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COMPARE: a web accessible tool for investigating mechanisms of cell growth inhibition
Daniel W Zaharevitz1, Susan L Holbeck, Christopher Bowerman
1Information Technology Branch, Developmental Therapeutics Program, National Cancer Institute, Bethesda, MD 20892, USA. zaharevitz@dtpax2.ncifcrf.gov
Abstract:
For more than 10 years the National Cancer Institute (NCI) has tested compounds for their ability to inhibit the growth of human tumor cell lines in culture (NCI screen). Work of Ken Paull [J. Natl. Cancer Inst. 81 (1989) 1088] demonstrated that compounds with similar mechanism of cell growth inhibition show similar patterns of activity in the NCI screen. This observation was developed into an algorithm called COMPARE and has been successfully used to predict mechanisms for a wide variety of compounds. More recently, this method has been extended to associate patterns of cell growth inhibition by compounds with measurements of molecular entities (such as gene expression) in the cell lines in the NCI screen. The COMPARE method and associated data are freely available on the Developmental Therapeutics Program (DTP) web site (http://dtp.nci.nih.gov/). Examples of the use of COMPARE on these web pages will be explained and demonstrated. Published by Elsevier Science Inc.
Insights
The National Cancer Institute
Area of Science:
- Computational Biology
- Drug Discovery
- Cancer Research
Background:
- The National Cancer Institute (NCI) has a decade-long history of screening compounds for anti-cancer properties.
- Ken Paull's research established that similar mechanisms of cell growth inhibition yield comparable activity patterns in NCI screens.
- This led to the development of the COMPARE algorithm for predicting compound mechanisms.
Purpose of the Study:
- To extend the COMPARE algorithm's utility by linking compound activity patterns to molecular data.
- To demonstrate the application and accessibility of the COMPARE method and its data.
- To facilitate drug discovery by predicting compound mechanisms of action.
Main Methods:
- Utilizing the COMPARE algorithm to analyze patterns of cell growth inhibition in human tumor cell lines.
- Integrating COMPARE analysis with molecular data, such as gene expression, from NCI-screened cell lines.
- Making the COMPARE algorithm and associated data publicly available via the Developmental Therapeutics Program (DTP) website.
Main Results:
- The COMPARE algorithm successfully predicts mechanisms of action for diverse compounds.
- The extended COMPARE method associates compound-induced growth inhibition patterns with specific molecular profiles.
- The DTP website provides a platform for accessing and utilizing COMPARE tools and data.
Conclusions:
- The COMPARE algorithm is a valuable tool for predicting drug mechanisms in cancer research.
- Integrating molecular data enhances the predictive power of COMPARE for drug discovery.
- Freely accessible resources, like the DTP website, promote advancements in cancer therapeutics.