Estimating Disease-Free Survival of Thyroid Cancer Based on Novel Cuprotosis-Related Gene Model

Author:

Du Rui1,Li Jingting1,li Fang1,Mi Lusi1,Dionigi Gianlorenzo2,Sun Hui1,Liang Nan1

Affiliation:

1. Jilin University

2. Istituto Auxologico Italiano IRCCS (Istituto di Ricovero e Cura a Carattere Scientifco), University of Milan

Abstract

Abstract Background: Cuprotosis is a newlydiscovered form of cell death that differs from other types of cell death. The aim of this study wasto investigate the functional role and a possible prognosticmodel for thyroid cancer. Methods: TCGA 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. Results: Among 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. Conclusion: Three CRG models (FDX1, BUB1, RPL3) could better predict the prognosis of thyroid cancer. Immune cell infiltration and the ATM pathway were the possible mechanisms.

Publisher

Research Square Platform LLC

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