Date Published: July 18, 2017
Publisher: Public Library of Science
Author(s): Wei Kong, Xiaoyang Mou, Jin Deng, Benteng Di, Ruxing Zhong, Shuaiqun Wang, Yang Yang, Weiming Zeng, Xia Li.
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.
Alzheimer’s disease (AD), which is the most common form of dementia, is a progressively fatal neurodegenerative disorder characterized by irreversible cognitive and memory deterioration that inevitably leads to death. AD has been known for more than 100 years and affects more than 13% of people older than 65 and 43% older than 85. However, the genetic mechanism and pathogenesis of AD are still unclear. An increasing number of studies show that chronic inflammation and immunosenescence play an important role in the progression of AD [1, 2]. Cancer, another type of age-related disorder, is a major health problem today. The immune system has been shown to play a significant role in its pathogenesis, though the exact pathophysiological mechanism has not been clearly defined [3, 4].
Accumulating epidemiological evidence and meta-analysis data suggest that there is a strong inverse correlation between AD and cancer. This suggests that there are shared genes or biological pathways regulated by both AD and cancer with dramatically different directions. Some significant genes and signaling pathways play critical but opposing roles in both AD and BC, such as p53 and Pin1; the Wnt, ERK/MAPK, and UPS signaling pathways; and some biological processes associated with metabolic dysregulation, such as oxidative stress, DNA damage/repair, aerobic glycolysis, inflammation and cellular immunity. Convincing evidence suggests that both AD and cancer are age-related immune dysregulation diseases and that age plays a crucial role in their pathogenesis. We know that high-throughput DNA microarray datasets can successfully investigate hundreds of thousands of gene expression profiles simultaneously; the high-dimensional data are typically the regulatory results of a small set of TFs through an interacting network. However, high-throughput technologies that measure TF activities are not yet available on a genome-wide scale. Therefore, some statistical computational methods were applied in this study to deduce the biologically significant information and underlying transcriptional regulatory structure for the inverse regulatory mechanisms between AD and BC. Based on our current understanding of the innate and adaptive immune system in neurodegenerative diseases and cancer, we focused on the contribution of inverse TFs in the present study to determine the immune balance and pathogenesis of AD and BC.