Kim Byungsik, Bang Seunghyun, Lee Seungkoo, Kim Soonok, Jung Yusun, Lee Changhee, Choi Kyungho, Lee Seong-Gene, Lee Kiwhan, Lee Yongsung, Kim Sang-Soo, Yeom Yeong-Il, Kim Yong-Sung, Yoo Hyang-Sook, Song Kyuyoung, Lee Inchul
Department of General Surgery, University of Ulsan College of Medicine, Seoul, Korea.
Cancer Res. 2003 Dec 1;63(23):8248-55.
The expression profiling and molecular grouping of stomach cancers has been a challenging task because of their complexity and variation. We have analyzed gene expression profiles of 22 gastric cancer/nontumor mucosa couples using 14K cDNA microarray chips designed for gastric cancer analysis. Upon pairwise analysis of the individual couples at the false significance rate 0.91%, 79 and 398 genes were reported to be up-regulated and down-regulated in tumors, respectively. Tumors were clustered into two groups having high and low inflammatory infiltration, respectively. The latter consisted of three subgroups, including diffuse type carcinomas and intestinal types with distinct pathological characteristics of aggressive behavior. When the pooled tumor was hybridized against the pooled nontumor mucosa samples, more genes were detected to express differentially than those detected by the pairwise analysis at the same threshold level. However, they did not render satisfactory clustering of individual tumors. Our data showed that stomach cancers could be clustered effectively using stomach-specific microarrays and pairwise analysis of tumor/nontumor mucosa couples. It is suggested that the application of specific goal-oriented experimental designing would be advantageous for efficient analysis of expression profiles of such a complex disease as gastric cancer.
由于胃癌的复杂性和变异性,其表达谱分析和分子分组一直是一项具有挑战性的任务。我们使用为胃癌分析设计的14K cDNA微阵列芯片,分析了22对胃癌/非肿瘤黏膜样本的基因表达谱。在以0.91%的假显著性率对各样本对进行成对分析时,分别有79个和398个基因在肿瘤中上调和下调。肿瘤被分为两组,分别具有高炎症浸润和低炎症浸润。后者由三个亚组组成,包括弥漫型癌和具有侵袭性行为不同病理特征的肠型癌。当将合并的肿瘤样本与合并的非肿瘤黏膜样本进行杂交时,与在相同阈值水平下通过成对分析检测到的基因相比,检测到更多表达有差异的基因。然而,它们并没有使单个肿瘤得到令人满意的聚类。我们的数据表明,使用胃特异性微阵列和肿瘤/非肿瘤黏膜样本对的成对分析,可以有效地对胃癌进行聚类。建议应用特定的目标导向实验设计,对于高效分析像胃癌这样复杂疾病的表达谱将是有利的。