Identification of necroptotic biomarkers associated with immune microenvironment in sepsis based on the protein–protein interaction network and machine learning

•Machine learning and protein-protein interaction network identify CD40LG, TXN, and AIM2 as the key players of necroptosis in sepsis.•CD40LG, TXN, and AIM2 showed their diagnostic utility in distinguishing sepsis from control samples.•The mRNA levels of CD40LG, TXN, and AIM2 strongly correlated with...

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Bibliographic Details
Published in:	Clinica chimica acta Vol. 577; p. 120489
Main Authors:	Wu, Mengze, Zou, Zhao, Peng, Yuce, Luo, Suxin
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 01.09.2025
Subjects:	AIM2 Animals Biomarkers - analysis Biomarkers - metabolism CD40LG Humans Immune Infiltration Machine Learning Mice Necroptosis Necroptosis - genetics Protein Interaction Maps - genetics Sepsis Sepsis - diagnosis Sepsis - genetics Sepsis - immunology Sepsis - metabolism TXN PPIN AUC NF-κB TUNEL Necroptosis LASSO iNOS KEGG MF sCD40LG RT-qPCR RIPK3 GSEA IL-1β MAPK NRDEGs PCA GEO NETs AIM2 GSVA SVM-RFE mCD40LG Sepsis NGS GAPDH TLR4 TXN Machine Learning BP LPS TPM DEGs ANOVA CCL5 RIPK1 FADD ssGSEA CC CCR1 MLKL PMA GO hub-NRDEGs SALI Immune Infiltration CD40LG NRGs TNF-α
ISSN:	0009-8981, 1873-3492, 1873-3492
Online Access:	Get full text
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