m6A related metabolic genes in breast cancer and their relationship with prognosis.

Breast cancer (BC) is the most prevalent malignancy among women, with incidence rates rising annually. N6-methyladenosine (m6A) modification has been recognized as a key regulator in the onset and progression of BC. Nevertheless, the role of m6A-associated metabolic genes (mMGs) in BC regulation remains insufficiently understood. In this study, we first analyzed and clustered single-cell transcriptomic (scRNA-seq) data from the peripheral blood of BC patients. Differentially expressed genes (DEGs) across various cell populations were intersected with mMGs to identify differentially expressed mMGs (DEmMGs). The AUCell algorithm was employed to score DEmMGs across cell populations, followed by subgroup clustering of high-scoring cell types. Additionally, DEGs from BC and control transcriptomic (RNA-seq) data in The Cancer Genome Atlas (TCGA) were intersected with DEmMGs. BC subtypes were identified based on the expression levels of overlapping genes, and differences in survival rates and immune microenvironment characteristics were examined across subtypes. A BC risk model was constructed using Lasso-Cox regression, and variations in prognosis, tumor mutational burden, immune cell infiltration, and drug sensitivity were explored. Finally, real-time quantitative PCR (qRT-PCR) and Western blot (WB) were used to validate the identified prognostic genes. NDUFAB1, VDAC1, TYMP, UGDH, ATP6AP1, and ALDH2 showed consistent and significant expression differences between the BC and control groups. This study's identification of key prognostic genes and the development of a risk model offer potential new targets for therapeutic intervention and clinical management of BC.