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

Lei Li; Fengyuan Sun; Fanyang Kong; Yongpu Feng; Yingxiao Song; Yiqi Du; Feng Liu; Xiangyu Kong

doi:10.3389/fonc.2023.1083956

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

Front Oncol. 2023 Jun 13:13:1083956. doi: 10.3389/fonc.2023.1083956. eCollection 2023.

Authors

Lei Li^{1

2}, Fengyuan Sun³, Fanyang Kong³, Yongpu Feng³, Yingxiao Song³, Yiqi Du³, Feng Liu¹, Xiangyu Kong^{3

4}

Affiliations

¹ Digestive Endoscopy Center, Shanghai Tenth People's Hospital, Shanghai, China.
² Department of Gastroenterology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China.
³ Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai, China.
⁴ Clinical Research Unit, Changhai Hospital, Naval Medical University, Shanghai, China.

Abstract

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.

Keywords: colorectal cancer; cuproptosis; elesclomol; immune infiltration; prognosis.

Grants and funding

This work is supported in part by National Key R&D Program of China No. 2019YFC1315900 and 2019YFC1315802; grant 81872043 and 82172572 (LL) from the National Natural Science Foundation of China; grant 82072760 and 81772640 (XYK) from the National Natural Science Foundation of China.