Literature DB >> 15890268

Predicting drug response and toxicity based on gene polymorphisms.

Jacques Robert1, Valérie Le Morvan, Denis Smith, Philippe Pourquier, Jacques Bonnet.   

Abstract

The sequencing of the human genome has allowed the identification of thousands of gene polymorphisms, most often single nucleotide polymorphims (SNP), which may play an important role in the expression level and activity of the corresponding proteins. When these polymorphisms occur at the level of drug metabolising enzymes or transporters, the disposition of the drug may be altered and, consequently, its efficacy may be compromised or its toxicity enhanced. Polymorphisms can also occur at the level of proteins directly involved in drug action, either when the protein is the target of the drug or when the protein is involved in the repair of drug-induced lesions. There again, these polymorphisms may lead to alterations in drug efficacy and/or toxicity. The identification of functional polymorphisms in patients undergoing chemotherapy may help the clinician prescribe the optimal drug combination or schedule and predict with more accuracy the response to these prescriptions. We have recorded in this review the polymorphisms that have been identified up till now in genes involved in anticancer drug activity. Some of them appear especially important in predicting drug toxicity and should be determined in routine before drug administration; this is the case of the most common variations of thiopurine methyltransferase for 6-mercaptopurine and of dihydropyrimidine dehydrogenase for fluorouracil. Other appear determinant for drug response, such as the common SNPs found in glutathione S-transferase P1 or xereoderma pigmentosum group D enzyme for the activity of oxaliplatin. However, confusion factors may exist between the role of gene polymorphisms in cancer risk or overall prognosis and their role in drug response.

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Year:  2005        PMID: 15890268     DOI: 10.1016/j.critrevonc.2005.01.005

Source DB:  PubMed          Journal:  Crit Rev Oncol Hematol        ISSN: 1040-8428            Impact factor:   6.312


  24 in total

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