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, GSK3B, and HSPA9) and miRNAs (miR-146a-5p, MiR-34a-5p, miR-21-5p, miR-9-5p, and 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.

Candidate Genes and MiRNAs Linked to the Inverse Relationship Between Cancer and Alzheimer’s Disease: Insights From Data Mining and Enrichment Analysis / C. Battaglia, M. Venturin, A. Sojic, N. Jesuthasan, A. Orro, R. Spinelli, M. Musicco, G. De Bellis, F. Adorni. - In: FRONTIERS IN GENETICS. - ISSN 1664-8021. - 10(2019 Sep 24), pp. 846.1-846.14. [10.3389/fgene.2019.00846]

Candidate Genes and MiRNAs Linked to the Inverse Relationship Between Cancer and Alzheimer’s Disease: Insights From Data Mining and Enrichment Analysis

C. Battaglia
Primo
;
M. Venturin
Secondo
;
2019

Abstract

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, GSK3B, and HSPA9) and miRNAs (miR-146a-5p, MiR-34a-5p, miR-21-5p, miR-9-5p, and 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.
genes, miRNAs, cancer, Alzheimer, inverse relationship, data mining, enrichment analysis, protein-protein interaction network
Settore BIO/10 - Biochimica
Settore BIO/13 - Biologia Applicata
24-set-2019
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/677943
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