A novel gene signature unveils three distinct immune-metabolic rewiring patterns conserved across diverse tumor types and associated with outcomes - Pedrosa, Leire; Foguet, Carles; Oliveres, Helena; Archilla, Iván; de Herreros, Marta García; Rodríguez, Adela; Postigo, Antonio; Benítez-Ribas, Daniel; Camps, Jordi; Cuatrecasas, Miriam; Castells, Antoni; Prat, Aleix; et al. (Frontiers in Immunology, 2022)
Existing immune markers and tumor mutational burden signatures have modest predictive accuracies of immune-check-point inhibitors (ICI) therapeutic efficacy. In this study, we developed an immune metabolic signature suitable for personalized ICI therapies. A classifier using an immune-metabolic signature (IMMETCOLS) was developed on a training set of 77 metastatic colorectal cancer (mCRC) samples and validated on 4,200 tumors from the TCGA database belonging to 11 types. Here we reveal that IMMETCOLS signature classifies tumors into 3 distinct immune-metabolic clusters. Cluster 1 displays enhanced glycolysis-Warburg, hexosamine biosynthesis and epithelial-to-mesenchymal biomarkers. On multivariate analysis, Cluster 1 tumors were enriched in pro-immune signature but not Immunophenoscore, and were associated with the poorest median survival. It’s predicted tumor metabolic features suggest an acidic-lactate-rich tumor microenvironment (TME) geared to an immunosuppressive setting, enriched in fibroblasts. Cluster 2 displays features of gluconeogenesis ability, which is needed for glucose-independent survival and preferential use of alternative carbon sources, including glutamine and lipid uptake/β-oxidation. Its metabolic features suggest a hypoxic and hypoglycemic TME, associated with poor tumor-associated antigen presentation. Finally, cluster 3 is highly glycolytic, but also has a solid mitochondrial function, with concomitant up- regulation of glutamine and essential amino acids transporters and the pentose phosphate pathway leading to glucose exhaustion in the TME and immunosuppression. Together these findings suggest that IMMETCOLS signature provides a classifier of tumors from diverse origins, yielding three clusters with distinct immune-metabolic profiles, representing a new predictive tool for patient selection for specific immune-metabolic therapeutic approaches