Background
Cuproptosis is a novel type of mediated cell death strongly associated with the progression of several cancers and has been implicated as a potential therapeutic target. However, the role of cuproptosis in cholangiocarcinoma (CCA) for prognostic prediction, subgroup classification, and therapeutic strategies remains largely unknown.
Methods
A systematic analysis was conducted among 146 cuproptosis-related genes (CRGs) and clinical information based on independent mRNA and protein datasets to elucidate the potential mechanisms and prognostic prediction value of CRGs. A ten-CRG prediction model was constructed, and its effects on CCA prognosis were significantly connected to poor patient survival. Additionally, the expression patterns of our model included genes that were validated with several CCA cancer cell lines and a normal biliary epithelial cell line.
Results
First, a ten-CRG signature (ADAM9, ADAM17, ALB, AQP1, CDK1, MT2A, PAM, SOD3, STEAP3 and TMPRSS6) displayed excellent predictive performance for the overall survival of CCA. The low-cuproptosis group had a significantly better prognosis than the high-cuproptosis group with transcriptome and protein cohorts. Second, compared with the high-risk and low-risk groups, the two groups displayed distinct tumor microenvironments, reduced proportions of endothelial cells and increased levels of cancer-associated fibroblasts based on CIBERSORTx and EPIC analyses. Third, patients’ sensitivities to chemotherapeutic drugs and immune checkpoints revealed distinctive differences between the two groups. Finally, in replicating the expression patterns of the ten genes, these results were validated with qRT‒PCR results validating the abnormal expression pattern of the target genes in CCA.
Conclusions
Collectively, we established and verified an effective prognostic model that could separate CCA patients into two heterogeneous cuproptosis subtypes based on the molecular or protein characteristics of ten CRGs. These findings may provide potential benefits for unveiling molecular characteristics, and defining subgroups could improve the early diagnosis and individualized treatment of CCA patients.