This new technology, a result of collaboration with the University of Milan-Bicocca (Italy) and Yale School of Medicine (USA), generates detailed maps revealing how tumor cells obtain energy and nutrients based on their location. The study has been published in the journal Systems biology and applications.
Tumors are complex ecosystems where each cancer cell plays a role defined by its gene expression. Spatial sequencing had already allowed for the localization of these cells and their gene expressions. Now, the spatial Flux Balance Analysis (spFBA) method goes a step further, integrating this genetic information to infer metabolic activity, such as growth, survival, and cellular expansion.
“Our objective was to understand how the location of each cell within the tumor influences its way of obtaining energy and nutrients,” explains Dr. Davide Maspero, a researcher at CNAG and lead author of the study. “We can now integrate their gene expression to infer their metabolic activity, such as growth, survival, and cellular expansion.”
The resulting metabolic maps show, for example, which tumor regions consume more glycolysis for energy, which allocate more resources to biomass production, or which release lactate. This information is crucial for understanding proliferation, immune evasion, and metastasis strategies, paving the way for future, more targeted therapies.
Initial analyses have focused on colorectal and kidney cancer. In colorectal cancer, the maps revealed a metabolic cooperation network between different tumor regions, where some produce lactate and others consume it to build tumor biomass. In kidney cancer, the heterogeneity of the Warburg phenotype was confirmed, with regions producing lactate even in the presence of oxygen.
The team is already working on a new version of the spFBA program to expand its compatibility with more spatial transcriptomics databases, thereby facilitating its adoption by other research centers and hospitals.
