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Updated: Jun 6, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Prognostic gene network modules in breast cancer hold promise
Andrew E Teschendorff1, Yan Jiao, Carlos Caldas
1Medical Genomics Group, Paul O'Gorman Building, UCL Cancer Institute, University College London, London WC1E 6BT, UK. a.teschendorff@ucl.ac.uk
Abstract:
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.
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