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运用基因芯片和拓扑网络技术筛选候选生物标志物基因(CBG),以预测水源致癌风险对小鼠 Mus musculus 的影响。

Integration of gene chip and topological network techniques to screen a candidate biomarker gene (CBG) for predication of the source water carcinogenesis risks on mouse Mus musculus.

机构信息

State Key Laboratory of Pollution Control & Resource Reuse and School of the Environment, Nanjing University, 163# Xianlindadao, Nanjing, 210046, China.

出版信息

Ecotoxicology. 2011 Jul;20(5):1026-32. doi: 10.1007/s10646-011-0687-0. Epub 2011 May 4.

DOI:10.1007/s10646-011-0687-0
PMID:21541659
Abstract

Screening of a candidate biomarker gene (CBG) to predicate the carcinogenesis risks in the Yangtze River source of drinking water in Nanjing area (YZR-SDW-NJ) on mouse (Mus musculus) was conducted in this research. The effects of YZR-SDW-NJ on the genomic transcriptional expression levels were measured by the GeneChip(®) Mouse Genome and data treated by the GO database analysis. The 298 genes discovered as the differently expressed genes (DEGs) were down-regulated and their values were ≤-1.5-fold. Of the 298 DEGs, 25 were cancer-related genes selected as the seed genes to build a topological network map with Genes2Networks software, only 7 of them occurred at the constructed map. Smad2 gene was at the constructed map center and could be identified as a candidate biomarker gene (CBG) primarily which involves the genesis and development of colorectal, leukemia, lung and prostate cancers directly. Analysis of the gene signal pathway further approved that smad2 gene had the relationships closely to other 16 cancer-related genes and could be used as a CBG to indicate the carcinogenic risks in YZR-SDW-NJ. The data suggest that integration of gene chip and network techniques may be a way effectively to screen a CBG. And the parameter values for further judgment of the CBG through signal pathway relationship analysis also will be discussed.

摘要

本研究采用基因芯片技术检测南京长江水源水(YZR-SDW-NJ)对小鼠(Mus musculus)基因组转录表达水平的影响,并利用 GO 数据库分析处理数据。发现 298 个基因表达下调且其值≤-1.5 倍,作为差异表达基因(DEGs)。其中,选择 25 个与癌症相关的基因作为种子基因,利用 Genes2Networks 软件构建拓扑网络图,只有 7 个基因出现在构建的图谱中。Smad2 基因位于构建的图谱中心,可初步鉴定为候选生物标志物基因(CBG),直接涉及结直肠癌、白血病、肺癌和前列腺癌的发生和发展。基因信号通路分析进一步证实,smad2 基因与其他 16 个癌症相关基因密切相关,可作为 YZR-SDW-NJ 致癌风险的 CBG。数据表明,基因芯片与网络技术的整合可能是筛选 CBG 的有效方法。并将通过信号通路关系分析进一步判断 CBG 的参数值进行讨论。

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