Immunotherapy has been applied to patients with breast cancer. However, only part of patients benefits from the current immunotherapy. Accurate prediction of individual response to immunotherapy can be beneficial for breast cancer management. CD8+ T cells are the main force of anti-tumor immunity. This study aimed to establish a CD8+ T cell-related gene expression signature for prediction of breast cancer prognostic and immunotherapy efficacy. RNA-seq transcriptomic data was the basics of this research. Weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis established the prognostic signature. We identified 290 CD8+ T cell-related genes in the training set and established a risk-score model based on 8-genes panel (SOCS1, IL10, CAMK4, CXCL13, KIR2DS4, TESPA1, CD70 and ICAM4). Subsequently, univariate Cox regression analysis suggested that high risk-score was a risk factor for breast cancer (HR = 3.1, 95%CI 2.0-4.8, P < 0.001). In tumor microenvironment, high-risk tumors present decreased tumor infiltrating CD8+ T cells and increased M2 macrophages. The low-risk patients may benefit more from immune checkpoint blockade immunotherapy than the high-risk patients. Moreover, breast tumors which sensitive to immune checkpoint inhibitor (ICI) showed higher IL10 expression.
Keywords: Breast cancer; Immune checkpoint blockade; Immunotherapy response; Prognosis; T cell.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.