Integrating single-cell RNA-seq and bulk RNA-seq to construct prognostic signatures to explore the role of glutamine metabolism in breast cancer.

Background: Although breast cancer (BC) treatment has entered the era of precision therapy, the prognosis is good in the case of comprehensive multimodal treatment such as neoadjuvant, endocrine, and targeted therapy. However, due to its high heterogeneity, some patients still cannot benefit from conventional treatment and have poor survival prognoses. Amino acids and their metabolites affect tumor development, alter the tumor microenvironment, play an increasingly obvious role in immune response and regulation of immune cell function, and are involved in acquired and innate immune regulation; therefore, amino acid metabolism is receiving increasing attention. Methods: Based on public datasets, we carried out a comprehensive transcriptome and single-cell sequencing investigation. Then we used 2.5 Weighted Co-Expression Network Analysis (WGCNA) and Cox to evaluate glutamine metabolism-related genes (GRGs) in BC and constructed a prognostic model for BC patients. Finally, the expression and function of the signature key gene SNX3 were examined by Results: In this study, we constituted a risk signature to predict overall survival (OS) in BC patients by glutamine-related genes. According to our risk signature, BC patients can obtain a Prognostic Risk Signature (PRS), and the response to immunotherapy can be further stratified according to PRS. Compared with traditional clinicopathological features, PRS demonstrated robust prognostic power and accurate survival prediction. In addition, altered pathways and mutational patterns were analyzed in PRS subgroups. Our study sheds some light on the immune status of BC. In Conclusion: We established a brand-new PRS consisting of genes associated with glutamine metabolism. It expands unique ideas for the diagnosis, treatment, and prognosis of BC.