Literature DB >> 17512431

New generation of molecular prognostic and predictive tests for breast cancer.

Lajos Pusztai1, Massimo Cristofanilli, Soonmyung Paik.   

Abstract

Breast cancer is a clinically heterogeneous disease, and it is generally accepted that the different clinical courses of patients with histologically similar tumors are due to molecular differences among cancers. Therefore, detailed molecular analysis of the cancer could yield prognostic information. Recent advances in molecular analytical techniques have led to rapid expansion of novel diagnostics designed to personalize breast cancer care. Diagnostic companies are also increasingly adopting a clinical trial-based approach to develop their products. This article reviews some of the most important advances in this field in the past few years, including the emergence of several multigene and prognostic predictors, as well as methods allowing enumeration of circulating tumor cells that are currently offered as commercially available diagnostic assays.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 17512431     DOI: 10.1053/j.seminoncol.2007.03.015

Source DB:  PubMed          Journal:  Semin Oncol        ISSN: 0093-7754            Impact factor:   4.929


  7 in total

Review 1.  Gene expression profiles of NO- and HNO-donor treated breast cancer cells: insights into tumor response and resistance pathways.

Authors:  Robert Y S Cheng; Debashree Basudhar; Lisa A Ridnour; Julie L Heinecke; Aparna H Kesarwala; Sharon Glynn; Christopher H Switzer; Stefan Ambs; Katrina M Miranda; David A Wink
Journal:  Nitric Oxide       Date:  2014-08-19       Impact factor: 4.427

2.  Protein expression profile and prevalence pattern of the molecular classes of breast cancer--a Saudi population based study.

Authors:  Dalal M Al Tamimi; Mohamed A Shawarby; Ayesha Ahmed; Ammar K Hassan; Amal A AlOdaini
Journal:  BMC Cancer       Date:  2010-05-21       Impact factor: 4.430

Review 3.  Advances in breast cancer: pathways to personalized medicine.

Authors:  Olufunmilayo I Olopade; Tatyana A Grushko; Rita Nanda; Dezheng Huo
Journal:  Clin Cancer Res       Date:  2008-12-15       Impact factor: 12.531

4.  A pathway-based classification of breast cancer integrating data on differentially expressed genes, copy number variations and microRNA target genes.

Authors:  Hae-Seok Eo; Jee Yeon Heo; Yongjin Choi; Youngdon Hwang; Hyung-Seok Choi
Journal:  Mol Cells       Date:  2012-09-13       Impact factor: 5.034

Review 5.  Minireview: nuclear receptors and breast cancer.

Authors:  Suzanne D Conzen
Journal:  Mol Endocrinol       Date:  2008-04-16

6.  Maximum predictive power of the microarray-based models for clinical outcomes is limited by correlation between endpoint and gene expression profile.

Authors:  Chen Zhao; Leming Shi; Weida Tong; John D Shaughnessy; André Oberthuer; Lajos Pusztai; Youping Deng; W Fraser Symmans; Tieliu Shi
Journal:  BMC Genomics       Date:  2011-12-23       Impact factor: 3.969

7.  [Breast cancer in Morocco: phenotypic profile of tumors].

Authors:  Ahmadaye Ibrahim Khalil; Karima Bendahhou; Houriya Mestaghanmi; Rachid Saile; Abdellatif Benider
Journal:  Pan Afr Med J       Date:  2016-10-06
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.