Clinical Research Experiment Center, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230012, Anhui, China; College of Pharmacy, Anhui University of Chinese Medicine, Hefei 230011, Anhui, China.
Clinical Research Experiment Center, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230012, Anhui, China.
Genomics. 2024 Mar;116(2):110800. doi: 10.1016/j.ygeno.2024.110800. Epub 2024 Jan 28.
Cellular senescence is associated with a dysregulated inflammatory response, which is an important driver of the development of liver fibrosis (LF). This study aimed to investigate the effect of cellular senescence on LF and identify potential key biomarkers through bioinformatics analysis combined with validation experiments in vivo and in vitro.
The Gene Expression Omnibus (GEO) database and GeneCards database were used to download the LF dataset and the aging-related gene set, respectively. Functional enrichment analysis of differential genes was then performed using GO and KEGG. Hub genes were further screened using Cytoscape's cytoHubba. Diagnostic values for hub genes were evaluated with a receiver operating characteristic (ROC) curve. Next, CIBERSORTx was used to estimate immune cell types and ratios. Finally, in vivo and in vitro experiments validated the results of the bioinformatics analysis. Moreover, molecular docking was used to simulate drug-gene interactions.
A total of 44 aging-related differentially expressed genes (AgDEGs) were identified, and enrichment analysis showed that these genes were mainly enriched in inflammatory and immune responses. PPI network analysis identified 6 hub AgDEGs (STAT3, TNF, MMP9, CD44, TGFB1, and TIMP1), and ROC analysis showed that they all have good diagnostic value. Immune infiltration suggested that hub AgDEGs were significantly associated with M1 macrophages or other immune cells. Notably, STAT3 was positively correlated with α-SMA, COL1A1, IL-6 and IL-1β, and was mainly expressed in hepatocytes (HCs). Validation experiments showed that STAT3 expression was upregulated and cellular senescence was increased in LF mice. A co-culture system of HCs and hepatic stellate cells (HSCs) further revealed that inhibiting STAT3 reduced HCs senescence and suppressed HSCs activation. In addition, molecular docking revealed that STAT3 was a potential drug therapy target.
STAT3 may be involved in HCs senescence and promote HSCs activation, which in turn leads to the development of LF. Our findings suggest that STAT3 could be a potential biomarker for LF.
细胞衰老与失调的炎症反应有关，炎症反应是肝纤维化 (LF) 发展的重要驱动因素。本研究旨在通过生物信息学分析结合体内和体外验证实验，研究细胞衰老对 LF 的影响，并确定潜在的关键生物标志物。
使用基因表达综合 (GEO) 数据库和基因卡片 (GeneCards) 数据库分别下载 LF 数据集和衰老相关基因集。然后使用 GO 和 KEGG 对差异基因进行功能富集分析。使用 Cytoscape 的 cytoHubba 进一步筛选枢纽基因。使用受试者工作特征 (ROC) 曲线评估枢纽基因的诊断价值。接下来，使用 CIBERSORTx 估计免疫细胞类型和比例。最后，在体内和体外实验中验证了生物信息学分析的结果。此外，分子对接用于模拟药物-基因相互作用。
共鉴定出 44 个衰老相关差异表达基因 (AgDEGs)，富集分析表明这些基因主要富集在炎症和免疫反应中。PPI 网络分析确定了 6 个枢纽 AgDEGs (STAT3、TNF、MMP9、CD44、TGFB1 和 TIMP1)，ROC 分析表明它们均具有良好的诊断价值。免疫浸润表明枢纽 AgDEGs 与 M1 巨噬细胞或其他免疫细胞显著相关。值得注意的是，STAT3 与 α-SMA、COL1A1、IL-6 和 IL-1β呈正相关，主要在肝细胞 (HCs) 中表达。验证实验表明，LF 小鼠中 STAT3 表达上调，细胞衰老增加。HCs 和肝星状细胞 (HSCs) 的共培养系统进一步表明，抑制 STAT3 可减少 HCs 衰老并抑制 HSCs 激活。此外，分子对接表明 STAT3 是一种潜在的药物治疗靶点。
STAT3 可能参与 HCs 衰老并促进 HSCs 激活，从而导致 LF 的发展。我们的研究结果表明，STAT3 可能是 LF 的潜在生物标志物。
