Abstract
Cuproptosis, a novel form of cell death mediated by protein lipoylation, is intricately linked to mitochondrial metabolism. However, the clinical association of cuproptosis- related 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 cancer (PTC) and constructed a CRG signature to predict the prognosis of PTC patients. 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). 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. 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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Combinatorial chemistry & high throughput screening
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.