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A Novel Cuproptosis-Related Gene Signature Predicts Prognosis in Papillary Thyroid Carcinoma Patients
Jun Cao1, Shijia Zhang2,3, Kehui Zhou2,3
1Department of Head and Neck and Rare Oncology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China.
Background:
Cuproptosis, a novel form of cell death mediated by protein lipoylation, is intricately linked to mitochondrial metabolism. However, the clinical association of cuproptosisrelated genes (CRGs) in thyroid cancer remains unclear. In this study, we performed a systematic investigation on the differential expression and genetic alterations of CRGs in papillary thyroid carcinoma (PTC) and constructed a CRG signature to predict the prognosis of PTC patients.
Methods:
We integrated the data of The Cancer Genome Atlas (TCGA) database and analyzed the expression of 10 CRGs in PTC. CRG signature was constructed using univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) Cox regression. In addition, the signature-related molecular features were validated by a combination of functional enrichment, Cox regression, and immune infiltration analysis. Independent validation cohort and quantitative real-time polymerase chain reaction (qRT-PCR) were used to validate the expression of differentially expressed CRG (CDKN2A).
Results:
Thyroid cancer patients could be divided into two subtypes (high and low CRG score groups). We found that the overall survival (OS) of patients was lower in the high CRG score group (HCSG) than in the low CRG score group (LCSG) (P < 0.001). The area under the curve (AUC) values for 3 years, 5 years, and 8 years were 0.872, 0.941, and 0.976, respectively. Cox regression analysis indicated that the CRG score could serve as an independent prognostic indicator for PTC. Functional enrichment analysis indicated that the CRG prognostic signature was also associated with the tumor immune microenvironment. In HCSG, the immune suppression cell score was significantly higher than in LCSG. In addition, we identified the expression of CRG (CDKN2A) by qRT-PCR, and the results aligned with the TCGA database.
Conclusion:
Our CRG signature demonstrates excellent predictive capabilities for the prognosis of PTC patients. CRGs may play an important role in tumorigenesis and could be used to predict the immunotherapy efficacy of PTC.
