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Updated: May 3, 2026
Assessing Specificity of Anticancer Drugs In Vitro
Published on: March 23, 2016
Genome-wide association and pharmacological profiling of 29 anticancer agents using lymphoblastoid cell lines
Chad C Brown1, Tammy M Havener, Marisa W Medina
1Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, NC 27607, USA.
Aim:
Association mapping with lymphoblastoid cell lines (LCLs) is a promising approach in pharmacogenomics research, and in the current study we utilized LCLs to perform association mapping for 29 chemotherapy drugs.
Materials & Methods:
Currently, we use LCLs to perform genome-wide association mapping of the cytotoxic response of 520 European-Americans to 29 different anticancer drugs; the largest LCL study to date. A novel association approach using a multivariate analysis of covariance design was employed with the software program MAGWAS, testing for differences in the dose-response profiles between genotypes without making assumptions about the response curve or the biologic mode of association. Additionally, by classifying 25 of the 29 drugs into eight families according to structural and mechanistic relationships, MAGWAS was used to test for associations that were shared across each drug family. Finally, a unique algorithm using multivariate responses and multiple linear regressions across pairs of response curves was used for unsupervised clustering of drugs.
Results:
Among the single-drug studies, suggestive associations were obtained for 18 loci, 12 within/near genes. Three of these, MED12L, CHN2 and MGMT, have been previously implicated in cancer pharmacogenomics. The drug family associations resulted in four additional suggestive loci (three contained within/near genes). One of these genes, HDAC4, associated with the DNA alkylating agents, shows possible clinical interactions with temozolomide. For the drug clustering analysis, 18 of 25 drugs clustered into the appropriate family.
Conclusion:
This study demonstrates the utility of LCLs in identifying genes that have clinical importance in drug response and for assigning unclassified agents to specific drug families, and proposes new candidate genes for follow-up in a large number of chemotherapy drugs.
Insights
This study used lymphoblastoid cell lines (LCLs) to map gene associations with responses to 29 chemotherapy drugs, identifying potential new drug targets and classifying drug families.
Area of Science:
- Pharmacogenomics
- Genetics
- Cancer Research
Background:
- Lymphoblastoid cell lines (LCLs) are valuable tools in pharmacogenomics.
- Understanding individual responses to chemotherapy is crucial for personalized medicine.
Purpose of the Study:
- To perform genome-wide association mapping for the cytotoxic response to 29 anticancer drugs using LCLs.
- To identify genetic loci associated with drug response and shared across drug families.
- To cluster drugs based on their response profiles.
Main Methods:
- Utilized LCLs from 520 European-Americans for genome-wide association mapping.
- Employed a novel multivariate analysis of covariance approach with MAGWAS software.
- Classified drugs into families and performed unsupervised clustering using multivariate responses and multiple linear regressions.
Main Results:
- Identified 18 suggestive loci for single-drug associations, including previously implicated genes MED12L, CHN2, and MGMT.
- Found four additional suggestive loci for drug family associations, with HDAC4 linked to DNA alkylating agents.
- Successfully clustered 18 of 25 drugs into their appropriate families.
Conclusions:
- LCLs are effective for identifying clinically relevant genes in drug response.
- The study proposes new candidate genes for chemotherapy drug response.
- This approach aids in assigning unclassified drugs to specific families.
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