICI)-induced myocarditis is a rare immune-related adverse event (irAE) with a fatality rate of 40%-46%. However, irMyocarditis can be asymptomatic. Thus, improved monitoring, detection and therapy are needed. This study aims to generate knowledge on pathogenesis and assess outcomes in cancer centers with intensified patient management.

Methods: Patients with cardiac irAEs from the SERIO registry (www.serio-registry.org) were analyzed for demographics, ICI-related information (type of ICI, therapy line, combination with other drugs, onset of irAE, and tumor response), examination results, irAE treatment and outcome, as well as oncological endpoints. Cardiac biopsies of irMyocarditis cases (n = 12) were analyzed by Nanostring and compared to healthy heart muscle (n = 5) and longitudinal blood sampling was performed for immunophenotyping of irMyocarditis-patients (n = 4 baseline and n = 8 during irAE) in comparison to patients without toxicity under ICI-therapy (n = 4 baseline and n = 7 during ICI-therapy) using flow cytometry.

Results: A total of 51 patients with 53 cardiac irAEs induced by 4 different ICIs (anti-PD1, anti-PD-L1, anti-CTLA4) were included from 12 centers in 3 countries. Altogether, 83.0% of cardiac irAEs were graded as severe or life-threatening, and 11.3% were fatal (6/53). Thus, in centers with established consequent troponin monitoring, work-up upon the rise in troponin and consequent treatment of irMyocarditis with corticosteroids and -if required-second-line therapy mortality rate is much lower than previously reported. The median time to irMyocarditis was 36 days (range 4-1,074 days) after ICI initiation, whereas other cardiotoxicities, e.g. asystolia or myocardiopathy, occurred much later. The cytokine-mediated signaling pathway was differentially regulated in myocardial biopsies as compared to healthy heart based on enrichment Gene Ontology analysis. Additionally, longitudinal peripheral blood mononuclear cell (PBMC) samples from irMyocarditis-patients indicated ICI-driven enhanced CD4+ Treg cells and reduced CD4+ T cells. Immunophenotypes, particularly effector memory T cells of irMyocarditis-patients differed from those of ICI-treated patients without side effects. LAG3 expression on T cells and PD-L1 expression on dendritic cells could serve as predictive indicators for the development of irMyocarditis.

Conclusion: Interestingly, our cohort shows a very low mortality rate of irMyocarditis-patients. Our data indicate so far unknown local and systemic immunological patterns in cardiotoxicity.

Keywords: cardiovascular toxicity; checkpoint inhibitor; immunotherapy; melanoma; myocarditis.

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Conflict of interest statement

