{"title":"Thyroid differentiation score-related genes and prognostic model for thyroid cancer.","authors":"Shang Lin, Di Chen, Chen-Wei Pan, Xiang-Chou Yang","doi":"10.21037/tcr-2025-460","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Thyroid differentiation score (TDS) reflects the differentiation degree of thyroid cancer (THCA). This study aimed to construct a TDS-related prognostic risk model for THCA and explore the potential biomarkers.</p><p><strong>Methods: </strong>Using The Cancer Genome Atlas (TCGA)-THCA dataset, overlapping differentially expressed genes (DEGs) between THCA-DEGs and TDS-DEGs were identified for functional enrichment analyses to determine their biological functions. Least absolute shrinkage and selection operator (Lasso) and Cox regression analyses were applied to construct a prognostic model. The model's predictive performance was validated through Kaplan-Meier curves, receiver operating characteristic curves, and decision curve analyses. Gene set enrichment analysis (GSEA) was performed to explore the functional pathways. Single-cell RNA sequencing analysis was performed to further explore the role of risk genes.</p><p><strong>Results: </strong>A four-gene risk model, including ATPase secretory pathway Ca<sup>2+</sup> transporting 2 (<i>ATP2C2</i>), mast cell expressed membrane protein 1 (<i>MCEMP1</i>), FAM111 trypsin-like peptidase B (FAM111B), and uronyl 2-sulfotransferase (<i>UST</i>), was established, with significant predictive value for overall survival. High expression of <i>ATP2C2</i> and <i>MCEMP1</i> correlated with poorer prognosis, while <i>FAM111B</i> and <i>UST</i> were protective factors. GSEA revealed the involvement of apoptosis and p53 signaling pathways with four risk genes. Additionally, <i>UST</i> was linked to p53 signaling pathways in CD4<sup>+</sup> memory cells, suggesting its critical role in THCA progression.</p><p><strong>Conclusions: </strong>The TDS-related gene risk model demonstrates strong prognostic utility in THCA. UST may inhibit the p53 signaling pathway to activate CD4<sup>+</sup> memory cells in THCA, highlighting its potential as a therapeutic target.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4662-4678"},"PeriodicalIF":1.7000,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432675/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational cancer research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/tcr-2025-460","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/27 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Thyroid differentiation score (TDS) reflects the differentiation degree of thyroid cancer (THCA). This study aimed to construct a TDS-related prognostic risk model for THCA and explore the potential biomarkers.
Methods: Using The Cancer Genome Atlas (TCGA)-THCA dataset, overlapping differentially expressed genes (DEGs) between THCA-DEGs and TDS-DEGs were identified for functional enrichment analyses to determine their biological functions. Least absolute shrinkage and selection operator (Lasso) and Cox regression analyses were applied to construct a prognostic model. The model's predictive performance was validated through Kaplan-Meier curves, receiver operating characteristic curves, and decision curve analyses. Gene set enrichment analysis (GSEA) was performed to explore the functional pathways. Single-cell RNA sequencing analysis was performed to further explore the role of risk genes.
Results: A four-gene risk model, including ATPase secretory pathway Ca2+ transporting 2 (ATP2C2), mast cell expressed membrane protein 1 (MCEMP1), FAM111 trypsin-like peptidase B (FAM111B), and uronyl 2-sulfotransferase (UST), was established, with significant predictive value for overall survival. High expression of ATP2C2 and MCEMP1 correlated with poorer prognosis, while FAM111B and UST were protective factors. GSEA revealed the involvement of apoptosis and p53 signaling pathways with four risk genes. Additionally, UST was linked to p53 signaling pathways in CD4+ memory cells, suggesting its critical 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, highlighting its potential as a therapeutic target.
期刊介绍：
Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.
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