ArticleNPJ systems biology and applications2026
Integrated multi-omics and single-cell analysis reveals CDKN2A-mediated cuproptosis mechanisms driving thyroid carcinoma progression.
Article in NPJ systems biology and applications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Interpretable four-class machine learning prediction of initial I-131 therapy responses in differentiated thyroid cancer.Annals of medicine · 2026Article
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2 authors.
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Abstract
Cuproptosis is a recently identified copper-dependent cell death pathway with growing relevance in tumor biology, yet its involvement in thyroid carcinoma (TC) remains poorly understood. In this study, we integrated multi-omics datasets to characterize the functional roles of cuproptosis-related genes (CRGs) in TC progression. Bulk and single-cell transcriptomic datasets from public repositories were analyzed to classify TC into two CRG-based molecular subtypes that showed significant associations with clinicopathological features and immune cell infiltration. A prognostic model derived from CRG-related differentially expressed genes exhibited high predictive accuracy for patient survival. CDKN2A emerged as the only consistently upregulated CRG in TC and correlated with adverse prognosis. Single-cell analyses further revealed distinct cellular distributions of CRGs within the tumor microenvironment, with notable enrichment in immune cell populations. In addition, a previously unrecognized competing endogenous RNA network, the GAS5/miR-128-3p/CDKN2A axis, was identified and experimentally validated. Functional assays demonstrated that this regulatory circuit modulates TC cell proliferation, invasion, and metastasis in vitro and in vivo, with GAS5 acting for miR-128-3p to regulate CDKN2A expression. These findings provide a comprehensive systems-level perspective on cuproptosis-related mechanisms in TC and highlight the therapeutic promise of targeting the cuproptosis pathway and its regulatory networks in thyroid cancer management.
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