MicroRNA networks linked with BRCA1/2, PTEN, and common genes for Alzheimer's disease and breast cancer share highly enriched pathways that may unravel targets for the AD/BC comorbidity treatment.

Nina Petrović, Magbubah Essack, Ahmad Šami, George Perry, Takashi Gojobori, Esma R Isenović, Vladan P Bajić

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

MicroRNAs (miRNAs) are involved in the regulation of various cellular processes including pathological conditions. MiRNA networks have been extensively researched in age-related degenerative diseases, such as cancer, Alzheimer's disease (AD), and heart failure. Thus, miRNA has been studied from different approaches, in vivo, in vitro, and in silico including miRNA networks. Networks linking diverse biomedical entities unveil information not readily observable by other means. This work focuses on biological networks related to Breast cancer susceptibility 1 (BRCA1) in AD and breast cancer (BC). Using various bioinformatics approaches, we identified subnetworks common to AD and BC that suggest they are linked. According to our results, miR-107 was identified as a potentially good candidate for both AD and BC treatment (targeting BRCA1/2 and PTEN in both diseases), accompanied by miR-146a and miR-17. The analysis also confirmed the involvement of the miR-17-92 cluster, and miR-124-3p, and highlighted the importance of poorly researched miRNAs such as mir-6785 mir-6127, mir-6870, or miR-8485. After filtering the in silico analysis results, we found 49 miRNA molecules that modulate the expression of at least five genes common to both BC and AD. Those 49 miRNAs regulate the expression of 122 genes in AD and 93 genes in BC, from which 26 genes are common genes for AD and BC involved in neuron differentiation and genesis, cell differentiation and migration, regulation of cell cycle, and cancer development. Additionally, the highly enriched pathway was associated with diabetic complications, pointing out possible interplay among molecules underlying BC, AD, and diabetes pathology.
Original languageEnglish (US)
Pages (from-to)107925
JournalComputational Biology and Chemistry
Volume106
DOIs
StatePublished - Jul 22 2023

Bibliographical note

KAUST Repository Item: Exported on 2023-07-26
Acknowledged KAUST grant number(s): FCC/1/1976-20-01, OSR#4129
Acknowledgements: This work is part of the collaboration between the Department of Radiobiology and Molecular Genetics, “VINČA” Institute of Nuclear Sciences - National Institute of the Republic of Serbia, University of Belgrade, Belgrade, Serbia, Computational Bioscience Research Center (CBRC) at King Abdullah University of Science and Technology (KAUST) and Department of Radiation Oncology, University Medical Center Mannheim, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany. This work was funded by the Ministry of Education, Science and Technological Development of the Republic of Serbia (Contract no. #451-03-47/2023-01/200017) and KAUST Grant OSR#4129 (awarded to E.R.I. and T.G) and FCC/1/1976-20-01 (awarded to T.G).

ASJC Scopus subject areas

  • Biochemistry
  • Structural Biology
  • Organic Chemistry
  • Computational Mathematics

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