Computational dissection of tissue contamination for identification of colon cancer-specific expression profiles
Computational dissection of tissue contamination for identification of colon cancer-specific expression profiles
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DOI：
10.1096/fj.02-0478com
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发表时间：
2003-03-01
期刊：
影响因子：
4.8
通讯作者：
Hammer, J
中科院分区：
文献类型：
--
作者：
Türeci, Ö;Ding, JY;Hammer, J
大块肿瘤组织的微阵列图谱反映了恶性细胞以及许多不同类型的污染正常细胞对应的基因表达。在本报告中，我们评估了查询基线多组织转录组数据库以解剖疾病特异性基因的可行性。使用结肠癌作为模型肿瘤，我们展示了布尔运算符（AND， OR， BUTNOT）在数据库搜索中的应用导致具有感兴趣的表达模式的基因。例如，BUTNOT操作符允许对正常组织标本分配“表达签名”。然后使用这些表达特征来计算识别常规解剖组织标本中的污染细胞。将多个逻辑算子与基于多个人体组织标本的表达数据库相结合，可以解决组织污染问题，揭示新的癌症特异性基因表达。提供了一些以前不知道与结肠癌相关的标记物。
Microarray profiles of bulk tumor tissues reflect gene expression corresponding to malignant cells as well as to many different types of contaminating normal cells. In this report, we assess the feasibility of querying baseline multitissue transcriptome databases to dissect disease-specific genes. Using colon cancer as a model tumor, we show that the application of Boolean operators (AND, OR, BUTNOT) for database searches leads to genes with expression patterns of interest. The BUTNOT operator for example allows the assignment of "expression signatures" to normal tissue specimens. These expression signatures were then used to computationally identify contaminating cells within conventionally dissected tissue specimens. The combination of several logic operators together with an expression database based on multiple human tissue specimens can resolve the problem of tissue contamination, revealing novel cancer-specific gene expression. Several markers, previously not known to be colon cancer associated, are provided.