Thyroid differentiation score-related genes and prognostic model for thyroid cancer

Area of Science:

• Oncology
• Genomics
• Molecular Biology

Background:

• Thyroid differentiation score (TDS) is crucial for assessing thyroid cancer (THCA) differentiation.
• Developing prognostic models for THCA is essential for patient management.
• Identifying novel biomarkers can improve THCA treatment strategies.

Purpose of the Study:

• To construct a prognostic risk model for THCA based on TDS-related genes.
• To explore the potential biomarkers and their role in THCA progression.
• To investigate the functional pathways associated with the identified risk genes.

Main Methods:

• Utilized The Cancer Genome Atlas (TCGA)-THCA dataset.
• Identified differentially expressed genes (DEGs) between THCA and TDS.
• Constructed a prognostic model using Least Absolute Shrinkage and Selection Operator (Lasso) and Cox regression.
• Validated the model using Kaplan-Meier curves, ROC curves, and decision curve analyses.
• Performed Gene Set Enrichment Analysis (GSEA) and single-cell RNA sequencing.

Main Results:

• Established a four-gene risk model (ATP2C2, MCEMP1, FAM111B, UST) with significant prognostic value for THCA overall survival.
• High ATP2C2 and MCEMP1 expression correlated with poorer prognosis; FAM111B and UST showed protective effects.
• GSEA indicated involvement of apoptosis and p53 signaling pathways.
• UST was linked to p53 signaling in CD4+ memory cells, suggesting a role in THCA progression.

Conclusions:

• The TDS-related gene risk model demonstrates strong prognostic utility in THCA.
• UST may inhibit the p53 signaling pathway to activate CD4+ memory cells in THCA.
• UST presents a potential therapeutic target for THCA treatment.