Literature DB >> 27651157

Breast cancer classification and prognostication through diverse systems along with recent emerging findings in this respect; the dawn of new perspectives in the clinical applications.

Vida Pourteimoor1, Samira Mohammadi-Yeganeh2,3, Mahdi Paryan4.   

Abstract

Breast cancer is the most common malignancy among women and the second leading cause of mortality due to cancer worldwide. The complexity of breast cancer resembles an intricate ecosystem comprising various cleverly designed interaction levels of internal and external factors to generate a pliable context in the clonal evolution of breast cancer cells. Principally, the complex entity can become evident toward delineating a number of significant variations in the specific fields of breast cancer analyses, including the molecular, physiological, and morphological characteristics, clinical presentations, risk factors, the histopathological conditions, and response to systemic therapy regarding the maintenance of tumor as a whole. In hindsight, various classification systems developing based on specific inclusion criteria have indisputably changed both our appreciation of the biological demeanor of breast cancer and the main strategies for designing tailored therapy regimens through the proper evaluation of diagnosis and prognostication of given specimens. Here, we endeavor to provide a general overview of different types of breast cancer classification as well as the clinical acceptance of their applications along with the latest findings in this area. Taken together, the major significance of breast cancer management that can be ascertained by operational convergent points of its stratification areas is owing to the fact that the achievement of individualized and targeted therapy may denounce new horizons of surveillance and treatment strategies in which they may function as a rheostat of specific therapy regimens toward reducing the detected distances between experimental data and operating options in clinical practice.

Entities:  

Keywords:  Breast cancer; Breast cancer subtypes; Classification systems

Mesh:

Substances:

Year:  2016        PMID: 27651157     DOI: 10.1007/s13277-016-5349-7

Source DB:  PubMed          Journal:  Tumour Biol        ISSN: 1010-4283


  204 in total

Review 1.  Practical implications of gene-expression-based assays for breast oncologists.

Authors:  Aleix Prat; Matthew J Ellis; Charles M Perou
Journal:  Nat Rev Clin Oncol       Date:  2011-12-06       Impact factor: 66.675

2.  Outcome signature genes in breast cancer: is there a unique set?

Authors:  Liat Ein-Dor; Itai Kela; Gad Getz; David Givol; Eytan Domany
Journal:  Bioinformatics       Date:  2004-08-12       Impact factor: 6.937

Review 3.  Systems Medicine: Sketching the Landscape.

Authors:  Marc Kirschner
Journal:  Methods Mol Biol       Date:  2016

4.  Development and clinical utility of a 21-gene recurrence score prognostic assay in patients with early breast cancer treated with tamoxifen.

Authors:  Soonmyung Paik
Journal:  Oncologist       Date:  2007-06

5.  Improving the quality of cancer staging.

Authors:  Elliot A Asare; Mary Kay Washington; Donna M Gress; Jeffrey E Gershenwald; Frederick L Greene
Journal:  CA Cancer J Clin       Date:  2015-05-07       Impact factor: 508.702

6.  Prognostic factors in metastatic melanoma: a pooled analysis of Eastern Cooperative Oncology Group trials.

Authors:  J Manola; M Atkins; J Ibrahim; J Kirkwood
Journal:  J Clin Oncol       Date:  2000-11-15       Impact factor: 44.544

7.  Gene expression profiling shows medullary breast cancer is a subgroup of basal breast cancers.

Authors:  François Bertucci; Pascal Finetti; Nathalie Cervera; Emmanuelle Charafe-Jauffret; Emilie Mamessier; José Adélaïde; Stéphane Debono; Gilles Houvenaeghel; Dominique Maraninchi; Patrice Viens; Colette Charpin; Jocelyne Jacquemier; Daniel Birnbaum
Journal:  Cancer Res       Date:  2006-05-01       Impact factor: 12.701

8.  Poor prognosis in carcinoma is associated with a gene expression signature of aberrant PTEN tumor suppressor pathway activity.

Authors:  Lao H Saal; Peter Johansson; Karolina Holm; Sofia K Gruvberger-Saal; Qing-Bai She; Matthew Maurer; Susan Koujak; Adolfo A Ferrando; Per Malmström; Lorenzo Memeo; Jorma Isola; Pär-Ola Bendahl; Neal Rosen; Hanina Hibshoosh; Markus Ringnér; Ake Borg; Ramon Parsons
Journal:  Proc Natl Acad Sci U S A       Date:  2007-04-23       Impact factor: 11.205

9.  Molecular profiles of progesterone receptor loss in human breast tumors.

Authors:  Chad J Creighton; C Kent Osborne; Marc J van de Vijver; John A Foekens; Jan G Klijn; Hugo M Horlings; Dimitry Nuyten; Yixin Wang; Yi Zhang; Gary C Chamness; Susan G Hilsenbeck; Adrian V Lee; Rachel Schiff
Journal:  Breast Cancer Res Treat       Date:  2008-04-19       Impact factor: 4.872

10.  Gene expression signature of fibroblast serum response predicts human cancer progression: similarities between tumors and wounds.

Authors:  Howard Y Chang; Julie B Sneddon; Ash A Alizadeh; Ruchira Sood; Rob B West; Kelli Montgomery; Jen-Tsan Chi; Matt van de Rijn; David Botstein; Patrick O Brown
Journal:  PLoS Biol       Date:  2004-01-13       Impact factor: 8.029

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  1 in total

Review 1.  Early Steps of Mammary Stem Cell Transformation by Exogenous Signals; Effects of Bisphenol Endocrine Disrupting Chemicals and Bone Morphogenetic Proteins.

Authors:  Nora Jung; Veronique Maguer-Satta; Boris Guyot
Journal:  Cancers (Basel)       Date:  2019-09-12       Impact factor: 6.639

  1 in total

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