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A protein expression database for the molecular pharmacology of cancer
T G Myers1, N L Anderson, M Waltham
1Laboratory of Molecular Pharmacology, National Cancer Institute (NCI), Bethesda, MD 20852, USA. tgm@nih.gov
Abstract:
In the last six years, the Developmental Therapeutics Program (DTP) of the US National Cancer Institute (NCI) has screened over 60,000 chemical compounds and a larger number of natural product extracts for their ability to inhibit growth of 60 different cancer cell lines representing different organs of origin. Whereas inhibition of the growth of one cancer cell type gives no information on drug specificity, the relative growth inhibitory activities against 60 different cells constitute patterns that encode detailed information on mechanisms of action and resistance (as reviewed in Boyd and Paull, Drug Devel. Res. 1995, 34, 19-109 and Weinstein et al., Science 1997, 275, 343-349). In order to correlate the patterns of activity with properties of the cells, we and other laboratories are characterizing the cells with respect to a large number of factors at the DNA, mRNA, and protein levels. As part of that effort, we have developed a two-dimensional gel electrophoresis (2-DE) protein expression database covering all 60 cell types (Buolamwini et al., submitted). Here we present analyses of the correlations among protein spots (i) in terms of their patterns of expression and (ii) in terms of their apparent relationships to the pharmacology of a set of 3989 screened compounds. The correlations tend to be stronger for the latter than for the former, suggesting that the spots have more robust signatures in terms of the pharmacology than in terms of expression levels. Links to pertinent databases and tools of analysis will be updated progressively at http:@www.nci.nih.gov/intra/lmp/jnwbio.htm and http:@epnwsl.ncifcrf.gov:2345/dis3d/dtp.++ +html.
Insights
The National Cancer Institute
Area of Science:
- Cancer research
- Drug discovery
- Proteomics
Background:
- The Developmental Therapeutics Program (DTP) screened numerous compounds against 60 cancer cell lines.
- Drug specificity is determined by activity patterns across diverse cell types.
- Understanding drug mechanisms requires correlating activity with cellular properties.
Purpose of the Study:
- To analyze correlations between protein expression patterns and drug pharmacology.
- To investigate the relationship between 2-DE protein spots and compound activity.
- To identify robust cellular signatures for drug response.
Main Methods:
- Developed a two-dimensional gel electrophoresis (2-DE) protein expression database for 60 cancer cell lines.
- Analyzed correlations between protein spot expression patterns and drug activity.
- Correlated protein spot patterns with the pharmacology of 3989 screened compounds.
Main Results:
- Protein spots showed stronger correlations with drug pharmacology than with expression levels.
- This suggests protein signatures are more indicative of drug response than mere expression.
- Identified potential cellular markers linked to drug action and resistance.
Conclusions:
- Two-dimensional gel electrophoresis (2-DE) protein expression data can predict drug response.
- Protein signatures offer robust insights into drug mechanisms and resistance.
- This approach aids in the development of targeted cancer therapeutics.