Screening and validation of diagnostic markers for keloids via bioinformatics analysis.

ABSTRACT:

Background

Keloid (KD) disease is a skin lesions caused by abnormal wound healing that involve complex cellular and molecular mechanisms. The aim of this study was to screen diagnostic markers of KD via bioinformatics methods and evaluate their clinical application value.

Methods

The GSE44270, GSE145725, GSE7890 and GSE83286 datasets were analyzed in combination with difference analysis and weighted gene coexpression network analysis (WGCNA) and machine learning algorithms, candidate genes related to KD were screened and verified via receiver operating characteristic (ROC) curves and external datasets. KD samples were classified by consistent clustering, and the infiltration of immune cells was investigated. Simultaneously, a diagnostic biomarker-related ceRNA network was co

SUBMITTER: Wang Z 

PROVIDER: S-EPMC12420520 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature