Literature DB >> 20436504

Classification and prognosis of invasive breast cancer: from morphology to molecular taxonomy.

Stuart J Schnitt1.   

Abstract

For many years, patient age, axillary lymph node status, tumor size, histological features (especially histological grade and lymphovascular invasion), hormone receptor status, and HER2 status have been the major factors used to categorize patients with breast cancer in order to assess prognosis and determine the appropriate therapy. These factors are most often viewed in combination to group patients into various risk categories. Although these risk categories are useful for assessing prognosis and risk in groups of patients with breast cancer, their role in determining prognosis and evaluating risk in an individual patient is more limited. Therefore, better methods are required to help assess prognosis and determine the most appropriate treatment for patients on an individual basis. Recently, various molecular techniques, particular gene expression profiling, have been increasingly used to help refine breast cancer classification and to assess prognosis and response to therapy. Although the precise role of these newer techniques in the daily management of patients with breast cancer continues to evolve, it is clear that they have the potential to provide value above and beyond that provided by the traditional clinical and pathological prognostic and predictive factors.

Entities:  

Mesh:

Year:  2010        PMID: 20436504     DOI: 10.1038/modpathol.2010.33

Source DB:  PubMed          Journal:  Mod Pathol        ISSN: 0893-3952            Impact factor:   7.842


  130 in total

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Journal:  Cell Oncol (Dordr)       Date:  2017-11-27       Impact factor: 6.730

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Journal:  Tumour Biol       Date:  2014-01-09

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7.  Taxonomy of breast cancer based on normal cell phenotype predicts outcome.

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10.  PTP1B promotes aggressiveness of breast cancer cells by regulating PTEN but not EMT.

Authors:  Xue Liu; Qian Chen; Xu-Gang Hu; Xian-Chao Zhang; Ti-Wei Fu; Qing Liu; Yan Liang; Xi-Long Zhao; Xia Zhang; Yi-Fang Ping; Xiu-Wu Bian
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