Identification of novel immune-related signatures for keloid diagnosis and treatment: insights from integrated bulk RNA-seq and scRNA-seq analysis.

ABSTRACT:

Background

Keloid is a disease characterized by proliferation of fibrous tissue after the healing of skin tissue, which seriously affects the daily life of patients. However, the clinical treatment of keloids still has limitations, that is, it is not effective in controlling keloids, resulting in a high recurrence rate. Thus, it is urgent to identify new signatures to improve the diagnosis and treatment of keloids.

Method

Bulk RNA seq and scRNA seq data were downloaded from the GEO database. First, we used WGCNA and MEGENA to co-identify keloid/immune-related DEGs. Subsequently, we used three machine learning algorithms (Randomforest, SVM-RFE, and LASSO) to identify hub immune-related genes of keloid (KHIGs) and investigated the heterogeneous expression of KHIGs during fibro

SUBMITTER: Xiao K 

PROVIDER: S-EPMC11251391 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature