Frontiers in Endocrinology (Sep 2023)

Estimating disease-free survival of thyroid cancer based on novel cuprotosis-related gene model

  • Rui Du,
  • Jingting Li,
  • Fang Li,
  • Lusi Mi,
  • Gianlorenzo Dionigi,
  • Hui Sun,
  • Nan Liang

DOI
https://doi.org/10.3389/fendo.2023.1209172
Journal volume & issue
Vol. 14

Abstract

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BackgroundCuprotosis is a newly discovered form of cell death that differs from other types of cell death. The aim of this study was to investigate the functional role and a possible prognostic model for thyroid cancer.MethodsTCGA and GEO were used to investigate the differential expression of CRGs in THCA. KEGG and GO enrichment analyses were applied to investigate the possible molecular functions. The features of CRGs were selected by LASSO regression. 20 pairs of samples were randomly collected from the hospital to compare expression between tumor and normal.ResultsAmong the 19 CRGs related to thyroid cancer recurrence, 16 genes were differentially expressed in thyroid cancer. KEGG analysis showed that the 19 CRGs were mainly enriched in cell death, cell cycle and ribosomal pathways. K-M survival analysis and subsequent multiple logistic regression revealed that the expression of BUB1 and GINS2 were potential risk factors for disease-free survival (DFS) of thyroid cancer. In addition, further LASSO-regression selected the following three DFS-related CRGs: FDX1, BUB1 and RPL3. A novel prognostic prediction model was constructed by nomogram, and the prediction probability for 1-, 3- and 5-year survival approached the actual time. As for the possible mechanisms, FDX1, BUB1 and RPL3 were associated with immune infiltration. The cell model experiment illustrated that the ATM signaling pathway might be involved in thyroid cancer cell death.ConclusionThree CRG models (FDX1, BUB1, RPL3) could better predict the prognosis of thyroid cancer. Immune cell infiltration and the ATM pathway were the possible mechanisms.

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