Abstract
Background: Triple-negative breast cancer remains a highly malignant disease due to the lack of specific targeted therapy and immunotherapy. A growing body of evidence supports the role of pyroptosis in tumorigenesis and prognosis, but further exploration is needed to improve our understanding of the tumor microenvironment in patients with triple-negative breast cancer. Methods: Consensus clustering analysis was performed to construct pattern clusters. A correlation analysis was conducted between the pattern clusters and the tumor microenvironment using GSVA, ESTIMATE, and CIBERSORT. Then, a risk score and a nomogram were constructed and verified to predict overall survival. Results: Two pyro-clusters and three pyro-gene clusters that differed significantly in terms of prognosis, biological processes, clinical features, and tumor microenvironment were identified. The different clusters corresponded to different immune expression profiles. The constructed risk score predicted patient prognosis and response to immunotherapy. Patients with low risk scores exhibited favorable outcomes with increased immune cell infiltration and expression of immune checkpoint molecules. Compared to other models, the nomogram was extremely effective in predicting prognosis. Conclusion: In the landscape of the immune microenvironment, pyroptosis-mediated pattern clusters differed markedly. Both the developed risk score and the nomogram were effective predictive models. These findings could help develop customized treatment for patients with triple-negative breast cancer.