Genomic Tools Identify Profiles of Gene Activity Underlying Cancer

We are just beginning to see the predictive value of gene expression data that reflects gene activity in determining how a tumor will fare under a particular therapy,' said study co-author Mike West, Ph.D., Arts & Sciences professor of statistics and decision sciences at Duke University. This new study focuses on specific gene networks known to contribute to a wide variety of human cancers including those of the breast, lung, and colon. The team analyzed information from microarrays to explore changes in the activity of genes and identify clusters of genes, which the Duke team has dubbed metagenes, whose increase or decrease in mRNA levels differed between normal cells and those with increased activity in particular cancer-related genes. These metagene profiles were then used in a statistical model to predict the activity of other genes controlled by the oncogenes. They found that their genetic model accurately identified cells in which the pathways were active.

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