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Assessing Specificity of Anticancer Drugs In Vitro
Published on: March 23, 2016
Integrating data on DNA copy number with gene expression levels and drug sensitivities in the NCI-60 cell line panel
Kimberly J Bussey1, Koei Chin, Samir Lababidi
1Laboratory of Molecular Pharmacology, National Cancer Institute, Building 37, Room 5056, NIH, MSC 4255, 9000 Rockville Pike, Bethesda, MD 20892-4255, USA.
Abstract:
Chromosome rearrangement, a hallmark of cancer, has profound effects on carcinogenesis and tumor phenotype. We used a panel of 60 human cancer cell lines (the NCI-60) as a model system to identify relationships among DNA copy number, mRNA expression level, and drug sensitivity. For each of 64 cancer-relevant genes, we calculated all 4,096 possible Pearson's correlation coefficients relating DNA copy number (assessed by comparative genomic hybridization using bacterial artificial chromosome microarrays) and mRNA expression level (determined using both cDNA and Affymetrix oligonucleotide microarrays). The analysis identified an association of ERBB2 overexpression with 3p copy number, a finding supported by data from human tumors and a mouse model of ERBB2-induced carcinogenesis. When we examined the correlation between DNA copy number for all 353 unique loci on the bacterial artificial chromosome microarray and drug sensitivity for 118 drugs with putatively known mechanisms of action, we found a striking negative correlation (-0.983; 95% bootstrap confidence interval, -0.999 to -0.899) between activity of the enzyme drug L-asparaginase and DNA copy number of genes near asparagine synthetase in the ovarian cancer cells. Previous analysis of drug sensitivity and mRNA expression had suggested an inverse relationship between mRNA levels of asparagine synthetase and L-asparaginase sensitivity in the NCI-60. The concordance of pharmacogenomic findings at the DNA and mRNA levels strongly suggests further study of L-asparaginase for possible treatment of a low-synthetase subset of clinical ovarian cancers. The DNA copy number database presented here will enable other investigators to explore DNA transcript-drug relationships in their own domains of research focus.
Insights
Cancer cell DNA copy number variations influence drug sensitivity. This study links gene copy number to drug response, identifying L-asparaginase as a potential treatment for ovarian cancers with low asparagine synthetase.
Area of Science:
- Cancer Biology
- Genomics
- Pharmacogenomics
Background:
- Chromosome rearrangements are key drivers of cancer development and tumor characteristics.
- Understanding the interplay between DNA copy number, gene expression, and drug response is crucial for targeted cancer therapies.
Purpose of the Study:
- To investigate the relationships among DNA copy number, mRNA expression, and drug sensitivity using the NCI-60 cancer cell line panel.
- To identify specific genetic alterations associated with drug efficacy and explore novel therapeutic strategies.
Main Methods:
- Comparative genomic hybridization (CGH) using bacterial artificial chromosome (BAC) microarrays to assess DNA copy number.
- mRNA expression profiling using cDNA and Affymetrix oligonucleotide microarrays.
- Calculation of Pearson's correlation coefficients to link DNA copy number, mRNA levels, and drug sensitivity for 118 drugs.
Main Results:
- Identified a correlation between ERBB2 (ERBB2) overexpression and 3p copy number alterations, validated in human tumors and mouse models.
- Discovered a strong negative correlation between L-asparaginase activity and DNA copy number near asparagine synthetase in ovarian cancer cells.
- Concordance between DNA copy number and mRNA expression findings supports the role of asparagine synthetase in L-asparaginase sensitivity.
Conclusions:
- The study establishes a comprehensive DNA copy number database for cancer cell lines, facilitating exploration of DNA-transcript-drug relationships.
- Findings suggest L-asparaginase as a potential therapeutic agent for ovarian cancers characterized by low asparagine synthetase levels.
- This pharmacogenomic approach provides a valuable resource for future cancer research and drug development.
