American Association for Cancer Research
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Supplementary Table 1 from A First Step toward Personalized Medicine in Osteosarcoma: Pharmacogenetics as Predictive Marker of Outcome after Chemotherapy-Based Treatment

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posted on 2023-03-31, 18:08 authored by Melanie M. Hagleitner, Marieke J.H. Coenen, Hans Gelderblom, Remco R. Makkinje, Hanneke I. Vos, Eveline S.J.M. de Bont, Winette T.A. van der Graaf, H.W. Bart Schreuder, Uta Flucke, Frank N. van Leeuwen, Peter M. Hoogerbrugge, Henk-Jan Guchelaar, Dunja M.W.M te Loo

Supplementary Table 1. Set of 381 SNPs



Purpose: Overall survival in patients with osteosarcoma is only 60%. Poor response to chemotherapy is the dominant risk factor for poor survival. Pharmacogenetic research can offer possibilities to optimize treatment and improve outcome. We applied a pathway-based approach to evaluate the cumulative effect of genes involved in the metabolism of cisplatin and doxorubicin in relationship to clinical outcome.Experimental Design: We included 126 patients with osteosarcoma. To comprehensively assess common genetic variation in the 54 genes selected, linkage disequilibrium (LD; r2 = 0.8)–based tag-single nucleotide polymorphisms (SNP) strategy was used. A final set of 384 SNPs was typed using Illumina Beadarray platform. SNPs significantly associated with 5-year progression-free survival (PFS) were replicated in another 64 patients with osteosarcoma.Results: We identified five variants in FasL, MSH2, ABCC5, CASP3, and CYP3A4 that were associated with 5-year PFS. Risk stratification based on the combined effects of the risk alleles showed a significant improvement of 5-year PFS. Patients that carried no or only one risk allele had a 5-year PFS of 100% compared with a 5-year PFS of 84.4% for carriers of two or three risk alleles, 66.7% PFS if a patient carried four to five alleles, and a 5-year PFS of 41.8% for patients with >5 risk alleles (P < 0.001).Conclusions: We identified several genes that showed association with PFS in patients with osteosarcoma. These pharmacogenetic risk factors might be useful to predict treatment outcome and to stratify patients immediately after diagnosis and offer the possibility to improve treatment and outcome. Clin Cancer Res; 21(15); 3436–41. ©2015 AACR.

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