A serum proteomics‐based predictive model for steroid‐resistant immune checkpoint inhibitor associated myocarditis
4 affiliations
- 1Department of Echocardiography Zhongshan Hospital Fudan University Shanghai Institute of Cardiovascular Diseases Shanghai China
- 2Department of Cardiovascular Medicine Guangdong Cardiovascular Institute Guangdong Provincial People's Hospital Guangdong Academy of Medical Sciences Southern Medical University Guangzhou China
- 3Department of Cardiology Zhongshan Hospital Fudan University Shanghai Institute of Cardiovascular Diseases Shanghai China
- 4Department of Medical Oncology Zhongshan Hospital Fudan University Shanghai China
Abstract
Background Immune checkpoint inhibitor–associated myocarditis (ICIAM) is one of the immune–related adverse events (irAEs) with low incidence but extremely high mortality. High–dose glucocorticoid pulse therapy remains the recommended initial treatment for patients with ICIAM. However, an inadequate response to corticosteroid therapy is observed in some patients, who are subsequently classified as having steroid‐resistant immune checkpoint inhibitor‐associated myocarditis (srICIAM). Early combination of second‐line immunosuppression may represent an effective therapeutic strategy. However, Biomarkers capable of identifying such patients before treatment are currently lacking. We therefore sought to characterize circulating inflammatory proteins associated with corticosteroid responsiveness and to derive a preliminary serum‐based prediction model for steroid‐resistant ICIAM (srICIAM). Methods Serum specimens obtained from patients with ICIAM at baseline and after methylprednisolone treatment were analyzed to quantify circulating immune‐related proteins using an antibody‐based proteomic assay. We developed a preliminary model for the early identification of patients at risk of srICIAM using proteins selected by three complementary machine–learning algorithms and evaluated its discriminatory performance in an internal hold‐out cohort. Results Pretreatment serum samples from 47 patients with ICIAM were used to establish a protein–based prediction model, with 33 patients assigned to model development and 14 to internal validation. Patients with a high srICIAM predictive score (≥.5625) based on CXCL9, TRANCE and MMP1 were more likely to show an inadequate early response to corticosteroid therapy and may warrant closer clinical monitoring and further evaluation. The analysis also revealed that several serum immune proteins decreased in patients with ICIAM after methylprednisolone therapy. Serum CXCL9 levels were positively correlated with lactate dehydrogenase (LDH) and cardiac troponin T (cTnT). Conclusion Serum immune proteins were dynamically altered in patients with ICIAM after methylprednisolone therapy. The preliminary score may enable earlier recognition of patients at risk of an inadequate corticosteroid response.
Related
- Age-stratified reporting of immune checkpoint inhibitor-associated myocarditis: disproportionality is amplified in older adults, with implications for geriatric oncology
- Rechallenge After Immune Checkpoint Inhibitors Myocarditis: Evidence and a Practical Framework
- Microbiome-derived TOPOSCORE is associated with response to immune checkpoint inhibitor re-induction after chemotherapy in primary resistant metastatic melanoma
- Research advances in Janus kinase inhibitors for immune checkpoint inhibitors-related myocarditis
- Management and Surveillance of Immune Checkpoint Inhibitor Myocarditis: Managing the Aftermath
BibTeX
@article{zhang2026serum,
title = {{A serum proteomics‐based predictive model for steroid‐resistant immune checkpoint inhibitor associated myocarditis}},
author = {Yerui Zhang and Yihan Li and Jian Zhang and Xiaozhen He and Yihui Shen and Yuchen Xu and Hui Zhang and Jianan Pan and Xuejun Wang and Shilong Zhang and Yan Wang and Leilei Cheng},
journal = {Clinical and Translational Medicine},
year = {2026},
month = oct,
doi = {10.1002/ctm2.70843},
url = {https://doi.org/10.1002/ctm2.70843},
note = {CC BY},
}
RIS
TY - JOUR
TI - A serum proteomics‐based predictive model for steroid‐resistant immune checkpoint inhibitor associated myocarditis
AU - Yerui Zhang
AU - Yihan Li
AU - Jian Zhang
AU - Xiaozhen He
AU - Yihui Shen
AU - Yuchen Xu
AU - Hui Zhang
AU - Jianan Pan
AU - Xuejun Wang
AU - Shilong Zhang
AU - Yan Wang
AU - Leilei Cheng
PY - 2026
DA - 2026/10/26
JO - Clinical and Translational Medicine
DO - 10.1002/ctm2.70843
UR - https://doi.org/10.1002/ctm2.70843
AB - Background Immune checkpoint inhibitor–associated myocarditis (ICIAM) is one of the immune–related adverse events (irAEs) with low incidence but extremely high mortality. High–dose glucocorticoid pulse therapy remains the recommended initial treatment for patients with ICIAM. However, an inadequate response to corticosteroid therapy is observed in some patients, who are subsequently classified as having steroid‐resistant immune checkpoint inhibitor‐associated myocarditis (srICIAM). Early combination of second‐line immunosuppression may represent an effective therapeutic strategy. However, Biomarkers capable of identifying such patients before treatment are currently lacking. We therefore sought to characterize circulating inflammatory proteins associated with corticosteroid responsiveness and to derive a preliminary serum‐based prediction model for steroid‐resistant ICIAM (srICIAM). Methods Serum specimens obtained from patients with ICIAM at baseline and after methylprednisolone treatment were analyzed to quantify circulating immune‐related proteins using an antibody‐based proteomic assay. We developed a preliminary model for the early identification of patients at risk of srICIAM using proteins selected by three complementary machine–learning algorithms and evaluated its discriminatory performance in an internal hold‐out cohort. Results Pretreatment serum samples from 47 patients with ICIAM were used to establish a protein–based prediction model, with 33 patients assigned to model development and 14 to internal validation. Patients with a high srICIAM predictive score (≥.5625) based on CXCL9, TRANCE and MMP1 were more likely to show an inadequate early response to corticosteroid therapy and may warrant closer clinical monitoring and further evaluation. The analysis also revealed that several serum immune proteins decreased in patients with ICIAM after methylprednisolone therapy. Serum CXCL9 levels were positively correlated with lactate dehydrogenase (LDH) and cardiac troponin T (cTnT). Conclusion Serum immune proteins were dynamically altered in patients with ICIAM after methylprednisolone therapy. The preliminary score may enable earlier recognition of patients at risk of an inadequate corticosteroid response.
SN - 2001-1326
ER -