Wilson Cindy A, Dering Judy
Department of Hematology/Oncology, David Geffen School of Medicine at UCLA, University of California, Los Angeles, USA.
Breast Cancer Res. 2004;6(5):192-200. doi: 10.1186/bcr917. Epub 2004 Jul 19.
Genomic expression profiling has greatly improved our ability to subclassify human breast cancers according to shared molecular characteristics and clinical behavior. The logical next question is whether this technology will be similarly useful for identifying the dominant signaling pathways that drive tumor initiation and progression within each breast cancer subtype. A major challenge will be to integrate data generated from the experimental manipulation of model systems with expression profiles obtained from primary tumors. We highlight some recent progress and discuss several obstacles in the use of expression profiling to identify pathway signatures in human breast cancer.
基因组表达谱分析极大地提高了我们根据共同分子特征和临床行为对人类乳腺癌进行亚分类的能力。接下来合乎逻辑的问题是，这项技术是否同样有助于识别驱动每种乳腺癌亚型肿瘤发生和进展的主要信号通路。一个主要挑战将是整合从模型系统的实验操作中产生的数据与从原发性肿瘤获得的表达谱。我们重点介绍了一些最新进展，并讨论了在利用表达谱分析识别人类乳腺癌通路特征方面的几个障碍。
