The Center for Alternatives to Animal Testing is an academic center affiliated with the Division of Toxicological Sciences in the Department of Environmental Health Sciences of the Johns Hopkins University Bloomberg School of Public Health.
February 25-26
Hyatt Fair Lakes Hotel
12777 Fair Lakes Circle
Fairfax, VA
Program Committee:
Richard A. Becker, American Chemistry Council
Alan M. Goldberg, Johns Hopkins University
Pamela J. Lein, Johns Hopkins University
Ellen K. Silbergeld, Johns Hopkins University
Gary Timm, US Environmental Protection Agency
James D. Yager, Johns Hopkins University
Bernard Robaire
McGill University
Kevin Gaido
CIIT
Barbara Hales
McGill University

Sequencing of genomes (human, mouse, rat, Drosophila) gives us a map, but doesn't tell us where to go.
Another critical issue is understanding how genes are turned on or off. Methylation and acetylation of DNA are important mechanisms for regulating transcription of specific genes, and methods for studying methylation are improving rapidly. Histones are also critical in determining which stretches of DNA are available for transcription.
Genomics currently focuses primarily on analyzing RNA expression. Data acquisition is relatively straightforward and consists of expression profiling, cDNA arrays or ESTs. The medium used can vary. It is possible to examine up to 8000 sequences at once with a plastic array. Tissue specific arrays are being developed, which would be particularly useful in ED screening and testing (e.g., could examine gene expression in testes vs. prostate, etc.)
The most difficult aspect of genomics is data analysis and interpretation. It is easy to get data from arrays - but then what do you do with it? Cluster analysis? Some statisticians feel that normalized stats are not appropriate for analyzing array data. Every 2-3 months there seems to be a new approach. One need that must be addressed before this methodology can be applied to ED screening and testing is a unified approach to data analysis and interpretation.
Other technical questions include storage and retrieval of data. Some advocate standard structure, others recommend putting the data on web sites. Who owns the data? How can you effectively share the data without losing ownership?
The methodology used in proteomics consists of resolving a protein mixture on 2-D gels and then identifying specific proteins in the resultant spots. This methodology is rapidly evolving. Problems associated with the methodology include post-translational modification of proteins that can alter their migration patterns in gels (and thus different spots are not necessarily different proteins) and protein-protein interactions. Questions exist concerning whether or not this tool is too sensitive to use for standardized screening and testing. At the moment, it is difficult to classify the data.
Another approach to proteomics involves antibody arrays. These are commercially available; however, this methodology has many of the same problems observed with genomics, e.g., data analysis, interpretation, storage and retrieval. A relatively novel approach to proteomics involves analyzing expression pattern of transcription factors, which is done by examining binding of proteins to DNA, e.g., analyzing protein-DNA interactions. This method is also evolving rapidly.
Summary of techniques: if you know what your targets are, use non-array techniques; if you have a discovery question, use arrays.
Endpoints particularly amenable to genomics and proteomics:
Suggested Applications in ED screening and testing:
Approaches to determining sensitivity and specificity:
Issues pertaining to validation and standardization: