Affiliations: Institute of Statistics and Decision Sciences, Duke
University, Durham, NC, USA | Department of Genetics, Howard Hughes Medical
Institute, Duke University Medical Center, Durham, NC, USA | Department of Experimental Surgery, Duke University
Medical Center, Durham, NC, USA
Abstract: We have developed a complete statistical model for the analysis of
tumor specific gene expression profiles. The approach provides investigators
with a global overview on large scale gene expression data, indicating aspects
of the data that relate to tumor phenotype, but also summarizing the
uncertainties inherent in classification of tumor types. We demonstrate the use
of this method in the context of a gene expression profiling study of 27 human
breast cancers. The study is aimed at defining molecular characteristics of
tumors that reflect estrogen receptor status. In addition to good predictive
performance with respect to pure classification of the expression profiles, the
model also uncovers conflicts in the data with respect to the classification of
some of the tumors, highlighting them as critical cases for which additional
investigations are appropriate.
