Gene expression based classification of gastric carcinoma
Gene expression based classification of gastric carcinoma
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DOI：
10.1016/j.canlet.2004.01.022
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发表时间：
2004-07-16
期刊：
影响因子：
9.7
通讯作者：
Sandvik, AK
中科院分区：
文献类型：
--
作者：
Norsett, KG;Lægreid, A;Sandvik, AK
本研究的目的是识别分子标志物，根据重要的临床病理参数对胃癌进行分类。用2.504基因探针组对胃腺癌进行了基因芯片分析。使用基于Rosetta粗糙集的学习系统，根据Lauren的分类和有无淋巴结转移，生成了良好的分类器，用于基于基因表达的肠道或弥漫性生长模式的预测。据我们所知，这是第一个基于微阵列基因表达谱对多个临床病理参数进行分子分类的胃癌研究。(C)2004爱思唯尔爱尔兰有限公司。保留所有权利。
The aim of the present work is to identify molecular markers that allow classification of gastric carcinoma with respect to important clinicopathological parameters. Gastric adenocarcinomas were subjected to cDNA microarray analysis with a 2.504 gene probe set. Using the Rosetta rough-set based learning system, good classifiers were generated for gene-expression based prediction of intestinal or diffuse growth pattern according to Lauren's classification and presence of lymph node metastases. To our knowledge, this is the first study on gastric carcinoma in which molecular classification has been achieved for more than one clinicopathological parameter based on microarray gene expression profiles. (C) 2004 Elsevier Ireland Ltd. All rights reserved.