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Updated: Feb 22, 2026

A Doxorubicin-induced Cardiomyopathy Model in Adult Zebrafish
Published on: June 7, 2018
Exome array analysis identifies ETFB as a novel susceptibility gene for anthracycline-induced cardiotoxicity in
Sara Ruiz-Pinto1, Guillermo Pita1, Miguel Martín2
1Human Genotyping Unit-CeGen, Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain.
Purpose:
Anthracyclines are widely used chemotherapeutic drugs that can cause progressive and irreversible cardiac damage and fatal heart failure. Several genetic variants associated with anthracycline-induced cardiotoxicity (AIC) have been identified, but they explain only a small proportion of the interindividual differences in AIC susceptibility.
Methods:
In this study, we evaluated the association of low-frequency variants with risk of chronic AIC using the Illumina HumanExome BeadChip array in a discovery cohort of 61 anthracycline-treated breast cancer patients with replication in a second independent cohort of 83 anthracycline-treated pediatric cancer patients, using gene-based tests (SKAT-O).
Results:
The most significant associated gene in the discovery cohort was ETFB (electron transfer flavoprotein beta subunit) involved in mitochondrial β-oxidation and ATP production (P = 4.16 × 10-4) and this association was replicated in an independent set of anthracycline-treated cancer patients (P = 2.81 × 10-3). Within ETFB, we found that the missense variant rs79338777 (p.Pro52Leu; c.155C > T) made the greatest contribution to the observed gene association and it was associated with increased risk of chronic AIC in the two cohorts separately and when combined (OR 9.00, P = 1.95 × 10-4, 95% CI 2.83-28.6).
Conclusions:
We identified and replicated a novel gene, ETFB, strongly associated with chronic AIC independently of age at tumor onset and related to anthracycline-mediated mitochondrial dysfunction. Although experimental verification and further studies in larger patient cohorts are required to confirm our finding, we demonstrated that exome array data analysis represents a valuable strategy to identify novel genes contributing to the susceptibility to chronic AIC.
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