This research introduces MetroSCREEN, a computational framework designed to map the metabolic landscape of individual cells by integrating gene expression with regulatory mechanisms. By analyzing single-cell transcriptomic data, the tool calculates MetaModule scores to identify specific metabolic subtypes and uses causal inference to pinpoint the internal and external factors driving these states. The authors demonstrate how metabolic reprogramming—such as the shift between glycolysis and oxidative phosphorylation—correlates with the specialized functions of fibroblasts and macrophages within the tumor microenvironment. Their findings reveal that these metabolic profiles are closely linked to immunosuppression and patient survival outcomes, suggesting that metabolic signatures can predict how well a person might respond to immunotherapy. Ultimately, this work provides a comprehensive platform, MetroTIME, to help scientists discover new therapeutic targets by understanding the complex chemistry of cancer-associated cells.

References:

• Tang K, Han Y, Sun D, et al. Reference-guided computational framework identifies microenvironment metabolic subtypes and targets using pan-cancer single-cell datasets[J]. Genome Medicine, 2025, 17(1): 150.