AUTHOR=Sha Shengnan , Si Luyi , Wu Xinrui , Chen Yuanbiao , Xiong Hui , Xu Ying , Liu Wangrui , Mei Haijun , Wang Tao , Li Mei TITLE=Prognostic analysis of cuproptosis-related gene in triple-negative breast cancer JOURNAL=Frontiers in Immunology VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.922780 DOI=10.3389/fimmu.2022.922780 ISSN=1664-3224 ABSTRACT=Background

Cuproptosis is a copper-dependent cell death mechanism that is associated with tumor progression, prognosis, and immune response. However, the potential role of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of triple-negative breast cancer (TNBC) remains unclear.

Patients and methods

In total, 346 TNBC samples were collected from The Cancer Genome Atlas database and three Gene Expression Omnibus datasets, and were classified using R software packages. The relationships between the different subgroups and clinical pathological characteristics, immune infiltration characteristics, and mutation status of the TME were examined. Finally, a nomogram and calibration curve were constructed to predict patient survival probability to improve the clinical applicability of the CRG_score.

Results

We identified two CRG clusters with immune cell infiltration characteristics highly consistent with those of the immune-inflamed and immune-desert clusters. Furthermore, we demonstrated that the gene signature can be used to evaluate tumor immune cell infiltration, clinical features, and prognostic status. Low CRG_scores were characterized by high tumor mutation burden and immune activation, good survival probability, and more immunoreactivity to CTLA4, while high CRG_scores were characterized by the activation of stromal pathways and immunosuppression.

Conclusion

This study revealed the potential effects of CRGs on the TME, clinicopathological features, and prognosis of TNBC. The CRGs were closely associated with the tumor immunity of TNBC and are a potential tool for predicting patient prognosis. Our data provide new directions for the development of novel drugs in the future.