A Prognostic Risk Model Based on Immune Genes in Thyroid Cancer and Its Correlation With Tumor‐Associated Immune Cell Infiltration Abundance
Yufan Zhang, Shili Song, Xiaochen Yu, Jie LiABSTRACT
Objective
To investigate a prognostic risk model for thyroid cancer based on immune genes and its link to immune cell infiltration in tumors.
Method
This was a retrospective study of 117 thyroid cancer patients treated at our hospital from May 2021 to December 2023. Patients were categorized into 82 with a good prognosis and 35 with a poor prognosis. A COX regression model was validated using ROC curves and goodness‐of‐fit tests. Flow cytometry was used to detect the proportion of each immune cell subset in tumor tissues. The correlation was analyzed using Spearson correlation test. The TCGA thyroid cancer RNA‐seq data ( n = 512) were downloaded for external validation.
Results
LNM, capsule invasion, and immune genes were independent factors for poor prognosis in thyroid cancer ( p < 0.05). A prognosis prediction model was developed: [1/1 + exp. (4.854 + 1.085 × LNM + 1.510 × capsule invasion + 1.318 × CDK1 + 1.940 × B3GNT7 + 0.860 × S100A9 + 0.956 × MMP12)], with an AUC of 0.925 and a chi‐square value of 10.846 ( p = 0.178 > 0.05). Poor‐prognosis patients showed reduced B, CD4 + T, and CD8 + T lymphocyte infiltration, but increased neutrophil and macrophage infiltration ( p < 0.05). CDK1, B3GNT7, S100A9, and MMP12 mRNA levels were negatively correlated with B lymphocyte infiltration in thyroid cancer. CD4 + T lymphocytes and CD8 + T lymphocytes were positively correlated with the infiltration abundance of neutrophils and macrophages ( p < 0.05). Spearman correlation analysis of the TCGA database showed that S100A9 was positively correlated with infiltration of B cells, CD4 + T cells, macrophages, and NK cells, but negatively correlated with infiltration of CD8 + T cells and endothelial cells. MMP12 was positively correlated with infiltration of B cells, CD4 + T cells, macrophages, and NK cells, but negatively correlated with infiltration of endothelial cells (all p < 0.05 ).
Conclusion
The prognostic prediction model based on the influencing factors had high predictive value. The immune‐related genes were correlated with the abundance of immune cell infiltration; the above correlation has been partially validated in the TCGA database.