基于互信息研究的乳腺癌与阿尔茨海默症的免疫系统发病机理探寻

doi:10.3969/j.issn.0258-8021. 2016. 03.006

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Abstract In recent years, a growing number of epidemiological studies have shown that many kinds of cancer and Alzheimer′s disease have an inverse association, but the molecular biological mechanism remains unclear. Researching the inverse association from gene signal transduction and regulatory networks will play an important role in exploring the pathogenesis of both diseases. Breast cancer (BC) and AD were selected to be analyzed. Taking account of that the traditional genes extraction algorithms focused on a single gene expressed differently in different samples and ignored the links among the correlation genes, mutual information (MI) was utilized to extract the differentially expressed genes in the two diseases basing on the correlation among genes using as feature genes. In this paper, considering the limitation of network component analysis (NCA),such as the strong constraint conditions and the long running time, fast-network component analysis (FastNCA), improved by NCA,was brought up to get the activity of transcription factors among feature genes and TF′s regulate strength of target genes, and construct two diseases transcriptional regulatory networks, respectively. Experimental results showed that the activities and the regulate and control strength of TFs were totally opposite in the two diseases, for example POLR2E, RFC5, THOC4, FBXO22, KPNA1, MYST3 and PTBP1, for example, transcription factors RFC5 activities in BC decreased from 0.269 to 0.077, and in AD increased by -0.430 to 0.307. According to the experiment and analysis of molecular biology, the regulate relationship and the biological process influence from these TFs play a vital role in BC and AD.

Key words： breast cancer Alzheimer′s disease mutual information fast network component analysis immunity

Received: 28 October 2015

PACS:

Q343.1

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	Liu Fang
	Kong Wei
	Mou Xiaoyang

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Liu Fang,Kong Wei,Mou Xiaoyang. Exploration of Pathogenesis in Immune System of Breast Cancer and Alzheimer′s Disease Based on Mutual Information[J]. Chinese Journal of Biomedical Engineering, 2016, 35(3): 292-300.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021. 2016. 03.006 OR http://cjbme.csbme.org/EN/Y2016/V35/I3/292

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