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Updated: Aug 21, 2026
Assessing Specificity of Anticancer Drugs In Vitro
Published on: March 23, 2016
A functional genomic study on NCI's anticancer drug screen
Abstract:
Pharmacogenomics requires massive computer exploration on heterogeneous databases. COMPARE, the gateway to the NCI's anticancer drug screen database, allows users to correlate drug-sensitivity profiles with a functional genomic database. However, most drugs of known molecular mechanism turn out to be uncorrelated with their molecular-target gene expression. Based on a novel statistical concept, liquid association, we develop an on-line system to identify candidate genes that intervene, confound and weaken the drug-gene correlation. The system takes queries and returns button-clickable tables of functionally associated genes for rerouting to knowledgebases such as Locus Link, OMIM and PubMed. We report results that link methotrexate resistance to DNA component biosynthesis, and taxol sensitivity to genes associated with human immunodeficiency virus infection. The drug-sensitivity database can be synergistically coanalyzed with gene expression data to study proteins of poorly understood physiological roles. When applied to the human prion, a cellular context embroidered with the gene expression network of Alzheimer disease is revealed.
Insights
This study introduces a novel system for pharmacogenomics research, linking drug sensitivity to gene expression. It identifies candidate genes influencing drug-gene correlations, revealing new biological insights.
Area of Science:
- Genomics
- Pharmacology
- Bioinformatics
Background:
- Pharmacogenomics research necessitates extensive computational analysis of diverse biological databases.
- Existing systems like COMPARE facilitate correlating anticancer drug sensitivity with genomic data.
- A significant challenge is the frequent lack of correlation between drug molecular mechanisms and their target gene expression.
Purpose of the Study:
- To develop an online system for identifying genes that influence drug-gene correlations using a novel statistical concept.
- To enable users to explore functional associations between drug sensitivity and gene expression.
- To uncover novel therapeutic targets and biological pathways.
Main Methods:
- Development of an online system based on the statistical concept of 'liquid association'.
- Integration of the NCI's anticancer drug screen database with a functional genomic database.
- Implementation of query functions returning clickable tables of associated genes linked to external knowledgebases (Locus Link, OMIM, PubMed).
Main Results:
- Identification of candidate genes that intervene, confound, or weaken drug-gene correlations.
- Demonstration of links between methotrexate resistance and DNA component biosynthesis.
- Revealed association between taxol sensitivity and genes related to human immunodeficiency virus infection.
- Uncovered a gene expression network related to Alzheimer disease when analyzing the human prion protein.
Conclusions:
- The developed system enhances the synergistic analysis of drug sensitivity and gene expression data.
- It facilitates the study of proteins with poorly understood physiological roles.
- The findings suggest novel pathways and gene interactions relevant to drug response and disease mechanisms.
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