Constructing a thyroid cancer prognostic risk model based on CD8⁺ T cell associated genes

Area of Science:

• Oncology
• Immunology
• Bioinformatics

Background:

• Thyroid cancer (TC) is a common endocrine malignancy with a generally favorable prognosis.
• Understanding the tumor immune microenvironment is crucial for identifying prognostic biomarkers in TC.
• Existing research highlights the potential role of immune cell infiltration in TC outcomes.

Purpose of the Study:

• To investigate the immune microenvironment of thyroid cancer and identify novel biomarkers for prognosis.
• To develop and validate a prognostic risk assessment model for TC based on immune cell infiltration.
• To explore the relationship between immune cell subsets, gene expression, and clinical outcomes in TC.

Main Methods:

• Utilized The Cancer Genome Atlas-Thyroid Cancer (TCGA-THCA) dataset for mRNA and clinical data.
• Employed CIBERSORT to assess immune cell infiltration differences between TC and normal samples.
• Developed a prognostic risk model using Cox regression analysis based on CD8+ T cell-related differentially expressed genes (DEGs).
• Validated the model's predictive ability using survival and ROC curves.
• Performed Gene Set Enrichment Analysis (GSEA) and ESTIMATE to evaluate pathway enrichment and tumor microenvironment characteristics.
• Conducted simple-sample GSEA (ssGSEA) to analyze immune cell infiltration and function-related gene sets.

Main Results:

• CD8+ T cell abundance was significantly correlated with patient survival status in TC.
• A 6-gene prognostic risk model was successfully established and validated, demonstrating strong predictive power.
• High-risk groups exhibited distinct pathway enrichments, including ECM receptor interaction and TGF-β signaling.
• The ESTIMATE algorithm revealed higher stromal scores in the high-risk group.
• ssGSEA indicated differential infiltration of NK cells and varying expression of immune function-related genes (APC co-inhibition, cytolytic activity, HLA, T cell co-inhibition) between risk groups.

Conclusions:

• A novel 6-gene prognostic risk assessment model based on CD8+ T cells has been developed for thyroid cancer.
• This model provides a valuable tool for clinicians to assess TC patient prognosis.
• The study elucidates key differences in the tumor immune microenvironment between high- and low-risk TC groups, offering potential therapeutic targets.