Basal keratin expression in breast cancer by quantification of mRNA and by immunohistochemistry

Definitions of basal-like breast cancer phenotype vary, and microarray-based expression profiling analysis remains the gold standard for the identification of these tumors. Immunohistochemical identification of basal-like carcinomas is hindered with a fact, that on microarray level not all of them express basal-type cytokeratin 5/6, 14 and 17. We compared expression of cytokeratin 5, 14 and 17 in 115 patients with operable breast cancer estimated by real-time RT-PCR and immunohistochemistry

New insights into the role of androgen and oestrogen receptors in molecular apocrine breast tumours

Two recent studies on a rare androgen-dependent form of breast cancer have shed light on the biology of luminal tumours and reinforced the view that interfering with androgen signalling may have a place in the therapy of some forms of breast cancer

A simple method for assigning genomic grade to individual breast tumours

<p>Abstract</p> <p>Background</p> <p>The prognostic value of grading in breast cancer can be increased with microarray technology, but proposed strategies are disadvantaged by the use of specific training data or parallel microscopic grading. Here, we investigate the performance of a method that uses no information outside the breast profile of interest.</p> <p>Results</p> <p>In 251 profiled tumours we optimised a method that achieves grading by comparing rank means for genes predictive of high and low grade biology; a simpler method that allows for truly independent estimation of accuracy. Validation was carried out in 594 patients derived from several independent data sets. We found that accuracy was good: for low grade (G1) tumors 83- 94%, for high grade (G3) tumors 74- 100%. In keeping with aim of improved grading, two groups of intermediate grade (G2) cancers with significantly different outcome could be discriminated.</p> <p>Conclusion</p> <p>This validates the concept of microarray-based grading in breast cancer, and provides a more practical method to achieve it. A simple R script for grading is available in an additional file. Clinical implementation could achieve better estimation of recurrence risk for 40 to 50% of breast cancer patients.</p

From normal cell types to malignant phenotypes

The phenotypic diversity of breast cancer has been proposed to result from different target cell types undergoing oncogenic transformation and giving rise to cancer stem cells. Global gene expression profiling revealed distinct molecular phenotypes and some of these signatures were held to reflect the cell of origin, with the basal carcinomas arising from basal/progenitor cells. Recent work challenges this view by providing evidence that luminal precursor cells are involved in the pathogenesis of basal breast cancers and has made new links between normal cell populations and molecular tumor phenotypes