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. 2022 Jul 6:9:954283.
doi: 10.3389/fcvm.2022.954283. eCollection 2022.

The Long Non-coding RNA AC148477.2 Is a Novel Therapeutic Target Associated With Vascular Smooth Muscle Cells Proliferation of Femoral Atherosclerosis

Kangjie Wang  1   2 , Yanchen Ye  1   2 , Lin Huang  1   2 , Ridong Wu  1   2 , Rongzhou He  1   2 , Chen Yao  1   2 , Shenming Wang  1   2
Affiliations

The Long Non-coding RNA AC148477.2 Is a Novel Therapeutic Target Associated With Vascular Smooth Muscle Cells Proliferation of Femoral Atherosclerosis

Kangjie Wang et al. Front Cardiovasc Med. .

Abstract

Arteriosclerosis obliterans (ASO) is a limb manifestation of large vessel atherosclerosis. Phenotype switching of vascular smooth muscle cells (VSMCs) occurs in the course of the pathological process. The underlying mechanism of SMCs proliferation remains unclear. Several studies have demonstrated that the dysregulation of long non-coding RNA (lncRNAs) plays a pivotal part in the progression of ASO by exacerbating the proliferation of VSMCs. Based on the endogenous competitive RNA (ceRNA) hypothesis, the mechanism of lncRNAs involved in the pathology of VSMCs was exposed, while the entire map of the regulatory network remains to be elucidated. In the current study, genes and the lncRNAs modules that are relevant to the clinical trait were confirmed through weighted gene co-expression network analysis (WGCNA). In this study, we comprehensively constructed a specific lncRNAs-mediated ceRNA and RBP network. The three lncRNAs, HMGA1P4, C5orf66, and AC148477.2, influenced the proliferation of VSMCs and were found to be associated with the immune landscape, thus they were ultimately screened out. Further verification revealed that AC147488.2 was significantly down-regulated in both ASO arteries and all stages of proliferative VSMCs, which implied that AC147488.2 might have a significant impact on ASO. This finding would improve our understanding of the epigenetic regulation of ASO and unravel novel diagnostic and therapeutic targets.

Keywords: arteriosclerosis obliterans; femoral atherosclerosis; long non-coding RNA; superficial femoral artery; vascular smooth muscle cells.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
The flow chart of the procedures carried out in this study.
FIGURE 2
FIGURE 2
WGCNA analysis of genes in femoral atherosclerosis. (A) The chosen soft threshold power of genes matrix. (B) The cluster dendrogram of gene module. (C) The correlation heatmap of module-trait relationships. The first-row number in each block indicates the correlation coefficient. The number in parentheses represents the p-value. (D) Heatmap displays the expression of genes in the screened modules between two groups.
FIGURE 3
FIGURE 3
WGCNA analysis of lncRNAs in femoral atherosclerosis. (A) The soft threshold power was screened for the lncRNAs matrix. (B) The cluster dendrogram of lncRNAs modules. (C) The correlation heatmap displays the association between lncRNAs modules and clinical traits. (D) Heatmap exhibits the expression of lncRNAs in screened modules.
FIGURE 4
FIGURE 4
Enrichment analysis of gene modules and GSEA analysis. (A) The top 10 GO enrichment analyses of two modules. (B) The top 10 signal pathways of KEGG pathway enrichment. Criteria threshold of p < 0.05 and adjusted. p < 0.05. (C) Gene set enrichment analysis in femoral atherosclerosis. Criteria threshold of adjusted. p < 0.05.
FIGURE 5
FIGURE 5
Construction of VSMCs-specific PPI networks. (A,B) Volcano plots show the DEGs (A) and DElncRNAs (B) in proliferative VSMCs. Significantly upregulated genes and lncRNAs are marked in red and those that were downregulated are marked in blue with the threshold of |log2FC| ≥ 1 and adjusted. p < 0.05. (B,C) Venn diagrams display the specific proliferative VSMCs genes (B) and lncRNAs (D). (E) The PPI network of the defined sp-SMCGs. Each gene is displayed in a green node with the label. The red nodes indicate the common Hub genes of the five algorithms in CytoHubba.
FIGURE 6
FIGURE 6
Construction of VSMCs specific ceRNA network. Green nodes indicate the mRNAs, blue nodes indicate the predicted miRNAs, and the red nodes indicate the lncRNAs.
FIGURE 7
FIGURE 7
Construction of VSMC-specific RBP network. Nodes with a green border represent the mRNAs, nodes with a blue border indicate the predicted RNA binding proteins, and red border nodes reveal the lncRNAs. The thickness of the edge reflects the number of binding sites.
FIGURE 8
FIGURE 8
Univariate logistic regression and ROC curves of 3 lncRNAs. (A) Univariate logistic regression analysis of HMGA1P4, C5orf66, and AC148477.2. (B) AUC of ROC curves of HMGA1P4, C5orf66, and AC148477.2.
FIGURE 9
FIGURE 9
Validated expression of the three lncRNAs. Validation of each lncRNAs in the artery samples (n = 12 in each group), PDGF-bb (n = 3), ox-LDL (n = 4), and TNF-α (n = 4) treated VSMCs are shown by histogram (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001).
FIGURE 10
FIGURE 10
Immune infiltration of 37 artery samples based on CIBESORT analysis tool. (A) The infiltrated immune landscape is visualized in the heat map. (B) The correlation heat map presents the association between lncRNAs and immune cells. The red square represents positive correlation and the blue square represents negative correlation (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001).
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