Pharmacogenomics: road to anticancer therapeutics nirvana?

Desai, Apurva A.; Innocenti, Federico; Ratain, Mark J.

doi:10.1038/sj.onc.1206958

Cited by 52 publications

(29 citation statements)

References 74 publications

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“…We performed a pharmacogenomic study with genomic DNA from peripheral blood mononuclear cells, not with tumoral DNA from cancer tissues. Even though there are still some controversies, genomic DNA is considered to have the genetic information of normal tissue rather than tumor DNA [41]. Thus, we thought that it was more rational to use genomic DNA to predict the influence of S-1 on normal tissue (toxicity) rather than on tumor tissue (response).…”

Section: Discussionmentioning

confidence: 99%

Multi-Institutional Phase II Study of S-1 Monotherapy in Advanced Gastric Cancer with Pharmacokinetic and Pharmacogenomic Evaluations

et al. 2007

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This study describes the first phase II study of S-1, a novel oral fluoropyrimidine, in a non-Japanese Asian population with advanced gastric cancer. S-1 was administered twice daily for 28 days every 6 weeks. A pharmacokinetic study was performed on day 28 of cycles 1 and 3. Genomic DNA from peripheral mononuclear cells was analyzed using a cDNA microarraybased comparative genomic hybridization (CGH) method. Thirty-one patients were initially given a dose of 35 mg/m 2 twice daily (bid) (group 1); then, the protocol was amended by increasing the dose to 40 mg/m 2 bid for an additional 31 patients (group 2) because of good tolerability to S-1. The overall response rate was 19.3% (95% confidence interval, 9.2%-29.5%). Over a median follow-up duration of 265 days, the median time to progression and overall survival time were 126 and 264 days, respectively. The 1-year survival rate was 34%. There was no grade 4 toxicity and the major adverse event was anemia. Pharmacokinetic parameters were similar to those of the previous Japanese reports. Microarray CGH identified 18 genes with copy number changes that were associated with hemoglobin reduction with S-1 treatment. A logistic regression analysis, integrating one clinical parameter (initial hemoglobin level) combined with three genetic copy number variations (HIST1H2BL, C10orf127, and XPNPEP2), provided a predictive model for the development of severe hemoglobin reduction. In conclusion, this study showed the feasibility of using S-1 at 35 mg/m 2 bid in gastric cancer. We suggest that the pharmacogenomic markers identified in this study may be potential candidates for predicting anemia after S-1 treatment. The Oncologist 2007;12:543-554

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Section: Discussionmentioning

confidence: 99%

Multi-Institutional Phase II Study of S-1 Monotherapy in Advanced Gastric Cancer with Pharmacokinetic and Pharmacogenomic Evaluations

et al. 2007

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“…rapid elimination from the host circulation) could also explain inter-individual differences in response to standard regimens. Pharmacokinetic and pharmacogenomic analyses of the host are aimed at defining the role of such parameters in order to optimize treatment (Desai et al, 2003).…”

Section: General Mechanisms Of Chemotherapy Resistance and Implicatiomentioning

confidence: 99%

Apoptosis defects and chemotherapy resistance: molecular interaction maps and networks

et al. 2004

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Intrinsic (innate) and acquired (adaptive) resistance to chemotherapy critically limits the outcome of cancer treatments. For many years, it was assumed that the interaction of a drug with its molecular target would yield a lethal lesion, and that determinants of intrinsic drug resistance should therefore be sought either at the target level (quantitative changes or/and mutations) or upstream of this interaction, in drug metabolism or drug transport mechanisms. It is now apparent that independent of the factors above, cellular responses to a molecular lesion can determine the outcome of therapy. This review will focus on programmed cell death (apoptosis) and on survival pathways (Bcl-2, Apaf-1, AKT, NF-jB) involved in multidrug resistance. We will present our molecular interaction mapping conventions to summarize the AKT and IjB/NF-jB networks. They complement the p53, Chk2 and c-Abl maps published recently. We will also introduce the 'permissive apoptosis-resistance' model for the selection of multidrug-resistant cells.

