Gene-expression microarrays provide new prognostic and predictive tests for breast cancer

Author:

Gong Yun1,Symmans W Fraser1,Pusztai Lajos2

Affiliation:

1. University of Texas, Department of Pathology, Anderson Cancer Center, Unit 53, 1515 Holcombe Blvd, Houston, TX 77030, USA.

2. University of Texas, Breast Medical Oncology, 1515 Holcombe Blvd, Houston, TX 77030, USA

Abstract

Wide availability of systemic therapy agents has led to a considerable decline in mortality from breast cancer. However, the biology of breast cancer remains poorly understood. Currently, highly accurate markers to predict prognosis and probability of response to a given systemic therapy on an individual basis are lacking, and routinely used clinicopathologic variables fail to fully capture the heterogeneity of breast cancer. As a result, many patients are overtreated, whereas others may not receive the necessary therapy. It has been hypothesized that molecular differences in breast cancers might account for the heterogeneous potential in growth, invasion and metastasis in each individual tumor. Gene-expression microarrays have been extensively applied in breast cancer research in the hope that a combination of multiple genes (i.e., gene signatures) will more informatively predict disease outcome and response to a specific systemic therapy. This technique holds substantial promise for optimizing clinical decision making and tailoring therapeutic regimens to individual patients in the near future. This review focuses on the recent progression in feasibility and reliability of gene-expression microarrays in identifying new prognostic and predictive indicators of breast cancer.

Publisher

Future Medicine Ltd

Subject

Pharmacology,Genetics,Molecular Medicine

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3