Oct 2026· Frontiers in Immunology· Vol 17· 0 citations· 68 references
Medicine
TL;DR
This study aims to systematically identify key hub genes in psoriasis pathogenesis through the integration of bioinformatics, machine learning and experimental validation methods, and emerged HPSE emerged as a multifunctional core gene associated with immune dysregulation.
Abstract
This study aims to systematically identify key hub genes in psoriasis pathogenesis through the integration of bioinformatics, machine learning and experimental validation methods. Four psoriasis microarray datasets were retrieved from the GEO database, with differentially expressed genes identified through comparative analysis. A dual machine learning approach screened core hub genes, whose expression levels and diagnostic efficacy were validated in an independent cohort. CIBERSORT was employed for immune cell infiltration analysis, whilst a multi-database approach constructed an mRNA-miRNA-lncRNA regulatory network. Molecular docking technology assessed interactions between the environmental pollutant bisphenol A, predicted drugs, and hub genes. Finally, an in vitro psoriasis model was established by stimulating HaCaT cells with the M5 cytokine mixture, with hub gene expression validated via RT-qPCR. Results show that 77 co-differentially expressed genes were identified in psoriasis. Machine learning screened five key hub genes: CARHSP1, HPSE, PCLAF, SERPINB4, and SPRR2C. These were significantly upregulated in the validation cohort and demonstrated strong discriminative value for distinguishing psoriatic lesional skin from paired non-lesional skin, rather than serving as standalone diagnostic biomarkers for psoriasis. Immune cell infiltration analysis revealed extensive associations with immune subpopulations including T cells and macrophages. Molecular docking computationally predicted a potential binding interaction between the environmental pollutant BPA and the hub gene HPSE, which awaits future experimental validation. Concurrently, Genistein and HPSE were suggested a potential interaction that awaits functional validation. In vitro experiments confirmed significant upregulation of HPSE, PCLAF, and SPRR2C mRNA levels in M5-induced psoriasis cell models. HPSE emerged as a multifunctional core gene associated with immune dysregulation. Molecular docking additionally predicted a potential interaction between the environmental pollutant BPA and HPSE; however, this interaction remains a computational hypothesis requiring experimental validation.
Early-onset gastric cancer (EOGC) represents a clinically and biologically distinct subtype of gastric cancer characterized by unique molecular features. However, its underlying molecular mechanisms remain unclear. This study aimed to identify EOGC-associated hub genes using an integrated bioinformatics and machine...
Shao-Xiong Yi, Qiu-Xia Chen, Jia-Xin Wu et al.· Frontiers in Oncology· 0 citations
CA4 is prioritized as a reproducible LUAD-associated candidate supported by transcriptomic, machine-learning, immune, survival, and docking evidence, but the computational findings do not demonstrate direct phytochemical regulation of CA4 or therapeutic efficacy.
Awaji Y. Safhi, Fahad Y. Sabei, Ali Hanbashi et al.· Journal of Pharmaceutical In...· 0 citations
This study suggests that CDC20 may serve as a potential biomarker for cell cycle and immune-inflammatory processes in psoriasis, providing a basis for further mechanistic and translational studies.
Ling-Yi Yang, Wen-Sheng Mo, Gang Wang et al.· Clinical, Cosmetic and Inves...· 0 citations
A psoriasis-specific metabolic-immune imbalance network with CD36, IL1B, and CREB1 as the core is outlined and Multidimensional validation supports their potential for patient stratification and targeted treatment and provides a basis for future drug development.
Hui-Huang He, Xue-Song Xiang, Yan-Fang Zhang et al.· Journal of the College of Ph...· 0 citations
Background Osteoarthritis (OA) poses a significant global health risk, with programmed cell death (PCD) playing a key role in its development. Methods This study utilized integrated bioinformatics tools to discover new biomarkers and therapeutic targets for OA. A comprehensive set of 1,254 PCD-related genes encompassin...
Xiao-Ning Lin, Yu-Jian Lan, Xuan Lin et al.· Frontiers in Immunology· 0 citations
Objective To identify osteoarthritis (OA) associated transcripts overlapping a predefined N4-acetylcytidine (ac4C) related gene set and evaluate their potential as an exploratory classification signature and basis for expression based clustering. Methods Five GEO datasets were analyzed using differential expression, fu...