Genome-wide expression profiles can be produced from endometrial cancer samples. With the help of bioinformatic tools, these expression profiles can be used to cluster tumour samples into biologically relevant groups. These specific groups can be linked to pathological staging of the tumours, progesterone receptor status of the samples, clinical outcome of therapy and other clinically relevant data (e.g. radiotherapy). This way a classifier is built. From literature it is known that excessive estrogen signalling induces endometrial cancer. Furthermore, approximately 50% of patient samples will harbour PTEN mutations; Wnt-signalling will be activated in 25-40% of cases; growth factor signalling (ErbB) is elevated in 30% of cases; P53 mutations will be found in 20% of the samples; and the progesterone receptor is lost from most recurrent cancers. Using molecular tools, these pathways (ER, PTEN, WNT, ErbB, P53, PR) can be analysed in the endometrial cancer sample-expression profiles, and genes, or clusters of genes, involved in these pathways can be identified. These genes and clusters of genes are the best putative targets for future therapies.

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Keywords Endometrium, ER, Gene profiling, Pathway, PR
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Blok, L.J, & Burger, C.W. (2005). Investigations into the molecular background of endometrial cancer. doi:10.1016/j.ics.2004.12.036