Literature DB >> 28040199

Molecular classification of breast cancer: what the pathologist needs to know.

Emad A Rakha1, Andrew R Green2.   

Abstract

Breast cancer is a heterogeneous disease featuring distinct histological, molecular and clinical phenotypes. Although traditional classification systems utilising clinicopathological and few molecular markers are well established and validated, they remain insufficient to reflect the diverse biological and clinical heterogeneity of breast cancer. Advancements in high-throughput molecular techniques and bioinformatics have contributed to the improved understanding of breast cancer biology, refinement of molecular taxonomies and the development of novel prognostic and predictive molecular assays. Application of such technologies is already underway, and is expected to change the way we manage breast cancer. Despite the enormous amount of work that has been carried out to develop and refine breast cancer molecular prognostic and predictive assays, molecular testing is still in evolution. Pathologists should be aware of the new technology and be ready for the challenge. In this review, we provide an update on the application of molecular techniques with regard to breast cancer diagnosis, prognosis and outcome prediction. The current contribution of emerging technology to our understanding of breast cancer is also highlighted.
Copyright © 2016 Royal College of Pathologists of Australasia. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Breast cancer; HER2; basal-like; gene expression profiling; luminal; molecular prognostic assays; molecular taxonomy; next generation sequencing

Mesh:

Substances:

Year:  2016        PMID: 28040199     DOI: 10.1016/j.pathol.2016.10.012

Source DB:  PubMed          Journal:  Pathology        ISSN: 0031-3025            Impact factor:   5.306


  23 in total

1.  Time resolved gene expression analysis during tamoxifen adaption of MCF-7 cells identifies long non-coding RNAs with prognostic impact.

Authors:  Martin Porsch; Esra Özdemir; Martin Wisniewski; Sebastian Graf; Fabian Bull; Katrin Hoffmann; Atanas Ignatov; Johannes Haybaeck; Ivo Grosse; Thomas Kalinski; Norbert Nass
Journal:  RNA Biol       Date:  2019-03-05       Impact factor: 4.652

2.  Coactosin-Like Protein in Breast Carcinoma: Friend or Foe?

Authors:  Bei Wang; Limiao Zhao; Dandan Chen
Journal:  J Inflamm Res       Date:  2022-07-15

3.  Predicting the molecular subtype of breast cancer and identifying interpretable imaging features using machine learning algorithms.

Authors:  Mengwei Ma; Renyi Liu; Chanjuan Wen; Weimin Xu; Zeyuan Xu; Sina Wang; Jiefang Wu; Derun Pan; Bowen Zheng; Genggeng Qin; Weiguo Chen
Journal:  Eur Radiol       Date:  2021-10-13       Impact factor: 7.034

Review 4.  A proposal for early and personalized treatment of diabetic retinopathy based on clinical pathophysiology and molecular phenotyping.

Authors:  Thomas W Gardner; Jeffrey M Sundstrom
Journal:  Vision Res       Date:  2017-08-02       Impact factor: 1.886

5.  Prognostic and predictive parameters in breast pathology: a pathologist's primer.

Authors:  Kimberly H Allison
Journal:  Mod Pathol       Date:  2020-11-05       Impact factor: 7.842

Review 6.  Autocrine and paracrine purinergic signaling in the most lethal types of cancer.

Authors:  M Reyna-Jeldes; M Díaz-Muñoz; J A Madariaga; C Coddou; F G Vázquez-Cuevas
Journal:  Purinergic Signal       Date:  2021-05-12       Impact factor: 3.765

Review 7.  Genomics applied to the treatment of breast cancer.

Authors:  Anne Janin; Guilhem Bousquet; Diaddin Hamdan; Thi Thuy Nguyen; Christophe Leboeuf; Solveig Meles
Journal:  Oncotarget       Date:  2019-07-30

Review 8.  Treatment of Breast Cancer With Gonadotropin-Releasing Hormone Analogs.

Authors:  Maira Huerta-Reyes; Guadalupe Maya-Núñez; Marco Allán Pérez-Solis; Eunice López-Muñoz; Nancy Guillén; Jean-Christophe Olivo-Marin; Arturo Aguilar-Rojas
Journal:  Front Oncol       Date:  2019-10-01       Impact factor: 6.244

9.  LncRNA GNAS-AS1 facilitates ER+ breast cancer cells progression by promoting M2 macrophage polarization via regulating miR-433-3p/GATA3 axis.

Authors:  Shi-Qin Liu; Zhi-Yang Zhou; Xue Dong; Lei Guo; Ke-Jing Zhang
Journal:  Biosci Rep       Date:  2020-07-31       Impact factor: 3.840

10.  Curcumin⁻Copper Complex Nanoparticles for the Management of Triple-Negative Breast Cancer.

Authors:  Khaled Greish; Valeria Pittalà; Sebastien Taurin; Safa Taha; Fatemah Bahman; Aanchal Mathur; Anfal Jasim; Fatima Mohammed; Ibrahim M El-Deeb; Salim Fredericks; Fiza Rashid-Doubell
Journal:  Nanomaterials (Basel)       Date:  2018-11-01       Impact factor: 5.076

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