Fundación Investigación del Hospital Clínico Universitario de Valencia/INCLIVA, Av. Blasco Ibáñez 17, 46010 Valencia, Spain.
Cancer Treat Rev. 2012 Oct;38(6):698-707. doi: 10.1016/j.ctrv.2011.11.005. Epub 2011 Dec 16.
The last decade has brought a breakthrough in the knowledge of the biology of breast cancer. The technological development, and in particular the high throughput technologies, have allowed researchers to inquire more deeply into the nature of the disease through the comparative study of large numbers of samples. The classification of breast cancer by traditional parameters has been joined by rankings based on gene expression. Among the most popular platforms are MammaPrint®, Oncotype DX® the wound-response model, the rate of two genes model, the genomic grade index and the intrinsic subtype model. The latter one provides the amplest biological information and allows for the classification of breast cancer into six intrinsic subtypes: luminal A, luminal B, HER2-enriched, basal-like, normal breast and claudin-low. These new classifications are not yet fully applicable to clinical practice not only because they have not been standardized, but also because they entail a substantial economic outlay. Nevertheless, they have provided valuable information on tumor biology that has led to a better understanding of the signaling pathways governing the processes of formation, maintenance and expansion of the tumors. Researchers now know more about the HER2, estrogen receptor, IGF1R, PI3K/AKT, mTOR, AMPK and angiogenesis pathways which has allowed for the development of new targeted therapeutics now being tested in ongoing clinical trials. In general, one can say that the last decade has changed the way researchers understand, classify and study breast cancer, and it has reshaped the way doctors diagnose and treat this disease. In addition, it has undoubtedly changed the search for alternative therapies by integrating molecular studies and the selection of study populations based on their molecular markers into clinical trials. The present review summarizes the advances that have allowed researchers to both better classify the disease, as well as explore some of the most important signaling pathways.
过去十年，乳腺癌生物学的研究取得了突破性进展。技术的发展，尤其是高通量技术，使得研究人员能够通过对大量样本的比较研究，更深入地探究疾病的本质。传统参数的乳腺癌分类方法已被基于基因表达的分类方法所取代。其中最受欢迎的平台包括 MammaPrint®、Oncotype DX®、伤口反应模型、双基因评分模型、基因组分级指数和内在亚型模型。后者提供了最丰富的生物学信息，可将乳腺癌分为六种内在亚型：luminal A、luminal B、HER2 富集型、基底样型、正常乳腺型和 Claudin-low 型。这些新的分类方法尚未完全适用于临床实践，不仅因为它们尚未标准化，还因为它们需要大量的经济投入。然而，它们提供了有关肿瘤生物学的宝贵信息，使人们对控制肿瘤形成、维持和扩张的信号通路有了更好的理解。研究人员现在对 HER2、雌激素受体、IGF1R、PI3K/AKT、mTOR、AMPK 和血管生成途径有了更多的了解，这些途径促使新的靶向治疗方法得以开发，并正在进行中的临床试验中进行测试。总的来说，可以说过去十年改变了研究人员对乳腺癌的理解、分类和研究方式，也改变了医生诊断和治疗这种疾病的方式。此外，它无疑通过将分子研究和基于分子标志物的研究人群选择纳入临床试验，改变了寻找替代疗法的方式。本文综述了使研究人员能够更好地对疾病进行分类以及探索一些最重要的信号通路的进展。
