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A rational approach to personalized anticancer therapy: chemoinformatic analysis reveals mechanistic gene-drug

Kerby Shedden1, Leroy B Townsend, John C Drach

  • 1Department of Statistics, The University of Michigan, 428 Church Street, Ann Arbor, Michigan 48109, USA.

Pharmaceutical Research
|June 24, 2003
PubMed
Abstract

Insights

Gene expression profiles can predict cancer drug response. Adenosine kinase (ADK) expression strongly correlates with triciribine phosphate (TCN-P) sensitivity, suggesting personalized cancer therapy based on enzyme levels.

Area of Science:

  • Chemoinformatics
  • Genomics
  • Pharmacology

Background:

  • Predicting patient response to chemotherapy is crucial for effective cancer treatment.
  • Gene expression profiling offers a potential method for predicting drug efficacy.
  • The National Cancer Institute's (NCI) 60 cell line panel is a valuable resource for such studies.

Purpose of the Study:

  • To predict cellular response to chemotherapeutic agents using gene expression profiles.
  • To identify mechanistically-relevant gene-drug associations within a panel of 60 human tumor cell lines.
  • To investigate the correlation between gene expression and drug activity for standard anticancer agents.

Main Methods:

  • Literature review to identify mechanistically-relevant gene-drug associations.
  • Calculation of correlations between drug target gene expression and drug activity across the NCI 60 cell line panel.
  • Analysis of gene expression and chemosensitivity data within and across tumor tissue types.

Main Results:

  • An exceptionally strong association was found between triciribine phosphate (TCN-P) and adenosine kinase (ADK).
  • This TCN-P:ADK association was significant overall and within specific tumor tissue types.
  • The correlation held true across the 60 cell lines profiled for both chemosensitivity and gene expression.

Conclusions:

  • Adenosine kinase (ADK) expression may serve as a biomarker for stratifying tumors responsive to TCN-P.
  • The observed TCN-P:ADK association supports a mechanistic basis for personalized cancer therapy.
  • Tumor-specific differences in drug-activating enzyme expression can guide personalized treatment strategies.

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