A 16-gene signature associated with homologous recombination deficiency for prognosis prediction in patients with triple-negative breast cancer

Abstract

Homologous recombination deficiency (HRD) commonly occurs in breast cancer, which is the second cause of cancer death in women with a high rate of relapse and poor outcomes. Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. Thus, we aim to develop a prognostic signature based on HRD expecting to help improve outcomes in TNBC. The Cancer Genome Atlas (TCGA)–TNBC cohort was divided into the training set and the testing set randomly. Sixteen genes were filtered from the prognostic HRD-associated genes to establish a prognostic model in the training set. Patients were divided into high-risk and low-risk groups based on the median value of the risk score. Prognosis analysis showed that the high-risk group was associated with a worse prognosis in the training set, the testing set, the entire TCGA–TNBC cohort, and the METABRIC–TNBC cohort. The time-dependent receiver operating characteristic curve showed that our model had very good accuracy in the prediction of 1–5-year overall survival in the TCGA–TNBC cohort. Besides, a comparison of the area under curve value and C-index between our model and four published models showed that our model had the best predictive efficiency compared to other models. Subsequently, a nomogram was established. Finally, our finding also indicated that our model was associated with immunoregulation in TNBC and had the potential to be the target for TNBC treatment. Therefore, our findings not only provided a new strategy in the personalized prognosis management of TNBC but also offered new insight into precision treatment in TNBC.

Keywords

• breast cancer
• triple-negative
• prognosis model
• homologous recombination deficiency
• hrd score