4.5 Article

DNA Adducts from Anticancer Drugs as Candidate Predictive Markers for Precision Medicine

期刊

CHEMICAL RESEARCH IN TOXICOLOGY
卷 30, 期 1, 页码 388-409

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.chemrestox.6b00380

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资金

  1. European Research Council [260341, 680920]
  2. Swiss National Science Foundation [156280, 152621]
  3. ETH research commission [ETH-43 14-1]
  4. NIH [CA93373]
  5. SBIR [HHSN261201000133C, HHSN261201200048C]
  6. LLNL [LDRD 08-LW-100]
  7. NIH/NIGMS [P41 RR13461]
  8. American Cancer Society
  9. Knapp Family Fund
  10. U.S. Department of Energy [DE-AC52-07NA27344]
  11. National Institutes of Health, National Center for Research Resources, Biomedical Technology Program [P41 RR13461]
  12. European Research Council (ERC) [680920] Funding Source: European Research Council (ERC)

向作者/读者索取更多资源

Biomarker-driven drug selection plays a central role in cancer drug discovery and development, and in diagnostic strategies to improve the use of traditional chemotherapeutic drugs. DNA-modifying anticancer drugs are still used as first line medication, but drawbacks such as resistance and side effects remain an issue. Monitoring the formation and level of DNA modifications induced by anticancer drugs is a potential strategy for stratifying patients and predicting drug efficacy. In this perspective, preclinical and clinical data concerning the relationship between drug-induced DNA adducts and biological response for platinum drugs and combination therapies, nitrogen mustards and half-mustards, hypoxia-activated drugs, reductase-activated drugs, and minor groove binding agents are presented and discussed. Aspects including measurement strategies, identification of adducts, and biological factors that influence the predictive relationship between DNA modification and biological response are addressed. A positive correlation between DNA adduct levels and response was observed for the majority of the studies, demonstrating the high potential of using DNA adducts from anticancer drugs as mechanism-based biomarkers of susceptibility, especially as bioanalysis approaches with higher sensitivity and throughput emerge.

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