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Comparative Study
. 2017 Jul 18;12(7):e0180337.
doi: 10.1371/journal.pone.0180337. eCollection 2017.

Differences of immune disorders between Alzheimer's disease and breast cancer based on transcriptional regulation

Affiliations
Comparative Study

Differences of immune disorders between Alzheimer's disease and breast cancer based on transcriptional regulation

Wei Kong et al. PLoS One. .

Abstract

Although chronic inflammation and immune disorders are of great importance to the pathogenesis of both dementia and cancer, the pathophysiological mechanisms are not clearly understood. In recent years, growing epidemiological evidence and meta-analysis data suggest an inverse association between Alzheimer's disease (AD), which is the most common form of dementia, and cancer. It has been revealed that some common genes and biological processes play opposite roles in AD and cancer; however, the biological immune mechanism for the inverse association is not clearly defined. An unsupervised matrix decomposition two-stage bioinformatics procedure was adopted to investigate the opposite behaviors of the immune response in AD and breast cancer (BC) and to discover the underlying transcriptional regulatory mechanisms. Fast independent component analysis (FastICA) was applied to extract significant genes from AD and BC microarray gene expression data. Based on the extracted data, the shared transcription factors (TFs) from AD and BC were captured. Second, the network component analysis (NCA) algorithm in this study was presented to quantitatively deduce the TF activities and regulatory influences because quantitative dynamic regulatory information for TFs is not available via microarray techniques. Based on the NCA results and reconstructed transcriptional regulatory networks, inverse regulatory processes and some known innate immune responses were described in detail. Many of the shared TFs and their regulatory processes were found to be closely related to the adaptive immune response from dramatically different directions and to play crucial roles in both AD and BC pathogenesis. From the above findings, the opposing cellular behaviors demonstrate an invaluable opportunity to gain insights into the pathogenesis of these two types of diseases and to aid in developing new treatments.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Structure flowchart of the proposed two-stage procedure.
This flowchart shows the two-stage procedure in this study to detect the inverse transcriptional regulatory process of AD and BC. The first stage is to extract the feature genes of AD and BC datasets by FastICA, and the second stage is to deduce the regulatory activities and control strength of common TFs by NCA, then the TFs with inverse association will be selected for further study.
Fig 2
Fig 2. Dynamic transcriptional regulatory networks for the AD dataset.
(A) presents the transcriptional regulatory network for the control samples, and (B) shows the transcriptional regulatory network for AD samples. The diamonds in the middle denote TFs with different colors according to their activity values. The different colored circles display TG gene expression, and the different colored lines between the TFs and TGs show the control strength.
Fig 3
Fig 3. Dynamic transcriptional regulatory networks for the BC dataset.
(A) presents the transcriptional regulatory network for the control samples, and (B) shows transcriptional regulatory network for the BC samples. The diamonds in the middle denote TFs, with different colors according to their activity values. The different colored circles display TG gene expression, and the different colored lines between the TFs and TGs show the control strength.
Fig 4
Fig 4. Flowchart of the experiments for different datasets of one disease (AD/BC).
(A) gives the flowchart of the two-stage procedure in comparing AD-HIP dataset with AD in 3 severities dataset; (B) gives the flowchart of the two-stage procedure in comparing BC with no metastasis dataset with BC in 3 grades dataset.
Fig 5
Fig 5. The inversely associated TFs in Table 2 and their related genes, pathways and biological processes.
This figure shows the inverse regulatory activities of the common TFs and pathways between AD and BC. From the biological analysis we can know that they are closely related to innate and adaptive immune response.

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Publication types

Grants and funding

This work was supported by the National Natural Science Foundation of China (No. 61271446 and 31170952) and Innovation Program of Shanghai Municipal Education Commission (No. 15ZZ079).
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