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Analysis of gene expression profile of pancreatic carcinoma using cDNA microarray

机译:利用cDNA微阵列分析胰腺癌的基因表达谱

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摘要

AIM: To identify new diagnostic markers and drug targets, the gene expression profiles of pancreatic cancer were compared with that of adjacent normal tissues utilizing cDNA microarray analysis.METHODS: cDNA probes were prepared by labeling mRNA from samples of six pancreatic carcinoma tissues with Cy5-dUTP and mRNA from adjacent normal tissues with Cy3-dUTP respectively through reverse transcription. The mixed probes of each sample were then hybridized with 12800 cDNA arrays (12648 unique human cDNA sequences), and the fluorescent signals were scanned by ScanArray 3000 scanner (General Scanning, Inc.). The values of Cy5-dUTP and Cy3-dUTP on each spot were analyzed and calculated by ImaGene 3.0 software (BioDiscovery, Inc.). Differentially expressed genes were screened according to the criterion that the absolute value of natural logarithm of the ratio of Cy5-dUTP to Cy3-dUTP was greater-than 0.69.RESULTS: Among 6 samples investigated, 301 genes, which accounted for 2.38% of genes on the microarry slides, exhibited differentially expression at least in 5. There were 166 over-expressed genes including 136 having been registered in Genebank, and 135 under-expressed genes including 79 in Genebank in cancerous tissues.CONCLUSION: Microarray analysis may provide invaluable information on disease pathology, progression, resistance to treatment, and response to cellular microenvironments of pancreatic carcinoma and ultimately may lead to improving early diagnosis and discovering innovative therapeutic approaches for cancer.
机译:目的:通过cDNA微阵列分析,比较胰腺癌和邻近正常组织的基因表达谱,以鉴定新的诊断标志物和药物靶标。方法:用Cy5-标记六种胰腺癌组织中的mRNA,制备cDNA探针。 Cy3-dUTP通过逆转录分别来自邻近正常组织的dUTP和mRNA。然后将每个样品的混合探针与12800个cDNA阵列(12648个独特的人cDNA序列)杂交,并通过ScanArray 3000扫描仪(General Scanning,Inc.)扫描荧光信号。通过ImaGene 3.0软件(BioDiscovery,Inc。)分析和计算每个斑点上的Cy5-dUTP和Cy3-dUTP的值。根据Cy5-dUTP与Cy3-dUTP之比的自然对数的绝对值大于0.69的标准筛选差异表达基因。结果:在所调查的6个样本中,有301个基因占基因的2.38%。在微载玻片上,至少在5个细胞中有差异表达。在癌组织中,有166个过表达的基因,其中136个已在基因库中注册,135个表达不足的基因,其中79个在基因库中。结论:微阵列分析可能提供宝贵的信息胰腺癌的病理,进展,治疗抗性以及对细胞微环境的反应,最终可能会改善早期诊断并发现创新的癌症治疗方法。

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