A signature of immune-related genes correlating with clinical prognosis and immune microenvironment in sepsis.

ABSTRACT:

Background

Immune-related genes (IRGs) remain poorly understood in their function in the onset and progression of sepsis.

Methods

GSE65682 was obtained from the Gene Expression Omnibus database. The IRGs associated with survival were screened for subsequent modeling using univariate Cox regression analysis and least absolute shrinkage and selection operator in the training cohort. Then, we assessed the reliability of the 7 IRGs signature's independent predictive value in the training and validation cohorts following the creation of a signature applying multivariable Cox regression analysis. After that, we utilized the E-MTAB-4451 external dataset in order to do an independent validation of the prognostic signature. Finally, the CIBERSORT algorithm and single-sample gene set

SUBMITTER: Chen ZH 

PROVIDER: S-EPMC9843880 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature