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构建用于圆锥角膜诊断的疾病特异性ceRNA共调控网络及免疫环境全景图。

Constructing a disease-specific ceRNA coregulatory network for keratoconus diagnosis and landscape of the immune environment.

作者信息

Lu Jianqun, Le Yuan, Bi Juan

机构信息

Department of Ophthalmology, People's Hospital of Leshan, Leshan, Sichuan, China.

出版信息

Int Ophthalmol. 2025 Mar 22;45(1):115. doi: 10.1007/s10792-025-03488-4.

Abstract

PURPOSE

The early diagnosis of keratoconus (KC) is crucial for making treatment decisions. Therefore, the purpose of this study was to determine the potential disease-specific gene biomarker and landscape the immune environment in KC.

METHODS

The transcriptome data of KC was obtained from Gene Expression Omnibus (GEO) and ArrayExpress databases for next analysis. The differently expressed mRNAs, microRNAs and lncRNAs between KC and control groups were firstly identified and the disease-specific protein-protein interaction (PPI) network as well as competing endogenous RNA (ceRNA) coregulatory network were constructed to explore the underlying molecular mechanism of KC. Besides, ElasticNet algorithm was used to develop a diagnostic model and associated nomograms to improve diagnosis of KC. Finally, multiple deconvolution methodologies were applied to decode the immune environment of KC patients.

RESULTS

In brief, we constructed the disease-specific PPI and ceRNA networks in KC through integrative analyses. The pathway enrichment manifested that these networks were significantly associated with lipopolysaccharide, chemokine and inflammatory related pathways. Based on the ceRNA network, we constructed a diagnostic model and associated nomogram which manifested a good performance for diagnosis of KC. Moreover, contrasted to control groups, we obviously observed that a distinct immune microenvironment existed in KC patients. Via single-cell sequencing analysis, we found that immune cells (Monocytes, Macrophages, and T cells) were strongly connected with corneal cells in KC patients.

CONCLUSIONS

In sum, we systematically constructed a diagnostic model and associated nomogram which provided novel biomarkers for the early detection of KC. Besides, our study comprehensively displayed the immune microenvironment of KC which provided new insights for understanding the molecular mechanism of KC.

摘要

目的

圆锥角膜(KC)的早期诊断对于制定治疗决策至关重要。因此,本研究的目的是确定潜在的疾病特异性基因生物标志物,并描绘KC中的免疫环境。

方法

从基因表达综合数据库(GEO)和ArrayExpress数据库获取KC的转录组数据用于后续分析。首先鉴定KC组和对照组之间差异表达的mRNA、microRNA和lncRNA,并构建疾病特异性蛋白质-蛋白质相互作用(PPI)网络以及竞争性内源性RNA(ceRNA)共调控网络,以探索KC的潜在分子机制。此外,使用弹性网络算法开发诊断模型和相关列线图以改善KC的诊断。最后,应用多种去卷积方法解析KC患者的免疫环境。

结果

简而言之,我们通过综合分析构建了KC中的疾病特异性PPI和ceRNA网络。通路富集表明这些网络与脂多糖、趋化因子和炎症相关通路显著相关。基于ceRNA网络,我们构建了一个诊断模型和相关列线图,其在KC诊断中表现出良好的性能。此外,与对照组相比,我们明显观察到KC患者中存在独特的免疫微环境。通过单细胞测序分析,我们发现免疫细胞(单核细胞、巨噬细胞和T细胞)与KC患者的角膜细胞紧密相连。

结论

总之,我们系统地构建了一个诊断模型和相关列线图,为KC的早期检测提供了新的生物标志物。此外,我们的研究全面展示了KC的免疫微环境,为理解KC的分子机制提供了新的见解。

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