Literature DB >> 10481944

Pathobiologic identification of two distinct breast carcinoma subsets with diverging clinical behaviors.

S Ménard1, P Casalini, G Tomasic, S Pilotti, N Cascinelli, R Bufalino, F Perrone, C Longhi, F Rilke, M I Colnaghi.   

Abstract

Many different pathological and biological variables which characterize breast carcinomas have been found to be associated. The aim of this work was to analyze the complex relationship among these parameters. The pathologic, biologic, and clinical characteristics of a series of primary breast carcinomas from 676 patients were retrospectively investigated. Multiple correspondence analysis of 13 factors revealed clustering of eight pathobiologic variables, that is histologic grade, necrosis, lymphoid infiltration, number of mitoses, c-erbB-2 overexpression, p53, progesterone receptor, and bcl2 expression. An index for each tumor calculated on the basis of these eight factors served to distinguish two different tumor phenotypes, designated A and B. Phenotype A is represented by tumors sharing most of the biologic features of normal breast tissues: indeed, these tumors are characterized by a relatively high degree of differentiation, low proliferation, no necrosis or leukocyte infiltration, and no gene alterations. By contrast, phenotype B is quite divergent from the normal tissue because of its poor differentiation, high proliferation, frequent gene alterations and evidence of a host immune reaction. As regards the disease progression, these two subsets showed marked differences: phenotype A tumors had a low recurrence rate per year that remained constant over time and affected more frequently elderly patients, whereas group B tumors showed high aggressivity in the first years after surgery followed by a low long-term recurrence rate and were more frequently seen in younger patients. These data suggest that breast carcinoma consists of two different subsets that can be identified on the basis of pathobiologic features.

Entities:  

Mesh:

Substances:

Year:  1999        PMID: 10481944     DOI: 10.1023/a:1006262324959

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  8 in total

Review 1.  Mouse Mammary Tumor Virus (MMTV) and MMTV-like Viruses: An In-depth Look at a Controversial Issue.

Authors:  Francesca Parisi; Giulia Freer; Chiara Maria Mazzanti; Mauro Pistello; Alessandro Poli
Journal:  Viruses       Date:  2022-05-06       Impact factor: 5.818

2.  Level of HER2/neu gene amplification as a predictive factor of response to trastuzumab-based therapy in patients with HER2-positive metastatic breast cancer.

Authors:  Giuseppe Gullo; Daniela Bettio; Valter Torri; Giovanna Masci; Piermario Salvini; Armando Santoro
Journal:  Invest New Drugs       Date:  2008-07-29       Impact factor: 3.850

3.  Role of hormonal risk factors in HER2-positive breast carcinomas.

Authors:  A Balsari; P Casalini; R Bufalino; F Berrino; S Ménard
Journal:  Br J Cancer       Date:  2003-04-07       Impact factor: 7.640

4.  Prognostic significance of deregulated dicer expression in breast cancer.

Authors:  Emer Caffrey; Helen Ingoldsby; Deirdre Wall; Mark Webber; Kate Dinneen; Laura S Murillo; Celine Inderhaug; John Newell; Sanjeev Gupta; Grace Callagy
Journal:  PLoS One       Date:  2013-12-30       Impact factor: 3.240

Review 5.  HER2 amplification level is not a prognostic factor for HER2-positive breast cancer with trastuzumab-based adjuvant treatment: a systematic review and meta-analysis.

Authors:  Qian-Qian Xu; Bo Pan; Chang-Jun Wang; Yi-Dong Zhou; Feng Mao; Yan Lin; Jing-Hong Guan; Song-Jie Shen; Xiao-Hui Zhang; Ya-Li Xu; Ying Zhong; Xue-Jing Wang; Yan-Na Zhang; Qiang Sun
Journal:  Oncotarget       Date:  2016-09-27

6.  T-cell metagene predicts a favorable prognosis in estrogen receptor-negative and HER2-positive breast cancers.

Authors:  Achim Rody; Uwe Holtrich; Laos Pusztai; Cornelia Liedtke; Regine Gaetje; Eugen Ruckhaeberle; Christine Solbach; Lars Hanker; Andre Ahr; Dirk Metzler; Knut Engels; Thomas Karn; Manfred Kaufmann
Journal:  Breast Cancer Res       Date:  2009-03-09       Impact factor: 6.466

7.  Interactions between immunity, proliferation and molecular subtype in breast cancer prognosis.

Authors:  Srikanth Nagalla; Jeff W Chou; Mark C Willingham; Jimmy Ruiz; James P Vaughn; Purnima Dubey; Timothy L Lash; Stephen J Hamilton-Dutoit; Jonas Bergh; Christos Sotiriou; Michael A Black; Lance D Miller
Journal:  Genome Biol       Date:  2013-04-29       Impact factor: 13.583

8.  Altered monocyte differentiation and macrophage polarization patterns in patients with breast cancer.

Authors:  Chih-Hsing Hung; Fang-Ming Chen; Yi-Ching Lin; Mei-Lan Tsai; Shih-Ling Wang; Yen-Chun Chen; Yi-Ting Chen; Ming-Feng Hou
Journal:  BMC Cancer       Date:  2018-04-03       Impact factor: 4.430

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.