Shi HaiXia, Guo Yuan, Chen JuPing, Yuan HaoChen, Wang LiYa, Zhang Yun, Li YanHua
Department of Dermatology, The Affiliated Hospital of Yangzhou University, Yangzhou University, No. 368, Hanjiang Middle Road, Hanjiang District, Yangzhou, 225012, Jiangsu Province, China.
Discov Oncol. 2025 Aug 2;16(1):1460. doi: 10.1007/s12672-025-03305-5.
Psoriasis has been associated with an increased risk of various cancers, including thyroid cancer (TC), yet the molecular mechanisms linking these two diseases remain unclear.
This study aimed to identify and analyze the differentially expressed genes (DEGs) between TC and psoriasis using bioinformatics approaches to explore potential molecular mechanisms and shared pathways. To the best of our knowledge, this is the first bioinformatics-based study to systematically identify and validate shared hub genes between thyroid cancer and psoriasis.
A TC dataset from the TCGA database and five GEO datasets (GSE35570, GSE13355, GSE14905, GSE53431, and GSE29265) were analyzed, with GSE53431 and GSE29265 serving as validation sets. Differential expression was identified using Xiantao and GEO2R, followed by a series of bioinformatics analyses, including Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) enrichment, protein-protein interaction (PPI) network construction, transcription factor (TF)-gene interaction, TF-miRNA coregulatory network analysis, and drug molecule prediction.
A total of 79 DEGs associated with TC were identified. Key Enrichr KEGG pathways included a response to the bacterium, NABA MATRISOME ASSOCIATED, negative regulation of cell population proliferation, response to wounding, and HALLMARK KRAS SIGNALING UP. Six hub genes (SERPINA1, S100A9, CCL20, SLPI, LCN2, and CXCL8) were identified from the PPI network, with three genes (SERPINA1, CCL20, and LCN2) showing high diagnostic value for both TC and psoriasis. TF gene and miRNA interactions involving these hub genes and potential drug molecules were also identified.
This study provides insight into potential biomarkers and therapeutic targets relevant to TC and psoriasis, identifying shared molecular pathways and hub genes that may guide future diagnostic and therapeutic approaches for these diseases.
银屑病与包括甲状腺癌（TC）在内的多种癌症风险增加有关，但连接这两种疾病的分子机制仍不清楚。
本研究旨在使用生物信息学方法识别和分析TC与银屑病之间的差异表达基因（DEG），以探索潜在的分子机制和共同途径。据我们所知，这是第一项基于生物信息学的系统识别和验证甲状腺癌与银屑病之间共享枢纽基因的研究。
分析了来自TCGA数据库的一个TC数据集和五个GEO数据集（GSE35570、GSE13355、GSE14905、GSE53431和GSE29265），其中GSE53431和GSE29265用作验证集。使用仙桃工具和GEO2R识别差异表达，随后进行一系列生物信息学分析，包括京都基因与基因组百科全书（KEGG）、基因本体（GO）富集、蛋白质-蛋白质相互作用（PPI）网络构建、转录因子（TF）-基因相互作用、TF-miRNA共调控网络分析和药物分子预测。
共鉴定出79个与TC相关的DEG。关键的Enrichr KEGG途径包括对细菌的反应、NABA基质体相关、细胞群体增殖的负调控、对伤口的反应以及HALLMARK KRAS信号上调。从PPI网络中鉴定出六个枢纽基因（SERPINA1、S100A9、CCL20、SLPI、LCN2和CXCL8），其中三个基因（SERPINA1、CCL20和LCN2）对TC和银屑病均显示出高诊断价值。还鉴定了涉及这些枢纽基因和潜在药物分子的TF基因与miRNA相互作用。
本研究为与TC和银屑病相关的潜在生物标志物和治疗靶点提供了见解，识别出可能指导这些疾病未来诊断和治疗方法的共享分子途径和枢纽基因。
