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Characterization of a cuproptosis-related signature to evaluate immune features and predict prognosis in colorectal cancer

PURPOSE: Cuproptosis is a newly discovered type of cell death. Little is known about the roles that cuproptosis related genes (CRGs) play in colorectal cancer (CRC). The aim of this study is to evaluate the prognostic value of CRGs and their relationship with tumor immune microenvironment. METHODS:...

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Detalles Bibliográficos
Autores principales: Li, Lei, Sun, Fengyuan, Kong, Fanyang, Feng, Yongpu, Song, Yingxiao, Du, Yiqi, Liu, Feng, Kong, Xiangyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10299831/
https://www.ncbi.nlm.nih.gov/pubmed/37384293
http://dx.doi.org/10.3389/fonc.2023.1083956
Descripción
Sumario:PURPOSE: Cuproptosis is a newly discovered type of cell death. Little is known about the roles that cuproptosis related genes (CRGs) play in colorectal cancer (CRC). The aim of this study is to evaluate the prognostic value of CRGs and their relationship with tumor immune microenvironment. METHODS: TCGA-COAD dataset was used as the training cohort. Pearson correlation was employed to identify CRGs and paired tumor-normal samples were used to identify those CRGs with differential expression pattern. A risk score signature was constructed using LASSO regression and multivariate Cox stepwise regression methods. Two GEO datasets were used as validation cohorts for confirming predictive power and clinical significance of this model. Expression patterns of seven CRGs were evaluated in COAD tissues. In vitro experiments were conducted to validate the expression of the CRGs during cuproptosis. RESULTS: A total of 771 differentially expressed CRGs were identified in the training cohort. A predictive model termed riskScore was constructed consisting of 7 CRGs and two clinical parameters (age and stage). Survival analysis suggested that patients with higher riskScore showed shorter OS than those with lower (P<0.0001). ROC analysis revealed that AUC values of cases in the training cohort for 1-, 2-, and 3-year survival were 0.82, 0.80, 0.86 respectively, indicating its good predictive efficacy. Correlations with clinical features showed that higher riskScore was significantly associated with advanced TNM stages, which were further confirmed in two validation cohorts. Single sample gene set enrichment analysis (ssGSEA) showed that high-risk group presented with an immune-cold phenotype. Consistently, ESTIMATE algorithm analysis showed lower immune scores in riskScore-high group. Expressions of key molecules in riskScore model are strongly associated with TME infiltrating cells and immune checkpoint molecules. Patients with a lower riskScore exhibited a higher complete remission rate in CRCs. Finally, seven CRGs involved in riskScore were significantly altered between cancerous and paracancerous normal tissues. Elesclomol, a potent copper ionophore, significantly altered expressions of seven CRGs in CRCs, indicating their relationship with cuproptosis. CONCLUSIONS: The cuproptosis-related gene signature could serve as a potential prognostic predictor for colorectal cancer patients and may offer novel insights into clinical cancer therapeutics.