Lower connectivity of tumor coexpression networks is not specific to cancer.

Q2 Medicine
Ertuğrul Dalgıç, Özlen Konu, Zehra Safi Öz, Christina Chan
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引用次数: 4

Abstract

Global level network analysis of molecular links is necessary for systems level view of complex diseases like cancer. Using genome-wide expression datasets, we constructed and compared gene co-expression based specific networks of pre-cancerous tumors (adenoma) and cancerous tumors (carcinoma) with paired normal networks to assess for any possible changes in network connectivity. Previously, loss of connectivity was reported as a characteristics of cancer samples. Here, we observed that pre-cancerous conditions also had significantly less connections than paired normal samples. We observed a loss of connectivity trend for colorectal adenoma, aldosterone producing adenoma and uterine leiomyoma. We also showed that the loss of connectivity trend is not specific to positive or negative correlation based networks. Differential hub genes, which were the most highly differentially less connected genes in tumor, were mostly different between different datasets. No common gene list could be defined which underlies the lower connectivity of tumor specific networks. Connectivity of colorectal cancer methylation targets was different from other genes. Extracellular space related terms were enriched in negative correlation based differential hubs and common methylation targets of colorectal carcinoma. Our results indicate a systems level change of lower connectivity as cells transform to not only cancer but also pre-cancerous conditions. This systems level behavior could not be attributed to a group of genes.

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肿瘤共表达网络的低连通性并不是癌症特有的。
分子链接的全局网络分析对于癌症等复杂疾病的系统水平视图是必要的。利用全基因组表达数据集,我们构建并比较了癌前肿瘤(腺瘤)和癌性肿瘤(癌)与配对正常网络的基因共表达特异性网络,以评估网络连通性的任何可能变化。以前,连通性的丧失被报道为癌症样本的一个特征。在这里,我们观察到癌前病变的连接也明显少于配对的正常样本。我们观察到结直肠腺瘤、醛固酮产生腺瘤和子宫平滑肌瘤的连通性丧失趋势。我们还表明,连通性的丧失趋势并不特定于基于正相关或负相关的网络。差异中心基因是肿瘤中差异程度最高的基因,在不同的数据集之间大多存在差异。没有一个共同的基因列表可以定义肿瘤特异性网络较低连通性的基础。结直肠癌甲基化靶点的连通性不同于其他基因。细胞外空间相关术语在结直肠癌的差异中心和常见甲基化靶点中丰富。我们的研究结果表明,当细胞不仅转变为癌症,而且转变为癌前状态时,低连通性的系统水平发生了变化。这种系统级的行为不能归因于一组基因。
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来源期刊
In Silico Biology
In Silico Biology Computer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍: The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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