Clinical, cosmetic and investigational dermatology
HEXB as a Candidate Target Gene in Keloid Radiotherapy: Based on Multi-Omics Analysis and Mendelian Randomization
By Shang Y, Gao S and Guan X.
Abstract
Introduction
Keloid is a common and treatment-refractory conditions in plastic surgery and dermatology. Although radiotherapy for keloid has attracted increasing attention in recent years, its mechanism at the genetic level remains poorly characterized. This study investigated the relationship between radiation-related genes (RRGs) and keloid through an integrated multi-omics and machine learning framework, and to explore potential therapeutic agents targeting the identified key gene.
Methods
Single-cell RNA sequencing and multiple Gene Expression Omnibus (GEO) datasets were integrated to investigate the association between RRGs and keloid. Multiple machine learning algorithms were applied to assess potential causal relationships, followed by Mendelian randomization (MR) analysis to investigate potential relationships. Spatial transcriptomics was employed to localize gene expression within keloid tissue, and virtual knockout analysis was performed to assess the functional role of the candidate gene in tissue architecture. Finally, molecular docking was conducted to screen potential therapeutic agents targeting HEXB, and molecular dynamics (MD) simulations were performed to evaluate the stability of the resulting protein-ligand complexes.