Title: "Functional analysis reveals the biological underpinnings of predictive genomic signatures"
Speaker:Yuri Nikolsky, Ph.D.; GeneGo, Inc., 500 Renaissance Drive, St. Joseph, MI 49085
Place: LILLY G126; September 21, 2010, Tuesday, 4:30pm


Gene expression signatures of toxicity and clinical response benefit both safety assessment and clinical practice. However, difficulties in understanding the association of the signatures to the predicted endpoints have limited their application. Lead by FDA, the Microarray Quality Control (MAQC) II project generated 262 predictive "gene signatures" for ten clinical and three toxicological endpoints from six gene expression datasets by over 30 expression analysis teams. A comprehensive functional analysis of these signatures and their non-redundant unions was conducted using ontology enrichment, biological network building and interactome connectivity analyses. Different signatures for a given endpoint were more similar at the level of biological entities and transcriptional control than at the gene level. Signatures tended to be enriched in function and pathway in an endpoint and model-specific manner, and showed a topological bias for incoming interactions. Importantly, the level of biological similarity between different signatures correlated positively with the accuracy of the signature predictions. These findings will impact the design, understanding, and application of predictive genomic signatures and support their broader application in predictive medicine.
Associated Reading:
Shi W., Tsyganova M., Dosymbekov D., Dezso Z., Nikolskaya T. Dudoladova M. Serebryiskaya T., Guryanov A., Brennan R., Shah R., Dopazo J., Chen M., Deng Y. Shi Y., Jurman G., Furlanello G., Thomas R.S., Corton J.C.; Tong W., Shi L., Nikolsky Y. Functional analysis reveals the biological underpinnings of predictive genomic signatures. The Pharmacogenomics J., 2010, in press

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