Breast cancer combined prognostic model based on lactate metabolism genes

To investigate the impact of lactate metabolism genes, lactate metabolism-related genes (LMRG), and immune infiltrating cells on the prognosis of breast cancer. LMRG was identified via single-cell sequencing. Immune cell infiltration was obtained by the CIBERSORT method. The prognostic genes were chosen by cox regression and the least absolute selection operator approach. lactate metabolism-associated immune-infiltrating cells was determined by difference analysis. The GSE20685 dataset was used as an external validation cohort. The model's prognostic usefulness was evaluated utilizing survival, immunological microenvironment, and drug sensitivity assessments. NDUFAF6 was most associated with breast cancer prognosis. We obtained a total of 450 LMRG. SUSD3, IL18, MAL2, and CDKN1C comprised the Model2. NK cell activation was most relevant to lactate metabolism. The combined prognostic model outperformed the individual model, with the area under the curve ranging from 0.7 to 0.8 in all three cohorts. The lactate metabolism-related combination model assisted in evaluating breast cancer prognosis, providing new insights for treatment, particularly immunotherapy.