Identification of STAT3 as a biomarker for cellular senescence in liver fibrosis: A bioinformatics and experimental validation study

Genomics. 2024 Mar;116(2):110800. doi: 10.1016/j.ygeno.2024.110800. Epub 2024 Jan 28.

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Keywords: Bioinformatics analysis; Biomarker; Cellular senescence; Experimental verification; Liver fibrosis; STAT3.

MeSH terms

  • Aging*
  • Animals
  • Biomarkers
  • Cellular Senescence*
  • Computational Biology
  • Mice
  • Molecular Docking Simulation

Substances

  • Biomarkers