title: 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.
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.
authors.affiliation: Department of Biochemistry, University of Zanjan, Zanjan, Iran.
authors.forename: Vida
authors.initials: V
authors.lastname: Pourteimoor
authors.affiliation: Cellular and Molecular Biology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran. s.mohammadiyeganeh@sbmu.ac.ir.|Department of Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran. s.mohammadiyeganeh@sbmu.ac.ir.
authors.forename: Samira
authors.initials: S
authors.lastname: Mohammadi-Yeganeh
authors.affiliation: Department of Research and Development, Production and Research Complex, Pasteur Institute of Iran, Tehran, Iran.
authors.forename: Mahdi
authors.initials: M
authors.lastname: Paryan
mesh_terms: D001940:Breast / Q000473:pathology; D018270:Carcinoma, Ductal, Breast / Q000145:classification* / Q000401:mortality / Q000473:pathology*; D002285:Carcinoma, Intraductal, Noninfiltrating / Q000145:classification* / Q000401:mortality / Q000473:pathology*; D018275:Carcinoma, Lobular / Q000145:classification* / Q000401:mortality / Q000473:pathology*; D005260:Female; D006801:Humans; D060787:Neoplasm Grading; D009367:Neoplasm Staging; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism; D011960:Receptors, Estrogen / Q000378:metabolism; D011980:Receptors, Progesterone / Q000378:metabolism
chemical_list: D018719:Erb-b2 Receptor Tyrosine Kinases; D011960:Receptors, Estrogen; D011980:Receptors, Progesterone; C508053:ERBB2 protein, human
keywords: Breast cancer; Breast cancer subtypes; Classification systems