Serum Proteins Predict Treatment-Related Cardiomyopathy Among Survivors of Childhood Cancer

Suresh Poudel, Him Shrestha, Yue Pan, Qian Li, Kendrick Li, Cindy Im, Stephanie B. Dixon, Matthew J. Ehrhardt, Daniel A. Mulrooney, Suiping Zhou, Haiyan Tan, Anthony A. High, Paul W. Burridge, Smita Bhatia, John L. Jefferies, Kirsten K. Ness, Melissa M. Hudson, Leslie L. Robison, Gregory T. Armstrong, Junmin PengBonnie Ky, Yutaka Yasui, Yadav Sapkota*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Background: Anthracyclines, a highly effective chemotherapy for many pediatric malignancies, cause cardiomyopathy, a major late effect in adult survivors. Biomarkers are needed for early detection and targeted interventions for anthracycline-associated cardiomyopathy. Objectives: The aim of this study was to determine if serum proteins and/or metabolites in asymptomatic childhood cancer survivors can discriminate symptomatic cardiomyopathy. Methods: Using an untargeted mass spectrometry–based approach, 867 proteins and 218 metabolites were profiled in serum samples of 75 asymptomatic survivors with subclinical cardiomyopathy and 75 individually matched survivors without cardiomyopathy from SJLIFE (St. Jude Lifetime Cohort Study). Models were developed on the basis of the most influential differentially expressed proteins and metabolites, using conditional logistic regression with a least absolute shrinkage and selection operator penalty. The best performing model was evaluated in 23 independent survivors with severe or symptomatic cardiomyopathy and 23 individually matched cardiomyopathy-free survivors. Results: A 27-protein model identified using conditional logistic regression with a least absolute shrinkage and selection operator penalty discriminated symptomatic or severe cardiomyopathy requiring heart failure medications in independent survivors; 19 of 23 individually matched survivors with and without cardiomyopathy were correctly discriminated with 82.6% (95% CI: 71.4%-93.8%) accuracy. Pathway enrichment analysis revealed that the 27 proteins were enriched in various biological processes, many of which have been linked to anthracycline-related cardiomyopathy. Conclusions: A risk model was developed on the basis of the differential expression of serum proteins in subclinical cardiomyopathy, which accurately discriminated the risk for severe cardiomyopathy in an independent, matched sample. Further assessment of these proteins as biomarkers of cardiomyopathy risk should be conducted in external larger cohorts and through prospective studies.

Original languageEnglish (US)
Pages (from-to)56-67
Number of pages12
JournalJACC: CardioOncology
Volume7
Issue number1
DOIs
StatePublished - Jan 2025

Keywords

  • anthracycline
  • biomarkers
  • cancer survivorship
  • childhood cancer
  • metabolomics
  • proteomics

ASJC Scopus subject areas

  • Oncology
  • Cardiology and Cardiovascular Medicine

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