Immune cell metabolism has emerged as a critical regulator of tumor progression and therapeutic response. In breast cancer, metabolic reprogramming of immune cells within the tumor microenvironment profoundly influences antitumor immunity, immune evasion, and resistance to immunotherapy. Metabolic pathways such as glycolysis, lactate metabolism, lipid metabolism, and ferroptosis have increasingly been implicated in immune dysfunction. However, a systematic overview of research trends in this rapidly evolving field remains lacking. A dual-database bibliometric analysis was conducted using the Web of Science Core Collection and Scopus to comprehensively characterize global research on immune cell metabolic reprogramming in breast cancer. Parallel analyses with cross-database consistency checks were applied to enhance robustness. Visualization tools, including CiteSpace, VOSviewer, and Bibliometrix, were used to evaluate publication trends, collaborative networks, thematic evolution, and citation dynamics. Parallel analyses of two independent datasets were performed, including 618 publications from the Web of Science Core Collection and 862 publications from Scopus (1,480 records in total). The analysis revealed a clear transition from early investigations of general immune dysregulation to mechanistic studies focusing on immunometabolic pathways. Keywords such as “tumor microenvironment,” “T cell exhaustion,” “macrophage polarization,” “lactate metabolism,” and “ferroptosis” exhibited prominent citation bursts and stable clustering patterns, indicating their emergence as core research frontiers. China and the United States were identified as leading contributors, and consistent patterns across databases reinforced the credibility of these findings. This study delineates the evolving knowledge landscape of immune cell metabolic reprogramming in breast cancer. By highlighting convergent bibliometric signals, our findings identify ferroptosis and lactate-related metabolic programs as priority directions for future mechanistic investigations and combination immunotherapy strategies, providing a data-driven framework for hypothesis generation in breast cancer immunometabolism.
Zhang et al. (Thu,) studied this question.