Inflammation, adenoma and cancer: objective classification of colon biopsy specimens with gene expression signature.
Inflammation, adenoma and cancer: objective classification of colon biopsy specimens with gene expression signature.
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DOI：
10.1155/2008/586721
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
Molnár B
中科院分区：
文献类型：
--
作者：
Galamb O;Györffy B;Sipos F;Spisák S;Németh AM;Miheller P;Tulassay Z;Dinya E;Molnár B
使用高密度寡核苷酸微阵列对结肠活检进行基因表达分析有助于理解局部病理生理学变化，并有助于腺瘤（15个样本）、结直肠癌（CRC）（15）和炎症性肠病（IBD）（14）的功能分类。从冷冻的结肠活检组织中提取总RNA，扩增并生物素化。全基因组基因表达谱通过HGU 133 plus 2芯片进行评估，并通过RT-PCR进行验证。我们应用了两种独立的方法进行数据归一化，并使用PAM进行特征选择。采用留一法逐步判别分析。最有效的基因包括CRC中的胶原IV α1、脂质运载蛋白-2、钙调蛋白、水通道蛋白-8基因;腺瘤中的CD 44、met原癌基因、趋化因子配体-12、ADAM样decysin-1和ATP结合盒-A8基因; IBD中的脂质运载蛋白-2、泛素D和IFITM 2基因。溃疡性结肠炎和克罗恩病之间最好的鉴别标志物是细胞周期蛋白-G2;包含三重基序的-31; TNFR脱落氨肽酶调节剂-1和AMICA。判别分析能够使用7个判别基因（吲哚胺-吡咯-2，3-双加氧酶、外胚层-神经皮质、TIMP 3、岩藻糖基转移酶-8、胶原聚集蛋白亚家族成员12、羧肽酶D和转氨酶-2）对总体96.2%的样品进行分类。使用常规活检样品，我们成功地进行了全基因组微阵列分析，以确定区别性的签名。我们的研究结果提供了进一步了解结肠疾病的病理生理背景。研究结果建立了数据仓库，可供进一步挖掘。
Gene expression analysis of colon biopsies using high-density oligonucleotide microarrays can contribute to the understanding of local pathophysiological alterations and to functional classification of adenoma (15 samples), colorectal carcinomas (CRC) (15) and inflammatory bowel diseases (IBD) (14). Total RNA was extracted, amplified and biotinylated from frozen colonic biopsies. Genome-wide gene expression profile was evaluated by HGU133plus2 microarrays and verified by RT-PCR. We applied two independent methods for data normalization and used PAM for feature selection. Leave one-out stepwise discriminant analysis was performed. Top validated genes included collagenIVα1, lipocalin-2, calumenin, aquaporin-8 genes in CRC; CD44, met proto-oncogene, chemokine ligand-12, ADAM-like decysin-1 and ATP-binding casette-A8 genes in adenoma; and lipocalin-2, ubiquitin D and IFITM2 genes in IBD. Best differentiating markers between Ulcerative colitis and Crohn's disease were cyclin-G2; tripartite motif-containing-31; TNFR shedding aminopeptidase regulator-1 and AMICA. The discriminant analysis was able to classify the samples in overall 96.2% using 7 discriminatory genes (indoleamine-pyrrole-2,3-dioxygenase, ectodermal-neural cortex, TIMP3, fucosyltransferase-8, collectin sub-family member 12, carboxypeptidase D, and transglutaminase-2). Using routine biopsy samples we successfully performed whole genomic microarray analysis to identify discriminative signatures. Our results provide further insight into the pathophysiological background of colonic diseases. The results set up data warehouse which can be mined further.
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影响因子：
3.8
作者：
Kirman, I;Poltoratskaia, N;Whelan, RL
通讯作者：
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2.1
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作者：
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