Comprehensive analysis of a necroptosis-associated diagnostic signature for myelodysplastic syndromes based on single-cell RNA-seq and bulk RNA-seq.

IF 2.7 3区 生物学
Huimin Zhang, Li Zhang, Xiaoning Liang, Lihong Zhang, Bing Ma, Yuexian Li, Jianying Wang, Yang Shen, Yuhui Pang, Jianjun Xiong
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引用次数: 0

Abstract

Background: Myelodysplastic syndromes (MDS) are heterogeneous and clonal hematological disorders. The role and mechanism of necroptosis in MDS remain poorly understood.

Methods: mRNA expression profiles and single-cell RNA-sequencing (scRNA-seq) data were sourced from the GEO database. ScRNA-seq data were processed using the "Seurat" package. After cell annotation, necroptosis-related scores (NRscores) for each cell were calculated using the "UCell" package. Differentially expressed genes (DEGs) and their associated biological functions in NRscore-related cell populations were identified. Additionally, DEGs and necroptosis-related genes (DE-NRGs) between MDS patients and healthy controls were identified. Consensus clustering was employed to classify MDS patients into distinct subclusters based on DE-NRGs. The biological functions and immune characteristics of these classifications were analyzed. Prognostic gene signatures were determined using LASSO and SVM-RFE analyses, and a nomogram was constructed based on the prognostic gene signature.

Results: A total of 12 cell types were identified in MDS and healthy controls. NRscore was found to be elevated in monocytes and common lymphoid precursors (CLPs). Enrichment analysis revealed that monocytes and CLPs with high NRscore were associated with mitochondria-related and immune-related pathways. Eleven DEGs in monocytes and CLPs between MDS patients and healthy controls were identified. Additionally, 13 DE-NRGs were identified from 951 DEGs between MDS and healthy controls. MDS patients were classified into two distinct subclusters based on these 13 DE-NRGs, revealing several immune-related processes and signaling pathways. Differences in immune subpopulations between the two subclusters were observed. A necroptosis-related diagnostic gene signature (IRF9, PLA2G4A, MLKL, BAX, JAK2, and STAT3) was identified as predictive of MDS prevalence.

Conclusion: Necroptosis plays a role in MDS progression by inducing inflammation. A novel necroptotic gene signature has been developed to distinguish and diagnose MDS at early stages of the disease.

基于单细胞RNA-seq和大体RNA-seq的骨髓增生异常综合征坏死相关诊断特征的综合分析
背景:骨髓增生异常综合征(MDS骨髓增生异常综合征(MDS)是一种异质性克隆性血液病。方法:mRNA表达谱和单细胞RNA测序(scRNA-seq)数据来自GEO数据库。使用 "Seurat "软件包处理 ScRNA-seq 数据。细胞注释后,使用 "UCell "软件包计算每个细胞的坏死相关分数(NRscores)。在与 NRscores 相关的细胞群中,确定了差异表达基因(DEGs)及其相关的生物学功能。此外,还确定了 MDS 患者和健康对照组之间的 DEGs 和坏死相关基因(DE-NRGs)。根据 DE-NRGs 采用共识聚类将 MDS 患者分为不同的亚群。分析了这些分类的生物功能和免疫特征。利用LASSO和SVM-RFE分析确定了预后基因特征,并根据预后基因特征构建了提名图:结果:在 MDS 和健康对照组中共发现了 12 种细胞类型。发现单核细胞和普通淋巴前体(CLPs)的NRscore升高。富集分析显示,NRscore较高的单核细胞和CLPs与线粒体相关和免疫相关通路有关。在MDS患者和健康对照组的单核细胞和CLP中发现了11个DEGs。此外,还从MDS和健康对照组的951个DEG中鉴定出13个DE-NRG。根据这 13 个 DE-NRGs 将 MDS 患者分为两个不同的亚群,揭示了多个免疫相关过程和信号通路。两个亚群之间的免疫亚群存在差异。与坏死相关的诊断基因特征(IRF9、PLA2G4A、MLKL、BAX、JAK2 和 STAT3)被确定为可预测 MDS 患病率:结论:坏死基因通过诱导炎症在MDS进展过程中发挥作用。结论:坏死因子通过诱导炎症在 MDS 的进展过程中发挥作用。已开发出一种新型坏死因子基因特征,用于在疾病的早期阶段区分和诊断 MDS。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Hereditas
Hereditas Biochemistry, Genetics and Molecular Biology-Genetics
CiteScore
3.80
自引率
3.70%
发文量
0
期刊介绍: For almost a century, Hereditas has published original cutting-edge research and reviews. As the Official journal of the Mendelian Society of Lund, the journal welcomes research from across all areas of genetics and genomics. Topics of interest include human and medical genetics, animal and plant genetics, microbial genetics, agriculture and bioinformatics.
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