基于大型微阵列参考数据库的数据驱动方法对未知原发性肿瘤的分类。
Classification of unknown primary tumors with a data-driven method based on a large microarray reference database.
机构信息
Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Tukholmankatu 8, 00140 Helsinki, Finland.
出版信息
Genome Med. 2011 Oct 17;3(9):63. doi: 10.1186/gm279.
We present a new method to analyze cancer of unknown primary origin (CUP) samples. Our method achieves good results with classification accuracy (88% leave-one-out cross validation for primary tumors from 56 categories, 78% for CUP samples), and can also be used to study CUP samples on a gene-by-gene basis. It is not tied to any a priori defined gene set as many previous methods, and is adaptable to emerging new information.
我们提出了一种新的方法来分析原发灶不明的癌症（CUP）样本。我们的方法在分类准确性方面取得了很好的结果（56 个分类的原发肿瘤的留一交叉验证准确率为 88%，CUP 样本的准确率为 78%），也可以用于逐个基因研究 CUP 样本。与许多先前的方法不同，它不受任何先验定义的基因集的限制，并且能够适应新出现的信息。
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