Identification of copper metabolism-related subtypes, the development of a prognosis model, and characterization of the immune landscape in colorectal cancer.

Objective: Abnormalities in copper metabolism are implicated in colorectal cancer (CRC) progression and unfavorable survival outcomes. Although there has been a recent surge of studies on cuprotosis-related genes, most have not elucidated the relationship between copper and tumors from the perspective of copper metabolism in tumors. This study explores the prognostic value of copper metabolism-related genes (CMGs) in CRC and their molecular characteristics within the tumor immune microenvironment.

Method: We investigated the expression profile of 112 copper CMGs which were obtained from MSigDB in 1340 CRC patients from four independent datasets (TCGA-COAD/READ, GSE17536, GSE40967, and GSE103479). Cox regression analysis was used to identify CMGs related to prognosis genes. Then, we used consensus unsupervised clustering analysis to classify the 1340 patients into different CMGs subtypes. Differences in prognosis, clinicopathological features, tumor microenvironment score, abundance of immune cells, and DEGs between different CMGs subtypes were systematically analyzed. Further we classified patients into different gene subtypes based on the expression of DEGs in different CMGs subtypes. The Lasso Cox regression algorithm was used to calculate CMGs risk scores which was used to stratify CRC patients into high and low-risk groups. The OS time, clinicopathological features, stromal-immune score, abundance of immune cells, expression of immune checkpoints and drugs sensitivity between the two groups were compared. Finally, the nomogram incorporating CMGs risk scores, patient age, and TNM staging was constructed and validated.

Results: 1340 CRC patients were classified into 3 distinct subtypes: CMGs subtype A exhibited the most active copper metabolism, followed by CMGs subtype B, with CMGs subtype C being the least active. Notably, patients in CMGs subtype A exhibited reduced overall survival (OS) compared to subtypes B and C, with an immune microenvironment enriched in TAMs and TANs, a paucity of CD8 T cells and plasma cells. The expression of immune checkpoints was highest in CMGs subtype A, including PD1, PDL1, TIGIT, and B7H3. Based on the DEGs between different CMGs subtypes, we identified two gene subtypes and gene subtype A demonstrated a strong association with poor survival outcomes and shared a similar tumor microenvironment with CMGs subtype A. CRC patients were further stratified into high and low-risk groups based on median CMGs risk scores. Patients in the high-risk group were associated with shorter OS, unfavorable survival outcomes and most of them were in advanced stages. Moreover, the high-risk group showed elevated stromal-immune scores, greater prevalence of TAMs and TANs, and higher expression of immune checkpoints, including PD1, TIM3, B7H3, and SIGLEC15. Significantly, high-risk group also had a higher incidence of microsatellite instability-high (MSI-H), tumor mutational burden (TMB) and somatic mutation, suggesting enhanced responsiveness to immunotherapy. Finally, The AUC values of the nomogram at 1, 3, 5, 10 years were 0.769, 0.745, 0.730, and 0.799. The calibration curves demonstrated substantial concordance with the ideal model in OS predictions.

Conclusion: Heterogeneity in copper metabolism exists within CRC, and abnormalities in copper metabolism levels influence CRC progression and the immune microenvironment. CMGs are effective biomarkers for predicting the prognosis of CRC patient and guiding immunotherapy.

Supplementary Information: The online version contains supplementary material available at 10.1007/s12672-025-03183-x.