title: Gene set analysis of purine and pyrimidine antimetabolites cancer therapies.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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].
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota 55905, USA. fridley.brooke@mayo.edu
authors.forename: Brooke L
authors.initials: BL
authors.lastname: Fridley
authors.forename: Anthony
authors.initials: A
authors.lastname: Batzler
authors.forename: Liang
authors.initials: L
authors.lastname: Li
authors.forename: Fang
authors.initials: F
authors.lastname: Li
authors.forename: Alice
authors.initials: A
authors.lastname: Matimba
authors.forename: Gregory D
authors.initials: GD
authors.lastname: Jenkins
authors.forename: Yuan
authors.initials: Y
authors.lastname: Ji
authors.forename: Liewei
authors.initials: L
authors.lastname: Wang
authors.forename: Richard M
authors.initials: RM
authors.lastname: Weinshilboum
mesh_terms: D000963:Antimetabolites / Q000627:therapeutic use*; D000970:Antineoplastic Agents / Q000627:therapeutic use*; D019540:Area Under Curve; D045744:Cell Line, Tumor; D003841:Deoxycytidine / Q000031:analogs & derivatives / Q000494:pharmacology / Q000627:therapeutic use; D052138:Genes, Neoplasm / Q000235:genetics*; D006801:Humans; D009369:Neoplasms / Q000188:drug therapy* / Q000235:genetics*; D010641:Phenotype; D011687:Purines / Q000627:therapeutic use*; D011743:Pyrimidines / Q000627:therapeutic use*; D015203:Reproducibility of Results; D013866:Thioguanine / Q000494:pharmacology / Q000627:therapeutic use; D000093542:Gemcitabine
chemical_list: D000963:Antimetabolites; D000970:Antineoplastic Agents; D011687:Purines; D011743:Pyrimidines; D003841:Deoxycytidine; D013866:Thioguanine; C030986:pyrimidine; C030985:purine; D000093542:Gemcitabine