Identification of cuproptosis-related molecular subtypes and a novel predictive model of COVID-19 based on machine learning.

ABSTRACT:

Background

To explicate the pathogenic mechanisms of cuproptosis, a newly observed copper induced cell death pattern, in Coronavirus disease 2019 (COVID-19).

Methods

Cuproptosis-related subtypes were distinguished in COVID-19 patients and associations between subtypes and immune microenvironment were probed. Three machine algorithms, including LASSO, random forest, and support vector machine, were employed to identify differentially expressed genes between subtypes, which were subsequently used for constructing cuproptosis-related risk score model in the GSE157103 cohort to predict the occurrence of COVID-19. The predictive values of the cuproptosis-related risk score were verified in the GSE163151 cohort, GSE152418 cohort and GSE171110 cohort. A nomogram was created to faci

SUBMITTER: Luo H 

PROVIDER: S-EPMC10393044 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature