Xiong Panhui, Liu Lei, Pi Jingting, Wang Ji, Lu Tao, Ke Xia, Jiang Yu, Shen Yang, Yang Yucheng
Department of Otolaryngology Head and Neck Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.
Department of Otolaryngology Head and Neck Surgery, Mianyang Central Hospital, Mianyang, 621000, People's Republic of China.
J Inflamm Res. 2025 Jul 30;18:10081-10098. doi: 10.2147/JIR.S536790. eCollection 2025.
The study aimed to identify key genes related to lipid metabolism in chronic sinusitis and understand their biological implications, considering the growing interest in the association between chronic sinusitis - a complex inflammatory condition - and lipid metabolism due to lipids' role in inflammation and immunity.
Gene expression data from bulk - RNA sequence was analyzed and intersected with lipid metabolism genes and WGCNA module genes from the MSigDB database. Immune infiltration analysis was conducted. Machine learning techniques were used to develop a diagnostic model. qRT - PCR and immunofluorescence techniques were employed to confirm gene involvement. Potential targeted drugs were identified through relevant analyses.
41 hub genes were identified, which were involved in pathways like G protein - coupled receptor signaling, TGF - beta receptor signaling, and responses to oxidative stress and nitrogen compounds. Enrichment analyses suggested links to ubiquitin - mediated proteolysis, mTOR signaling, and MAPK signaling. A significant presence of immune cells was detected in the chronic sinusitis group. A combined RF+Stepglm model was developed, comprising six genes (KPNA3, RAB35, GLE1, RNF139, OSMR, and PDPK1), which demonstrated good diagnostic performance (AUC = 0.848). Potential targeted drugs such as Raloxifene and Hesperidin were identified. qRT - PCR and immunofluorescence confirmed that the expression levels of RAB35, GLE1, and OSMR were significantly higher in CRS samples compared to normal ones.
This research highlights the role of lipid metabolism in chronic sinusitis and provides a basis for the development of targeted therapies.
鉴于慢性鼻窦炎（一种复杂的炎症性疾病）与脂质代谢之间的关联因脂质在炎症和免疫中的作用而受到越来越多的关注，本研究旨在确定与慢性鼻窦炎脂质代谢相关的关键基因，并了解其生物学意义。
分析来自批量RNA序列的基因表达数据，并与来自MSigDB数据库的脂质代谢基因和WGCNA模块基因进行交叉分析。进行免疫浸润分析。使用机器学习技术开发诊断模型。采用qRT-PCR和免疫荧光技术来确认基因的参与情况。通过相关分析确定潜在的靶向药物。
鉴定出41个枢纽基因，它们参与G蛋白偶联受体信号传导、TGF-β受体信号传导以及对氧化应激和氮化合物的反应等途径。富集分析表明与泛素介导的蛋白水解、mTOR信号传导和MAPK信号传导有关。在慢性鼻窦炎组中检测到大量免疫细胞。开发了一种组合的RF+Stepglm模型，包含六个基因（KPNA3、RAB35、GLE1、RNF139、OSMR和PDPK1），该模型具有良好的诊断性能（AUC = 0.848）。确定了如雷洛昔芬和橙皮苷等潜在的靶向药物。qRT-PCR和免疫荧光证实，与正常样本相比，CRS样本中RAB35、GLE1和OSMR的表达水平显著更高。
本研究突出了脂质代谢在慢性鼻窦炎中的作用，并为靶向治疗的开发提供了依据。
