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利用基因表达谱分析以更好地理解雌激素受体阳性乳腺癌的临床异质性及他莫昔芬反应。

The use of gene-expression profiling to better understand the clinical heterogeneity of estrogen receptor positive breast cancers and tamoxifen response.

作者信息

Loi Sherene, Piccart Martine, Sotiriou Christos

机构信息

Translational Unit, Microarray Laboratories and Department of Medical Oncology, Jules Bordet Institute, Brussels, Belgium.

出版信息

Crit Rev Oncol Hematol. 2007 Mar;61(3):187-94. doi: 10.1016/j.critrevonc.2006.09.005. Epub 2006 Nov 7.

Abstract

In a short period of time DNA microarray technology has revolutionized our understanding of human cancer biology. This has been particularly impressive in the field of breast cancer research, where the clinical heterogeneity long observed by physicians seems to be mirrored by different molecular phenotypes exposed by microarray analysis. Gene-expression signatures have been developed to predict prognosis and treatment response and pending adequate validation, are on the verge of entry into the clinical setting. In this review article we explore how gene-expression profiling has influenced our understanding of the ER-positive breast cancers: that proliferation and cell-cycle genes seem to be the strongest predictor for metastasis and relapse in this group, and discuss the various gene predictors and molecular subtype classifications that exist that may help us individualize therapy for these women.

摘要

在短时间内,DNA微阵列技术彻底改变了我们对人类癌症生物学的理解。这在乳腺癌研究领域尤其令人印象深刻,在该领域,医生长期观察到的临床异质性似乎与微阵列分析所揭示的不同分子表型相对应。已经开发出基因表达特征来预测预后和治疗反应,并且在经过充分验证后,即将进入临床应用。在这篇综述文章中,我们探讨了基因表达谱如何影响我们对雌激素受体阳性乳腺癌的理解:增殖和细胞周期基因似乎是该组中转移和复发的最强预测指标,并讨论了现有的各种基因预测指标和分子亚型分类,这些可能有助于我们为这些女性制定个性化治疗方案。

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