281
Views
3
CrossRef citations to date
0
Altmetric
Research Article

Genome-Wide Association and Pharmacological Profiling of 29 Anticancer Agents Using Lymphoblastoid Cell Lines

, , , , , & show all
Pages 137-146 | Received 13 Aug 2013, Accepted 16 Oct 2013, Published online: 21 Jan 2014
 

Abstract

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.

Original submitted 16 August 2013; Revision submitted 16 October 2013

Financial & competing interests disclosure

This work was supported by NIH NCI grant number RO1CA161608. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Ethical conduct of research

The authors state that they have obtained appropriate institutional review board approval or have followed the principles outlined in the Declaration of Helsinki for all human or animal experimental investigations. In addition, for investigations involving human subjects, informed consent has been obtained from the participants involved.

Additional information

Funding

This work was supported by NIH NCI grant number RO1CA161608. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 99.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 303.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.