The integrated single-cell analysis interpret the lactate metabolism-driven immune suppression in triple-negative breast cancer.

BACKGROUND: Individuals with triple-negative breast cancer (TNBC) exhibit elevated lactate levels, which offers a valuable lead for investigating the molecular mechanisms underlying the tumor microenvironment (TME) and identifying more efficacious treatments. METHODS: TNBC samples were classified based on lactate-associated genes. A single-cell transcriptomic approach was employed to examine functional differences across cells with varying lactate metabolism. Immunohistochemistry was used to explore the relationship between lactate metabolism and the CXCL12/CXCR4 signaling axis. In addition, utilizing machine learning techniques, we constructed a prognostic model based on lactic acid phenotype genes. RESULTS: Lactate-associated gene-based stratification revealed increased immune cell infiltration and immune checkpoint expression in Lactate Cluster 1. Elevated lactate metabolism scores were observed in both cancer-associated fibroblasts (CAFs) and malignant cells. CAFs with high lactate metabolism exhibited immune suppression through the CXCL12/CXCR4 axis. Immunohistochemistry confirmed elevated LDHA, LDHB, CXCL12, and CXCR4 levels in the high lactate group. CONCLUSION: This study elucidates the complex interplay between lactate and immune cells in TNBC and highlights the CXCL12/CXCR4 axis as a key pathway through which lactate mediates immune suppression, offering new insights into metabolic regulation within the TME. Furthermore, we developed a prognostic model based on lactate metabolism phenotype genes to predict the prognosis of TNBC patients and guide immunotherapy.