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A genome-wide approach to identify genetic variants that contribute to etoposide-induced cytotoxicity
Open accessAbstract
Large interindividual variance has been observed in sensitivity to drugs. To comprehensively decipher the genetic contribution to these variations in drug susceptibility, we present a genome-wide model using human lymphoblastoid cell lines from the International HapMap consortium, of which extensive genotypic information is available, to identify genetic variants that contribute to chemotherapeutic agent-induced cytotoxicity. Our model integrated genotype, gene expression, and sensitivity of HapMap cell lines to drugs. Cell lines derived from 30 trios of European descent (Center d'Etude du Polymorphisme Humain population) and 30 trios of African descent (Yoruban population) were used. Cell growth inhibition at increasing concentrations of etoposide for 72 h was determined by using alamarBlue assay. Gene expression on 176 HapMap cell lines (87 Center d'Etude du Polymorphisme Humain population and 89 Yoruban population) was determined by using the Affymetrix GeneChip Human Exon 1.0ST Array. We evaluated associations between genotype and cytotoxicity, genotype and gene expression and correlated gene expression of the identified candidates with cytotoxicity. The analysis identified 63 genetic variants that contribute to etoposide-induced toxicity through their effect on gene expression. These include genes that may play a role in cancer ( AGPAT2 , IL1B , and WNT5B ) and genes not yet known to be associated with sensitivity to etoposide. This unbiased method can be used to elucidate genetic variants contributing to a wide range of cellular phenotypes induced by chemotherapeutic agents.
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Cites
A General Test of Association for Quantitative Traits in Nuclear Families
Abecasis, G. R., Cardon, L. R., & Cookson, W. O. C. (2000) · The American Journal of Human Genetics · doi:10.1086/302698 · Cited by 1,126
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GSVA: gene set variation analysis for microarray and RNA-Seq data
Hänzelmann, S., Castelo, R., & Guinney, J. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-7 · Cited by 15,440
Understanding mechanisms underlying human gene expression variation with RNA sequencing
Pickrell, J. K., Marioni, J. C., Pai, A. A., Degner, J. F., Engelhardt, B. E., Nkadori, E., Veyrieras, J.-B., Stephens, M., Gilad, Y., & Pritchard, J. K. (2010) · Nature · doi:10.1038/nature08872 · Cited by 1,256
Methods of integrating data to uncover genotype-phenotype interactions
Ritchie, M. D., Holzinger, E. R., Li, R., Pendergrass, S. A., & Kim, D. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3868 · Cited by 1,085
Human metabolic individuality in biomedical and pharmaceutical research
CARDIoGRAM, Suhre, K., Shin, S.-Y., Petersen, A.-K., Mohney, R. P., Meredith, D., Wägele, B., Altmaier, E., Deloukas, P., Erdmann, J., et al. (2011) · Nature · doi:10.1038/nature10354 · Cited by 1,017
Mapping complex disease traits with global gene expression
Cookson, W., Liang, L., Abecasis, G., Moffatt, M., & Lathrop, M. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2537 · Cited by 849
Metadata
- Authors
- Huang, R. S., Duan, S., Bleibel, W. K., Kistner, E. O., Zhang, W., Clark, T. A., Chen, T. X., Schweitzer, A. C., Blume, J. E., Cox, N. J., & Dolan, M. E.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2007-06-05
- Volume
- 104
- Issue
- 23
- Pages
- 9758-9763
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2021151787
- Cited by
- 198
- References
- 1
- FWCI
- 16.10
- Type
- journal article
- Language
- en
- Open access
- green
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- Huang, R. S., Duan, S., Bleibel, W. K., Kistner, E. O., Zhang, W., Clark, T. A., Chen, T. X., Schweitzer, A. C., Blume, J. E., Cox, N. J., & Dolan, M. E. (2007). A genome-wide approach to identify genetic variants that contribute to etoposide-induced cytotoxicity. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0703736104
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