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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Official URL: https://doi.org/10.1093/jjco/hyq227 |
Abstract
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 |
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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 (https://ror.org/01ee9ar58) |
Depositing User: | Daniel Soria |
Date Deposited: | 08 Dec 2022 10:19 UTC |
Last Modified: | 05 Nov 2024 13:04 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/98901 (The current URI for this page, for reference purposes) |
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