Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Institutes of Health, Bethesda, MD, USA.
Wiley Interdiscip Rev Syst Biol Med. 2009 Jul-Aug;1(1):89-96. doi: 10.1002/wsbm.6.
Metastasis is the final stage of cancer and the primary cause of mortality for most solid malignancies. This terminal phase of cancer progression has been investigated using a variety of high-throughput technologies (i.e., gene expression arrays, array comparative genomic hybridization (aCGH), and proteomics) to identify prognostic expression profiles and better characterize the metastatic process. For decades, the predominant model for the metastatic process has been the 'progression model', yet recent microarray results tend to support an inherent metastatic capability within primary tumors. Moreover, studies using a highly metastatic transgenic mammary tumor model suggest that germline polymorphisms are significant determinants of metastatic efficiency. Likewise, a strong concordance of survival has been observed between family members with cancer, further supporting the link between genetic inheritance and survival. In addition, chromosomal aberrations and signaling pathways related to metastatic capacity have been identified by array comparative genomic hybridization (aCGH) and proteomic studies, respectively. Lastly, carcinoma enzyme activity profiles using activity-based proteomics (ABPP), may be more clinically useful than expression-based proteomics for certain cancers. Most importantly, the application of these high-throughput techniques should expedite the search for additional biomarkers, germline polymorphisms, and expression signatures with greater prognostic value.
转移是癌症的终末阶段，也是大多数实体恶性肿瘤死亡的主要原因。人们使用各种高通量技术（如基因表达谱芯片、阵列比较基因组杂交(aCGH)和蛋白质组学）来研究癌症进展的终末阶段，以确定预后表达谱并更好地描述转移过程。几十年来，转移过程的主要模型一直是“进展模型”，但最近的微阵列结果倾向于支持原发性肿瘤中固有的转移能力。此外，使用高度转移的转基因乳腺肿瘤模型的研究表明，种系多态性是转移效率的重要决定因素。同样，癌症患者的家庭成员之间也观察到生存的高度一致性，这进一步支持了遗传继承与生存之间的联系。此外，通过阵列比较基因组杂交(aCGH)和蛋白质组学研究分别鉴定了与转移能力相关的染色体异常和信号通路。最后，使用基于活性的蛋白质组学（ABPP）的癌酶活性谱对于某些癌症可能比基于表达的蛋白质组学更具临床意义。最重要的是，这些高通量技术的应用应该加快寻找具有更大预后价值的其他生物标志物、种系多态性和表达特征的速度。
