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免疫相关基因诊断和甲状腺癌预后

Diagnosis and Prognosis of Thyroid Cancer by Immune-related Genes.

机构信息

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.

出版信息

Am J Clin Oncol. 2024 Jan 1;47(1):1-10. doi: 10.1097/COC.0000000000001048. Epub 2023 Oct 2.

Abstract

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

摘要

背景

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。

方法

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。

结果

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。

结论

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。

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