Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota 55905, USA.
Pharmacogenet Genomics. 2011 Nov;21(11):701-12. doi: 10.1097/FPC.0b013e32834a48a9.
Responses to therapies, either with regard to toxicities or efficacy, are expected to involve complex relationships of gene products within the same molecular pathway or functional gene set. Therefore, pathways or gene sets, as opposed to single genes, may better reflect the true underlying biology and may be more appropriate units for analysis of pharmacogenomic studies. Application of such methods to pharmacogenomic studies may enable the detection of more subtle effects of multiple genes in the same pathway that may be missed by assessing each gene individually.
A gene set analysis of 3821 gene sets is presented assessing the association between basal messenger RNA expression and drug cytotoxicity using ethnically defined human lymphoblastoid cell lines for two classes of drugs: pyrimidines [gemcitabine (dFdC) and arabinoside] and purines [6-thioguanine and 6-mercaptopurine].
The gene set nucleoside-diphosphatase activity was found to be significantly associated with both dFdC and arabinoside, whereas gene set γ-aminobutyric acid catabolic process was associated with dFdC and 6-thioguanine. These gene sets were significantly associated with the phenotype even after adjusting for multiple testing. In addition, five associated gene sets were found in common between the pyrimidines and two gene sets for the purines (3',5'-cyclic-AMP phosphodiesterase activity and γ-aminobutyric acid catabolic process) with a P value of less than 0.0001. Functional validation was attempted with four genes each in gene sets for thiopurine and pyrimidine antimetabolites. All four genes selected from the pyrimidine gene sets (PSME3, CANT1, ENTPD6, ADRM1) were validated, but only one (PDE4D) was validated for the thiopurine gene sets.
In summary, results from the gene set analysis of pyrimidine and purine therapies, used often in the treatment of various cancers, provide novel insight into the relationship between genomic variation and drug response.
对于治疗的反应，无论是毒性还是疗效，都预计涉及同一分子途径或功能基因集中的基因产物的复杂关系。因此，与单个基因相比，途径或基因集可能更好地反映真实的潜在生物学，并且可能更适合分析药物基因组学研究。将这些方法应用于药物基因组学研究可能能够检测到同一途径中多个基因的更微妙影响，而通过单独评估每个基因可能会错过这些影响。
本文提出了一种基因集分析方法，使用两种药物（嘧啶类[吉西他滨（dFdC）和阿拉伯糖苷]和嘌呤类[6-硫代鸟嘌呤和 6-巯基嘌呤]）的种族定义的人类淋巴母细胞系，评估了基础信使 RNA 表达与药物细胞毒性之间的关联。
发现核苷二磷酸酶活性基因集与 dFdC 和阿拉伯糖苷均显著相关，而 γ-氨基丁酸分解代谢过程基因集与 dFdC 和 6-硫代鸟嘌呤相关。即使在进行多次测试调整后，这些基因集与表型仍显著相关。此外，在嘧啶类和嘌呤类之间发现了五个共同相关的基因集（3'，5'-环磷酸二酯酶活性和 γ-氨基丁酸分解代谢过程），其 P 值小于 0.0001。尝试对硫嘌呤和嘧啶抗代谢物基因集中的每个基因进行功能验证，在嘧啶基因集中选择了四个基因（PSME3、CANT1、ENTPD6、ADRM1），均得到验证，但只有一个基因（PDE4D）在硫嘌呤基因集中得到验证。
总之，嘧啶类和嘌呤类治疗药物的基因集分析结果为基因组变异与药物反应之间的关系提供了新的见解，这些治疗药物常用于治疗各种癌症。
