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Linking the growth inhibition response from the National Cancer Institute's anticancer screen to gene expression
Anders Wallqvist1, Alfred A Rabow, Robert H Shoemaker
1Science Applications International Corporation, National Cancer Institute at Frederick, National Institutes of Health Frederick, MD 21702, USA. wallqvist@ncifrcf.gov
Motivation:
Data mining tools are proposed to establish mechanistic connections between chemotypes and specific cellular functions. Drawing on a previous study that classified the cellular response patterns of growth inhibition measurements log( GI(50)) from the National Cancer Institute's (NCI's) anticancer screen, we have examined additional data for mRNA expression, sets of known molecular targets and mutational status against these same tumor cell lines to relate chemosensitivity more precisely to biochemical pathways.
Results:
Our analysis finds that gene expression levels do not, in general, correlate with log(GI(50)) measurements, instead they reflect a generic toxic condition. Within the remaining set of non-generic conditions, examples were found where a correlation suggesting a biochemical basis for cellular cytotoxicity could be supported. These included reconfirmation of previously observed associations between mutant and wild-type status of p53, and chemosensitivity to alkylating agents, while extending these results to reveal associations with gamma-induced expressions of MDM2, WAF1 and GADD45, signals that were not apparent in measurements of basal mRNA expression levels for any of these genes. Additional examinations revealed that mRNA expression levels directly correlated with paclitaxel chemosensitivity to mitosis, while also identifying additional chemotypes as P-glycoprotein substrates. Our analysis revealed well-known direct associations between p16 mutant status and chemotypes implicated in cell cycle control, and extended these results to include expression levels for three additional tyrosine kinase proteins (TEK, transgelin and hCdc4). Links were also found that suggested associations between chemosensitivity and the endocrine, paracrine ligand-receptor loops, via expression of the adrenergic receptor, calcium second messenger pathways via expression levels of carbonic anhydrase and cellular communication pathways via fibrillin.
Insights
This study links cancer drug sensitivity to specific gene expression patterns, revealing new biochemical pathways for targeted therapies. We found correlations between gene mutations and drug response, improving our understanding of cellular cytotoxicity.
Area of Science:
- Biochemistry
- Genomics
- Pharmacology
Background:
- Utilizing data mining to connect chemotypes with cellular functions.
- Leveraging previous National Cancer Institute (NCI) anticancer screen data on growth inhibition (log(GI(50))).
- Expanding analysis to include mRNA expression, molecular targets, and mutational status.
Purpose of the Study:
- To precisely relate chemosensitivity to biochemical pathways.
- To identify mechanistic connections between drug compounds and cellular responses.
- To explore correlations beyond generic toxicity.
Main Methods:
- Analysis of mRNA expression, molecular targets, and mutational status in tumor cell lines.
- Correlation analysis between gene expression and drug sensitivity (log(GI(50))).
- Examination of specific gene-environment interactions and pathway associations.
Main Results:
- General gene expression levels did not correlate with drug sensitivity, often indicating generic toxicity.
- Specific correlations were found, supporting biochemical bases for cytotoxicity, including p53 status and alkylating agents.
- Associations were identified between mRNA expression and paclitaxel sensitivity, P-glycoprotein substrates, cell cycle control genes (p16), and various signaling pathways (tyrosine kinases, adrenergic receptor, calcium signaling, cell communication).
Conclusions:
- Gene expression is not a universal predictor of drug sensitivity but can indicate specific pathway involvement.
- Identified novel associations between gene expression, mutations, and chemosensitivity, offering potential for targeted therapeutic strategies.
- The study highlights the complexity of chemosensitivity, involving multiple biochemical and cellular pathways.
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