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Annals of Oncology
Article
License: Elsevier Non-Commercial
Data sources: UnpayWall
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Annals of Oncology
Article . 2004 . Peer-reviewed
License: Elsevier Non-Commercial
Data sources: Crossref
https://doi.org/10.1007/978-1-...
Part of book or chapter of book . 2006 . Peer-reviewed
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Pharmacogenomics and colorectal cancer

Authors: Heinz-Josef Lenz;

Pharmacogenomics and colorectal cancer

Abstract

The current methods of treating cancer patients with chemotherapeutics do not account for interpatient variability in the expression of particular target genes. This variability leads to unpredictable tumor responses and host toxicity. The approach we have taken is to determine gene expression levels in the metabolic pathways of drugs used in the treatment of gastrointestinal tumors. One of the main obstacles in the evaluation and determination of these markers has been the limitations of available technology. Many advances have been made in the development of more sophisticated techniques and the ability to perform these techniques on paraffin-embedded tumor tissue. In fact, with the identification of genetic polymorphisms, these markers may be obtained from peripheral blood specimens, thus making access to tissues a moot issue. An immediate goal is the application of this nascent technology and incorporation of these data in prospective clinical trials that would stratify patients according to their molecular profile. The ability to predict with a high degree of accuracy which patients are likely to respond to treatment and identify those who are not likely to respond will significantly influence the design of new treatment regimens with fluoropyrimidines and platinum. Tumors with high TS, TP, and DPD expression levels should be treated with such non-TS-directed anticancer drugs as irinotecan or oxaliplatin, or in combination with 5-FU. Patients with high expression of ERCC1 should be treated with nonplatinum-based regimens, whereas patients with low levels would be good candidates for cisplatin or oxaliplatin. We now understand that molecular determinants play an important role in response to 5-FU. With the development of new effective anticancer drugs such as irinotecan and oxaliplatin, it is important to gain a better understanding about the metabolism of these new active agents and mechanisms of resistance. It is essential to understand why some patients develop life-threatening toxicity and why some tumors are resistant to irinotecan or oxaliplatin. With the integration of novel-targeted therapies such as Erbitux and Avastin, molecular characterization and profiling will become more important for patient selection. Preliminary data suggest that germ line polymorphisms of cyclin D and gene expression levels of VEGF are associated with efficacy of Erbitux therapy.

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Keywords

Polymorphism, Genetic, DNA Repair, Organoplatinum Compounds, Gene Expression Profiling, Antineoplastic Agents, Thymidylate Synthase, Prognosis, Oxaliplatin, Drug Resistance, Neoplasm, Pharmacogenetics, Antineoplastic Combined Chemotherapy Protocols, Humans, Fluorouracil, Colorectal Neoplasms, Germ-Line Mutation

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    40
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
40
Average
Top 10%
Top 10%
hybrid
Related to Research communities
Cancer Research