Prognostic Value of Endoplasmic Reticulum Stress-Related Gene Signature in Thyroid Cancer

To investigate the contribution of endoplasmic reticulum (ER) stress to the progression of thyroid cancer (TC) and to construct a prognostic gene signature.

Differential expression analysis was performed on 572 samples from The Cancer Genome Atlas (TCGA). ER stress-related genes (ERSGs) were obtained from the GeneCards database. Overlap analysis revealed 178 differentially expressed ERSGs. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression were used to construct a prognostic risk model. The model was validated in a test set (n = 172) and an independent clinical cohort (n = 90) by RT-qPCR. Immune infiltration, immune checkpoint expression, and drug sensitivity were compared between the high- and low-risk groups using the CIBERSORT algorithm and the Genomics of Drug Sensitivity in Cancer (GDSC) database.

A total of 5,253 differentially expressed genes and 518 ERSGs were identified, yielding 178 overlapping genes. An 11-gene prognostic model (CDKN1A, HTR2A, ATF3, MTTP, BRSK2, EGF, CASP12, HSPA5, IL1A, FOXRED2, CASQ2) was constructed. Patients in the high-risk group had significantly worse overall survival than those in the low-risk group did (log-rank P < 0.001; hazard ratio [HR] = 2.34; 95% CI: 1.58-3.47). The model showed good predictive performance, with AUC values of 0.74, 0.72, and 0.71 for 1-, 3-, and 5-year overall survival, respectively. Significant differences in tumor immune cell infiltration (e.g., Tregs, P < 0.01; M2 macrophages, P < 0.05) and drug sensitivity (e.g., gefitinib, P < 0.05) were detected between the two groups. In 90 clinical samples, the expression patterns of the 11 genes were validated by RT-qPCR (all P < 0.05), which was consistent with the bioinformatics findings.

The 11-gene ER stress-related signature independently predicted prognosis in patients with TC across both the TCGA cohort and an independent cohort. This study provides new insight into the role of ER stress in TC and may facilitate the identification of prognostic biomarkers and support clinical decision-making.