Lactate metabolism gene signature predicts prognosis in breast cancer using bulk and single cell sequencing data

Lactate metabolism, a key feature of the tumor microenvironment, plays a crucial role in cancer progression and immune suppression. However, the prognostic implication of lactate metabolism-related genes in breast cancer (BC) is not fully understood. This study aimed to explore key lactate metabolism-related genes related to the prognosis and immune cell clusters in BC. Based on The Cancer Genome Atlas (TCGA) RNA-seq data, lactate-related differentially expressed genes in BC were identified from lactate gene sets from MSigDB. A prognostic risk model was built through univariate and LASSO Cox regression analyses and validated in an independent Gene Expression Omnibus (GEO) cohort. Based on single-cell RNA-seq datasets from GEO database, immune infiltration was assessed via CIBERSORT, MCP-counter, and ssGSEA. Single-cell data analysis using Seurat, Monocle3, and CellChat elucidated cellular heterogeneity, developmental trajectories, and cell-cell communication. A 15-gene lactate-related prognostic signature was established. High-risk scores correlated significantly with poorer overall survival, advanced pathological stage, and lymph node metastasis. Single-cell analysis revealed nine major cell types. Cancer-associated fibroblasts promoted ECM remodeling via COL1A1, while tumor epithelial cells engaged in immunosuppressive interactions. Key molecules such as the lactate transporters MCT1/4 and CD147 axis were associated with poor prognosis. Immune regulatory pathways involving macrophage migration inhibitory factor-CD74 and MDK-SDC4 were linked to tumor migration and immune evasion, representing potential therapeutic targets. This study established a robust lactate metabolism-related gene signature for prognostic stratification in BC and highlighted its link to an immunosuppressive microenvironment, offering novel insights for developing targeted therapeutic strategies.