Ru Zixuan, Li Siwei, Wang Minnan, Ni Yanan, Qiao Hong
Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China.
Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin 150081, China.
Biomedicines. 2025 Apr 8;13(4):903. doi: 10.3390/biomedicines13040903.
: The increasing incidence and poor outcomes of recurrent thyroid cancer highlight the need for innovative therapies. Ferroptosis, a regulated cell death process linked to the tumour microenvironment (TME), offers a promising antitumour strategy. This study explored immune-related ferroptosis genes (IRFGs) in thyroid cancer to uncover novel therapeutic targets. : CIBERSORTx and WGCNA were applied to data from TCGA-THCA to identify hub genes. A prognostic model composed of IRFGs was constructed using LASSO Cox regression. Pearson correlation was employed to analyse the relationships between IRFGs and immune features. Single-cell RNA sequencing (scRNA-seq) revealed gene expression in cell subsets, and qRT-PCR was used for validation. : Twelve IRFGs were identified through WGCNA, leading to the classification of thyroid cancer samples into three distinct subtypes. There were significant differences in patient outcomes among these subtypes. A prognostic risk score model was developed based on six key IRFGs (, , , , , and ), which were found to be closely associated with immune cell infiltration and immune responses within the TME. The prognostic risk score was identified as a risk factor for thyroid cancer outcomes (HR = 14.737, 95% CI = 1.95-111.65; = 0.009). ScRNA-seq revealed the predominant expression of these genes in myeloid cells, with differential expression validated using qRT-PCR in thyroid tumour and normal tissues. : This study integrates bulk and single-cell RNA sequencing data to identify IRFGs and construct a robust prognostic model, offering new therapeutic targets and improving prognostic evaluation for thyroid cancer patients.
复发性甲状腺癌发病率的上升及预后不佳凸显了创新疗法的必要性。铁死亡是一种与肿瘤微环境(TME)相关的程序性细胞死亡过程,提供了一种有前景的抗肿瘤策略。本研究探索了甲状腺癌中与免疫相关的铁死亡基因(IRFGs),以发现新的治疗靶点。:将CIBERSORTx和WGCNA应用于来自TCGA-THCA的数据以鉴定枢纽基因。使用LASSO Cox回归构建由IRFGs组成的预后模型。采用Pearson相关性分析IRFGs与免疫特征之间的关系。单细胞RNA测序(scRNA-seq)揭示了细胞亚群中的基因表达,并使用qRT-PCR进行验证。:通过WGCNA鉴定出12个IRFGs,从而将甲状腺癌样本分为三种不同的亚型。这些亚型之间的患者预后存在显著差异。基于六个关键的IRFGs(、、、、、和)开发了一种预后风险评分模型,发现这些基因与TME内的免疫细胞浸润和免疫反应密切相关。预后风险评分被确定为甲状腺癌预后的一个危险因素(HR = 14.737,95% CI = 1.95 - 111.65; = 0.009)。scRNA-seq揭示了这些基因在髓系细胞中的主要表达,通过qRT-PCR在甲状腺肿瘤和正常组织中验证了差异表达。:本研究整合了批量和单细胞RNA测序数据以鉴定IRFGs并构建一个强大的预后模型,为甲状腺癌患者提供了新的治疗靶点并改善了预后评估。