Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels T cell-related prognostic risk model and tumor immune microenvironment modulation in triple-negative breast cancer

Background: Triple negative breast cancer (TNBC) is an aggressive and fatal malignancy. The current success of tumor immunotherapy has focused attention on intermediate T-cell subsets and the tumor microenvironment, which are essential for activation of the anti-tumor response. Therefore, both areas require further research to accelerate progress in developing tailored immunotherapeutic approaches for patients with TNBC.

Methods: We obtained scRNA-seq data of TNBC from the GEO database. A multiplex strategy was used to analyze and identify the T-cell heterogeneity of TNBC. By combining the METABRIC and GEO databases, a prognostic risk model for T-cell marker genes was constructed and validated. In addition, the immune-infiltrating cells of TNBC was analyzed using CIBERSORT, and the association between the risk model and response to immunotherapy was investigated.

Results: Based on scRNA-seq data, 25,932 cells were identified for multiple analyzes. T cells were studied with a focus on 2 subtypes, including CD8⁺ and CD4⁺. There were also communication relationships between T cells and multiple cell types. The results of the enrichment analysis showed that the T-cell marker genes were focused in pathways related to the immune system. In addition, OPTN, TMEM176A, PKM and HES1 deserve attention as prognostic markers in TNBC. The immune infiltration results showed that the high-risk group had significant immune cell infiltration and immunosuppression status.

Conclusion: This study provides a resource for understanding T-cell heterogeneity and the associated prognostic risk model for TNBC. The results show that the model helps predict prognosis and response to treatment in breast cancer.