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“…The promise of pharmacogenomics lies in maximizing the efficacy of a medical intervention while minimizing the toxicity. It is widely accepted that such a need is most pronounced in anticancer treatments due to the inherent toxicity of the drugs used and the wide variability in individual responses (18). Ratain and coworkers have, for example, presented a very detailed analysis of the potential effect of pharmacogenomics using irinotecan, 5-fluorouracil, and epidermal growth factor receptor inhibitors as specific examples (18).…”

Section: Cancer Chemotherapy and The Promise Of Pharmacogenomicsmentioning

confidence: 99%

“…It is widely accepted that such a need is most pronounced in anticancer treatments due to the inherent toxicity of the drugs used and the wide variability in individual responses (18). Ratain and coworkers have, for example, presented a very detailed analysis of the potential effect of pharmacogenomics using irinotecan, 5-fluorouracil, and epidermal growth factor receptor inhibitors as specific examples (18). There is also the recognition that many emerging anticancer agents will not affect cures but act as disease-stabilizing agents (19).…”

Section: Cancer Chemotherapy and The Promise Of Pharmacogenomicsmentioning

confidence: 99%

Silent Polymorphisms Speak: How They Affect Pharmacogenomics and the Treatment of Cancer

et al. 2007

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Polymorphisms in the human genome contribute to wide variations in how individuals respond to medications, either by changing the pharmacokinetics of drugs or by altering the cellular response to therapeutic agents. The goal of the emerging discipline of pharmacogenomics is to personalize therapy based on an individual's genotype. Due to the relatively large frequency of single-nucleotide polymorphisms (SNP) in the human genome, synonymous SNPs are often disregarded in many pharmacogenomic studies based on the assumption that these are silent. We have shown recently that synonymous SNPs in ABCB1 (P-glycoprotein), which is implicated both in determining drug pharmacokinetics and multidrug resistance in human cancer cells, can affect protein conformation and function. We discuss the importance of polymorphisms in drug metabolizing enzymes and transporters in anticancer therapy and suggest that synonymous polymorphisms may play a more significant role than is currently assumed. [Cancer Res 2007;67(20):9609-12] Should Synonymous Single-Nucleotide Polymorphisms Be Ignored?Clinical observations beginning in the 1950s suggested that individuals exhibit differences in their responses to drugs and that these variations could be inherited (1). Numerous studies over the next few decades clearly established that genetic factors influence the heterogeneity of individual responses to medications with respect to both toxicity and efficacy (1). Although it was recognized that medical practice based on population responses did not reflect the best treatment for an individual (2), the difficulties associated with identifying the genetic determinants of drug sensitivity and toxicity in individual patients were almost insurmountable (1). The dramatic expansion in the development of functional genomics, bioinformatics and high-throughput screening that followed the completion of the human genome project has, however, led many authorities to predict that the dream of personalized medicine may soon be a reality. Analysis of the sequence of the human genome has shown that the extent of genetic variation in the human population is far greater than had been estimated (3), and the most common sequence variation is the single-nucleotide polymorphism (SNP). SNPs (which by definition have a minor allele frequency of >1%) are major determinants of variations in disease susceptibility, response to medication, and toxicity (4). As SNPs occur at a frequency of f1 per 100 to 1000 bp, 3 several strategies have been advocated to systematically or rationally reduce the number of SNPs that need to be studied. Risch, for example, classified SNPs into five types that constitute a hierarchy of importance (see Table 2 in ref. 4). One casualty of this approach has been the synonymous SNPs (which do not alter amino acid residues) based on the assumption that these are ''silent'' and do not affect protein expression or function.Genetic studies have indicated for several years that synonymous mutations can have significant ''fitness consequences'...

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Pharmacogenomics: road to anticancer therapeutics nirvana?

Cited by 52 publications

References 74 publications

Multi-Institutional Phase II Study of S-1 Monotherapy in Advanced Gastric Cancer with Pharmacokinetic and Pharmacogenomic Evaluations

Multi-Institutional Phase II Study of S-1 Monotherapy in Advanced Gastric Cancer with Pharmacokinetic and Pharmacogenomic Evaluations

Apoptosis defects and chemotherapy resistance: molecular interaction maps and networks

Silent Polymorphisms Speak: How They Affect Pharmacogenomics and the Treatment of Cancer

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