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<p>Thyroid carcinoma (THCA) prognosis is tightly linked to the tumor immune microenvironment, and immune-related genes (IRGs) are key regulators of this process. This study aimed to construct an IRG-based prognostic model to improve THCA clinical management. Transcriptome data from 509 THCA and 58 adjacent non-cancerous tissues from TCGA, combined with IRG sets from ImmPort, were used to screen differentially expressed IRGs (DEIRGs). Limma identified 82 DEIRGs, and core genes for the model were screened via univariate and multivariate Cox regression. A five-IRG prognostic signature (CXCL5, APOD, NOD1, IGHE, IFNE) was established, with risk scores stratified by the median. Survival analysis revealed that high-risk THCA patients had significantly worse overall survival (OS, <i>P</i> &lt; 0.001). The model showed robust predictive efficacy (AUC = 0.834), and age/risk score were independent prognostic factors (<i>P</i> &lt; 0.05). Expression of the five IRGs was correlated with clinical TNM stages (<i>P</i> &lt; 0.05), and risk scores were positively associated with dendritic cell infiltration. Immunohistochemistry confirmed higher CXCL5/APOD expression in THCA tissues. This five-IRG signature effectively predicts THCA prognosis, reflects immune microenvironment characteristics, and provides novel targets for THCA immunotherapy.</p>

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Analysis of expression differences of immune genes in thyroid carcinoma based on TCGA and ImmPort data sets and the application of a prognostic model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月16日

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  • Huanzhang Lin,
  • Weihao Hu,
  • Qishuo Zhang,
  • Shijie Huang,
  • Peixiu Yao,
  • Yang Xie,
  • Kai Gao

摘要

Thyroid carcinoma (THCA) prognosis is tightly linked to the tumor immune microenvironment, and immune-related genes (IRGs) are key regulators of this process. This study aimed to construct an IRG-based prognostic model to improve THCA clinical management. Transcriptome data from 509 THCA and 58 adjacent non-cancerous tissues from TCGA, combined with IRG sets from ImmPort, were used to screen differentially expressed IRGs (DEIRGs). Limma identified 82 DEIRGs, and core genes for the model were screened via univariate and multivariate Cox regression. A five-IRG prognostic signature (CXCL5, APOD, NOD1, IGHE, IFNE) was established, with risk scores stratified by the median. Survival analysis revealed that high-risk THCA patients had significantly worse overall survival (OS, P < 0.001). The model showed robust predictive efficacy (AUC = 0.834), and age/risk score were independent prognostic factors (P < 0.05). Expression of the five IRGs was correlated with clinical TNM stages (P < 0.05), and risk scores were positively associated with dendritic cell infiltration. Immunohistochemistry confirmed higher CXCL5/APOD expression in THCA tissues. This five-IRG signature effectively predicts THCA prognosis, reflects immune microenvironment characteristics, and provides novel targets for THCA immunotherapy.