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<p>Oxidative stress plays a crucial role in cancer progression and tumor immune microenvironment (TIME) modulation. However, its impact on thyroid cancer (THCA) subtypes and prognosis remains unclear. This study aimed to identify oxidative stress-related subgroups and construct a prognostic gene signature to enhance personalized treatment strategies in THCA. Using consensus clustering analysis, we categorized TCGA-THCA patients into two subgroups based on oxidative stress-related genes (OSRGs) expression. Cluster 1 had a poorer prognosis, higher BRAF mutation rates, and a suppressive TIME with fewer CD8 T cells. Kaplan-Meier survival analysis confirmed these findings. Six key OSRGs (<i>BMI1</i>, <i>CDK5</i>, <i>IL1RN</i>, <i>PDP1</i>, <i>TP53</i>, <i>UCN</i>) that significantly predicted THCA prognosis were identified. A risk model based on these genes accurately stratified patients into high and low-risk groups, with the high-risk group showing significantly worse outcomes. The model’s predictive performance was validated by ROC analysis. Nomogram revealed that higher OSRG-related risk score indicated lower survival probability in THCA patients. In vitro validation confirmed the high expression of six OSRGs in THCA cells and tissues, with most being associated with the Wnt signaling pathway. Additionally, <i>IL1RN</i> knockdown significantly inhibited THCA cell malignant characteristics and reduced ROS generation. This study provided a novel oxidative stress-related classification system for THCA, highlighting key signature genes with prognostic and therapeutic relevance. These results may guide future research on oxidative stress-targeted therapies and immune modulation in THCA.</p>

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Identification of oxidative stress-related subgroups and signature genes for the prediction of prognosis and immune microenvironment in thyroid cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月30日

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  • Zhenwei Qiu,
  • Jing Li,
  • Mei Tian

摘要

Oxidative stress plays a crucial role in cancer progression and tumor immune microenvironment (TIME) modulation. However, its impact on thyroid cancer (THCA) subtypes and prognosis remains unclear. This study aimed to identify oxidative stress-related subgroups and construct a prognostic gene signature to enhance personalized treatment strategies in THCA. Using consensus clustering analysis, we categorized TCGA-THCA patients into two subgroups based on oxidative stress-related genes (OSRGs) expression. Cluster 1 had a poorer prognosis, higher BRAF mutation rates, and a suppressive TIME with fewer CD8 T cells. Kaplan-Meier survival analysis confirmed these findings. Six key OSRGs (BMI1, CDK5, IL1RN, PDP1, TP53, UCN) that significantly predicted THCA prognosis were identified. A risk model based on these genes accurately stratified patients into high and low-risk groups, with the high-risk group showing significantly worse outcomes. The model’s predictive performance was validated by ROC analysis. Nomogram revealed that higher OSRG-related risk score indicated lower survival probability in THCA patients. In vitro validation confirmed the high expression of six OSRGs in THCA cells and tissues, with most being associated with the Wnt signaling pathway. Additionally, IL1RN knockdown significantly inhibited THCA cell malignant characteristics and reduced ROS generation. This study provided a novel oxidative stress-related classification system for THCA, highlighting key signature genes with prognostic and therapeutic relevance. These results may guide future research on oxidative stress-targeted therapies and immune modulation in THCA.