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      • Department of Molecular Biology and Genetics
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      Functional genomics in translational cancer research: focus on breast cancer

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      Author(s)
      Yulug, I. G.
      Gur-Dedeoglu, B.
      Date
      2008
      Source Title
      Briefings in Functional Genomics and Proteomics
      Print ISSN
      1473-9550
      Publisher
      Oxford University Press
      Volume
      7
      Issue
      1
      Pages
      1 - 7
      Language
      English
      Type
      Article
      Item Usage Stats
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      Abstract
      Conventional molecular and genetic methods for studying cancer are limited to the analysis of one locus at a time. A cluster of genes that are regulated together can be identified by DNA microarray, and the functional relationships can uncover new aspects of cancer biology. Breast cancer can be used to provide a model to demonstrate the current approaches to the molecular analysis of cancer. Meta-analysis is an important tool for the identification and validation of differentially expressed genes to increase power in clinical and biological studies across different sets of data. Recently, meta-analysis approaches have been applied to large collections of microarray datasets to investigate molecular commonalities of multiple cancer types not only to find the common molecular pathways in tumour development but also to compare the individual datasets to other cancer datasets to identify new sets of genes. Several investigators agree that microarray results should be validated. One commonly used method is quantitative reverse transcription PCR (qRT-PCR) to validate the expression profiles of the target genes obtained through microarray experiments. qRT-PCR is attractive for clinical use, since it can be automated and performed on fresh or archived formalin-fixed, paraffin-embedded tissue samples. The outcome of these analyses might accelerate the application of basic research findings into daily clinical practice through translational research and may have an impact on foreseeing the clinical outcome, predicting tumour response to specific therapy, identification of new prognostic biomarkers, discovering targets for the development of novel therapies and providing further insights into tumour biology. © The Author 2008. Published by Oxford University Press.
      Keywords
      Breast cancer
      Functional genomics
      Gene expression
      Meta-analysis
      Microarrays
      qRT-PCR
      Biological marker
      DNA
      Permalink
      http://hdl.handle.net/11693/23233
      Published Version (Please cite this version)
      http://dx.doi.org/10.1093/bfgp/eln009
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