title: Emerging issues of the expression profiling technologies for the study of gynecologic cancer.
abstract: Evaluation of the prognostic parameters of gynecologic cancer has shown their failure for classification according to the clinical behavior or the prediction of its outcome. This weakness has important implications on prognosis and treatment. The increasing understanding of the complexity of the human genome, coupled with the development of high throughput analysis techniques and bioinformatics tools, has changed our concepts on cancer biology, by shifting our targets to a global analysis of the transcriptome and the proteome, linking genes and their products into functional pathways. These approaches permit the documentation of expression patterns of thousands of genes within a cell. With the use of DNA microarray technology, it is feasible to identify signature patterns of expression in tumor samples that faithfully correlate with its biology, providing accurate prognosis for each cancer patient and thus a rational customized treatment. At this stage, there is a need for systematic studies for the validation of these novel approaches. In this review, we provide a basic background of the concept of the technology, highlight several emerging issues from their applications on gynecologic cancer, discuss a series of important themes and problems regarding their interpretation and relevance for the clinicians, and comment on future areas of research.
authors.affiliation: First Department of Obstetrics and Gynecology, University of Athens School of Medicine, Athens, Greece. kpappa@imbb.forth.gr
authors.forename: Kalliopi I
authors.initials: KI
authors.lastname: Pappa
authors.forename: Nicholas P
authors.initials: NP
authors.lastname: Anagnou
mesh_terms: D019295:Computational Biology; D016889:Endometrial Neoplasms / Q000175:diagnosis / Q000235:genetics; D005260:Female; D020869:Gene Expression Profiling; D005833:Genital Neoplasms, Female / Q000175:diagnosis* / Q000235:genetics*; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis / Q000235:genetics