Prognostic gene network modules in breast cancer hold promise
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* Corresponding authors: Andrew E Teschendorff a.teschendorff@ucl.ac.uk - Carlos Caldas carlos.caldas@cancer.org.uk
1 Medical Genomics Group, Paul O'Gorman Building, UCL Cancer Institute, University College London, 72 Huntley Street, London WC1E 6BT, UK
2 Breast Cancer Functional Genomics Laboratory, Cancer Research UK Cambridge Research Institute and Department of Oncology University of Cambridge, Li KaShing Centre, Robinson Way, Cambridge CB2 0RE, UK
3 Cambridge Breast Unit and NIHR Biomedical Research Centre, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Cambridge CB2 2QQ, UK
Breast Cancer Research 2010, 12:317 doi:10.1186/bcr2774
Published: 8 December 2010Abstract
A substantial proportion of lymph node-negative patients who receive adjuvant chemotherapy do not derive any benefit from this aggressive and potentially toxic treatment. However, standard histopathological indices cannot reliably detect patients at low risk of relapse or distant metastasis. In the past few years several prognostic gene expression signatures have been developed and shown to potentially outperform histopathological factors in identifying low-risk patients in specific breast cancer subgroups with predictive values of around 90%, and therefore hold promise for clinical application. We envisage that further improvements and insights may come from integrative expression pathway analyses that dissect prognostic signatures into modules related to cancer hallmarks.