David Housman, Ph.D.

Department of Biology
Professor of Biology
Center for Cancer Research

Room E18-521
617-253-3013 (phone)

Biosketch

Ph.D. - 1971 Biology Brandeis University

Research Summary

Pharmacogenetic Effects on Drug Response and Toxicity
Goal: We are interested in developing a system that includes cell-based screening of compounds using cells derived from different genetic backgrounds (virtual patients), combined with rapid genotyping to identify genetic markers linked to drug response and toxicity. This system can be used, along with conventional preclinical profiling methods, to qualify drug candidates before they are advanced to expensive clinical trials.

The discovery and development of novel drugs to treat human diseases is an arduous and expensive undertaking. One daunting challenge at the clinical stage arises from the fact that human subjects, unlike most preclinical models, exhibit considerable variation in pharmacologically important characteristics such as drug metabolism. Consequently, what constitutes a safe and effective dose for one patient may be neither safe nor effective in another patient. Studies of intra vs. inter-subject variation in twins and unrelated subjects suggest that a significant portion of the observed inter-individual heterogeneity in drug response is genetically determined. The genetic contribution to variable drug response was first described over four decades ago, but widespread efforts to identify the genetic basis of this variation began about five years ago. Moreover, much of this research focused on previously recognized functional polymorphisms to analyze the effect of one or several known polymorphisms in one (or a few) candidate genes. The clinical trial population in these studies invariably consists of unrelated patients, and the drug response phenotypes are usually standard clinical endpoints. While some important new associations between DNA polymorphism and drug response have been discovered using this approach, the overall progress has been disappointing, particularly in view of the significant resources expended. Furthermore, current methodologies are limited because of their genetic and environmental heterogeneity that obscures effects of specific polymorphisms on drug response.

We propose here to develop a new system purpose-built for investigation of genetic effects on drug response. The cell-based systems is designed to increase throughput and speed of genotyping assays (SNP analysis) and to reduce the heterogeneity of the study (genetic and environmental). In addition, the approach can be expanded to include related individuals and assess inheritance patterns of pharmacological traits. Finally, the usefulness of the system can be increased by using established cell lines where high-density genetic maps already exist (e.g. the CEPH pedigrees) so that powerful statistical tools for analysis of inheritance of complex traits can be instantly brought to bear on pharmacogenetic data, without the necessity of extensive additional genotyping.
Proof-of-concept: The model assay and genotyping system will be used to detect complex genetic markers rapidly, with high sensitivity and at low cost and link them to pharmacological response. Initial experiments will test the characteristics of the system by measuring its sensitivity of detecting known pharmacogenetic effects – that is, drugs that interact with functional polymorphisms in well characterized genes. These model cases will be used to optimize the performance of the system.

Applications: Subsequently, drugs with less well understood genetics will be investigated. Since the most extensive panels of cell lines from genetically mapped pedigrees are B-lymphoblastoid cell lines, experiments will be designed to analyze the genetics of traditional anti-neoplastic, immunosuppressive and immunomodulatory drugs in those cells. In addition, in collaboration with other CSBi investigators, we will develop innovative methods and devices for measuring and quantifying pharmacological responses in cells. This includes refinement of statistical methods for detecting genotype-phenotype interactions and pharmacogenetic analysis of small libraries of related compounds, in order to identify genes that interact with specific compounds. The proposed studies will lead to a better understanding of the genetic determinants of inter-patient variation in drug response.

Selected Publications

  • Shearman AM, Cupples LA, Demissie S, Peter I, Schmid CH, Karas RH, Mendelsohn ME, Housman DE, Levy D. Association between estrogen receptor alpha gene variation and cardiovascular disease. JAMA. 2003 Nov 5; 290(17): 2263-70.
  • Apostol BL, Kazantsev A, Raffioni S, Illes K, Pallos J, Bodai L, Slepko N, Bear JE, Gertler FB, Hersch S, Housman DE, Marsh JL, Thompson LM. A cell-based assay for aggregation inhibitors as therapeutics of polyglutamine-repeat disease and validation in Drosophila. Proc Natl Acad Sci U S A. 2003 May 13; 100(10): 5950-5. Epub 2003 May 01.
  • Charest A, Lane K, McMahon K, Park J, Preisinger E, Conroy H, Housman D. Fusion of FIG to the receptor tyrosine kinase ROS in a glioblastoma with an interstitial del(6)(q21q21). Genes Chromosomes Cancer. 2003 May; 37(1): 58-71.
  • Jordan B, Charest A, Dowd JF, Blumenstiel JP, Yeh Rf RF, Osman A, Housman DE, Landers JE. Genome complexity reduction for SNP genotyping analysis. Proc Natl Acad Sci U S A. 2002 Mar 5; 99(5): 2942-7.

Last Updated: April 16, 2008