Identification of a 15-pseudogene based prognostic signature for predicting survival and antitumor immune response in breast cancer.

Abstract

Pseudogenes are noncoding RNAs that have been revealed to play critical roles in oncogenesis and tumor progression. However, their functional roles have not been comprehensively clarified in breast cancer. Here, we systematically analyzed the RNA sequencing data of 13931 pseudogenes in 775 breast cancer patients from The Cancer Genome Atlas dataset, and ultimately identified 15 prognostic pseudogenes by univariate Cox proportional hazard regression. A risk score model was constructed based on the prognostic pseudogenes via LASSO analysis and dichotomized patients into low- and high-risk subgroups. Patients in the high-risk group had a significantly shorter overall survival than those in the low-risk group. The prognostic value of these 15 pseudogenes and the risk score model were further validated in the European Genome-Phenome Archive dataset. Furthermore, we performed consensus clustering of the 15 prognostic pseudogenes and found that their expression pattern was significantly associated with tumor malignancy and host antitumor immune response, in terms of infiltrating immune cell compositions, antigen presenting genes expression, cytolytic activity and T-cell exhausted markers. This study indicated that these 15 prognostic pseudogenes were significantly correlated with tumor malignancy and host antitumor immune response in breast cancer, and might serve as potential targets for immunotherapy.