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

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.

Keywords: anthracycline; biomarkers; cancer survivorship; childhood cancer; metabolomics; proteomics.

Graphical abstract

Figure 1

Differentially Expressed Serum Proteins in Subclinical Cardiomyopathy in Childhood Cancer Survivors Previously Treated With Anthracyclines The x-axis shows the log₂ fold change, estimating differential expression of 867 proteins quantified by tandem mass tag–based mass spectrometry between asymptomatic survivors with and without subclinical cardiomyopathy in the discovery sample, and statistical significance is shown on the y-axis. These results were obtained from a linear mixed-effects model in the discovery sample adjusted for age at cancer diagnosis, sex, cumulative anthracycline dose, race, and sample age as fixed effects and matched-pair indicator as a random effect. On the basis of these results, conditional logistic regression with a least absolute shrinkage and selection operator penalty (CLR-Lasso) was used to identify the most informative proteins and build models to discriminate the risk for subclinical cardiomyopathy. The best performing model was based on the top 20% differentially expression proteins (shown as light green triangles) and of these, CLR-Lasso selected 27 proteins (shown as red triangles).

Figure 2

Discrimination Accuracy of the Risk Discrimination Model Based on 27 Proteins Selected by Conditional Logistic Regression With a Least Absolute Shrinkage and Selection Operator Penalty The y-axis shows the logarithm of ratio of conditional probabilities of survivors with and without severe cardiomyopathy within each of the 23 individually matched pairs (x-axis) in the validation sample. A ratio of >1 (denoted by the dashed red horizontal line) indicates higher predicted conditional probability of a survivor with severe cardiomyopathy compared with the matched survivor without cardiomyopathy. Within each matched pair, a survivor having higher predicted conditional probability was labeled as affected, and the other matched survivor was labeled as unaffected. Discrimination accuracy was assessed by the concordance between predicted and observed cardiomyopathy outcomes per matched pair. Concordant matched pairs are shown in light green, and red shows discordant pairs.

Central Illustration

Serum Proteins Discriminating Cardiomyopathy Risk in Childhood Cancer Survivors Exposed to Anthracyclines Without Chest Radiation The study identified a combination of 27 serum proteins that accurately discriminated the risk for severe cardiomyopathy with 83% accuracy among survivors of childhood cancer previously exposed to anthracyclines but not chest radiation.