Several technologies now exist that allow the simultaneous evaluation of the amount of RNA produced by each cellular gene. Application of these technologies to measure transcriptional activity in cancer cells has provided a rich source of information that is being used to understand tumor biology. Analysis of the resulting gene expression data has evolved from the identification of individual gene expression differences between tumor and non-diseased cells to model-based evaluation of complex signal transduction pathways. Pathway-based models that utilize gene expression data have yielded new insights into tumor cell biology by more accurately describing both pleiotropic and polygenic cell processes. Further description and integration of gene expression-based models will be critical to fully exploit the information contained in gene expression data and to develop a more in-depth understanding of tumor cell development and progression. © 2010 Springer Science+Business Media B.V.
CITATION STYLE
Klomp, J. A., Teh, B. T., & Furge, K. A. (2010). An integrated oncogenomic approach: From genes to pathway analyses. In An Omics Perspective on Cancer Research (pp. 31–50). Springer Netherlands. https://doi.org/10.1007/978-90-481-2675-0_3
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