In-depth bioinformatics analysis uncovers the crosstalk genes and immune interactions among diagnostic markers linked to natural killer cells in patients with cirrhosis and sepsis.

This study conducted a comprehensive bioinformatics analysis to identify common diagnostic markers associated with natural killer (NK) cells in patients with cirrhosis and sepsis. The researchers used various computational techniques, including single-sample gene set enrichment analysis, weighted gene co-expression network analysis, and machine learning algorithms, to pinpoint the feature genes MS4A4A and CD59. These genes were validated across training and independent datasets, and their diagnostic significance was confirmed through receiver operating characteristic curve and decision curve analysis. Further experimental validation using qRT-PCR and immune cell profiling revealed distinct immune cell infiltration patterns in cirrhosis and sepsis subtypes defined by the feature genes. These findings provide valuable insights into the crosstalk between NK cells, cirrhosis, and sepsis, potentially leading to improved diagnostic strategies and targeted therapeutic interventions.