LH received speaker and consultancy fees from BiomeDx, BMS, Immunocore, Kyowa Kirin, Merck, MSD, Myoncare, Novartis, Pieris, Pierre-Fabre, Roche, Sanofi, Stemline Therapeutics, SUN and Therakos. The LMU received research grants or clinical study grants from Agenus, AstraZeneca Inc., BMS, Hoffmann-La Roche AG, Huya Bioscience, Immunocore, IO Biotech, Merck, Merck Sharp & Dome GmbH, Miltenyi Biomedicine GmbH, Novartis, Pfizer, Pierre Fabre, Regeneron, Replimune, and Sanofi Aventis. CE reports on speaker fees from BristolMyers Squibb, GSK, Immunocore, Kyowa Kirin, MSD CL received honoraria (lectures, presentations, speakers bureaus, manuscript writing or educational events) and travel support from: BMS, MSD Merck, Pierre-Fabre, Biontech, Almirall Hermal, Sun Pharma, KyowaKirin, Immunocore, Sanofi, Novartis. DT reports consultancy, speaker fees or travel grants: BMS, Roche, Novartis, Sanofi, Recordati, Kyowa Kirin, Sun Pharma and Pierre Fabre. LZ served as consultant and has received honoraria from BMS, MSD, Novartis, Pierre Fabre, Sanofi, and Sunpharma and travel support from MSD, BMS, Pierre Fabre, Sanofi, Sunpharma and Novartis, outside the submitted work. PJB reports research funding (inst) by BeiGene, BMS, MSD and Takeda; an advisory role to BeiGene, BMS, MSD, Need Inc., Stemline and Takeda; honoraria from BeiGene, BMS, Celgene, MSD, Need Inc., Stemline and Takeda and stock options from Need Inc. RG received honoraria for advice and lectures from BristolMyers Squibb, Roche Pharma, MerckSharpDohme, Novartis, Merck-Serono, Amgen, Almirall Hermal, Pierre-Fabre, Sun Pharma, Immunocore, 4SC, Delcath, Sanofi/Regeneron. Ralf Gutzmer received travel support from SUN Pharma, Boehringer Ingelheim and PierreFabre. Ralf Gutzmer received research grants from Novartis, Sanofi/Regeneron, Merck Serono, Amgen, SUN Pharma, KyowaKirin, Admiral Hermal. RD has intermittent, project focused consulting and/or advisory relationships with Novartis, Merck Sharp & Dhome (MSD), Bristol-Myers Squibb (BMS), Roche, Amgen, Takeda, Pierre Fabre, Sun Pharma, Sanofi, Catalym, Second Genome, Regeneron, Alligator, T3 Pharma, MaxiVAX SA, Pfizer, Simcere and touchIME outside the submitted work. All remaining authors have declared no conflicts of interest. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Documented cardiac irAE severity and outcome within the side effect registry immuno-oncology (SERIO). (A) Severity of irAE (grade 1-5 CTCAE). Data was available for 90.6% (48/53) of cases. (B) Outcome of irAE. Outcome data was available for 94.3% (50/53) of cases. CTCAE, common terminology criteria for adverse events version 5.0; IrAE, immune-related adverse event.
Figure 2
Figure 2
Bulk RNAseq reveals substantial differences in cytokine production pathways between irMyocarditis and healthy control. (A) Volcano plot shows 14 genes significantly downregulated in in irMyocarditis cohort and healthy heart cohort (violet) and 99 genes significantly upregulated in irMyocarditis compared to healthy control (green) (Log2 fold change ≤−1.5 or ≥1.5, p-value ≤0.05). Statistics were performed using Rosalind® software. (B) Enriched pathway analysis of significantly differentially expressed genes performed with STRING®, gene ontology and KEGG® reveals networks of enriched genes in irMyocarditis cohort and healthy heart cohort.
Figure 3
Figure 3
Enhanced activated Treg cells driven by ICI in irMyocarditis patient. PBMCs of patients with ae-irMyocarditis (n = 8) and bl (n = 4) were analyzed via flow cytometry. Distribution of activated T cells, Treg cells and other T cell phenotypes (Tn = naive T cells, Tcm = central memory T cells, Tem = effector memory T cells, Teff = effector T cells) in CD4+ and CD8+ T cells was determined. CD4+ and CD8+ T cells were also analyzed for expression of activation (CD27, CD28, ICOS, CD107a, CD44) and exhaustion (CTLA4, TIM-3, TIGIT, LAG3) markers using FACS. The abundance and activation of dendritic cell (DC) subsets was analyzed [activated DC, BDCA1- DC, BDCA1+ DC and monocyte derived DC (moDC)] using flow cytometry. (A) The frequencies of CD4+ and CD8+ in CD103+ activated CD4+ T cells and CD103+ activated CD8+ T cell. (B) The frequencies of live cells in CD103+ activated CD4+ Treg cells and CD103+ activated CD8+ Treg cells. (C) CD4+ and CD8+ T cells were analyzed for expression of activation CD44 markers using FACS. (D) The frequencies of live cells in CD80+, CD86+, HLA-DR, PD-L1 activated DC cells. (E) The frequencies of BDCA1- DC in PD-L1+ BDCA1- DC, PD-L1+ BDCA1+ DC and PD-L1+ moDC. IrAE, immune-related adverse event; bl, baseline.
Figure 4
Figure 4
Tem cell and exhaustion markers dominate in the induction of cardiotoxicity in irMyocarditis patients. PBMCs of patients with irMyocarditis (n = 8) and patients undergoing checkpoint-inhibitor therapy without development of toxicities (Ø tox ICI, n = 7) were analyzed via flow cytometry. Distribution of activated T cells, Treg cells, Tn, Tcm, Tem, Teff in CD4+ and CD8+ T cells was determined. CD4+ and CD8+ T cells were also analyzed for expression of activation (CD27, CD28, ICOS, CD107a, CD44) and exhaustion (CTLA4, TIM-3, TIGIT, LAG3) markers using FACS. The abundance and activation of dendritic cell (DC) subsets were analyzed using FACS. (A) The expression level of CD25 in activated CD4+, CD8+ T cell and the frequencies of lymphocytes of CD4+ Treg, CD8+ Treg cells (B) The frequencies of CD4 in CD4+ Tcm, CD4+ Teff, CD4+ Tem, and CD8+ Tem. (C) The expression level of TIGIT, TIM3 in CD4+ and CD8+ T cells. (D) The expression level of CD86 in activated DC, BDCA1- DC, BDCA1+ DC cells. (E) The expression level of CD80 of BDCA1- DC. (F) The expression level of HLA-DR of BDCA1- DC, BDCA1+ DC. (G) The frequencies of PD-L1 in activated DC, BDCA1- DC, BDCA1+ DC and moDC.
Figure 5
Figure 5
LAG3 and PD-L1 can be used as indicators to predict the occurrence of irMyocarditis. PBMCs of patients with bl-irMyocarditis (n = 4) and bl-tox ICI (n = 4) were analyzed via flow cytometry. Distribution of activated T cells, Treg cells, Tn, Tcm, Tem, Teff in CD4+ and CD8+ T cells was determined. CD4+ and CD8+ T cells were also analyzed for expression of activation (CD27, CD28, ICOS, CD107a, CD44) and exhaustion (CTLA4, TIM-3, TIGIT, LAG3) markers using FACS. The abundance and activation of dendritic cell (DC) subsets were analyzed using FACS. (A) The frequencies of CD4, CD8 in activated CD4+, CD8+ T cells. (B) The frequencies of CD4, CD8 in CD103+ activated CD4+ Treg, CD8+ Treg cells (C) The expression level of CD28, CD107a, and ICOS in CD4+ and CD8+ T cells. (D) The expression level of CTLA4, LAG3, TIGIT, and TIM3 in CD4+ and CD8+ T cells. (E) The expression level of PD-L1 in activated DC, BDCA1- DC, BDCA1+ DC, and moDC cells. (F) The frequencies of live cells of B cells and moDC.
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