Table 1_Identify and validate a novel ubiquitination-related biomarker for thyroid cancer prognosis and immunotherapy.xlsx

BackgroundUbiquitination is a critical protein modification process that plays a pivotal role in maintaining cellular homeostasis and is implicated in various pathophysiological processes, including thyroid cancer (THCA). Understanding the roles of ubiquitination-related genes in THCA progression and their interactions with the tumor microenvironment (TME) could provide valuable insights into prognosis and treatment strategies.
MethodsUsing iUUCD 2.0, ubiquitination-related genes were identified and subjected to consensus clustering on TCGA-THCA data. Differentially expressed genes (DEGs) between tumor and normal tissues were identified and used to construct a ubiquitination-related signature using Cox and LASSO regression. The signature’s prognostic ability was validated using training and test datasets from TCGA. Immune cell infiltration, immunotherapy response, and drug sensitivity were analyzed.
ResultsThree ubiquitination clusters were identified among 454 genes. Four prognostic DEGs (F12, FBXO15, FBXW10, and USP44) formed the signature, significantly correlating with survival, immune cell infiltration, clinical characteristics, immune checkpoints, immunotherapy response, and drug sensitivity. Low-risk THCA patients had better prognosis and immunotherapy responses than high-risk patients. A stable nomogram combining the signature and clinical characteristics predicted patient survival. RT-qPCR and immunohistochemistry confirmed differential expression of key genes.
ConclusionOur study identifies and validates a novel four-gene ubiquitination-related signature as a promising and independent prognostic biomarker in THCA. Beyond outcome prediction, this signature demonstrates significant translational potential by accurately predicting immunotherapy responses, thereby facilitating the development of more personalized and effective treatment strategies for patients with THCA.

研究背景
泛素化（Ubiquitination）是一类关键的蛋白质修饰过程，在维持细胞稳态中发挥核心作用，并参与包括甲状腺癌（THCA）在内的多种病理生理进程。阐明泛素化相关基因在甲状腺癌进展中的功能及其与肿瘤微环境（TME）的相互作用，可为患者预后评估与治疗策略研发提供重要参考价值。

研究方法
本研究依托iUUCD 2.0数据库筛选泛素化相关基因，并基于癌症基因组图谱甲状腺癌数据集（TCGA-THCA）开展一致性聚类分析。通过鉴定肿瘤与正常组织间的差异表达基因（DEGs），结合Cox回归与LASSO回归构建泛素化相关预后特征模型。利用TCGA数据集的训练集与测试集验证该特征模型的预后预测效能。此外，本研究还对免疫细胞浸润、免疫治疗响应及药物敏感性进行了分析。

研究结果
本研究在454个泛素化相关基因中鉴定出3个泛素化聚类亚型。由F12、FBXO15、FBXW10及USP44这4个预后相关差异表达基因构成的特征模型，与患者生存结局、免疫细胞浸润状态、临床特征、免疫检查点表达、免疫治疗响应及药物敏感性均呈显著相关性。低风险甲状腺癌患者的预后效果与免疫治疗响应均优于高风险患者。整合该特征模型与临床特征构建的稳定列线图（nomogram）可精准预测患者生存情况。通过实时定量聚合酶链反应（RT-qPCR）与免疫组化（immunohistochemistry）验证了关键基因的差异表达水平。

研究结论
本研究鉴定并验证了一种全新的4基因泛素化相关预后特征模型，其可作为甲状腺癌中极具潜力的独立预后生物标志物。该特征模型不仅可实现精准的预后预测，还能有效预判免疫治疗响应，具备重要的转化应用价值，可为甲状腺癌患者制定更具个性化与精准化的治疗策略提供理论支撑。