Detalle Publicación

Exome array analysis identifies ETFB as a novel susceptibility gene for anthracycline-induced cardiotoxicity in cancer patients.
Autores: Ruiz-Pinto, S.; Pita, G.; Martín, M.; Alonso-Gordoa, T.; Barnes, D.R.; Alonso, M.R.; Herraez, B.; García-Miguel, P.; Alonso, J.; Pérez-Martínez, A.; Cartón, A.J.; Gurtiérrez-Larraya, F.; García-Sáenz, J.A.; Benitez, J.; Easton, Douglas.F.; Patiño García, Ana; González-Neira, A.
ISSN: 0167-6806
Volumen: 167
Número: 1
Páginas: 249 - 256
Fecha de publicación: 2018
Lugar: WOS
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 ß-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.