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一种全基因组方法,用于鉴定导致依托泊苷诱导的细胞毒性的遗传变异。

A genome-wide approach to identify genetic variants that contribute to etoposide-induced cytotoxicity.

作者信息

Huang R Stephanie, Duan Shiwei, Bleibel Wasim K, Kistner Emily O, Zhang Wei, Clark Tyson A, Chen Tina X, Schweitzer Anthony C, Blume John E, Cox Nancy J, Dolan M Eileen

机构信息

Section of Hematology-Oncology, Biostatistics Consulting Laboratory, Department of Health Studies, University of Chicago, Chicago, IL 60637, USA.

出版信息

Proc Natl Acad Sci U S A. 2007 Jun 5;104(23):9758-63. doi: 10.1073/pnas.0703736104. Epub 2007 May 30.

Abstract

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.

摘要

在药物敏感性方面已观察到个体间存在很大差异。为了全面解读基因对药物敏感性这些差异的贡献,我们提出了一种全基因组模型,该模型使用来自国际人类基因组单体型图(HapMap)协会的人类淋巴母细胞系,这些细胞系有广泛的基因型信息,用于识别导致化疗药物诱导细胞毒性的基因变异。我们的模型整合了HapMap细胞系的基因型、基因表达和对药物的敏感性。使用了来自30个欧洲血统三人组(人类多态性研究中心群体)和30个非洲血统三人组(约鲁巴群体)的细胞系。通过使用alamarBlue检测法测定在不同浓度依托泊苷作用72小时后细胞生长的抑制情况。使用Affymetrix GeneChip Human Exon 1.0ST Array测定176个HapMap细胞系(87个来自人类多态性研究中心群体和89个来自约鲁巴群体)的基因表达。我们评估了基因型与细胞毒性之间的关联、基因型与基因表达之间的关联,并将已识别候选基因的基因表达与细胞毒性进行关联分析。该分析确定了63个通过影响基因表达而导致依托泊苷诱导毒性的基因变异。这些基因包括可能在癌症中起作用的基因(AGPAT2、IL1B和WNT5B)以及尚未知与依托泊苷敏感性相关的基因。这种无偏倚的方法可用于阐明导致化疗药物诱导的广泛细胞表型的基因变异。

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