Lactylation signature identifies liver fibrosis phenotypes and traces fibrotic progression to hepatocellular carcinoma

被引:2
|
作者
Li, Lin-na [1 ]
Li, Wen-wen [2 ]
Xiao, Lu-shan [3 ]
Lai, Wei-nan [4 ]
机构
[1] Southern Med Univ, Nanfang Hosp, Dept Endocrinol & Metab, Guangzhou, Guangdong, Peoples R China
[2] Guangzhou Wondfo Hlth Sci & Technol Co Ltd, Guangzhou, Peoples R China
[3] Southern Med Univ, Nanfang Hosp, Dept Infect Dis, Guangzhou, Peoples R China
[4] Southern Med Univ, Nanfang Hosp, Dept Rheumatol & Immunol, Guangzhou, Peoples R China
来源
FRONTIERS IN IMMUNOLOGY | 2024年 / 15卷
关键词
liver fibrosis; lactylation; machine learning; immune infiltration; hepatocellular carcinoma; HISTONE LACTYLATION; ACTIVATION;
D O I
10.3389/fimmu.2024.1433393
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Introduction Precise staging and classification of liver fibrosis are crucial for the hierarchy management of patients. The roles of lactylation are newly found in the progression of liver fibrosis. This study is committed to investigating the signature genes with histone lactylation and their connection with immune infiltration among liver fibrosis with different phenotypes.Methods Firstly, a total of 629 upregulated and 261 downregulated genes were screened out of 3 datasets of patients with liver fibrosis from the GEO database and functional analysis confirmed that these differentially expressed genes (DEGs) participated profoundly in fibrosis-related processes. After intersecting with previously reported lactylation-related genes, 12 DEGs related to histone lactylation were found and narrowed down to 6 core genes using R algorithms, namely S100A6, HMGN4, IFI16, LDHB, S100A4, and VIM. The core DEGs were incorporated into the Least absolute shrinkage and selection operator (LASSO) model to test their power to distinguish the fibrotic stage.Results Advanced fibrosis presented a pattern of immune infiltration different from mild fibrosis, and the core DEGs were significantly correlated with immunocytes. Gene set and enrichment analysis (GSEA) results revealed that core DEGs were closely linked to immune response and chemokine signaling. Samples were classified into 3 clusters using the LASSO model, followed by gene set variation analysis (GSVA), which indicated that liver fibrosis can be divided into status featuring lipid metabolism reprogramming, immunity immersing, and intermediate of both. The regulatory networks of the core genes shared several transcription factors, and certain core DEGs also presented dysregulation in other liver fibrosis and idiopathic pulmonary fibrosis (IPF) cohorts, indicating that lactylation may exert comparable functions in various fibrotic pathology. Lastly, core DEGs also exhibited upregulation in HCC.Discussion Lactylation extensively participates in the pathological progression and immune infiltration of fibrosis. Lactylation and related immune infiltration could be a worthy focus for the investigation of HCC developed from liver fibrosis.
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页数:16
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