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p53 status identifies two subgroups of triple-negative breast cancers with distinct biological features

Biganzoli, Elia, Coradini, Danila, Ambrogi, Federico, Garibaldi, Jonathan M., Lisboa, Paulo, Soria, Daniele, Green, Andrew R., Pedriali, Massimo, Piantelli, Mauro, Querzoli, Patrizia, and others. (2011) p53 status identifies two subgroups of triple-negative breast cancers with distinct biological features. Japanese Journal of Clinical Oncology, 41 (2). pp. 172-179. ISSN 0368-2811. E-ISSN 1465-3621. (doi:10.1093/jjco/hyq227) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:98901)

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Objective: Despite the clinical similarities triple-negative and basal-like breast cancer are not synonymous. Indeed, not all basal-like cancers are negative for estrogen receptor, progesterone receptor and HER2 expression while triple-negative also encompasses other cancer types. P53 protein appears heterogeneously expressed in triple-negative breast cancers, suggesting that it may be associated with specific biological subgroups with a different outcome. Methods: We comparatively analyzed p53 expression in triple-negative tumors from two independent breast cancer case series (633 cases from the University of Ferrara and 1076 cases from the University of Nottingham). Results: In both case series, p53 protein expression was able to subdivide the triple-negative cases into two distinct subsets consistent with a different outcome. In fact, triple-negative patients with a p53 expressing tumor showed worse overall and event-free survival. Conclusions: The immunohistochemical evaluation of p53 expression may help in taming the currently stormy relationship between pathological (triple-negative tumors) and biological (basal breast cancers) classifications and in selecting patient subgroups with different biological features providing a potentially powerful prognostic contribution in triple-negative breast cancers. © The Author (2011). Published by Oxford University Press. All rights reserved.

Item Type: Article
DOI/Identification number: 10.1093/jjco/hyq227
Uncontrolled keywords: breast cancer, triple-negative, prognosis, biological marker
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Funders: University of Nottingham (
Depositing User: Daniel Soria
Date Deposited: 08 Dec 2022 10:19 UTC
Last Modified: 09 Dec 2022 13:19 UTC
Resource URI: (The current URI for this page, for reference purposes)

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