通过大量和单细胞转录分析评估 IER3+ 巨噬细胞在肝纤维化预后中的作用

Ling Chu , Junbo Zhang , Ruoyu Meng , Quan Zhuang
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引用次数: 0

摘要

背景和目的肝纤维化(LF)是几乎所有肝病的共同病理过程,但其发病机制极其复杂,尚未完全阐明。因此,我们希望探索肝纤维化复杂的发病机制,并找出能预测肝纤维化预后的关键遗传标记。方法从基因表达总库(Gene Expression Omnibus,GEO,https://www.ncbi.nlm.nih.gov/geo/)中,我们包含了数据集 GSE84044 和 GSE130970。并涉及 GSE15654,其生存数据用于验证我们模型的预后价值。结果我们建立了一个包含四个基因(IER3、AKR1B10、ADCY1 和 PGM1)的全面的 LF 相关预后模型(FMSig,即纤维化巨噬细胞相关预后特征)。FMSig 可以区分 GSE15654 数据集中的生存结果。与其他三个 FMSig 基因相比,IER3 的危险比更高。此外,进一步的 scRNA-seq 分析表明,IER3 在骨髓细胞中高表达,而其他三个基因在六种免疫细胞类型和其他细胞群中很少表达。将髓系细胞重新聚类为 7 个细胞群后,我们发现 IER3 在髓系细胞群 3 中高表达,而髓系细胞群 3 与抗炎和脂质代谢功能有关。根据假时分析,我们认为髓系细胞 3 型是由肝硬化微环境中的髓系细胞 0 型转化而来的。在免疫组化染色中,LF 的 IER3 表达明显高于健康对照组。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating the role of IER3+ macrophages in the prognosis of liver fibrosis by bulk and single-cell transcriptional analyses

Background and aims

Liver fibrosis (LF) is the common pathological process of almost all liver diseases, but the pathogenesis is extremely complicated and has not been fully clarified. Therefore, we want to explore LF's complex pathogenesis and identify key genetic markers that can predict LF prognosis.

Methods

From Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/), we contained datasets GSE84044 and GSE130970. And involved GSE15654 whose survival data were for the validation of our model’s prognostic value. Then, Bulk RNA sequencing was used to establish a LF-related prognostic model and to determine key genes.The key genes were later analyzed using single-cell RNA sequencing (scRNA-seq) and the role of macrophages in LF was investigated.

Results

We established a comprehensive LF-related prognostic model (FMSig, i.e., fibrosis macrophage-related prognostic signature) containing four genes (IER3, AKR1B10, ADCY1, and PGM1). FMSig can distinguish between survival outcomes in dataset GSE15654. IER3 showed a higher hazard ratio than the other three FMSig genes. Moreover, further scRNA-seq analysis showed that IER3 is highly expressed in myeloid cells while the other three genes were rarely expressed in six immune cell types and other cell clusters. After reclustering the myeloid cells into seven clusters, we found that IER3 was highly expressed in myeloid cell cluster 3, shown to be related to anti-inflammation and lipid metabolism functions. Based on pseudotime analysis, we suggest that myeloid cell type 3 is transformed from myeloid cell type 0 in the liver cirrhosis microenvironment. On immunohistochemical staining, LF showed significantly higher IER3 expression than healthy controls.

Conclusion

This study established a predictive model, FMSig, to evaluate LF prognosis, and showed that IER3 and macrophages are related to LF.
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