Literature DB >> 21654357

Modern classification of breast cancer: should we stick with morphology or convert to molecular profile characteristics.

Emad A Rakha1, Ian O Ellis.   

Abstract

Breast cancer represents a heterogeneous group of tumors with varied morphologic and biological features, behavior, and response to therapy. The present routine clinical management of breast cancer relies on the availability of robust prognostic and predictive factors to support decision making. Breast cancer patients are stratified into risk groups based on a combination of classical time-dependent prognostic variables (staging) and biological prognostic and predictive variables. Staging variables include tumor size, lymph node stage, and extent of tumor spread. Classical biological variables include morphologic variables such as tumor grade and molecular markers such as hormone receptor and human epidermal growth factor receptor 2 status. Although individual molecular markers were introduced in the field of breast cancer management many years ago, the concept of molecular classification was raised after the introduction of global gene expression profiling and the identification of multigene classifiers. Although there is no doubt that gene expression profiling technology has revolutionized the field of breast cancer research and have been widely expected to improve breast cancer prognostication, the unprecedented speed of progress and publicity associated with the introduction of these commercially-based multigene classifiers should not lead us to expect this technology to replace the classical classification systems. These multigene classifiers have the potential to complement traditional methods through provision of additional biological prognostic and predictive information in presently indeterminate risk groups. Here we present updated information on the present clinical value of classical clinicopathologic factors, molecular taxonomy, and multigene classifiers in routine patients management and provide some critical views and practical expectations.

Entities:  

Mesh:

Year:  2011        PMID: 21654357     DOI: 10.1097/PAP.0b013e318220f5d1

Source DB:  PubMed          Journal:  Adv Anat Pathol        ISSN: 1072-4109            Impact factor:   3.875


  24 in total

1.  Immunohistochemistry profiles of breast ductal carcinoma: factor analysis of digital image analysis data.

Authors:  Arvydas Laurinavicius; Aida Laurinaviciene; Valerijus Ostapenko; Darius Dasevicius; Sonata Jarmalaite; Juozas Lazutka
Journal:  Diagn Pathol       Date:  2012-03-16       Impact factor: 2.644

Review 2.  Biological subtypes of breast cancer: Prognostic and therapeutic implications.

Authors:  Ozlem Yersal; Sabri Barutca
Journal:  World J Clin Oncol       Date:  2014-08-10

3.  Measures of outcome in metastatic breast cancer: insights from a real-world scenario.

Authors:  Marta Bonotto; Lorenzo Gerratana; Elena Poletto; Pamela Driol; Manuela Giangreco; Stefania Russo; Alessandro M Minisini; Claudia Andreetta; Mauro Mansutti; Federica E Pisa; Gianpiero Fasola; Fabio Puglisi
Journal:  Oncologist       Date:  2014-05-02

4.  Biological heterogeneity of primary cancer-associated fibroblasts determines the breast cancer microenvironment.

Authors:  Marika Musielak; Oliwia Piwocka; Katarzyna Kulcenty; Karolina Ampuła; Beata Adamczyk; Igor Piotrowski; Magdalena Fundowicz; Marta Kruszyna-Mochalska; Wiktoria M Suchorska; Julian Malicki
Journal:  Am J Cancer Res       Date:  2022-09-15       Impact factor: 5.942

5.  The Prognosis and Predictive Value of Estrogen Negative/Progesterone Positive (ER-/PR+) Phenotype: Experience of 1159 Primary Breast Cancer from a Single Institute.

Authors:  S Gamrani; S Boukansa; Z Benbrahim; N Mellas; F Fdili Alaoui; M A Melhouf; C Bouchikhi; A Banani; M Boubbou; T Bouhafa; H El Fatemi
Journal:  Breast J       Date:  2022-05-17       Impact factor: 2.269

6.  Diffusion magnetic resonance imaging in breast cancer characterisation: correlations between the apparent diffusion coefficient and major prognostic factors.

Authors:  Paolo Belli; Melania Costantini; Enida Bufi; Giuseppe Giovanni Giardina; Pierluigi Rinaldi; Gianluca Franceschini; Lorenzo Bonomo
Journal:  Radiol Med       Date:  2014-08-06       Impact factor: 3.469

7.  Molecular classification of breast cancer.

Authors:  Darina Vuong; Peter T Simpson; Benjamin Green; Margaret C Cummings; Sunil R Lakhani
Journal:  Virchows Arch       Date:  2014-05-31       Impact factor: 4.064

8.  Anti-Phosphohistone H3-Positive Mitoses Are Linked to Pathological Response in Neoadjuvantly Treated Breast Cancer.

Authors:  Sylvia Timme; Martin Sillem; Peter Bronsert; Lioudmila Bogatyreva; Dieter Hauschke; Axel Zur Hausen; Martin Werner; Elmar Stickeler
Journal:  Breast Care (Basel)       Date:  2017-08-02       Impact factor: 2.860

9.  Infrequent loss of luminal differentiation in ductal breast cancer metastasis.

Authors:  Julia Calvo; Lourdes Sánchez-Cid; Montserrat Muñoz; Juan José Lozano; Timothy M Thomson; Pedro L Fernández
Journal:  PLoS One       Date:  2013-10-21       Impact factor: 3.240

10.  Dual-color fluorescence in situ hybridization reveals an association of chromosome 8q22 but not 8p21 imbalance with high grade invasive breast carcinoma.

Authors:  Logan C Walker; Margaret McDonald; J Elisabeth Wells; Gavin C Harris; Bridget A Robinson; Christine M Morris
Journal:  PLoS One       Date:  2013-07-25       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.