Single-Cell RNA Sequencing of the Rat Carotid Arteries Uncovers Potential Cellular Targets of Neointimal Hyperplasia.
Single-Cell RNA Sequencing of the Rat Carotid Arteries Uncovers Potential Cellular Targets of Neointimal Hyperplasia.
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大鼠颈动脉的单细胞 RNA 测序揭示了新内膜增生的潜在细胞靶点
DOI:
10.3389/fcvm.2021.751525
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发表时间:
2021
影响因子:
3.6
通讯作者:
Chen SL
中科院分区:
文献类型:
--
作者:
Gao XF;Chen AQ;Wang ZM;Wang F;Luo S;Chen SY;Gu Y;Kong XQ;Zuo GF;Chen Y;Ge Z;Zhang JJ;Chen SL
Aims: In-stent restenosis (ISR) remains an Achilles heel of drug-eluting stents despite technical advances in devices and procedural techniques. Neointimal hyperplasia (NIH) is the most important pathophysiological process of ISR. The present study mapped normal arteries and stenotic arteries to uncover potential cellular targets of neointimal hyperplasia. Methods and Results: By comparing the left (control) and right (balloon injury) carotid arteries of rats, we mapped 11 clusters in normal arteries and 11 mutual clusters in both the control and experimental groups. Different clusters were categorized into 6 cell types, including vascular smooth muscle cells (VSMCs), fibroblasts, endothelial cells (ECs), macrophages, unknown cells and others. An abnormal cell type expressing both VSMC and fibroblast markers at the same time was termed a transitional cell via pseudotime analysis. Due to the high proportion of VSMCs, we divided them into 6 clusters and analyzed their relationship with VSMC phenotype switching. Moreover, N-myristoyltransferase 1 (NMT1) was verified as a credible VSMC synthetic phenotype marker. Finally, we proposed several novel target genes by disease susceptibility gene analysis, such as Cyp7a1 and Cdk4, which should be validated in future studies. Conclusion: Maps of the heterogeneous cellular landscape in the carotid artery were defined by single-cell RNA sequencing and revealed several cell types with their internal relations in the ISR model. This study highlights the crucial role of VSMC phenotype switching in the progression of neointimal hyperplasia and provides clues regarding the underlying mechanism of NIH.
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影响因子:
10.8
作者:
Durham AL;Speer MY;Scatena M;Giachelli CM;Shanahan CM
通讯作者:
Shanahan CM
影响因子:
6
作者:
Huaman, Jeannette;Ogunwobi, Olorunseun O.
通讯作者:
Ogunwobi, Olorunseun O.
影响因子:
5
作者:
Chen Yifan;Yang Fan;Pu Jun
通讯作者:
Pu Jun
影响因子:
15.9
作者:
Jain, Manish;Dhanesha, Nirav;Chauhan, Anil K.
通讯作者:
Chauhan, Anil K.
影响因子:
16.6
作者:
Liang, Jiyong;Xu, Zhi-Xiang;Mills, Gordon B.
通讯作者:
Mills, Gordon B.