Original Research ARTICLE
Candidate genes and miRNAs linked to the inverse relationship between cancer and Alzheimer’s disease: insights from data mining and enrichment analysis
- 1Department of Medical Biotechnology and Translational Medicine, Faculty of Medicine and Surgery, University of Milan, Italy
- 2Institute of Biomedical Technologies, Italian National Research Council, Italy
- 3IRIS State Higher Education Institute Versari Cesano Maderno, Italy
The incidence of cancer and Alzheimer’s disease (AD) increases exponentially with age. A growing body of epidemiological evidence and molecular investigations inspired the hypothesis of an inverse relationship between these two pathologies. It has been proposed that the two diseases might utilize the same proteins and pathways that are, however, modulated differently and sometimes in opposite directions. Investigation of the common processes underlying these diseases may enhance the understanding of their pathogenesis and may also guide novel therapeutic strategies. Starting from a text-mining approach, our in silico study integrated the dispersed biological evidence by combining data mining, gene set enrichment and protein-protein-interaction (PPI) analyses, while searching for common biological hallmarks linked to AD and cancer. We retrieved 138 genes (ALZCAN gene set), computed a significant number of enriched gene ontology clusters, and identified four PPI modules. The investigation confirmed the relevance of autophagy, ubiquitin proteasome system and cell death, as common biological hallmarks shared by cancer and AD. Then, from a closer investigation of the PPI modules and of the miRNAs enrichment data, several genes (SQSTM1, UCHL1, STUB1, BECN1, CDKN2A, TP53, EGFR, GSK3Β and HSPA9) and miRNAs (miR-146a-5p, MiR-34a-5p, miR-21-5p, miR-9-5p, miR-16-5p) emerged as promising candidates. The integrative approach uncovered novel miRNA-gene networks (e.g. miR-146 and miR-34 regulating p62 and Beclin1 in autophagy) that might give new insights into the complex regulatory mechanisms of gene expression in AD and cancer.
Keywords: text mining, miRNA, Metascape, Beegle, PPI Network, Aging, Autophagy, Genes, Enrichment
Received: 27 Mar 2019;
Accepted: 14 Aug 2019.
Edited by:Catia Scassellati, Centro San Giovanni di Dio Fatebenefratelli (IRCCS), Italy
Reviewed by:Claudia V. Maurer-Morelli, Campinas State University, Brazil
Carlo Maj, University of Bonn, Germany
Copyright: © 2019 Battaglia, Venturin, Sojic, Jesuthasan, Orro, Spinelli, Musicco, De Bellis and Adorni. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Prof. Cristina Battaglia, Department of Medical Biotechnology and Translational Medicine, Faculty of Medicine and Surgery, University of Milan, Milan, 20122, Lombardy, Italy, firstname.lastname@example.org