Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring
Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring
复制标题
DOI：
10.1126/science.286.5439.531
复制
发表时间：
1999-10-15
期刊：
影响因子：
56.9
通讯作者：
Lander, ES
中科院分区：
文献类型：
--
作者：
Golub, TR;Slonim, DK;Lander, ES
尽管癌症分类在过去30年中有所改进，但还没有用于识别新癌症类别（类别发现）或将肿瘤分配到已知类别（类别预测）的通用方法。在这里，一个通用的方法，癌症分类的基础上基因表达监测的DNA微阵列被描述和应用于人类急性白血病作为测试案例。类别发现程序自动发现急性髓性白血病（AML）和急性淋巴细胞白血病（ALL）之间的区别，而无需预先了解这些类别。自动衍生的类别预测器能够确定新的白血病病例的类别。结果表明，仅基于基因表达监测的癌症分类的可行性，并提出了一种发现和预测其他类型癌症的癌症类别的一般策略，独立于以前的生物学知识。
Although cancer classification has improved over the past 30 years, there has been no general approach for identifying new cancer classes (class discovery) or for assigning tumors to known classes (class prediction). Here, a generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute Leukemias as a test case. A class discovery procedure automatically discovered the distinction between acute myeloid Leukemia (AML) and acute Lymphoblastic Leukemia (ALL) without previous knowledge of these classes. An automatically derived class predictor was able to determine the class of new leukemia cases. The results demonstrate the feasibility of cancer classification based solely on gene expression monitoring and suggest a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.