Details

Autor(en) / Beteiligte

• Visscher, H.
• Ross, C.J.D.
• Rassekh, S.R.
• Sandor, G.S.S.
• Caron, H.N.
• van Dalen, E.C.
• Kremer, L.C.
• van der Pal, H.J.
• Rogers, P.C.
• Rieder, M.J.
• Carleton, B.C.
• Hayden, M.R.

Titel

Validation of variants in SLC28A3 and UGT1A6 as genetic markers predictive of anthracycline-induced cardiotoxicity in children

Ist Teil von

• Pediatric blood & cancer, 2013-08, Vol.60 (8), p.1375-1381

Ort / Verlag

United States: Blackwell Publishing Ltd

Erscheinungsjahr

2013

Quelle

Wiley Online Library Journals Frontfile Complete

Beschreibungen/Notizen

• Background . The use of anthracyclines as effective antineoplastic drugs is limited by the occurrence of cardiotoxicity. Multiple genetic variants predictive of anthracycline‐induced cardiotoxicity (ACT) in children were recently identified. The current study was aimed to assess replication of these findings in an independent cohort of children. Procedure . Twenty‐three variants were tested for association with ACT in an independent cohort of 218 patients. Predictive models including genetic and clinical risk factors were constructed in the original cohort and assessed in the current replication cohort. Results . We confirmed the association of rs17863783 in UGT1A6 and ACT in the replication cohort (P = 0.0062, odds ratio (OR) 7.98). Additional evidence for association of rs7853758 (P = 0.058, OR 0.46) and rs885004 (P = 0.058, OR 0.42) in SLC28A3 was found (combined P = 1.6 × 10−5 and P = 3.0 × 10−5, respectively). A previously constructed prediction model did not significantly improve risk prediction in the replication cohort over clinical factors alone. However, an improved prediction model constructed using replicated genetic variants as well as clinical factors discriminated significantly better between cases and controls than clinical factors alone in both original (AUC 0.77 vs. 0.68, P = 0.0031) and replication cohort (AUC 0.77 vs. 0.69, P = 0.060). Conclusions . We validated genetic variants in two genes predictive of ACT in an independent cohort. A prediction model combining replicated genetic variants as well as clinical risk factors might be able to identify high‐ and low‐risk patients who could benefit from alternative treatment options. Pediatr Blood Cancer 2013;601375‐1381. © 2013 Wiley Periodicals, Inc.