A Prognostic Risk Model Based on Immune Genes in Thyroid Cancer and Its Correlation With Tumor-Associated Immune Cell...

Area of Science:

• Oncology
• Immunology
• Genetics

Background:

• Thyroid cancer prognosis is influenced by various factors, including immune system components.
• Understanding the relationship between immune genes and tumor microenvironment is crucial for developing predictive models.

Purpose of the Study:

• To develop and validate a prognostic risk model for thyroid cancer based on immune-related genes.
• To investigate the correlation between identified immune genes and immune cell infiltration within thyroid tumors.

Main Methods:

• Retrospective analysis of 117 thyroid cancer patients.
• Development of a COX regression prognostic model, validated with ROC curves and goodness-of-fit tests.
• Flow cytometry for immune cell subset analysis and Spearman correlation for assessing gene-immune cell infiltration relationships.
• External validation using TCGA thyroid cancer RNA-seq data (n=512).

Main Results:

• Lymph node metastasis (LNM), capsule invasion, and specific immune genes (CDK1, B3GNT7, S100A9, MMP12) were independent predictors of poor thyroid cancer prognosis (p<0.05).
• A prognostic model incorporating these factors demonstrated high predictive accuracy (AUC=0.925).
• Poor prognosis was associated with reduced infiltration of B, CD4+ T, and CD8+ T cells, and increased neutrophil and macrophage infiltration (p<0.05).
• Gene expression levels of CDK1, B3GNT7, S100A9, and MMP12 correlated with immune cell infiltration patterns, partially validated in TCGA data.

Conclusions:

• The developed prognostic model for thyroid cancer exhibits significant predictive value.
• Immune-related genes are demonstrably linked to the abundance of immune cell infiltration in thyroid tumors.
• The observed correlations between immune genes and immune cell infiltration were partially confirmed using external TCGA data.