American Association for Cancer Research
00085472can076381-sup-can_5-1-08_huang.pdf (19.46 kB)

Supplementary Table 1 from Genetic Variants Contributing to Daunorubicin-Induced Cytotoxicity

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posted on 2023-03-30, 18:12 authored by R. Stephanie Huang, Shiwei Duan, Emily O. Kistner, Wasim K. Bleibel, Shannon M. Delaney, Donna L. Fackenthal, Soma Das, M. Eileen Dolan
Supplementary Table 1 from Genetic Variants Contributing to Daunorubicin-Induced Cytotoxicity



Identifying heritable genetic variants responsible for chemotherapeutic toxicities has been challenging due in part to its multigenic nature. To date, there is a paucity of data on genetic variants associated with patients experiencing severe myelosuppression or cardiac toxicity following treatment with daunorubicin. We present a genome-wide model using International HapMap cell lines that integrate genotype and gene expression to identify genetic variants that contribute to daunorubicin-induced cytotoxicity. A cell growth inhibition assay was used to measure variations in the cytotoxicity of daunorubicin. Gene expression was determined using the Affymetrix GeneChip Human Exon 1.0ST Array. Using sequential analysis, we evaluated the associations between genotype and cytotoxicity, those significant genotypes with gene expression and correlated gene expression of the identified candidates with cytotoxicity. A total of 26, 9, and 18 genetic variants were identified to contribute to daunorubicin-induced cytotoxicity through their effect on 16, 9, and 36 gene expressions in the combined, Centre d' Etude du Polymorphisme Humain (CEPH), and Yoruban populations, respectively. Using 50 non-HapMap CEPH cell lines, single nucleotide polymorphisms generated through our model predicted 29% of the overall variation in daunorubicin sensitivity and the expression of CYP1B1 was significantly correlated with sensitivity to daunorubicin. In the CEPH validation set, rs120525235 and rs3750518 were significant predictors of transformed daunorubicin IC50 (P = 0.005 and P = 0.0008, respectively), and rs1551315 trends toward significance (P = 0.089). This unbiased method can be used to elucidate genetic variants contributing to a wide range of cellular phenotypes. [Cancer Res 2008;68(9):3161–8]

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