肝细胞癌中表达水平的快速演变

Q4 Pharmacology, Toxicology and Pharmaceutics International Journal of Computational Biology and Drug Design Pub Date : 2020-01-01 DOI:10.1504/IJCBDD.2020.113830
Fan Zhang, M. Kuo
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引用次数: 0

摘要

人类进化与癌症进化的研究已经进行了多年,但人们对人类进化与癌症进化之间的分子相似性知之甚少。在比较和分析人类进化和癌症进化时,一个有趣而重要的问题是癌症易感性是否与人类进化有关。有一些关于人类进化或癌症发展的微阵列研究。然而,到目前为止,还没有对两者进行微阵列研究。由于癌症是在小时间和空间尺度上的进化,我们使用线性混合模型、方差分析(ANOVA)、基因本体(GO)和基于人类进化的癌症基因表达分析,比较和分析了猩猩、黑猩猩、人类、非肿瘤组织和原发性癌症的肝脏基因表达数据。我们的研究结果不仅揭示了肝细胞癌中表达水平相对于人类基因表达进化速度的快速进化,而且揭示了人类特异性基因表达与癌症特异性基因表达的相关性。进一步的基因本体论分析表明,基因功能与表达模式之间的统计关系可能有助于理解人类进化与癌症发生的关系。
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Rapid evolution of expression levels in hepatocellular carcinoma
The human evolution and cancer evolution have been researched for several years, but little is known about the molecular similarities between human and cancer evolution. One interesting and important question when comparing and analyzing human evolution and cancer evolution is whether cancer susceptibility is related to human evolution. There are a few microarray studies on human evolution or cancer development. Yet, to date, no microarray studies have been performed with both. Since cancer is an evolution on a small time and space scale, we compared and analyzed liver gene expression data among orangutan, chimpanzee, human, nontumor tissue, and primary cancer using linear mixed model, Analysis of Variance (ANOVA), Gene Ontology (GO), and Human Evolution Based Cancer Gene Expression Analysis. Our results revealed not only rapid evolution of expression levels in hepatocellular carcinoma relative to the gene expression evolution rate of human, but also the correlation between human specific gene expression and cancer specific gene expression. Further gene ontology analysis also suggested statistical relationship between gene function and expression pattern might help understanding the relationship between human evolution and cancer development.
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来源期刊
International Journal of Computational Biology and Drug Design
International Journal of Computational Biology and Drug Design Pharmacology, Toxicology and Pharmaceutics-Drug Discovery
CiteScore
1.00
自引率
0.00%
发文量
8
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