Identification of PRKCB, NLRC4, and TNFSF10 as Key Regulators of the Lipid Metabolism‐Autophagy Network in Atherosclerosis

BACKGROUND: The occurrence and development of atherosclerosis (AS) are closely related to disorders of lipid metabolism and dysfunction of autophagy. However, the key regulatory genes and immune microenvironment characteristics require further exploration. METHODS: This study integrated the bulk transcriptome and single-cell RNA sequencing data, and utilized bioinformatics methods to screen the differentially expressed genes (DEGs) of AS. The weighted gene co-expression network analysis (WGCNA) was used to identify the key gene modules related to lipid metabolism and autophagy. The core regulatory genes were further screened based on the machine learning algorithm (LASSO regression). The enrichment scores of 28 immune cell subtypes were calculated by ssGSEA, and the correlation between the immune infiltration characteristics and the expression levels of the three core genes (PRKCB, NLRC4, and TNFSF10) was analyzed by Spearman correlation analysis. The single-cell transcriptome data analysis was performed to determine the cell subtype distribution characteristics of the core genes and to compare the expression differences in lipid metabolism-autophagy-related gene expression across distinct cell subtypes. In addition, we screened potential drugs targeting the key genes from the public drug database, and simulated the binding mode of approved drugs with the active site of PRKCB by molecular docking technology. Ultimately, the expression of target factors in mouse aortic tissues was determined by quantitative real-time PCR (RT-qPCR), Western blotting, and immunohistochemical (IHC) analysis. Concurrently, the levels of TNFSF10 in mouse plasma were confirmed through enzyme-linked immunosorbent assay (ELISA). RESULT: Three lipid metabolism-autophagy core regulatory genes, PRKCB, NLRC4, and TNFSF10, were identified. These genes were significantly associated with the immune microenvironment of AS plaques and exhibited different cell subpopulation distribution patterns. The macrophage subpopulations showed higher lipid metabolism-autophagy regulatory activity. Molecular docking revealed that the anti-atherosclerotic drugs quercetin and atenolol can stably bind to the active site of PRKCB (with docking energies of -8.3 kcal/mol and -6.2 kcal/mol, respectively), a finding that identifies PRKCB as a candidate target worthy of further attention. Experimental evidence confirmed that the expression of these three key factors was significantly elevated in atherosclerotic plaque tissue, and the levels of TNFSF10 in the plasma of atherosclerotic mice were also significantly higher than those in the control group. CONCLUSION: This study identifies PRKCB, NLRC4, and TNFSF10 as key hub genes that link lipid metabolism and autophagy in AS, and highlights their potential as diagnostic biomarkers and therapeutic targets.

Authors

Institutions

Publication Details

Journal
Cell Biochemistry and Function
Published
2026-07-01
DOI
https://doi.org/10.1002/cbf.70221
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identification of PRKCB, NLRC4, and TNFSF10 as Key Regulators of the Lipid Metabolism‐Autophagy Network in Atherosclerosis

M Li, Yanyi Sun, Zhenyue Chen, Yanjun Sun
Cell Biochemistry and Function
Single-cell and spatial transcriptomics
article

Identification of PRKCB, NLRC4, and TNFSF10 as Key Regulators of the Lipid Metabolism‐Autophagy Network in Atherosclerosis

M Li, Yanyi Sun, Zhenyue Chen, Yanjun Sun
article en

Abstract

BACKGROUND: The occurrence and development of atherosclerosis (AS) are closely related to disorders of lipid metabolism and dysfunction of autophagy. However, the key regulatory genes and immune microenvironment characteristics require further exploration. METHODS: This study integrated the bulk transcriptome and single-cell RNA sequencing data, and utilized bioinformatics methods to screen the differentially expressed genes (DEGs) of AS. The weighted gene co-expression network analysis (WGCNA) was used to identify the key gene modules related to lipid metabolism and autophagy. The core regulatory genes were further screened based on the machine learning algorithm (LASSO regression). The enrichment scores of 28 immune cell subtypes were calculated by ssGSEA, and the correlation between the immune infiltration characteristics and the expression levels of the three core genes (PRKCB, NLRC4, and TNFSF10) was analyzed by Spearman correlation analysis. The single-cell transcriptome data analysis was performed to determine the cell subtype distribution characteristics of the core genes and to compare the expression differences in lipid metabolism-autophagy-related gene expression across distinct cell subtypes. In addition, we screened potential drugs targeting the key genes from the public drug database, and simulated the binding mode of approved drugs with the active site of PRKCB by molecular docking technology. Ultimately, the expression of target factors in mouse aortic tissues was determined by quantitative real-time PCR (RT-qPCR), Western blotting, and immunohistochemical (IHC) analysis. Concurrently, the levels of TNFSF10 in mouse plasma were confirmed through enzyme-linked immunosorbent assay (ELISA). RESULT: Three lipid metabolism-autophagy core regulatory genes, PRKCB, NLRC4, and TNFSF10, were identified. These genes were significantly associated with the immune microenvironment of AS plaques and exhibited different cell subpopulation distribution patterns. The macrophage subpopulations showed higher lipid metabolism-autophagy regulatory activity. Molecular docking revealed that the anti-atherosclerotic drugs quercetin and atenolol can stably bind to the active site of PRKCB (with docking energies of -8.3 kcal/mol and -6.2 kcal/mol, respectively), a finding that identifies PRKCB as a candidate target worthy of further attention. Experimental evidence confirmed that the expression of these three key factors was significantly elevated in atherosclerotic plaque tissue, and the levels of TNFSF10 in the plasma of atherosclerotic mice were also significantly higher than those in the control group. CONCLUSION: This study identifies PRKCB, NLRC4, and TNFSF10 as key hub genes that link lipid metabolism and autophagy in AS, and highlights their potential as diagnostic biomarkers and therapeutic targets.

Cell Biochemistry and FunctionVol. 44(7)
Ruijin Hospital (CN), Shanghai Institute of Hematology (CN)
Openalex Percentile: Top 11%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.