An IFNγ ⁺ double-negative T cell-associated score system for stratifying prognosis and therapy response in breast cancer

Abstract Objectives Recent studies have highlighted the significant role of double-negative T (DNT) cells in the immune response against tumors. This study aims to develop an Interferon-γ + (IFNγ + ) DNTs-related prognostic model (IDPM) for predicting clinical outcomes in breast cancer patients. Methods We utilized single-cell RNA sequencing data alongside bulk RNA data to identify a subset of IFNγ + DNT cells associated with clinical outcomes in breast cancer. Signature genes from this subset were used to construct a prognostic model through LASSO-Cox regression analysis in the TCGA cohort, which included 1,089 breast cancer patients. Survival analysis was performed, and responses to chemotherapy and immunotherapy were evaluated in a comprehensive dataset consisting of 3,588 breast cancer patients. Additionally, we examined the molecular profiles and immune infiltration characteristics of this model. Results We developed an IDPM scoring system based on the genes IL7R, HSPA8, and HNRNPA1. Patients with low IDPM scores showed improved survival outcomes compared to those with high scores. Low IDPM scores were linked to increased infiltration of M1 macrophages, CD8 + T cells, and CD4 + T cells, indicating higher drug sensitivity and a favorable response to both chemotherapy and immunotherapy. In contrast, high IDPM scores were associated with a greater presence of M2 macrophages, reduced drug sensitivity, and a diminished response to chemotherapy and immunotherapy. Conclusions The IDPM score demonstrates potential as a reliable biomarker for predicting prognosis, immune characteristics, and treatment responses in breast cancer patients. Further clinical validation is necessary to confirm its applicability.