Background: Due to the different infiltration abundance of immune cells in tumor, the efficacy of immunotherapy varies widely among individuals. Recently, growing evidence suggested that cuproptosis has impact on cancer immunity profoundly. However, the comprehensive roles of cuproptosis-related genes in tumor microenvironment (TME) and in response to immunotherapy are still unclear.

Methods: Based on 43 cuproptosis-related genes, we employed unsupervised clustering to identify cuproptosis-related patterns and single-sample gene set enrichment analysis algorithm to build a cuproptosis signature for individual patient’s immune cell infiltration and efficacy of immune checkpoint blockade (ICB) evaluation. Then, the cuproptosis-related genes were narrowed down using univariate Cox regression model and least absolute shrinkage and selection operator algorithm. Finally, a cuproptosis risk score was built by random survival forest based on these narrowed-down genes.

Results: Two distinct cuproptosis-related patterns were developed, with cuproptosis cluster 1 showing better prognosis and higher enrichment of immune-related pathways and infiltration of immune cells. For individual evaluation, the cuproptosis signature that we built could be used not only for predicting immune cell infiltration in TME but also for evaluating an individual’s sensitivity to ICBs. Patients with higher cuproptosis signature scores exhibited more activated cancer immune processes, higher immune cell infiltration, and better curative efficacy of ICBs. Furthermore, a robust cuproptosis risk score indicated that patients with higher risk scores showed worse survival outcomes, which could be validated in internal and external validation cohorts. Ultimately, a nomogram which combined the risk score with the prognostic clinical factors was developed, and it showed excellent prediction accuracy for survival outcomes.

Conclusion: Distinct cuproptosis-related patterns have significant differences on prognosis and immune cell infiltration in kidney renal clear cell carcinoma (KIRC). Cuproptosis signature and risk score are able to provide guidance for precision therapy and accurate prognosis prediction for patients with KIRC.

The study of metabolism provides important information for understanding the biological basis of cancer cells and the defects of cancer treatment. Disorders of polyamine metabolism is a common metabolic change in cancer. With the deepening of understanding of polyamine metabolism, including molecular functions and changes in cancer, polyamine metabolism as a new anti-cancer strategy has become the focus of attention. There are many kinds of polyamine biosynthesis inhibitors and transport inhibitors, but not many drugs have been put into clinical application. Recent evidence shows that polyamine metabolism plays essential roles in remodeling the tumor immune microenvironment (TIME), particularly treatment of DFMO, an inhibitor of ODC, alters the immune cell population in the tumor microenvironment. Tumor immunosuppression is a major problem in cancer treatment. More and more studies have shown that the immunosuppressive effect of polyamines can help cancer cells to evade immune surveillance and promote tumor development and progression. Therefore, targeting polyamine metabolic pathways is expected to become a new avenue for immunotherapy for cancer.