Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, United Kingdom.
Cancer Res. 2013 Jun 15;73(12):3483-8. doi: 10.1158/0008-5472.CAN-12-4717. Epub 2013 Jun 5.
Combinatorial approaches that integrate conventional pathology with genomic profiling and functional genomics have begun to enhance our understanding of the genetic basis of breast cancer. These methods have identified key genotypic-phenotypic correlations in different breast cancer subtypes that have led to the discovery of genetic dependencies that drive their behavior. Moreover, this knowledge has been applied to define novel tailored therapies for these groups of patients with cancer. With the current emphasis on characterizing the mutational repertoire of breast cancers by next-generation sequencing, the question remains as to what constitutes a driver event. By focusing efforts on homogenous subgroups of breast cancer and integrating orthogonal data-types combined with functional approaches, we can begin to unravel the heterogeneity and identify aberrations that can be therapeutically targeted.
联合应用传统病理学、基因组分析和功能基因组学的方法已经开始增强我们对乳腺癌遗传基础的理解。这些方法已经确定了不同乳腺癌亚型中关键的基因型-表型相关性,从而发现了驱动其行为的遗传依赖性。此外,这些知识已被应用于为这些癌症患者群体定义新的针对性治疗方法。随着目前通过下一代测序来描述乳腺癌突变谱的重点,问题仍然是哪些是驱动事件。通过将精力集中在乳腺癌同质亚群上,并整合正交数据类型与功能方法,我们可以开始揭示异质性并识别可治疗靶向的异常。