Overexpression of HER2 is an important prognostic marker, and the only predictive biomarker of response to HER2-targeted therapies in invasive breast cancer. HER2-HER3 dimer has been shown to drive proliferation and tumor progression, and targeting of this dimer with pertuzumab alongside chemotherapy and trastuzumab, has shown significant clinical utility. The purpose of this study was to accurately quantify HER2-HER3 dimerisation in formalin fixed paraffin embedded (FFPE) breast cancer tissue as a novel prognostic biomarker.
View Article and Find Full Text PDFBreast cancer heterogeneity demands that prognostic models must be biologically driven and recent clinical evidence indicates that future prognostic signatures need evaluation in the context of early compared with late metastatic risk prediction. In pre-clinical studies, we and others have shown that various protein-protein interactions, pertaining to the actin microfilament-associated proteins, ezrin and cofilin, mediate breast cancer cell migration, a prerequisite for cancer metastasis. Moreover, as a direct substrate for protein kinase Cα, ezrin has been shown to be a determinant of cancer metastasis for a variety of tumour types, besides breast cancer; and has been described as a pivotal regulator of metastasis by linking the plasma membrane to the actin cytoskeleton.
View Article and Find Full Text PDFHerein we discuss how FRET imaging can contribute at various stages to delineate the function of the proteome. Therefore, we briefly describe FRET imaging techniques, the selection of suitable FRET pairs and potential caveats. Furthermore, we discuss state-of-the-art FRET-based screening approaches (underpinned by protein interaction network analysis using computational biology) and preclinical intravital FRET-imaging techniques that can be used for functional validation of candidate hits (nodes and edges) from the network screen, as well as measurement of the efficacy of perturbing these nodes/edges by short hairpin RNA (shRNA) and/or small molecule-based approaches.
View Article and Find Full Text PDFGenomics and proteomics will improve outcome prediction in cancer and have great potential to help in the discovery of unknown mechanisms of metastasis, ripe for therapeutic exploitation. Current methods of prognosis estimation rely on clinical data, anatomical staging and histopathological features. It is hoped that translational genomic and proteomic research will discriminate more accurately than is possible at present between patients with a good prognosis and those who carry a high risk of recurrence.
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