Construction of a NETosis-related gene signature for predicting the prognostic status of sepsis patients.

ABSTRACT:

Background

Sepsis is a common traumatic complication of response disorder of the body to infection. Some studies have found that NETosis may be associated with the progression of sepsis.

Methods

Data of the sepsis samples were acquired from Gene Expression Omnibus (GEO) database. Gene set enrichment score was calculated using single-sample gene set enrichment analysis (ssGSEA). Weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) networks analysis, and stepwise multivariable regression analysis were performed to identify NETosis-associated genes for sepsis prognosis. To assess the infiltration of immune cells, the ESTIMATE and CIBERPSORT algorithms were used. Functional enrichment analysis was conducted in the clusterProfiler package.

Re

SUBMITTER: Wu J 

PROVIDER: S-EPMC11400959 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature