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

Petrović, Nina; Essack, Magbubah; Sami, Ahmad; Perry, George; Gojobori, Takashi; Isenović, Esma R.; Bajić, Vladan

doi:10.1016/j.compbiolchem.2023.107925

Cited by 4 publications

(2 citation statements)

References 113 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…CCR4 [407], hsa-mir-146a-5p [634] and NFKB1 [635] were associated with psychiatric disorders. LTF (lactotransferrin) [362], RHOB (ras homolog family member B) [396], CDH1 [377], CFTR (CF transmembrane conductance regulator) [380], hsa-mir-146a-5p [636], hsa-mir-195-5p [637], BRCA1 [638], ELK4 [639] and FOXO3 [640] might offer useful information for treating Alzheimer’s Disease. LTF (lactotransferrin) [541], CFTR (CF transmembrane conductance regulator) [551], hsa-mir-195-5p [627], BRCA1 [641], NFKB1 [642], TFAP2C [643], FOXO3 [644] and NRF1 [645] are associated with poor prognosis in patients with hypertension.…”

Section: Discussionmentioning

confidence: 99%

Identification of candidate biomarkers and pathways associated with multiple sclerosis using bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2023

Preprint

View full text Add to dashboard Cite

Multiple sclerosis (MS) is the main reason for disability caused by autoimmunity. However, effective biomarkers for MS have not been identified. This study explored the molecular mechanisms and potential therapeutic targets for MS occurrence and progression using bioinformatics and next generation sequencing (NGS) data analysis. NGS data GSE138614, including patients with MS and 25 normal control samples, were obtained from Gene Expression Omnibus (GEO) database Differentially expressed genes (DEGs) were filtered and subjected to gene ontology (GO) and pathway enrichment analyses. Protein–protein interaction (PPI) network and module analyses were performed based on the DEGs. MiRNA-hub gene regulatory network and TF-hub gene regulatory network analysis were built by Cytoscape to predict the underlying microRNAs (miRNAs) and transcription factors (TFs) associated with hub genes. We also validated the identified hub genes via receiver operating characteristic (ROC) curve analysis. A total of 959 DEGs (479 up regulated genes and 480 down regulated genes) were detected. The GO terms and pathways of DEGs involve immune system process, developmental process, immune system and regulation of cholesterol biosynthesis by SREBP (SREBF). The network analysis revealed that hub genes include LCK, PYHIN1, SLAMF1, DOK2, TAB2, CFTR, RHOB, LMNA, EGLN3 and ERBB3 might be involved in the development of MS. The present investigation illustrates a characteristic gene profile in MS, which might contribute to the interpretation of the progression of MS and provide novel biomarkers and therapeutic targets for MS.

show abstract

Section: Discussionmentioning

confidence: 99%

Identification of candidate biomarkers and pathways associated with multiple sclerosis using bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…miRNAs are involved in the regulation of various cellular processes including pathological conditions. Petrovic et al (2023) identified miR-107, miR-146a, and miR-17 as potentially good candidates for both AD and breast cancer treatment (targeting BRCA1/2 and PTEN in both diseases). Chen et al (2021) constructed circRNA-miRNA target network for explore the circRNA relationship between AD and cancer, and found three hub nodes CircPICALM, circRTN4 and circMAN2A1.…”

Section: Identification Of Shared Candidate Biomarkers Between Ad And...mentioning

confidence: 99%

A review and analysis of key biomarkers in Alzheimer’s disease

Zhang,

Liu,

Zhang

et al. 2024

Front. Neurosci.

View full text Add to dashboard Cite

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects over 50 million elderly individuals worldwide. Although the pathogenesis of AD is not fully understood, based on current research, researchers are able to identify potential biomarker genes and proteins that may serve as effective targets against AD. This article aims to present a comprehensive overview of recent advances in AD biomarker identification, with highlights on the use of various algorithms, the exploration of relevant biological processes, and the investigation of shared biomarkers with co-occurring diseases. Additionally, this article includes a statistical analysis of key genes reported in the research literature, and identifies the intersection with AD-related gene sets from databases such as AlzGen, GeneCard, and DisGeNet. For these gene sets, besides enrichment analysis, protein–protein interaction (PPI) networks utilized to identify central genes among the overlapping genes. Enrichment analysis, protein interaction network analysis, and tissue-specific connectedness analysis based on GTEx database performed on multiple groups of overlapping genes. Our work has laid the foundation for a better understanding of the molecular mechanisms of AD and more accurate identification of key AD markers.

show abstract

MicroRNA-based interventions in aberrant cell cycle diseases: Therapeutic strategies for cancers, central nervous system disorders and comorbidities

Tang,

Ren,

Zeng

et al. 2024

Biomedicine & Pharmacotherapy

View full text Add to dashboard Cite

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

Cited by 4 publications

References 113 publications

Identification of candidate biomarkers and pathways associated with multiple sclerosis using bioinformatics and next generation sequencing data analysis

Identification of candidate biomarkers and pathways associated with multiple sclerosis using bioinformatics and next generation sequencing data analysis

A review and analysis of key biomarkers in Alzheimer’s disease

MicroRNA-based interventions in aberrant cell cycle diseases: Therapeutic strategies for cancers, central nervous system disorders and comorbidities

Contact Info

Product

Resources

About