Department of Gastrointestinal Surgery, The Third People's Hospital of Hubei Province, Wuhan.
Department of Thyroid and Breast Surgery, Jingmen N0.2 People's Hospital, Jingmen, China.
Am J Clin Oncol. 2024 Jan 1;47(1):1-10. doi: 10.1097/COC.0000000000001048. Epub 2023 Oct 2.
Thyroid carcinoma (THCA) is the most common malignant endocrine tumor with low mortality and a relatively good prognosis. Immune genes have attracted much attention as molecular markers of THCA prognosis and potential targets of immunotherapy.
Our study analyzed the transcriptome and clinical data of immune-related genes (IRGs) of THCA in gene expression omnibus, the cancer genome atlas-THCA, and ImmPort databases. By univariate Cox regression analysis, 15 genes were significantly correlated with the survival of patients with THCA. Five IRGs ( NMU, UBE2C, CDKN2A, COL19A1, and GPM6A ) were selected by LASSO regression analysis as independent prognostic factors to construct a disease-free survival-related prognostic risk model.
Kaplan-Meier survival analysis showed that there was a significant difference in disease-free survival between high and low-risk groups. The higher the risk score, the worse the survival of patients. Clinical correlation analysis showed that age and Stage stage of patients were correlated with risk score ( P < 0.05). Quantitative real-time polymerase chain reaction confirmed that there were differences in the expression of 5 IRGs between tumor tissues and normal thyroid tissues. Spearman correlation analysis indicated that the relative expression levels of NMU, CDKN2A, UBE2C, COL19A1 , and GPM6A were positively correlated with programmed death-ligand 1 and recombinant a disintegrin and metalloproteinase with thrombospondin 1.
Based on the bioinformatics method, we constructed a prognosis evaluation model and risk score system of IRGs in THCA, which provided a reference for predicting the prognosis of patients with THCA.
甲状腺癌(THCA)是最常见的恶性内分泌肿瘤,死亡率低,预后相对较好。免疫基因作为 THCA 预后的分子标志物和免疫治疗的潜在靶点受到了广泛关注。
我们的研究分析了基因表达综合数据库、癌症基因组图谱-THCA 和 ImmPort 数据库中 THCA 的免疫相关基因(IRG)的转录组和临床数据。通过单因素 Cox 回归分析,筛选出与 THCA 患者生存相关的 15 个基因。通过 LASSO 回归分析,选择 5 个 IRG(NMU、UBE2C、CDKN2A、COL19A1 和 GPM6A)作为独立的预后因素,构建无病生存相关的预后风险模型。
Kaplan-Meier 生存分析表明,高低风险组之间无病生存率存在显著差异。风险评分越高,患者的生存越差。临床相关性分析表明,患者的年龄和分期与风险评分相关(P<0.05)。实时定量聚合酶链反应证实,肿瘤组织和正常甲状腺组织中 5 个 IRG 的表达存在差异。Spearman 相关性分析表明,NMU、CDKN2A、UBE2C、COL19A1 和 GPM6A 的相对表达水平与程序性死亡配体 1 和重组 a 型血小板反应蛋白 1 呈正相关。
基于生物信息学方法,我们构建了 THCA 的 IRG 预后评估模型和风险评分系统,为预测 THCA 患者的预后提供了参考。