Identification of brain endothelial cell-specific genes and pathways in ischemic stroke by integrated bioinformatical analysis

Yi Yan; Zhaohui Wang; Xiao Liu; Song Han; Junfa Li; Ying Zhang; Li Zhao

doi:10.4103/bc.bc_40_23

Identification of brain endothelial cell-specific genes and pathways in ischemic stroke by integrated bioinformatical analysis

Brain Circ. 2023 Nov 30;9(4):228-239. doi: 10.4103/bc.bc_40_23. eCollection 2023 Oct-Dec.

Authors

Yi Yan¹, Zhaohui Wang¹, Xiao Liu¹, Song Han^{1

2}, Junfa Li^{1

2}, Ying Zhang^{1

2

3}, Li Zhao^{1

2}

Affiliations

¹ Department of Neurobiology, Capital Medical University, Beijing, China.
² Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China.
³ Beijing Key Laboratory of Hypoxia Conditioning Translational Medicine, Beijing, China.

Abstract

Background: Ischemic stroke (IS) is a life-threatening condition with limited treatment options; thus, finding the potential key genes for novel therapeutic targets is urgently needed. This study aimed to explore novel candidate genes and pathways of brain microvessel endothelial cells (ECs) in IS by bioinformatics analysis.

Materials and methods: The gene expression profiles of brain tissues or brain ECs in IS mice were downloaded from the online gene expression omnibus (GEO) to obtain the differentially expressed genes (DEGs) by R software. Functional enrichment analyses were used to cluster the functions and signaling pathways of the DEGs, while DEG-associated protein-protein interaction network was performed to identify hub genes. The target microRNAs and competitive endogenous RNA networks of key hub genes were constructed by Cytoscape.

Results: Totally 84 DEGs were obtained from 6 brain tissue samples and 4 brain vascular EC samples both from IS mice in the datasets GSE74052 and GSE137482, with significant enrichment in immune responses, such as immune system processes and T-cell activation. Eight hub genes filtered by Cytoscape were validated by two other GEO datasets, wherein key genes of interest were verified by reverse transcription-polymerase chain reaction using an in vitro ischemic model of EC cultures. Our data indicated that AURKA and CENPF might be potential therapeutic target genes for IS, and Malat1/Snhg12/Xist-miR-297b-3p-CENPF, as well as Mir17 hg-miR-34b-3p-CENPF, might be RNA regulatory pathways to control IS progression.

Conclusions: Our work identified two brain EC-specific expressed genes in IS, namely, AURKA and CENPF, as potential gene targets for IS treatment. In addition, we presented miR-297b-3p/miR-34b-3p-CENPF as the potential RNA regulatory axes to prevent pathogenesis of IS.

Keywords: Bioinformatics analysis; RNA regulatory pathways; endothelial cells; gene expression omnibus datasets; ischemic stroke.