ArticleTranslational cancer research2026
Analysis and validation of prognostic markers for thyroid cancer by single-cell and bulk RNA sequencing.
Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Thyroid cancer represents the most prevalent malignancy within the endocrine system, exhibiting consistent increasing incidence rates over the years. We aim to utilize single-cell RNA sequencing (scRNA-seq) dataset to analyze key genes associated with prognosis in thyroid cancer. Methods: Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were applied to detect thyroid cell-related genes in the paratumor and tumor groups. Least absolute shrinkage and selection operator (LASSO) analysis was conducted on The Cancer Genome Atlas (TCGA) data to identify key genes and develop prognostic models. Immune infiltration analysis, correlation analysis, and differential expression analysis were used to explore the immunological features, correlation, and expression levels of the characterized genes. Western blot and immunohistochemical staining experiments were used to further validate the expression patterns of the characterized genes. Results: A total of 3,681 differentially expressed genes (DEGs) were recognized. There were 157 genes derived from the key modules in the WGCNA analysis. By performing intersection and conducting LASSO analysis, a prognostic model was developed based on the expression levels of six signature genes ( Conclusions:
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