Role of inflammation-related genes as prognostic biomarkers and mechanistic implications in idiopathic pulmonary fibrosis.

IF 2.8 3区 生物学 Q2 GENETICS & HEREDITY
Frontiers in Genetics Pub Date : 2025-06-18 eCollection Date: 2025-01-01 DOI:10.3389/fgene.2025.1602588
Bing Bai, Wenfei Zhao, Fazhan Li, Yang Mi, Pengyuan Zheng
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引用次数: 0

Abstract

Introduction: Idiopathic Pulmonary Fibrosis (IPF) is a chronic, progressive lung disorder characterized by excessive fibrosis and structural remodeling of lung tissue. The role of inflammation in developing and progressing IPF is increasingly recognized as critical. However, the precise mechanisms and pathways of inflammation in IPF remain unclear. This study aimed to identify inflammation-related genes in IPF and develop a prognostic risk model using machine learning approaches.

Methods: The IPF dataset GSE70866 from the Gene Expression Omnibus database was analyzed to identify inflammation-related genes. Unsupervised clustering algorithms were used to classify IPF samples, followed by weighted gene co-expression network analysis (WGCNA) to identify highly correlated genes. Least absolute shrinkage and selection operator (LASSO) regression was then applied, and the intersection of results pinpointed critical hub genes, primarily CCL2 and STAB1. A rat model of pulmonary fibrosis was established, and lentivirus transfection was used to knock down CCL2 expression. The transfection effect and hub gene expression were validated using Quantitative polymerase chain reaction, Western blot, immunohistochemistry, enzyme-linked immunosorbent assay, hematoxylin-eosin staining, and Masson's trichrome staining. Levels of α-SMA and COL1A1 were also assessed.

Results: WGCNA and LASSO regression analyses identified CCL2 and STAB1 as significant contributors to IPF, closely associated with patient prognosis and immune cell infiltration. Protein-protein interaction network analysis established CCL2 as a novel biomarker for IPF. In a rat model of IPF, CCL2 expression was significantly elevated compared to that in the controls. Knockdown of CCL2 expression alleviated pulmonary fibrosis and reduced the expression of COL1A1 protein and α-SMA protein. CCL2 promotes the expression of COL1A1 protein and α-SMA proteins, suggesting that the mechanism of inflammation-induced pulmonary fibrosis may involve the regulation of COL1A1 and α-SMA by CCL2.

Discussion: These findings establish CCL2 as a promising biomarker and potential therapeutic target for IPF.

炎症相关基因在特发性肺纤维化中作为预后生物标志物和机制意义的作用。
特发性肺纤维化(IPF)是一种慢性进行性肺疾病,其特征是肺组织过度纤维化和结构重塑。炎症在IPF的发展和进展中的作用越来越被认为是至关重要的。然而,炎症在IPF中的确切机制和途径尚不清楚。本研究旨在识别IPF中的炎症相关基因,并使用机器学习方法建立预后风险模型。方法:分析来自Gene Expression Omnibus数据库的IPF数据集GSE70866,鉴定炎症相关基因。使用无监督聚类算法对IPF样本进行分类,然后使用加权基因共表达网络分析(WGCNA)识别高相关基因。然后应用最小绝对收缩和选择算子(LASSO)回归,结果的交集确定了关键枢纽基因,主要是CCL2和STAB1。建立大鼠肺纤维化模型,采用慢病毒转染法下调CCL2的表达。采用定量聚合酶链反应、Western blot、免疫组织化学、酶联免疫吸附、苏木精-伊红染色、马松三色染色等方法验证转染效果和hub基因表达。同时评估α-SMA和COL1A1的水平。结果:WGCNA和LASSO回归分析发现CCL2和STAB1是IPF的重要贡献者,与患者预后和免疫细胞浸润密切相关。蛋白-蛋白相互作用网络分析证实CCL2是IPF的一种新的生物标志物。在IPF大鼠模型中,与对照组相比,CCL2的表达显著升高。下调CCL2表达可减轻肺纤维化,降低COL1A1蛋白和α-SMA蛋白的表达。CCL2可促进COL1A1蛋白和α-SMA蛋白的表达,提示炎症性肺纤维化的机制可能与CCL2对COL1A1和α-SMA的调控有关。讨论:这些发现表明CCL2是一种有前景的生物标志物和潜在的IPF治疗靶点。
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
Frontiers in Genetics
Frontiers in Genetics Biochemistry, Genetics and Molecular Biology-Molecular Medicine
CiteScore
5.50
自引率
8.10%
发文量
3491
审稿时长
14 weeks
期刊介绍: Frontiers in Genetics publishes rigorously peer-reviewed research on genes and genomes relating to all the domains of life, from humans to plants to livestock and other model organisms. Led by an outstanding Editorial Board of the world’s leading experts, this multidisciplinary, open-access journal is at the forefront of communicating cutting-edge research to researchers, academics, clinicians, policy makers and the public. The study of inheritance and the impact of the genome on various biological processes is well documented. However, the majority of discoveries are still to come. A new era is seeing major developments in the function and variability of the genome, the use of genetic and genomic tools and the analysis of the genetic basis of various biological phenomena.
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